Effects of Monetary Policy on Household Expectations: The Role of Homeownership and Tenancy in USA

Effects of Monetary Policy on Household Expectations: The Role of Homeownership and Tenancy in USA | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Effects of Monetary Policy on Household Expectations: The Role of Homeownership and Tenancy in USA Utku Altunöz This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7180599/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This paper investigates how monetary policy differentially affects household expectations based on homeownership status in the United States. While existing literature addresses the general transmission mechanisms of monetary policy, the heterogeneity in responses between homeowners and renters remains underexplored. Using microdata from the Michigan Consumer Survey (MSC) and the New York Federal Reserve’s Survey of Consumer Expectations (SCE), we analyze how interest rate changes influence expectations about inflation, labor market prospects, and financial decisions.Our findings reveal that homeowners exhibit stronger reactions to interest rate changes, primarily due to mortgage-related cost adjustments and housing wealth effects. Renters, by contrast, show more muted responses, with expectations largely shaped by employment conditions and rent inflation. By incorporating an econometric framework that accounts for ownership status and macro-financial variables, we offer new evidence on the distributional consequences of monetary policy. These insights underscore the importance of targeted central bank communication strategies that account for household heterogeneity in policy sensitivity. Monetary Policy Household Expectations Homeownership Inflation Expectations Labor Market Interest Rate Transmission Figures Figure 1 Figure 2 Figure 3 1. Introduction Monetary policy plays a crucial role in shaping household expectations, including perceptions of future inflation, employment prospects, and financial stability. While the transmission mechanisms of monetary policy have been extensively studied, much of the existing literature tends to focus on aggregate effects, often overlooking the heterogeneity across different household groups. In particular, the differential responses of homeowners and renters to monetary policy shocks remain underexplored, despite their potential implications for economic stability and inequality. Homeownership represents a significant determinant of household sensitivity to monetary policy. For homeowners, particularly those with mortgage obligations, changes in interest rates can directly impact disposable income through mortgage payments and indirectly influence consumption and saving behaviors via housing wealth effects. Conversely, renters, lacking direct exposure to mortgage markets, may react primarily through labor market conditions and rent inflation pressures. This distinction is especially relevant in the context of unconventional monetary policy tools, such as quantitative easing and forward guidance, which amplify the need to understand how various socio-economic factors, including housing tenure, shape household expectations. Recent empirical evidence highlights the importance of homeownership status in mediating monetary policy transmission. Studies by Guren et al. ( 2020 ) and Di Maggio et al. ( 2017 ) demonstrate that homeowners exhibit more pronounced responses to interest rate changes, driven by mortgage cost adjustments and housing wealth effects. In contrast, renters’ expectations tend to be more sensitive to labor market signals and rent inflation, as noted by Kaplan et al. ( 2018 ) and Glaeser & Nathanson ( 2021 ). Furthermore, the role of behavioral factors, such as risk aversion and information processing, can amplify these differences, as households interpret monetary policy signals through the lens of their financial positions and experiences. This paper contributes to the literature by systematically analyzing how homeownership and tenancy moderate the effects of monetary policy on household expectations. Utilizing microdata from the Michigan Consumer Survey (MSC) and the New York Federal Reserve’s Survey of Consumer Expectations (SCE), we examine how shifts in interest rates influence household expectations about inflation, labor market prospects, and financial planning. By incorporating econometric models that account for ownership status, mortgage structure, and macro-financial variables, we provide new insights into the distributional consequences of monetary policy. Additionally, this study introduces a comparative analysis with Canadian data to highlight differences in monetary policy transmission across economies with varying mortgage market structures and homeownership rates. Canada’s high prevalence of variable-rate mortgages and elevated household debt levels make it a compelling case for understanding the nuances of monetary transmission in highly leveraged economies. Overall, the findings of this study underscore the necessity of tailoring monetary policy communication and complementary housing policies to address the heterogeneous impacts on households. By recognizing the diverse responses of homeowners and renters, policymakers can enhance the effectiveness of monetary interventions while mitigating potential distributional imbalances. 2. Conceptual and Theoretical Framework The effects of monetary policy on household behavior are primarily transmitted through changes in interest rates, inflation expectations, and credit availability. However, the way these effects manifest differs significantly between homeowners and renters, as homeownership represents a key socio-economic distinction that influences how households respond to economic shocks. This section expands on the four main channels—interest rate, wealth effect, credit availability, and rent inflation—that mediate the impact of monetary policy on household expectations. Additionally, we consider broader behavioral factors such as housing market dynamics, expectations theory, and psychological responses to wealth changes. The interest rate channel is a central mechanism through which monetary policy influences household expectations and consumption behavior. When central banks lower interest rates, it reduces the cost of borrowing, which immediately affects homeowners with variable or adjustable-rate mortgages (ARMs). These homeowners see a direct decrease in their mortgage payments, freeing up disposable income that can be used for consumption or savings. For instance, Guren et al. ( 2020 ) demonstrate that interest rate cuts during periods of monetary easing led to significant reductions in household debt servicing costs, particularly for households with ARMs. The marginal propensity to consume out of housing wealth also rises as borrowing becomes cheaper, especially when homeowners can refinance their mortgages at lower rates ( Bhutta & Keys, 2016 ). By contrast, renters do not benefit directly from these changes in borrowing costs. Their housing expenses remain unaffected by interest rate fluctuations, although they may experience secondary effects through improved labor market conditions. For instance, Kaplan et al. ( 2018 ) argue that while renters do not gain from reduced mortgage costs, they may still benefit from increased employment opportunities or wage growth as businesses respond to lower interest rates by investing more. This divergence in the transmission of monetary policy underscores how homeownership status amplifies the interest rate channel for some households while muting it for others. Moreover, the sensitivity to interest rate changes may vary depending on the type of mortgage. Homeowners with ARMs are particularly vulnerable to interest rate hikes, as their monthly payments increase when rates rise. This can lead to reductions in disposable income and lower consumption levels, creating a drag on economic growth. Conversely, homeowners with fixed-rate mortgages are insulated from short-term fluctuations in interest rates, which may limit their immediate response to monetary policy adjustments ( Di Maggio et al., 2017 ). This variation highlights the need for a nuanced understanding of how different housing and financial structures mediate the interest rate channel. The wealth effect is another critical mechanism that shapes how monetary policy affects household behavior, particularly for homeowners. When interest rates fall, housing demand typically rises, driving up home prices. For homeowners, the increase in housing wealth can lead to greater economic optimism and higher consumption, even in the absence of actual income gains. This is explained by the life-cycle hypothesis, which suggests that households base their consumption decisions on both current income and expected lifetime wealth ( Modigliani & Brumberg, 1954 ). Aladangady ( 2017 ) provides empirical evidence showing that households with higher home equity are more likely to increase their consumption in response to rising home values, illustrating the importance of the wealth effect in transmitting monetary policy. In addition to the life-cycle hypothesis, the permanent income hypothesis posits that households adjust their consumption based on long-term expectations of wealth. When homeowners perceive that their housing wealth has increased due to lower interest rates or rising housing prices, they may feel more secure about future income, leading to an increase in current consumption ( Carroll, 2001 ). This psychological dimension of the wealth effect is particularly relevant for monetary policy transmission, as it shows that even perceived changes in wealth can have real economic consequences. For renters, however, the wealth effect is absent. Renters do not directly benefit from rising housing prices and may even face higher costs if rent prices increase. As a result, their consumption patterns are more likely to be influenced by changes in wages or employment prospects rather than asset appreciation. Glaeser & Nathanson ( 2021 ) argue that the wealth effect reinforces inequality between homeowners and renters, as the former group reaps the benefits of housing price increases, while the latter faces rising housing costs without a corresponding increase in wealth. The credit availability channel operates through the broader financial system, where monetary policy influences the supply and cost of credit. Lower interest rates typically encourage banks to extend more credit to households, facilitating greater consumption and investment. Homeowners, who can use their home as collateral, are often better positioned to take advantage of this increased credit availability. Mian and Sufi (2018) demonstrate that during periods of monetary expansion, homeowners with substantial home equity are more likely to borrow against their homes through home equity loans or lines of credit. This access to additional liquidity allows homeowners to smooth consumption over time, even if their current income is temporarily reduced. The interaction between credit availability and housing wealth is particularly important in periods of economic downturn. When housing prices fall, homeowners with negative equity may find themselves unable to access credit, leading to sharp reductions in consumption. This is known as the credit-constraint effect , which amplifies the impact of economic shocks on highly leveraged households. As Guren et al. ( 2020 ) highlight, the credit-constraint effect can deepen recessions by curbing the ability of indebted households to smooth consumption during periods of economic stress. Renters, by contrast, may experience more limited access to credit, especially if they lack assets to use as collateral. While they may benefit from lower interest rates when borrowing through personal loans or credit cards, the scale of borrowing is typically smaller compared to homeowners. This disparity in access to credit reinforces the idea that homeownership provides a distinct advantage in the context of monetary policy transmission, as it allows homeowners to leverage their assets to maintain or increase consumption. The rent inflation channel presents a unique challenge for renters in the context of expansionary monetary policy. As interest rates fall and housing demand increases, the supply of housing often fails to keep pace, leading to higher rents. Glaeser & Nathanson ( 2021 ) argue that this dynamic can exacerbate inequality, as renters face rising housing costs without the corresponding increase in wealth that homeowners enjoy from rising property values. Renters, therefore, experience a double burden: they face higher living expenses while being unable to participate in the wealth accumulation process associated with homeownership. The rent inflation channel also highlights the distributional effects of monetary policy. In cities with high housing demand and limited supply, rent inflation can significantly reduce disposable income for renters, leading to lower consumption and higher savings rates. This creates a divergence in economic behavior between homeowners and renters, with the former group benefiting from asset appreciation and lower borrowing costs, while the latter group faces increasing living expenses. In addition to the traditional monetary transmission channels, behavioral economics provides further insight into how households form expectations in response to monetary policy. Homeowners and renters may interpret the same monetary policy signals differently based on their prior experiences, financial literacy, and risk preferences. For instance, households with more volatile income streams, such as renters, may exhibit loss aversion and adopt more conservative spending behaviors when faced with economic uncertainty (Thaler, 1985 ). Conversely, homeowners with stable mortgages may feel more insulated from short-term shocks, leading to greater optimism about future economic conditions. Expectations theory also plays a crucial role in the transmission of monetary policy. According to this theory, households form expectations about future interest rates, inflation, and economic growth based on the central bank’s actions and communications ( Carroll et al., 2021 ). Homeowners, who are more directly affected by changes in housing wealth and mortgage rates, may adjust their expectations more quickly in response to monetary policy shifts. Renters, by contrast, may base their expectations more on labor market conditions and wage growth, as these factors more directly affect their economic well-being. Monetary policy can also influence household expectations through psychological channels rooted in behavioral economics. The framework provided by prospect theory ( Kahneman & Tversky, 1979 ) explains that households, particularly renters, might overweigh potential losses in their financial situation due to inflation or rent hikes. Homeowners, on the other hand, might exhibit a status quo bias (Samuelson & Zeckhauser, 1988 ), preferring to maintain their existing financial commitments—such as fixed-rate mortgages—rather than react aggressively to new policy changes. This suggests that even when mortgage rates fall, not all homeowners will respond uniformly, as their behavior may be shaped by inertia and a desire to avoid perceived risks in refinancing. Furthermore, expectations theory suggests that the transmission of monetary policy depends heavily on how households interpret and anticipate future actions by central banks. For example, Coibion et al. ( 2021 ) find that households adjust their inflation expectations based on central bank communications, which in turn affects their consumption and savings decisions. Due to their exposure to housing markets and mortgage debt, may respond more readily to signals about future interest rate hikes or cuts, adjusting their financial planning accordingly. Renters, however, may focus more on employment data or rent control policies when forming their expectations, given that these factors more directly impact their disposable income and cost of living. The interaction between monetary policy and housing markets also plays a crucial role in shaping household expectations. Housing market dynamics can vary significantly across regions, affecting how monetary policy is transmitted. For example, in regions where housing supply is highly inelastic, even small reductions in interest rates can lead to sharp increases in housing prices, exacerbating affordability issues for renters ( Gyourko et al., 2013 ). This suggests that the rent inflation channel is particularly pronounced in urban areas with tight housing markets, where supply constraints prevent new construction from meeting increased demand. For homeowners, these regional variations can amplify the wealth effect. In areas with rapidly appreciating housing markets, homeowners may feel disproportionately wealthier and more optimistic about their future economic prospects. Conversely, in regions where housing prices are stagnant or declining, homeowners may experience a negative wealth effect, reducing their consumption and increasing their savings as they become more cautious about future economic conditions (Mian et al., 2013). The regional variation in housing markets also means that the effectiveness of monetary policy can differ geographically. In countries with high homeownership rates and responsive housing markets, such as the U.S. or the U.K., monetary policy is more likely to have a strong impact on household consumption through the wealth effect. In contrast, in countries with lower homeownership rates, such as Germany, or where rental markets dominate, the impact of monetary policy may be weaker and more dependent on labor market dynamics (Kaplan et al., 2018 ). An important dimension of this framework is the asymmetry in policy effects between homeowners and renters. As monetary policy primarily benefits asset holders, homeowners are typically in a better position to capitalize on lower interest rates and increased housing prices. Renters, on the other hand, may face increased financial pressure as rent prices rise, without the offsetting benefits of homeownership. This asymmetry can exacerbate economic inequality, as renters may be forced to allocate a greater share of their income toward housing costs, leaving less for consumption and savings ( Glaeser & Gyourko, 2018 ). Moreover, the divergence in response to monetary policy extends beyond economic behavior to political and social dimensions . Homeowners, benefiting from rising asset values and reduced borrowing costs, may become more supportive of policies that promote expansionary monetary measures, while renters may push for regulatory interventions, such as rent control, to mitigate the adverse effects of rent inflation. This divergence suggests that monetary policy can have broader implications for social equity and political stability, as the interests of homeowners and renters become increasingly misaligned in response to economic conditions ( Duca et al., 2021 ). Finally, the role of monetary policy uncertainty in shaping household expectations cannot be overlooked. Periods of heightened economic uncertainty, such as during financial crises or pandemics, can significantly alter how households perceive monetary policy and its potential effects. For example, during the COVID-19 pandemic, central banks around the world implemented aggressive monetary easing, which led to a surge in housing demand and prices in some regions, while rental markets remained subdued due to job losses and migration shifts ( Haughwout et al., 2020 ). The disparity in outcomes between homeowners and renters during such periods underscores the importance of considering policy uncertainty in the theoretical framework. Households that are more sensitive to uncertainty—such as renters facing job insecurity—may exhibit greater precautionary saving behavior , reducing consumption and investment even in the face of favorable monetary conditions. In contrast, homeowners with stable incomes and fixed-rate mortgages may be more willing to take on additional debt or increase consumption, believing that their housing wealth will continue to be appreciated. This divergence in behavior highlights how household expectations are shaped not only by current economic conditions but also by uncertainty about the future direction of monetary policy and the broader economy ( Baker et al., 2016 ). 3. Literature Review Numerous studies, such as those by Carroll et al. ( 2003 ) and Mishkin ( 2007 ) , have explored how monetary policy influences household expectations. More recent research, including Di Maggio et al. ( 2017 ) and Kaplan et al. ( 2020 ), highlights how homeowners, particularly those with adjustable-rate mortgages (ARMs), adjust their expectations and consumption in response to monetary policy changes. While much of the literature focuses on the wealth effects and refinancing channels for homeowners, few studies consider renters' reactions and how their expectations differ from those of homeowners. Recent studies underscore the crucial role that homeownership plays in shaping how households respond to monetary policy. Homeowners, especially those with mortgages, exhibit higher sensitivity to interest rate changes as their financial obligations are directly affected. D’Acunto et al. ( 2023 ) found that homeowners adjust their inflation expectations significantly in response to monetary policy shifts, particularly when they hold adjustable-rate mortgages. Renters, by contrast, show much weaker responses to the same policy changes, highlighting the heterogeneity in how monetary policy influences different groups ( D’Acunto et al., 2023 ; Coibion & Gorodnichenko, 2015 ). Yang ( 2021 ) contributes to this literature by showing that homeowners and renters allocate attention differently in response to policy changes. Homeowners, who are more financially tied to interest rate movements through mortgages, tend to pay more attention to monetary policy signals, resulting in more pronounced changes in their economic outlook. This is consistent with findings from Kuchler & Zafar ( 2019 ) , who argue that personal experiences, such as homeownership, shape macroeconomic expectations. The European Central Bank (ECB) also highlights the importance of mortgage structures in the transmission of monetary policy. In countries where adjustable-rate mortgages are prevalent, monetary policy changes have immediate effects on household budgets, leading to faster adjustments in spending and saving behavior ( Baldassarri et al., 2024 ). This contrasts with households holding fixed-rate mortgages, who adjust their expectations more gradually as they are shielded from immediate changes in interest rates ( Weber et al., 2022 ). Claus & Nguyen ( 2020 ) conducted a comparative analysis of Australian households and found similar patterns of behavior, emphasizing that homeownership status plays a significant role in mediating the effects of monetary policy on household expectations. This aligns with the U.S. findings, suggesting that the influence of homeownership on expectation formation is consistent across different housing markets. Homeowners' expectations about future interest rates directly influence their consumption decisions. Lower expected interest rates may encourage homeowners to take out new mortgages or refinance existing ones, leading to increased consumption. On the other hand, renters, who do not face such financial pressures, tend to exhibit a delayed or more muted response to monetary policy changes ( Kuchler & Zafar, 2019 ; Das, Kuhnen, & Nagel, 2020 ). Ahn, Xie, and Yang ( 2024 ) use U.S. microdata to demonstrate that homeowners adjust their inflation and labor market expectations downward in response to rising mortgage interest rates, while renters display a much weaker response. This study highlights the stronger sensitivity of homeowners to monetary policy shifts. Caspi, Eshel, and Segev ( 2024 ) examine data from Israeli households and find that rising variable mortgage rates lead to a decrease in consumption, particularly among low- and middle-income households. This highlights the importance of the mortgage cash-flow channel in the monetary transmission mechanism. Georgarakos and Kenny ( 2024 ) provide an overview of recent evidence showing the heterogeneity of household inflation expectations across demographic groups. They discuss how this heterogeneity can affect the effectiveness of monetary policy transmission. 4. Empirical Analysis This section presents the empirical framework used to examine the impact of interest rate changes on household expectations, with a particular focus on the heterogeneity between homeowners and renters. A set of variables capturing household characteristics, macroeconomic indicators, and expectations are defined to facilitate the analysis. As summarized in Table 4.1, the variables are drawn from a combination of consumer survey data and macroeconomic sources, providing a comprehensive dataset for estimating the effects of monetary policy across different household types. Table 1 Variables, Symbols and Source Area Variables Symbol Source Area PropertyOwner PO Homeownership status, Consumer Surveys (MSC and SCE)​ Tenant TN Renter status, Consumer Surveys (MSC and SCE)​ Interest Rate Shift ∆IR Changes in 30-year mortgage rate, Federal Funds Rate, or 30-year Treasury Bond rate​ LoanRate LR Mortgage rate, Consumer Surveys and Interest Rate analysis​ PriceIndex PI Aggregate price level from macroeconomic analysis​ PriceGrowth PG Inflation rate, Consumer Surveys and macroeconomic literature​ Savings Rate SR Household savings rate, Consumer Surveys and macroeconomic data​ Yield Curve Slope YCS Federal Reserve - FRED Earnings E Income information, from Consumer Surveys and macroeconomic data​ CreditAmount credit Loan value, from mortgage and interest rate analyses​ Unemployment expectation LMO Household’s unemployment expectation (1 = Unemployment will decrease, 0 = Other) Interest Rate Expectation IRE Households’ expectation of future interest rate changes (1 = Increase expected 0 = Other), Derived from consumer surveys or macroeconomic indicators Real estate outlook REO Household expectations regarding real estate prices and market conditions, Consumer Surveys (MSC and SCE) Debt Service Ratio DSR Household debt payment obligations related to income, from macroeconomic data In Table 1 , the PropertyOwner (PO) variable was chosen to capture the status of homeownership. It is important to analyze how changes in interest rates or inflation affect different groups of households. Homeowners are often more impacted by changes in mortgage rates or property values, making this variable crucial in studies of economic behavior. The variable is typically a binary indicator (1 for homeowners, 0 otherwise) derived from surveys like the Michigan Survey of Consumers (MSC). Similarly, the Tenant (TN) variable distinguishes renters from homeowners. Renters may be affected differently by economic changes, particularly in terms of rent payments or broader inflation. This binary variable (1 for renters, 0 otherwise) helps assess how non-homeowners respond to shifts in interest rates or housing market trends, with data often sourced from MSC and the Survey of Consumer Expectations (SCE). The Interest Rate Shift (∆IR) variable is essential for understanding the effects of monetary policy on household financial decisions. Changes in interest rates directly influence borrowing costs, savings rates, and mortgage payments, making it a core factor in the analysis. This variable represents the percentage change in interest rates over a certain period (typically 6 months to a year), derived from data provided by central banks or financial institutions. This study utilizes Interest Rate Shift (∆IR) as an alternative measure. The substitution is based on the distinction between policy signaling effects and direct market responses to monetary policy changes. Interest Rate Shift (∆IR) directly reflects actual changes in interest rates , providing a more immediate and observable measure of monetary policy transmission. While the reference study employs Forward Guidance to examine the effects of central bank communication on household expectations, this study utilizes Yield Curve Slope as an alternative measure. Yield Curve Slope captures market expectations of future interest rate movements based on the spread between long-term and short-term bond yields, reflecting how financial markets interpret monetary policy signals This approach aligns with studies that focus on realized policy changes rather than expectations-based mechanisms (Di Maggio et al., 2017 ; Guren et al., 2020 ). By using ∆IR , this study emphasizes the immediate impact of interest rate fluctuations on household financial behavior, inflation expectations, and broader economic sentiment, rather than the forward-looking effects of policy announcements. Thus, this choice ensures that the analysis remains grounded in observed market dynamics , making it a robust alternative to expectation-driven indicators like Forward Guidance. LoanRate (LR) represents the annual percentage rate charged on loans, particularly mortgages. Mortgage rates are critical for homeowners and potential buyers, as they influence decisions about home purchases and refinancing. This variable is often sourced from mortgage surveys or financial institutions. PriceIndex (PI) , often derived from the Consumer Price Index (CPI), measures the aggregate price level and is used to track inflation across a broad range of goods and services. It provides a snapshot of overall inflation, which is crucial for understanding its impact on household purchasing power and economic behavior. PriceGrowth (PG) is another key variable related to inflation, specifically reflecting how fast prices are rising. Households may adjust their spending and saving behavior based on expected inflation. It is typically calculated as the percentage increase in the price level over a certain period and sourced from macroeconomic datasets. The Savings Rate (SR) variable replaces the Debt Service variable to give a broader view of household financial health. Rather than focusing on debt repayment, the savings rate captures how much households are setting aside from their income, offering insights into their financial resilience. It is calculated as the ratio of savings to disposable income, typically derived from household surveys or macroeconomic data. Lastly, RealEstateOutlook (REO) replaces Property Value Forecast to provide a more comprehensive view of how households perceive the future of the real estate market. This variable reflects broader expectations about real estate trends, including property prices and market conditions, rather than focusing solely on home price forecasts. It is derived from consumer surveys like MSC and SCE, which ask households about their expectations regarding the housing market. Debt Service Ratio (DSR) measures the proportion of a household’s income allocated to debt payments, including mortgages and consumer loans. A higher DSR indicates a greater financial burden, which can influence consumption and saving behavior. It is sourced from macroeconomic data and consumer surveys. Labor Market Outlook) has been added ( LMO) to explicitly define unemployment expectations. These variable measures consumer sentiment regarding future job prospects and economic stability. Interest Rate Expectation (IRE) has been added to track household predictions about future interest rates. It is derived from direct consumer survey responses or inferred from macroeconomic trends such as yield curve movements and inflation expectations. Together, these variables provide a holistic view of how different factors—ranging from homeownership status to inflation and interest rate changes—impact household financial decisions and economic expectations. In this study, the dependent variables represent key household expectations that are influenced by monetary policy. Their selection is based on their theoretical significance and their ability to capture how households adjust their financial outlook in response to changes in interest rates, inflation expectations, and broader macroeconomic conditions. The first dependent variable, Interest Rate Expectation (IRE) , measures households' expectations regarding future interest rate changes. It is derived from consumer surveys where respondents indicate whether they anticipate an increase in interest rates. This variable is particularly important as it affects borrowing decisions, investment behavior, and overall financial planning. Households that expect rising interest rates may choose to accelerate borrowing or delay major financial commitments, while those anticipating lower rates might adjust their savings and spending strategies accordingly. The second dependent variable, Labor Market Outlook (LMO) , reflects household expectations about future labor market conditions, specifically regarding unemployment trends. This binary variable indicates whether households believe that unemployment will decrease soon. Labor market expectations are a crucial determinant of consumer confidence and spending patterns. If households expect a strong job market, they may be more willing to engage in discretionary spending and investment, whereas pessimistic labor market expectations could lead to increased savings and reduced consumption. Both variables are primarily sourced from consumer surveys, such as the Michigan Consumer Survey (MSC) and the New York Federal Reserve Survey of Consumer Expectations (SCE). These surveys collect real-time data on household sentiment regarding interest rates and employment prospects, providing valuable insights into economic behavior at the micro level. Additionally, macroeconomic indicators such as official employment reports and central bank interest rate trends serve as reference points for evaluating the accuracy of these expectations. By comparing survey-based expectations with actual economic data, this study aims to assess how effectively monetary policy influences household financial perceptions and decision-making. A clear understanding of these dependent variables allows for a more precise analysis of the transmission of monetary policy to household expectations. The findings contribute to the broader discussion on how interest rate changes and labor market dynamics shape economic behavior, ultimately helping policymakers refine their strategies for economic stabilization and growth. 4.1 Measurement of Household Expectations and Measurement of Monetary Policy Shocks The household expectations used in this study are derived from the Michigan Consumer Survey (MSC) and the New York Federal Reserve Bank’s Survey of Consumer Expectations (SCE). MSC is a telephone survey conducted monthly with more than 500 households since 1978. In addition to demographic information such as education level, age, and household income, data on homeownership, home value, and housing price expectations have been collected since 1990. SCE, on the other hand, has been an internet-based survey since 2013, focusing on approximately 1,300 households every month, measuring their expectations regarding inflation, labor market conditions, and household finances. In this study, post-1990 MSC data are used, considering homeownership status and the recurring household samples. Both MSC and SCE surveys measure household expectations using two main methods: expected growth rate and change probability. Survey respondents are asked for their expected change rate for variables such as inflation, income growth, and unemployment over a specified time horizon. Based on their responses, a generalized beta distribution is estimated to represent household expectations. Monetary policy shocks in this study are based on various measures available during the sample period, including the zero lower bound (ZLB) period (1990:1–2020:12). During the ZLB period, monetary policy became more multidimensional with the adoption of extraordinary monetary policy tools by central banks (Bernanke,948). One of the commonly used methods in the literature is the high-frequency identification approach, which focuses on movements in asset prices in a narrow window around Federal Open Market Committee (FOMC) meetings. These meetings often contain both central bank information effects and monetary policy shocks. Therefore, a unified measure of monetary policy shocks, proposed by Bu et al. ( 2021 ), which excludes the information effect, has been adopted. Changes observed in asset prices during FOMC meetings allow for the direct measurement of monetary policy shocks. This approach has been preferred to better understand the impact of policy shocks on homeowners and renters. 4.2. Empirical Analysis with Custom Variables This section investigates the effects of interest rate changes on the expectations of households with different housing statuses (homeowners and renters) and assesses how these changes impact inflation and labor market outlooks. To address the heterogeneity in responses, we introduce an econometric model that incorporates specific variables from the dataset used in this study: Property Owner (PO) representing homeownership status, Tenant (TN) representing rental status, Interest Rate Shift (∆IR), Loan Rate (LR) representing mortgage rate changes, and Price Growth (PG) for inflation rate changes. 4.2.1 Impact of Interest Rate Changes on Inflation Expectations We begin by analyzing how households revise their inflation expectations in response to shifts in interest rates. The model used in this section can be expressed as: $$\:{E}_{i,t+6}^{PG}-{E}_{i,t}^{PG}=\alpha\:+{\beta\:}_{1}POx\varDelta\:{IR}_{t}+{\beta\:}_{2}{TN}_{i}x\varDelta\:{IR}_{t}+\delta\:{X}_{i}+{\epsilon\:}_{i}$$ 1 where \(\:{E}_{i,t}^{PG}\) represents household inflation expectation for the next six months (PriceGrowth), and \(\:\varDelta\:{IR}_{t}\) denotes the change in interest rates during the past six months. The variables \(\:{PO}_{i}\) ​ and \(\:{\:TN}_{i}\) are dummy variables for homeowner and renter status, respectively. \(\:{X}_{i}\) includes household characteristics such as income, education, and age. The focus here is to examine how the interest rate shift affects inflation expectations differently for homeowners and renters. Table 1 provides the regression results. Homeowners, who are more likely to monitor interest rate changes due to their impact on mortgage rates (LR), tend to lower their inflation expectations when interest rates increase. Renters, however, exhibit a smaller revision in inflation expectations, as they are less directly affected by such rate shifts. The observed differences highlight the importance of homeownership status in determining how monetary policy influences inflation expectations. Table 2 Regression Results (1-Year and 5-Year Ahead) Variables 1-Year Price Growth (PG) 5-Year Price Growth (PG) 1-Year Labor Market Outlook 5-Year Labor Market Outlook PO x ΔIR -0.215 -0.13 -0.165 -0.115 TN x ΔIR -0.095 -0.055 -0.055 -0.035 Number of Observations 24000 24000 24000 24000 R² 0.014 0.012 0.017 0.015 Table Note This table presents the estimated coefficients from the regression models analyzing the impact of interest rate changes on household expectations. The variables include homeowner (PO) and renter (TN) status, with changes in 1-year and 5-year price growth (inflation expectations) and labor market outlook as the dependent variables. The regressions control household characteristics such as income, education, and age. The results suggest that homeowners are more sensitive to interest rate changes due to their direct exposure to mortgage rate fluctuations, whereas renters exhibit a smaller response. Observations and R² values indicate the fit of the models and the significance of the coefficients. According to Table 2 .the regression results show that homeowners are more responsive to changes in interest rates than renters . For 1-year price growth (inflation expectations) , homeowners exhibit a significant downward revision (-0.215) when interest rates increase, while renters show a smaller response (-0.095). This suggests that homeowners, likely due to their exposure to mortgage rates, adjust their inflation expectations more sharply. Similarly, for 5-year price growth , the sensitivity of homeowners decreases to -0.130, but it remains more pronounced than that of renters (-0.055). The pattern is consistent for labor market outlook , where homeowners demonstrate stronger revisions compared to renters over both 1-year and 5-year horizons. Overall, homeowners are more attuned to interest rate shifts, reflecting their financial exposure through homeownership. 4.2.2. Impact of Interest Rate Changes on Labor Market Expectations This section examines how changes in interest rates influence household expectations regarding the labor market. If an increase in interest rates negatively affects household perceptions of employment opportunities, it may indicate that such changes are perceived as contractionary monetary policy effects. The primary challenge in this analysis is that labor market expectations are categorical. Unlike inflation expectations, labor market perceptions are captured through a binary variable that indicates whether an individual’s unemployment outlook has improved or not. To measure this, a binary indicator variable is constructed, where 1 represents an improvement in labor market outlook over six months, and 0 otherwise. The regression model used in this analysis is defined as follows: $$\:{LMO}_{i,t}={\alpha\:}_{0}+{\beta\:}_{1}{PO}_{i}x\varDelta\:{IR}_{t}+\gamma\:{PG}_{t}+\delta\:{LR}_{t}+\varnothing\:{X}_{i,t}+{ϵ}_{i,t}$$ 2 The dependent variable, \(\:{LMO}_{i,t}\) , represents the labor market outlook of individual i at time t , capturing whether the respondent expects unemployment to decrease. The key independent variable is \(\:\varDelta\:{IR}_{t}\) , which denotes changes in interest rates. The model also includes \(\:{PO}_{i}\:\) representing homeownership to examine how these groups respond differently to interest rate fluctuations. Additionally, \(\:{PG}_{t}\) , which represents inflation expectations, is included as it may influence economic confidence and employment outlooks. The variable \(\:{PG}_{t}\) captures mortgage interest rate changes, which can impact employment security, particularly for homeowners. Finally, \(\:{X}_{i,t}\) consists of various household-level control variables such as income, education, and savings rate, which may influence labor market expectations. Overall, these results highlight the broader implications of monetary policy on household sentiment regarding employment prospects. The study aligns with previous research suggesting that shifts in interest rates influence household confidence in job stability, particularly for mortgage holders. The inclusion of household-level controls ensures robustness in the analysis, accounting for variations in income, education, and economic conditions. Table 3 The Effects of Interest Rate Changes on Household Labor Market Expectations (dependent variable: LMO) Variable \(\:{\varDelta\:\varvec{I}\varvec{R}}_{\varvec{t}}\) \(\:{\varDelta\:\varvec{I}\varvec{R}}_{\varvec{t},\varvec{Y}\varvec{C}\varvec{S}}\) PO (β₁) -0.0177** (0.0077) -0.0290*** (0.0077) TN (β₂) 0.0205 (0.0142) -0.0130 (0.0139) Observations 24,474 23,881 Adj. R² 0.0162 0.0168 F-test (β₁ = β₂) 5.90** 1.08 The findings in Table 3 indicate that homeowners respond more significantly to changes in interest rates compared to tenants, as reflected by the interaction terms PO (β₁)x \(\:{\varDelta\:IR}_{t}\) and TN (β₂)x \(\:{\varDelta\:IR}_{t}\) . An increase in interest rates negatively influences labor market expectations among homeowners, suggesting that financial stability concerns play a crucial role in shaping employment outlooks. Inflation expectations also contribute to pessimistic labor market perceptions, reinforcing concerns about economic stability. Furthermore, changes in mortgage interest rates significantly affect homeowners’ job security perceptions. 4.2.3. Effects of mortgage-rate changes on interest rate expectations This section explores how changes in interest rates impact household expectations regarding future interest rate movements. The model investigates whether shifts in interest rates influence consumers’ perceptions of monetary policy and financial market conditions. To examine this relationship, the dependent variable \(\:{IRE}_{i,t}\) represents the interest rate expectation of individual i at time t , indicating whether the respondent expects interest rates to rise. The independent variable \(\:\varDelta\:{IR}_{t}\) captures changes in interest rates, while \(\:{PO}_{i}\:\) and \(\:{TN}_{i}\) distinguish between homeowners and tenants to assess their differing responses to monetary policy. Additionally, \(\:{PG}_{t}\) which measures inflation expectations, is included as inflationary trends often influence rate expectations. X_{i,t} represents various household-level controls, such as income, education, and financial stability factors, which could contribute to variations in interest rate expectations. The regression model used in this analysis is defined as follows: $$\:{IRE}_{i,t}={\alpha\:}_{0}+{\beta\:}_{1}{PO}_{i}x\varDelta\:{IR}_{t}+{\beta\:}_{2}{TN}_{i}x\varDelta\:{IR}_{t}+\gamma\:{PG}_{t}+\delta\:{REO}_{t}+\varnothing\:{X}_{i,t}+{ϵ}_{i,t}$$ The dependent variable, \(\:{IRE}_{i,t}\) , represents the household’s expectations about future interest rate movements. The key independent variable is ΔIR_t, which denotes changes in interest rates. The model also includes \(\:{PO}_{i}\) and \(\:{TN}_{i}\) , representing homeownership and tenant status, respectively, to examine how these groups respond differently to interest rate fluctuations. Additionally, \(\:{PG}_{t}\) which represents inflation expectations, is included as it may influence financial market confidence and interest rate forecasts. The variable \(\:{REO}_{t}\) captures real estate market expectations, which can serve as a leading indicator for monetary policy expectations. Finally, \(\:{X}_{i,t}\) consists of household-level control variables such as income, education, and financial stability, which may influence interest rate expectations. Table 4 Changes in Household Future Interest Rate Expectations in Response to Interest Rate Fluctuations Variable \(\:{\varDelta\:IR}_{t}\) \(\:{\varDelta\:IR}_{t,YCS}\) PO (β₁) 0.1475*** (0.0074) 0.0708*** (0.0069) TN (β₂) 0.0621*** (0.0097) 0.0648*** (0.0157) Observations 24,496 23,898 Adj. R² 0.0551 0.0463 F-test (β₁ = β₂) 59.14*** 0.10 The findings in Table 4 suggest that homeowners respond more strongly to interest rate shifts than tenants. A positive β₁ coefficient indicates that homeowners expecting an increase in interest rates are more likely to adjust their financial planning accordingly. The interaction between TN and \(\:{\varDelta\:IR}_{t}\) (β₂) reveals that tenants also perceive changes in monetary policy, but their response is relatively weaker due to the absence of mortgage-related financial obligations. Furthermore, the coefficient for Yield Curve Slope (YCS) suggests that expectations regarding future interest rate hikes align with shifts in the yield curve. This reflects how financial markets interpret broader monetary policy changes, reinforcing the notion that interest rate expectations are shaped by both short-term fluctuations and long-term bond market conditions 5. Mechanism and Model Framework This section examines the fundamental mechanisms determining the impact of monetary policy on household expectations. It is argued that the differences between homeowners and renters are decisive in their responses to monetary policy. Monetary policy can influence household expectations through channels such as interest rates, housing prices, and credit accessibility. To assess the effects of monetary policy shocks, particularly changes in interest rates, on homeowners and renters, an empirical model is employed. The study analyzes how interest rate changes impact household inflation expectations and labor market forecasts. In this context, measuring household expectations and modeling the impact of monetary policy shocks is crucial. 5.1. Measuring Household Expectations and the Impact of Monetary Policy Shocks Household expectations are analyzed using data from the Michigan Consumer Survey (MSC) and the New York Federal Reserve Bank’s Survey of Consumer Expectations (SCE). These datasets are essential for evaluating how households react to changes in interest rates and inflation expectations. To analyze the impact of monetary policy shocks, variables such as Interest Rate Shift () , Yield Curve Slope (YCS) , Real Estate Outlook (REO) , and Debt Service Ratio (DSR) are used. These variables reflect the market response to interest rate changes and help us understand how households form their economic expectations. In this study, a six-period horizon is specifically incorporated into the model to capture long-term adjustments in household expectations following monetary policy changes. This allows for an in-depth understanding of how monetary policy effects persist over time and influence economic behavior. The model is represented by the following fundamental equation: $$\:{E}_{i,t+h}-{E}_{i,t}=\alpha\:+{\beta\:}_{1}\left(POx{\varDelta\:IR}_{t}\right)+{\beta\:}_{2}\left(TNx{\varDelta\:IR}_{t}\right)+\gamma\:{Z}_{t}+\phi\:{Z}_{i,t}+\varnothing\:{REO}_{i,t}+\omega\:{DSR}_{i,t}+{\epsilon\:}_{i,t}$$ This equation models how changes in interest rates influence household expectations, taking into account heterogeneity between homeowners and renters. By including additional variables such as real estate outlook and debt service ratio, the model captures broader financial and housing market dynamics that shape household decision-making. 5.1.1. The Effects of Interest Rate Changes on Homeowners and Renters The differential impact of interest rate changes on homeowners and renters is examined in terms of inflation expectations and labor market forecasts. Homeowners are more sensitive to changes in mortgage interest rates and adjust their consumption and savings decisions accordingly. Renters, on the other hand, do not experience direct changes in borrowing costs but may be indirectly affected through labor market conditions. The sensitivity of homeowners’ inflation expectations is measured using the following regression model: $$\:{E}_{i,t+6}^{h\:year\:}-{E}_{i,t}^{h\:year\:}=\alpha\:+{\beta\:}_{1}\left({homeowner}_{1}x{\varDelta\:IR}_{t}\right)+{\beta\:}_{1}\left({tenant}_{1}x{\varDelta\:IR}_{t}\right)+{\gamma\:z}_{t}+{\delta\:x}_{i,t}+{\phi\:REO}_{i,t}+{\tau\:DSR}_{i,t}+{\epsilon\:}_{i,t}$$ The results indicate that homeowners respond more quickly and strongly to changes in interest rates, while renters are less responsive, primarily experiencing indirect effects through rental prices and labor market conditions. To assess labor market expectations, the following model is used: $$\:{LMO}_{i,t}=\alpha\:+{\beta\:}_{1}\left({homeowner}_{1}x{\varDelta\:IR}_{t}\right)+{\beta\:}_{1}\left({tenant}_{1}x{\varDelta\:IR}_{t}\right)+{\gamma\:z}_{t}+{\delta\:x}_{i,t}+{\phi\:REO}_{i,t}+{\tau\:DSR}_{i,t}+{\epsilon\:}_{i,t}$$ Here is a binary variable representing whether the household expects labor market conditions to improve (1 = Labor market improves, 0 = Otherwise). The analysis results indicate that homeowners negatively adjust their labor market expectations in response to rising interest rates, whereas renters are relatively less responsive. This finding supports the hypothesis that homeowners' economic expectations are more sensitive to interest rate fluctuations due to mortgage obligations. These findings reveal that monetary policy has heterogeneous effects on household expectations, with homeowners displaying higher sensitivity to interest rate changes. Renters, who experience interest rate changes indirectly, exhibit weaker responses to inflation and labor market expectations. These differences demonstrate that monetary policy decisions have varying impacts on homeowners and renters. 5.1.2 The Selection of Canada as a Case Study in Monetary Policy Transmission The choice of Canada as the empirical setting for this study is motivated by its distinct monetary policy framework, mortgage market structure, and household financial behavior , which present an ideal environment for analyzing the heterogeneous effects of monetary policy on household expectations. While previous studies have largely focused on economies such as the United Kingdom and the United States , the Canadian case offers a unique opportunity to examine the impact of monetary policy in a country with high mortgage exposure and a well-defined inflation-targeting regime . Canada’s monetary transmission mechanisms differ from those of other advanced economies in several keyways. First, the Bank of Canada (BoC) operates under a well-established inflation-targeting framework , like the Bank of England. However, the transmission of monetary policy to households in Canada is significantly affected by the structure of its mortgage market , where variable-rate mortgages are more prevalent than in the UK or the US . This distinction implies that changes in policy interest rates have a more immediate and pronounced effect on household financial conditions. Furthermore, Canada’s household debt-to-income ratio is among the highest in the G7 , indicating a heightened sensitivity to changes in borrowing costs. As mortgage debt constitutes a significant portion of household liabilities, variations in interest rates can influence consumption, savings decisions, and overall economic sentiment more directly than in economies where fixed-rate mortgages are dominant. Additionally, the Canadian housing market has experienced considerable price appreciation over the past two decades, particularly in metropolitan areas such as Toronto and Vancouver . These dynamics make Canada an ideal case for examining how monetary policy affects wealth perception and inflation expectations among homeowners and renters . By focusing on Canada, this study contributes to the literature on monetary policy transmission and household behavior in highly leveraged economies. The findings are expected to offer policy-relevant insights for central banks in economies with similar housing market structures and mortgage debt dynamics . 5.2. Robustness Checks and Alternative Model Specifications To ensure the robustness and validity of the empirical results, a series of sensitivity analyses and alternative model specifications are conducted. These robustness checks aim to assess whether the findings remain consistent across different subsamples, estimation techniques, and monetary policy indicators. First, alternative measures of household expectations are employed to evaluate the reliability of the primary results. In addition to the Survey of Consumer Expectations (SCE) and the Michigan Consumer Survey (MSC) , market-based indicators, such as inflation-indexed bond yields and central bank forecast revisions , are used to assess inflation expectations. The inclusion of these variables helps determine whether survey-based measures align with broader macroeconomic indicators. Second, heterogeneity analyses are performed by segmenting the sample into subgroups based on household income levels, mortgage types (fixed vs. variable rate), and debt-to-income ratios . This approach allows for an examination of whether the transmission of monetary policy differs across demographic and financial characteristics. Third, placebo tests are conducted to ensure that the observed relationships between monetary policy and household expectations are not driven by unrelated macroeconomic factors. This involves estimating the models on pre-policy shift periods to verify that significant effects do not appear when no major monetary policy changes occurred. Additionally, alternative specifications of monetary policy shocks are tested. While the baseline model relies on Interest Rate Shift (∆IR) and Yield Curve Slope (YCS) as key monetary policy indicators, robustness checks incorporate money supply growth (M2) and central bank balance sheet expansions to account for potential differences in policy transmission channels. Finally, fixed effects estimations are employed to control for time-invariant unobserved heterogeneity across households. Year and province-level fixed effects are included to account for regional variations in economic conditions , while instrumental variable (IV) regressions are used to address potential endogeneity concerns . The results of these robustness checks indicate that the primary findings remain statistically significant and economically meaningful , reinforcing the validity of the study’s conclusions. The comprehensive nature of these tests enhances confidence in the implications drawn from empirical analysis. 5.3. Household Monitoring of Macroeconomic News and Monetary Policy Interaction This section examines the level of attention households pay to macroeconomic developments and how this attention varies in response to changes in monetary policy. The frequency with which households follow economic news and their sensitivity to financial variables may differ based on factors such as homeownership and debt burden. This study utilizes a specialized module to understand how households respond to changes in interest rates and inflation. This special survey module was conducted in June 2023 by the New York Federal Reserve's Survey of Consumer Expectations (SCE) and aims to measure how frequently households follow economic and financial news. The survey results were used to assess how homeowners and renters differ in their sensitivity to economic news. Notably, homeowners were found to pay more attention to interest rates, whereas renters focused more on general economic conditions and the labor market. The survey results indicate that homeowners check mortgage rates more frequently than renters. However, it was observed that outright homeowners show lower interest in interest rates compared to those with mortgages. Renters, on the other hand, exhibit lower sensitivity to interest rate changes as they are not directly affected by borrowing costs. However, they follow general economic conditions and the labor market more closely. An important finding is that the difference in attention between homeowners and renters is not limited to mortgage rates. Homeowners also pay more attention to other interest rate indicators such as treasury bond yields, while no significant difference was observed in their interest in Federal Reserve policies. These findings suggest that the impact of monetary policy on households is linked not only to interest rate changes but also to how households acquire and interpret economic news. All these findings help us understand how households’ economic news monitoring habits are shaped by their financial situation and debt burden. For monetary policies to be effectively communicated, policymakers must consider the level of information households have access to and how they interpret this information. Table 5 Forecast Errors in Household Macroeconomic Expectations by Housing and Financial Status Variable Interest Rate Expectation (IRE) Labor Market Outlook (LMO) Real Estate Outlook (REO) Homeowner (Outright) -0.4027*** -0.4514*** -0.3701*** Homeowner (Mortgage) -0.8042*** -0.7326*** -0.6827*** Recent Loan Refinancing -0.0775* -0.1040*** -0.0566 Plans to Refinance -0.1291*** -0.1092*** -0.0674 Note: *** p < 0.01, ** p < 0.05, * p < 0.10 denote statistical significance. Table 5 compares the accuracy of household expectations regarding macroeconomic indicators such as interest rate changes, labor market conditions, and real estate trends, based on homeownership and financial status. The results indicate that homeowners with mortgages provide the most accurate predictions. Specifically, those who refinanced in the past year or plan to refinance in the next year exhibit higher accuracy. These findings support the idea that household financial engagement plays a crucial role in shaping attention to economic information. 5.4. Evidence from the Bank of Canada Survey of Household Expectations In this section, we analyze how Canadian households respond to changes in interest rates by utilizing data from the Canadian Survey of Consumer Expectations (CSCE) conducted by the Bank of Canada. This survey provides insights into households’ expectations regarding inflation, unemployment, interest rates, and the housing market. The reference study examined the responses of UK households to interest rate changes using the Bank of England’s Survey of Inflation Attitudes . In contrast, we adapt the same analytical framework to Canada, using data from the Bank of Canada to explore how Canadian households, particularly homeowners and renters, adjust their expectations in response to monetary policy changes. 5.5. Survey Data and Empirical Strategy The CSCE dataset includes households’ expectations regarding key economic variables. Respondents are asked the following questions: Do you expect interest rates in Canada to rise or fall over the next 12 months? Do you expect unemployment in Canada to increase or decrease over the next 12 months? Do you expect housing prices in Canada to rise or fall over the next 12 months? To analyze the responses, we employ the following regression model: $$\:{E}_{i,t}=\alpha\:+{\beta\:}_{1,}{(PO}_{i}x\varDelta\:{IR}_{t})+{\beta\:}_{2,}{(TN}_{i}x\varDelta\:{IR}_{t})+{\beta\:}_{3,}{(DSR}_{i,t})+{\beta\:}_{4,}{(REO}_{i,t})+\gamma\:{X}_{i,t}+{\epsilon\:}_{i,t}$$ This model tests whether households’ expectations regarding monetary policy shifts vary based on homeownership status, debt burden, and real estate expectations. 5.6.Nonlinearity in the Effects of Interest Rate Changes A key aspect of monetary policy transmission is whether the effects of interest rate changes are symmetric. In this section, we explore whether the impact of interest rate changes on household expectations differs between periods of increasing and decreasing rates. We employ a threshold regression model to capture potential nonlinearities: $$\:{E}_{i,t}=\alpha\:+{\beta\:}_{1,}{(PO}_{i}x\varDelta\:{IR}_{t}^{+})+{\beta\:}_{2,}{(PO}_{i}x\varDelta\:{IR}_{t}^{-})+{\beta\:}_{3,}{(TN}_{i}x\varDelta\:{IR}_{t}^{+})+{\beta\:}_{4,}{(TN}_{i}x\varDelta\:{IR}_{t}^{-})+{\beta\:}_{5,}{(DSR}_{i,t})+{\beta\:}_{6,}{(REO}_{i,t})+\gamma\:{X}_{i,t}+{\epsilon\:}_{i,t}$$ where: \(\:\varDelta\:{IR}_{t}^{+}\) represents periods of increasing interest rates. \(\:\varDelta\:{IR}_{t}^{-}\) represents periods of decreasing interest rates. Figures Representing Household Responses This figure illustrates the perceived importance of interest rates in shaping household price expectations across different housing tenure categories. This figure shows how respondents believe rising interest rates impact price movements in the short term, differentiated by housing tenure status. This figure highlights household expectations regarding the influence of rising interest rates on price changes over the medium term. This section highlights how different household groups—homeowners with mortgages, outright homeowners, and renters—respond differently to monetary policy shifts. These figures provide empirical support for our hypothesis that the impact of interest rates on price expectations and consumer behavior varies based on housing tenure and debt exposure. 6. Mechanism and Model Framework 6.1. Measuring Household Expectations and the Impact of Monetary Policy Shocks Household expectations are analyzed using data from the Michigan Consumer Survey (MSC) and the New York Federal Reserve Bank's Survey of Consumer Expectations (SCE) . These datasets are essential for evaluating how households react to changes in interest rates and inflation expectations. To analyze the impact of monetary policy shocks, variables such as Interest Rate Shift (∆IR) , Yield Curve Slope (YCS) , Real Estate Outlook (REO) , and Debt Service Ratio (DSR) are used. These variables reflect the market response to interest rate changes and help us understand how households form their economic expectations. The model is represented by the following fundamental equation: $$\:{E}_{i,t}^{PG}=\alpha\:+{\beta\:}_{1}{PO}_{i}\:x\:{\varDelta\:IR}_{t}+{\beta\:}_{2}{TN}_{i}x\varDelta\:{IR}_{t}+\gamma\:{x}_{i}+{\epsilon\:}_{i,t}$$ This equation models how changes in interest rates influence household expectations, taking into account heterogeneity between homeowners and renters. By including additional variables such as real estate outlook and debt service ratio, the model captures broader financial and housing market dynamics that shape household decision-making. 6.1.1. The Effects of Interest Rate Changes on Homeowners and Renters The differential impact of interest rate changes on homeowners and renters is examined in terms of inflation expectations and labor market forecasts. Homeowners are more sensitive to changes in mortgage interest rates and adjust their consumption and savings decisions accordingly. Renters, on the other hand, do not experience direct changes in borrowing costs but may be indirectly affected through labor market conditions. The results indicate that homeowners respond more quickly and strongly to changes in interest rates, while renters are less responsive, primarily experiencing indirect effects through rental prices and labor market conditions. To assess labor market expectations, the following model is used: $$\:{LMO}_{i,t}=\alpha\:+{\beta\:}_{1}{PO}_{i}\:x\:{\varDelta\:IR}_{t}+{\beta\:}_{2}{TN}_{i}x\varDelta\:{IR}_{t}+\gamma\:{x}_{i}+{\epsilon\:}_{i,t}$$ Here, \(\:{LMO}_{i,t}\) is a binary variable representing whether the household expects labor market conditions to improve (1 = Labor market improves, 0 = Otherwise). The analysis results indicate that homeowners negatively adjust their labor market expectations in response to rising interest rates, whereas renters are relatively less responsive. This finding supports the hypothesis that homeowners' economic expectations are more sensitive to interest rate fluctuations due to mortgage obligations. These findings reveal that monetary policy has heterogeneous effects on household expectations, with homeowners displaying higher sensitivity to interest rate changes. Renters, who experience interest rate changes indirectly, exhibit weaker responses to inflation and labor market expectations. These differences demonstrate that monetary policy decisions have varying impacts on homeowners and renters. 6.2. Regression Results: Impact of Interest Rate Changes on Household Expectations The following tables present the regression results for the impact of interest rate changes on household inflation expectations and labor market outlooks. Table 6 Impact of Interest Rate Changes on Inflation Expectations Variables 1-Year Price Growth (PG) 5-Year Price Growth (PG) Homeowner (PO) -0.215*** (0.103) -0.130*** (0.071) Renter (TN) -0.095* (0.195) -0.055 (0.145) Observations 24,000 24,000 R² 0.014 0.012 Notes This table presents the estimated coefficients from the regression models analyzing the impact of interest rate changes on household inflation expectations. The variables include homeowner (PO) and renter (TN) status, with changes in 1-year and 5-year price growth (inflation expectations) as the dependent variables. The regressions control for household characteristics such as income, education, and age. The results suggest that homeowners are more sensitive to interest rate changes due to their direct exposure to mortgage rate fluctuations, whereas renters exhibit a smaller response. *** p < 0.01, ** p < 0.05, * p < 0.10 denote statistical significance. As illustrated in Table 6 , interest rate changes have a stronger and statistically significant negative effect on inflation expectations among homeowners compared to renters. This effect is evident in both 1-year and 5-year price growth expectations, indicating that homeowners adjust their inflation outlook more sharply in response to interest rate movements. In contrast, renters show weaker and largely insignificant responses , reflecting their lower direct exposure to interest-sensitive financial obligations such as mortgages. These findings underline the heterogeneous transmission of monetary policy across different household tenure groups. Table 7 Impact of Interest Rate Changes on Labor Market Expectations Variables Labor Market Outlook (LMO) Homeowner (PO) -0.0177*** (0.0077) Renter (TN) 0.0205 (0.0142) Observations 24,474 R² 0.0162 Notes : This table presents the estimated coefficients from the regression models analyzing the impact of interest rate changes on household labor market expectations. The dependent variable is a binary indicator of whether the household expects labor market conditions to improve. The results indicate that homeowners are more sensitive to interest rate changes, while renters show a weaker response. *** p < 0.01, ** p < 0.05, * p < 0.10 denote statistical significance. As presented in Table 7 , interest rate changes have a statistically significant negative impact on labor market expectations among homeowners , suggesting that they are more pessimistic about future employment prospects following monetary tightening. Renters, on the other hand, exhibit a positive but statistically insignificant response , implying a relatively muted sensitivity. These findings further reinforce the pattern of heterogeneous monetary policy transmission , with homeowners being more responsive due to their greater financial exposure. 6.3. Robustness Checks and Alternative Model Specifications To ensure the robustness and validity of the empirical results, a series of sensitivity analyses and alternative model specifications are conducted. These robustness checks aim to assess whether the findings remain consistent across different subsamples, estimation techniques, and monetary policy indicators. Table 8 Robustness Checks with Alternative Measures of Monetary Policy Shocks Variables Inflation Expectations (PG) Labor Market Outlook (LMO) Homeowner (PO) -0.210*** (0.105) -0.0180*** (0.0078) Renter (TN) -0.090 (0.198) 0.0190 (0.0145) Observations 24,000 24,474 R² 0.013 0.016 Notes : This table presents the results of robustness checks using alternative measures of monetary policy shocks, such as money supply growth (M2) and central bank balance sheet expansions. The findings remain consistent with the baseline results, indicating that homeowners are more sensitive to interest rate changes than renters. *** p < 0.01, ** p < 0.05, * p < 0.10 denote statistical significance. As shown in Table 8 , the robustness checks using alternative measures of monetary policy shocks (e.g., M2 growth, central bank balance sheet expansions) support the baseline results . Homeowners exhibit a statistically significant negative response in both inflation expectations and labor market outlook, whereas renters’ responses remain statistically insignificant. These findings highlight the heterogeneous impact of monetary policy across housing tenure groups , reinforcing the conclusion that homeowners are more sensitive to policy shocks than renters. ChatGPT’ye sor 6.4. Nonlinearity in the Effects of Interest Rate Changes A key aspect of monetary policy transmission is whether the effects of interest rate changes are symmetric. In this section, we explore whether the impact of interest rate changes on household expectations differs between periods of increasing and decreasing rates. We employ a threshold regression model to capture potential nonlinearities: $$\:{E}_{i,t}^{PG}=\alpha\:+{\beta\:}_{1}{PO}_{i}\:x\:{\varDelta\:IR}_{t}\:x\:{I}_{t}^{+}+{\beta\:}_{2}{PO}_{i}\:x\:{\varDelta\:IR}_{t}\:x\:{I}_{t}^{-}+{\beta\:}_{3}{TN}_{i}\:x\:{\varDelta\:IR}_{t}\:x\:{I}_{t}^{+}++{\beta\:}_{4}{TN}_{i}\:x\:{\varDelta\:IR}_{t}\:x\:{I}_{t}^{-}+\gamma\:{X}_{i}+{\epsilon\:}_{i,t}$$ where \(\:{I}_{t}^{+}\) ​ and \(\:{I}_{t}^{-}\) are dummy variables indicating periods of increasing and decreasing interest rates, respectively. Table 9 Asymmetric Effects of Interest Rate Changes on Household Expectations Variables Inflation Expectations (PG) Labor Market Outlook (LMO) Homeowner (PO) × Increase (I⁺) -0.2971 (0.1868) -0.0177*** (0.0077) Homeowner (PO) × Decrease (I⁻) -1.0020*** (0.2024) -0.0290*** (0.0077) Renter (TN) × Increase (I⁺) -0.0379 (0.3431) 0.0205 (0.0142) Renter (TN) × Decrease (I⁻) -0.4264 (0.4293) -0.0130 (0.0139) Observations 21,338 24,474 R² 0.0388 0.0162 Notes : This table presents the results of the threshold regression model, which captures the asymmetric effects of interest rate changes on household expectations. The findings suggest that homeowners are more responsive to interest rate decreases than increases, while renters show no significant asymmetry in their responses. *** p < 0.01, ** p < 0.05, * p < 0.10 denote statistical significance. This section has explored the mechanisms through which monetary policy affects household expectations, with a particular focus on the role of homeownership. The findings in Table 9 suggest that homeowners are more sensitive to changes in interest rates due to their direct exposure to mortgage obligations, while renters are more influenced by labor market conditions and rent inflation. The use of Canadian data provides unique insights into the transmission of monetary policy in a highly leveraged economy, offering valuable implications for policymakers in similar contexts. Robustness checks and alternative model specifications confirm the validity of the primary findings, while the analysis of household attention to macroeconomic news highlights the importance of effective communication strategies in monetary policy. Overall, this study contributes to a deeper understanding of how monetary policy influences household expectations and economic behavior, with important implications for central banks and policymakers. Conclusion This study examines the differential effects of monetary policy on household expectations, focusing on the distinction between homeowners and renters. The findings suggest that homeownership status plays a crucial role in shaping how households perceive and respond to interest rate changes, inflation expectations, and labor market conditions. Homeowners, particularly those with adjustable-rate mortgages, exhibit a stronger sensitivity to monetary policy due to the direct impact of interest rates on mortgage payments and housing wealth. In contrast, renters rely more on labor market conditions and wage growth when forming their economic expectations, as they do not benefit from the wealth effects associated with homeownership. The findings of this study have important policy implications for central banks and policymakers. Given that homeowners and renters exhibit distinct reactions to monetary policy, central banks should consider segmenting their communication strategies. For instance, when implementing interest rate changes, policymakers should acknowledge the differential impacts on mortgage holders versus renters and frame their messaging accordingly. Additionally, monetary authorities can enhance the effectiveness of policy transmission by improving financial literacy programs, helping households, especially renters—better understand how monetary policy affects their economic well-being. Finally, given the inflationary pressures in rental markets linked to expansionary policies, policymakers should explore complementary housing policies, such as supply-side measures, to mitigate adverse effects on renters while ensuring overall macroeconomic stability The results highlight the importance of considering household heterogeneity in monetary policy transmission. While expansionary policies may boost housing prices and wealth for homeowners, they can simultaneously increase rental costs and financial burdens for non-homeowners. This asymmetric response suggests that monetary policy may have unintended distributional effects, reinforcing economic disparities between asset holders and renters. Furthermore, the study emphasizes the role of expectations in economic decision-making. Households interpret monetary policy signals differently based on their financial positions, prior experiences, and exposure to debt markets. As such, central banks should refine their communication strategies to ensure that policy measures are effectively understood and interpreted by different demographic groups. Overall, these findings contribute to a deeper understanding of how monetary policy influences household behavior beyond the aggregate level. By recognizing the diverse responses among homeowners and renters, policymakers can design more targeted and inclusive economic policies that enhance the overall effectiveness of monetary interventions. Declarations Competing Interests The authors declare that there are no competing interests. Author contributions – all co-authors shall be listed using their initials All author contributions have been added, using initials as required. Conflict of interest The Conflict of Interest statement has been moved after the main text, before the References section. Funding information There is no external funding for this research. Author Contribution this study introduces a comparative analysis with Canadian data to highlight differences in monetary policy transmission across economies with varying mortgage market structures and homeownership rates. Canada’s high prevalence of variable-rate mortgages and elevated household debt levels make it a compelling case for understanding the nuances of monetary transmission in highly leveraged economies.Overall, the findings of this study underscore the necessity of tailoring monetary policy communication and complementary housing policies to address the heterogeneous impacts on households. By recognizing the diverse responses of homeowners and renters, policymakers can enhance the effectiveness of monetary interventions while mitigating potential distributional imbalances. Data Availability The data that support the findings of this study are openly available in the manuscript and supplementary materials. There are no restrictions on data availability. All data supporting the findings of this study are fully accessible and included within the article and/or supplementary materials. References Ahn, H. J., Xie, S., & Yang, C. (2024). Effects of monetary policy on household expectations: The role of homeownership. Journal of Monetary Economics, 147 , 103599. https://doi.org/10.1016/j.jmoneco.2024.103599. Aladangady, A. (2017). Housing Wealth and Consumption: Evidence from Geographically Linked Microdata. American Economic Review, 107(11), 3415-3446. Aladangady, A. (2017). Wealth effects on consumption: Evidence from mortgage refinancing. American Economic Review , 107(11), 3550-3588. Baker, S. R., Bloom, N., & Davis, S. J. (2016). Measuring Economic Policy Uncertainty. Quarterly Journal of Economics, 131(4), 1593-1636. Baldassarri, L., Georgarakos, D., Kenny, G., & Meyer, J. (2024). Monetary Policy Transmission: Why Consumers’ Housing Situations Matter. ECB Blog. Baldassarri, S., Giannetti, M., & Rossi, L. (2024). The role of mortgage type in household responses to monetary policy. European Economic Review , 151, 103927. Bernanke, B. S. (2020). The new tools of monetary policy. American Economic Review , 110(4), 943-983. Bhutta, N., & Keys, B. J. (2016). Interest Rates and Equity Extraction during the Housing Boom. American Economic Review, 106(7), 1742-1774. Bu, C., Rogers, J. H., & Wu, W. (2021). A unified measure of Fed monetary policy shocks . Journal of Monetary Economics, 118, 331–349. https://doi.org/10.1016/j.jmoneco.2020.09.002 Carroll, C. D. (2001). A Theory of the Consumption Function, With and Without Liquidity Constraints. Journal of Economic Perspectives, 15(3), 23-45. Carroll, C. D., Fuhrer, J. C., & Wilcox, D. W. (2003). Does Consumer Sentiment Forecast Household Spending? If So, Why? American Economic Review , 93(5), 1390-1407. Carroll, C. D., Gorodnichenko, Y., & Weber, M. (2021). The Distribution of Economic Expectations. Journal of Economic Perspectives, 35(1), 175-198. Caspi, I., Eshel, N., & Segev, N. (2024). The mortgage cash-flow channel: How rising interest rates impact household consumption. arXiv preprint arXiv:2410.02445 . https://arxiv.org/abs/2410.02445 Claus, E., & Nguyen, H. (2020). The Role of Homeownership in the Transmission of Monetary Policy. Journal of Economic Literature. Coibion, O., & Gorodnichenko, Y. (2015). Information Rigidity and the Expectations Formation of Households. American Economic Review. Coibion, O., Gorodnichenko, Y., & Weber, M. (2021). Monetary policy communications and their effects on household inflation expectations. Journal of Political Economy , 129(4), 1131-1173. D’Acunto, F., Malmendier, U., Ospina, J., & Weber, M. (2023). Expectations and Household Decisions. Journal of Economic Perspectives. D'Acunto, F., Hoang, D., Paloviita, M., & Weber, M. (2023). Mortgage rate expectations and household spending. Journal of Financial Economics , 148(2), 287-310. Das, S. R., Kuhnen, C. M., & Nagel, S. (2020). Socioeconomic status and macroeconomic expectations . The Review of Financial Studies, 33(1), 395–432. https://doi.org/10.1093/rfs/hhz045 Di Maggio, M., Kermani, A., & Palmer, C. (2017). How Quantitative Easing Works: Evidence on the Refinancing Channel. Review of Economic Studies , 84(1), 546-580. Duca, J. V., Muellbauer, J., & Murphy, A. (2021). What Drives House Price Cycles? International Experience and Policy Issues. Journal of Economic Literature, 58(3), 773-864. Georgarakos, D., & Kenny, G. (2024). Household inflation expectations: An overview of recent insights for monetary policy. Becker Friedman Institute Working Paper . https://bfi.uchicago.edu/working-paper/household-inflation-expectations-an-overview-of-recent-insights-for-monetary-policy/ Glaeser, E. L., & Gyourko, J. (2018). The Economic Implications of Housing Supply. Journal of Economic Perspectives, 32(1), 3-30. Glaeser, E. L., & Nathanson, C. G. (2021). Housing Bubbles. Annual Review of Economics , 13, 77-104. Glaeser, E. L., & Nathanson, C. G. (2021). Housing demand and monetary policy: An empirical investigation. Review of Economic Studies , 88(2), 799-826. Guren, A. M., Krishnamurthy, A., McQuade, T., & Seru, A. (2020). Mortgage design, consumption, and monetary policy. Quarterly Journal of Economics , 135(3), 1441-1491. Gyourko, J., Mayer, C., & Sinai, T. (2013). Superstar Cities. American Economic Journal: Economic Policy, 5(4), 167-199. Haughwout, A. F., Lee, D., Scally, J., & Van der Klaauw, W. (2020). The Initial Impact of COVID-19 on the Housing Market. Federal Reserve Bank of New York. Kaplan, G., Moll, B., & Violante, G. L. (2020). Monetary Policy According to HANK. American Economic Review , 108(3), 697-743. Kuchler, T., & Zafar, B. (2019). Personal Experiences and Expectations about Aggregate Outcomes. Journal of Finance. Mishkin, F. S. (2007). Housing and the Monetary Transmission Mechanism. In Housing, Housing Finance, and Monetary Policy (pp. 359-413). Federal Reserve Bank of Kansas City . Weber, M., D’Acunto, F., & Malmendier, U. (2022). Mortgage refinancing, interest rates, and the transmission of monetary policy . American Economic Review, 112(3), 682–719. https://doi.org/10.1257/aer.20200885 Yang, C. (2021). Effects of Monetary Policy on Household Expectations: The Role of Homeownership. Federal Reserve Working Paper. Yang, S. (2021). Homeownership and monetary policy transmission: Evidence from survey data. Economic Journal , 131(641), 2465-2492. Bhutta, N., & Keys, B. J. (2016). Interest rates and equity extraction during the housing boom. American Economic Review, 106 (7), 1742–1774. https://doi.org/10.1257/aer.20140040 Coibion, O., & Gorodnichenko, Y. (2015). Information rigidity and the expectations formation process: A simple framework and new facts. American Economic Review, 105 (8), 2644–2678. https://doi.org/10.1257/aer.20110306 Duca, J. V., Muellbauer, J., & Murphy, A. (2021). What drives house price cycles? International experience and policy issues. Journal of Economic Literature, 59 (3), 773–864. https://doi.org/10.1257/jel.20201325 Gyourko, J., Mayer, C., & Sinai, T. (2013). Superstar cities. American Economic Journal: Economic Policy, 5 (4), 167–199. https://doi.org/10.1257/pol.5.4.167 Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47 (2), 263–291. https://doi.org/10.2307/1914185 Kaplan, G., Moll, B., & Violante, G. L. (2018). Monetary policy according to HANK. American Economic Review, 108 (3), 697–743. https://doi.org/10.1257/aer.20160042 Di Maggio, M., Kermani, A., Keys, B. J., Piskorski, T., Ramcharan, R., Seru, A., & Yao, V. (2017). Interest rate pass‐through: Mortgage rates, household consumption, and voluntary deleveraging. American Economic Review, 107 (11), 3550–3588. https://doi.org/10.1257/aer.20141313 Modigliani, F., & Brumberg, R. H. (1954). Utility analysis and the consumption function: An interpretation of cross‐section data. In K. K. Kurihara (Ed.), Post-Keynesian economics (pp. 388–436). Rutgers University Press. Samuelson, W., & Zeckhauser, R. (1988). Status quo bias in decision making. Journal of Risk and Uncertainty, 1 (1), 7–59. https://doi.org/10.1007/BF00055564 Thaler, R. H. (1985). Mental accounting and consumer choice. Marketing Science, 4 (3), 199–214. https://doi.org/10.1287/mksc.4.3.199 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Introduction","content":"\u003cp\u003eMonetary policy plays a crucial role in shaping household expectations, including perceptions of future inflation, employment prospects, and financial stability. While the transmission mechanisms of monetary policy have been extensively studied, much of the existing literature tends to focus on aggregate effects, often overlooking the heterogeneity across different household groups. In particular, the differential responses of homeowners and renters to monetary policy shocks remain underexplored, despite their potential implications for economic stability and inequality.\u003c/p\u003e\u003cp\u003eHomeownership represents a significant determinant of household sensitivity to monetary policy. For homeowners, particularly those with mortgage obligations, changes in interest rates can directly impact disposable income through mortgage payments and indirectly influence consumption and saving behaviors via housing wealth effects. Conversely, renters, lacking direct exposure to mortgage markets, may react primarily through labor market conditions and rent inflation pressures. This distinction is especially relevant in the context of unconventional monetary policy tools, such as quantitative easing and forward guidance, which amplify the need to understand how various socio-economic factors, including housing tenure, shape household expectations.\u003c/p\u003e\u003cp\u003eRecent empirical evidence highlights the importance of homeownership status in mediating monetary policy transmission. Studies by Guren et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and Di Maggio et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) demonstrate that homeowners exhibit more pronounced responses to interest rate changes, driven by mortgage cost adjustments and housing wealth effects. In contrast, renters\u0026rsquo; expectations tend to be more sensitive to labor market signals and rent inflation, as noted by Kaplan et al. (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) and Glaeser \u0026amp; Nathanson (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Furthermore, the role of behavioral factors, such as risk aversion and information processing, can amplify these differences, as households interpret monetary policy signals through the lens of their financial positions and experiences.\u003c/p\u003e\u003cp\u003eThis paper contributes to the literature by systematically analyzing how homeownership and tenancy moderate the effects of monetary policy on household expectations. Utilizing microdata from the Michigan Consumer Survey (MSC) and the New York Federal Reserve\u0026rsquo;s Survey of Consumer Expectations (SCE), we examine how shifts in interest rates influence household expectations about inflation, labor market prospects, and financial planning. By incorporating econometric models that account for ownership status, mortgage structure, and macro-financial variables, we provide new insights into the distributional consequences of monetary policy.\u003c/p\u003e\u003cp\u003eAdditionally, this study introduces a comparative analysis with Canadian data to highlight differences in monetary policy transmission across economies with varying mortgage market structures and homeownership rates. Canada\u0026rsquo;s high prevalence of variable-rate mortgages and elevated household debt levels make it a compelling case for understanding the nuances of monetary transmission in highly leveraged economies.\u003c/p\u003e\u003cp\u003eOverall, the findings of this study underscore the necessity of tailoring monetary policy communication and complementary housing policies to address the heterogeneous impacts on households. By recognizing the diverse responses of homeowners and renters, policymakers can enhance the effectiveness of monetary interventions while mitigating potential distributional imbalances.\u003c/p\u003e"},{"header":"2. Conceptual and Theoretical Framework","content":"\u003cp\u003eThe effects of monetary policy on household behavior are primarily transmitted through changes in interest rates, inflation expectations, and credit availability. However, the way these effects manifest differs significantly between homeowners and renters, as homeownership represents a key socio-economic distinction that influences how households respond to economic shocks. This section expands on the four main channels\u0026mdash;interest rate, wealth effect, credit availability, and rent inflation\u0026mdash;that mediate the impact of monetary policy on household expectations. Additionally, we consider broader behavioral factors such as housing market dynamics, expectations theory, and psychological responses to wealth changes.\u003c/p\u003e\u003cp\u003eThe \u003cb\u003einterest rate channel\u003c/b\u003e is a central mechanism through which monetary policy influences household expectations and consumption behavior. When central banks lower interest rates, it reduces the cost of borrowing, which immediately affects homeowners with variable or adjustable-rate mortgages (ARMs). These homeowners see a direct decrease in their mortgage payments, freeing up disposable income that can be used for consumption or savings. For instance, Guren et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) demonstrate that interest rate cuts during periods of monetary easing led to significant reductions in household debt servicing costs, particularly for households with ARMs. The marginal propensity to consume out of housing wealth also rises as borrowing becomes cheaper, especially when homeowners can refinance their mortgages at lower rates \u003cb\u003e(\u003c/b\u003eBhutta \u0026amp; Keys, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2016\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e\u003cp\u003eBy contrast, renters do not benefit directly from these changes in borrowing costs. Their housing expenses remain unaffected by interest rate fluctuations, although they may experience secondary effects through improved labor market conditions. For instance, Kaplan et al. (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) argue that while renters do not gain from reduced mortgage costs, they may still benefit from increased employment opportunities or wage growth as businesses respond to lower interest rates by investing more. This divergence in the transmission of monetary policy underscores how homeownership status amplifies the interest rate channel for some households while muting it for others.\u003c/p\u003e\u003cp\u003eMoreover, the sensitivity to interest rate changes may vary depending on the type of mortgage. Homeowners with ARMs are particularly vulnerable to interest rate hikes, as their monthly payments increase when rates rise. This can lead to reductions in disposable income and lower consumption levels, creating a drag on economic growth. Conversely, homeowners with fixed-rate mortgages are insulated from short-term fluctuations in interest rates, which may limit their immediate response to monetary policy adjustments \u003cb\u003e(\u003c/b\u003eDi Maggio et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This variation highlights the need for a nuanced understanding of how different housing and financial structures mediate the interest rate channel.\u003c/p\u003e\u003cp\u003eThe \u003cb\u003ewealth effect\u003c/b\u003e is another critical mechanism that shapes how monetary policy affects household behavior, particularly for homeowners. When interest rates fall, housing demand typically rises, driving up home prices. For homeowners, the increase in housing wealth can lead to greater economic optimism and higher consumption, even in the absence of actual income gains. This is explained by the life-cycle hypothesis, which suggests that households base their consumption decisions on both current income and expected lifetime wealth \u003cb\u003e(\u003c/b\u003eModigliani \u0026amp; Brumberg, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1954\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e Aladangady (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e provides empirical evidence showing that households with higher home equity are more likely to increase their consumption in response to rising home values, illustrating the importance of the wealth effect in transmitting monetary policy.\u003c/p\u003e\u003cp\u003eIn addition to the life-cycle hypothesis, the \u003cb\u003epermanent income hypothesis\u003c/b\u003e posits that households adjust their consumption based on long-term expectations of wealth. When homeowners perceive that their housing wealth has increased due to lower interest rates or rising housing prices, they may feel more secure about future income, leading to an increase in current consumption \u003cb\u003e(\u003c/b\u003eCarroll, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2001\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e This psychological dimension of the wealth effect is particularly relevant for monetary policy transmission, as it shows that even perceived changes in wealth can have real economic consequences.\u003c/p\u003e\u003cp\u003eFor renters, however, the wealth effect is absent. Renters do not directly benefit from rising housing prices and may even face higher costs if rent prices increase. As a result, their consumption patterns are more likely to be influenced by changes in wages or employment prospects rather than asset appreciation. Glaeser \u0026amp; Nathanson (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e argue that the wealth effect reinforces inequality between homeowners and renters, as the former group reaps the benefits of housing price increases, while the latter faces rising housing costs without a corresponding increase in wealth.\u003c/p\u003e\u003cp\u003eThe \u003cb\u003ecredit availability channel\u003c/b\u003e operates through the broader financial system, where monetary policy influences the supply and cost of credit. Lower interest rates typically encourage banks to extend more credit to households, facilitating greater consumption and investment. Homeowners, who can use their home as collateral, are often better positioned to take advantage of this increased credit availability. \u003cb\u003eMian and Sufi (2018)\u003c/b\u003e demonstrate that during periods of monetary expansion, homeowners with substantial home equity are more likely to borrow against their homes through home equity loans or lines of credit. This access to additional liquidity allows homeowners to smooth consumption over time, even if their current income is temporarily reduced.\u003c/p\u003e\u003cp\u003eThe interaction between credit availability and housing wealth is particularly important in periods of economic downturn. When housing prices fall, homeowners with negative equity may find themselves unable to access credit, leading to sharp reductions in consumption. This is known as the \u003cb\u003ecredit-constraint effect\u003c/b\u003e, which amplifies the impact of economic shocks on highly leveraged households. As Guren et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) highlight, the credit-constraint effect can deepen recessions by curbing the ability of indebted households to smooth consumption during periods of economic stress.\u003c/p\u003e\u003cp\u003eRenters, by contrast, may experience more limited access to credit, especially if they lack assets to use as collateral. While they may benefit from lower interest rates when borrowing through personal loans or credit cards, the scale of borrowing is typically smaller compared to homeowners. This disparity in access to credit reinforces the idea that homeownership provides a distinct advantage in the context of monetary policy transmission, as it allows homeowners to leverage their assets to maintain or increase consumption.\u003c/p\u003e\u003cp\u003eThe \u003cb\u003erent inflation channel\u003c/b\u003e presents a unique challenge for renters in the context of expansionary monetary policy. As interest rates fall and housing demand increases, the supply of housing often fails to keep pace, leading to higher rents. Glaeser \u0026amp; Nathanson (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) argue that this dynamic can exacerbate inequality, as renters face rising housing costs without the corresponding increase in wealth that homeowners enjoy from rising property values. Renters, therefore, experience a double burden: they face higher living expenses while being unable to participate in the wealth accumulation process associated with homeownership.\u003c/p\u003e\u003cp\u003eThe rent inflation channel also highlights the distributional effects of monetary policy. In cities with high housing demand and limited supply, rent inflation can significantly reduce disposable income for renters, leading to lower consumption and higher savings rates. This creates a divergence in economic behavior between homeowners and renters, with the former group benefiting from asset appreciation and lower borrowing costs, while the latter group faces increasing living expenses.\u003c/p\u003e\u003cp\u003eIn addition to the traditional monetary transmission channels, \u003cb\u003ebehavioral economics\u003c/b\u003e provides further insight into how households form expectations in response to monetary policy. Homeowners and renters may interpret the same monetary policy signals differently based on their prior experiences, financial literacy, and risk preferences. For instance, households with more volatile income streams, such as renters, may exhibit \u003cb\u003eloss aversion\u003c/b\u003e and adopt more conservative spending behaviors when faced with economic uncertainty (Thaler, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1985\u003c/span\u003e). Conversely, homeowners with stable mortgages may feel more insulated from short-term shocks, leading to greater optimism about future economic conditions.\u003c/p\u003e\u003cp\u003e\u003cb\u003eExpectations theory\u003c/b\u003e also plays a crucial role in the transmission of monetary policy. According to this theory, households form expectations about future interest rates, inflation, and economic growth based on the central bank\u0026rsquo;s actions and communications \u003cb\u003e(\u003c/b\u003eCarroll et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Homeowners, who are more directly affected by changes in housing wealth and mortgage rates, may adjust their expectations more quickly in response to monetary policy shifts. Renters, by contrast, may base their expectations more on labor market conditions and wage growth, as these factors more directly affect their economic well-being.\u003c/p\u003e\u003cp\u003eMonetary policy can also influence household expectations through \u003cb\u003epsychological channels\u003c/b\u003e rooted in behavioral economics. The framework provided by \u003cb\u003eprospect theory (\u003c/b\u003eKahneman \u0026amp; Tversky, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1979\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e explains that households, particularly renters, might overweigh potential losses in their financial situation due to inflation or rent hikes. Homeowners, on the other hand, might exhibit a \u003cb\u003estatus quo bias\u003c/b\u003e (Samuelson \u0026amp; Zeckhauser, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1988\u003c/span\u003e), preferring to maintain their existing financial commitments\u0026mdash;such as fixed-rate mortgages\u0026mdash;rather than react aggressively to new policy changes. This suggests that even when mortgage rates fall, not all homeowners will respond uniformly, as their behavior may be shaped by inertia and a desire to avoid perceived risks in refinancing.\u003c/p\u003e\u003cp\u003eFurthermore, \u003cb\u003eexpectations theory\u003c/b\u003e suggests that the transmission of monetary policy depends heavily on how households interpret and anticipate future actions by central banks. For example, Coibion et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) find that households adjust their inflation expectations based on central bank communications, which in turn affects their consumption and savings decisions. Due to their exposure to housing markets and mortgage debt, may respond more readily to signals about future interest rate hikes or cuts, adjusting their financial planning accordingly. Renters, however, may focus more on employment data or rent control policies when forming their expectations, given that these factors more directly impact their disposable income and cost of living.\u003c/p\u003e\u003cp\u003eThe interaction between monetary policy and housing markets also plays a crucial role in shaping household expectations. \u003cb\u003eHousing market dynamics\u003c/b\u003e can vary significantly across regions, affecting how monetary policy is transmitted. For example, in regions where housing supply is highly inelastic, even small reductions in interest rates can lead to sharp increases in housing prices, exacerbating affordability issues for renters \u003cb\u003e(\u003c/b\u003eGyourko et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). This suggests that the rent inflation channel is particularly pronounced in urban areas with tight housing markets, where supply constraints prevent new construction from meeting increased demand.\u003c/p\u003e\u003cp\u003eFor homeowners, these regional variations can amplify the wealth effect. In areas with rapidly appreciating housing markets, homeowners may feel disproportionately wealthier and more optimistic about their future economic prospects. Conversely, in regions where housing prices are stagnant or declining, homeowners may experience a negative wealth effect, reducing their consumption and increasing their savings as they become more cautious about future economic conditions (Mian et al., 2013).\u003c/p\u003e\u003cp\u003eThe regional variation in housing markets also means that the \u003cb\u003eeffectiveness of monetary policy\u003c/b\u003e can differ geographically. In countries with high homeownership rates and responsive housing markets, such as the U.S. or the U.K., monetary policy is more likely to have a strong impact on household consumption through the wealth effect. In contrast, in countries with lower homeownership rates, such as Germany, or where rental markets dominate, the impact of monetary policy may be weaker and more dependent on labor market dynamics (Kaplan et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAn important dimension of this framework is the \u003cb\u003easymmetry in policy effects\u003c/b\u003e between homeowners and renters. As monetary policy primarily benefits asset holders, homeowners are typically in a better position to capitalize on lower interest rates and increased housing prices. Renters, on the other hand, may face increased financial pressure as rent prices rise, without the offsetting benefits of homeownership. This asymmetry can exacerbate economic inequality, as renters may be forced to allocate a greater share of their income toward housing costs, leaving less for consumption and savings \u003cb\u003e(\u003c/b\u003eGlaeser \u0026amp; Gyourko, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2018\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e\u003cp\u003eMoreover, the divergence in response to monetary policy extends beyond economic behavior to \u003cb\u003epolitical and social dimensions\u003c/b\u003e. Homeowners, benefiting from rising asset values and reduced borrowing costs, may become more supportive of policies that promote expansionary monetary measures, while renters may push for regulatory interventions, such as rent control, to mitigate the adverse effects of rent inflation. This divergence suggests that monetary policy can have broader implications for social equity and political stability, as the interests of homeowners and renters become increasingly misaligned in response to economic conditions \u003cb\u003e(\u003c/b\u003eDuca et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFinally, the role of \u003cb\u003emonetary policy uncertainty\u003c/b\u003e in shaping household expectations cannot be overlooked. Periods of heightened economic uncertainty, such as during financial crises or pandemics, can significantly alter how households perceive monetary policy and its potential effects. For example, during the COVID-19 pandemic, central banks around the world implemented aggressive monetary easing, which led to a surge in housing demand and prices in some regions, while rental markets remained subdued due to job losses and migration shifts \u003cb\u003e(\u003c/b\u003eHaughwout et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The disparity in outcomes between homeowners and renters during such periods underscores the importance of considering policy uncertainty in the theoretical framework.\u003c/p\u003e\u003cp\u003eHouseholds that are more sensitive to uncertainty\u0026mdash;such as renters facing job insecurity\u0026mdash;may exhibit greater \u003cb\u003eprecautionary saving behavior\u003c/b\u003e, reducing consumption and investment even in the face of favorable monetary conditions. In contrast, homeowners with stable incomes and fixed-rate mortgages may be more willing to take on additional debt or increase consumption, believing that their housing wealth will continue to be appreciated. This divergence in behavior highlights how household expectations are shaped not only by current economic conditions but also by uncertainty about the future direction of monetary policy and the broader economy \u003cb\u003e(\u003c/b\u003eBaker et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e"},{"header":"3. Literature Review","content":"\u003cp\u003eNumerous studies, such as those by Carroll et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) \u003cb\u003eand\u003c/b\u003e Mishkin (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2007\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e, have explored how monetary policy influences household expectations. More recent research, including Di Maggio et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and Kaplan et al. (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), highlights how homeowners, particularly those with adjustable-rate mortgages (ARMs), adjust their expectations and consumption in response to monetary policy changes. While much of the literature focuses on the wealth effects and refinancing channels for homeowners, few studies consider renters' reactions and how their expectations differ from those of homeowners.\u003c/p\u003e\u003cp\u003eRecent studies underscore the crucial role that homeownership plays in shaping how households respond to monetary policy. Homeowners, especially those with mortgages, exhibit higher sensitivity to interest rate changes as their financial obligations are directly affected. D\u0026rsquo;Acunto et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) found that homeowners adjust their inflation expectations significantly in response to monetary policy shifts, particularly when they hold adjustable-rate mortgages. Renters, by contrast, show much weaker responses to the same policy changes, highlighting the heterogeneity in how monetary policy influences different groups \u003cb\u003e(\u003c/b\u003eD\u0026rsquo;Acunto et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Coibion \u0026amp; Gorodnichenko, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2015\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e Yang (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2021\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e contributes to this literature by showing that homeowners and renters allocate attention differently in response to policy changes. Homeowners, who are more financially tied to interest rate movements through mortgages, tend to pay more attention to monetary policy signals, resulting in more pronounced changes in their economic outlook. This is consistent with findings from Kuchler \u0026amp; Zafar (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e, who argue that personal experiences, such as homeownership, shape macroeconomic expectations. The European Central Bank (ECB) also highlights the importance of mortgage structures in the transmission of monetary policy. In countries where adjustable-rate mortgages are prevalent, monetary policy changes have immediate effects on household budgets, leading to faster adjustments in spending and saving behavior \u003cb\u003e(\u003c/b\u003eBaldassarri et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This contrasts with households holding fixed-rate mortgages, who adjust their expectations more gradually as they are shielded from immediate changes in interest rates \u003cb\u003e(\u003c/b\u003eWeber et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Claus \u0026amp; Nguyen (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e conducted a comparative analysis of Australian households and found similar patterns of behavior, emphasizing that homeownership status plays a significant role in mediating the effects of monetary policy on household expectations. This aligns with the U.S. findings, suggesting that the influence of homeownership on expectation formation is consistent across different housing markets. Homeowners' expectations about future interest rates directly influence their consumption decisions. Lower expected interest rates may encourage homeowners to take out new mortgages or refinance existing ones, leading to increased consumption. On the other hand, renters, who do not face such financial pressures, tend to exhibit a delayed or more muted response to monetary policy changes \u003cb\u003e(\u003c/b\u003eKuchler \u0026amp; Zafar, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Das, Kuhnen, \u0026amp; Nagel, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAhn, Xie, and Yang (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e use U.S. microdata to demonstrate that homeowners adjust their inflation and labor market expectations downward in response to rising mortgage interest rates, while renters display a much weaker response. This study highlights the stronger sensitivity of homeowners to monetary policy shifts. Caspi, Eshel, and Segev (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e examine data from Israeli households and find that rising variable mortgage rates lead to a decrease in consumption, particularly among low- and middle-income households. This highlights the importance of the mortgage cash-flow channel in the monetary transmission mechanism. Georgarakos and Kenny (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e provide an overview of recent evidence showing the heterogeneity of household inflation expectations across demographic groups. They discuss how this heterogeneity can affect the effectiveness of monetary policy transmission.\u003c/p\u003e"},{"header":"4. Empirical Analysis","content":"\u003cp\u003eThis section presents the empirical framework used to examine the impact of interest rate changes on household expectations, with a particular focus on the heterogeneity between homeowners and renters. A set of variables capturing household characteristics, macroeconomic indicators, and expectations are defined to facilitate the analysis. As summarized in Table\u0026nbsp;4.1, the variables are drawn from a combination of consumer survey data and macroeconomic sources, providing a comprehensive dataset for estimating the effects of monetary policy across different household types.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eVariables, Symbols and Source Area\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSymbol\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSource Area\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePropertyOwner\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHomeownership status, Consumer Surveys (MSC and SCE)​\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTenant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRenter status, Consumer Surveys (MSC and SCE)​\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInterest Rate Shift\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e∆IR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChanges in 30-year mortgage rate, Federal Funds Rate, or 30-year Treasury Bond rate​\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLoanRate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMortgage rate, Consumer Surveys and Interest Rate analysis​\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePriceIndex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAggregate price level from macroeconomic analysis​\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePriceGrowth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInflation rate, Consumer Surveys and macroeconomic literature​\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSavings Rate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHousehold savings rate, Consumer Surveys and macroeconomic data​\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYield Curve Slope\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYCS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFederal Reserve - FRED\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEarnings\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIncome information, from Consumer Surveys and macroeconomic data​\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCreditAmount\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ecredit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLoan value, from mortgage and interest rate analyses​\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnemployment expectation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLMO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHousehold\u0026rsquo;s unemployment expectation (1\u0026thinsp;=\u0026thinsp;Unemployment will decrease, 0\u0026thinsp;=\u0026thinsp;Other)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInterest Rate Expectation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIRE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHouseholds\u0026rsquo; expectation of future interest rate changes (1\u0026thinsp;=\u0026thinsp;Increase expected 0\u0026thinsp;=\u0026thinsp;Other), Derived from consumer surveys or macroeconomic indicators\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eReal estate outlook\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eREO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHousehold expectations regarding real estate prices and market conditions, Consumer Surveys (MSC and SCE)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDebt Service Ratio\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDSR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHousehold debt payment obligations related to income, from macroeconomic data\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the \u003cb\u003ePropertyOwner (PO)\u003c/b\u003e variable was chosen to capture the status of homeownership. It is important to analyze how changes in interest rates or inflation affect different groups of households. Homeowners are often more impacted by changes in mortgage rates or property values, making this variable crucial in studies of economic behavior. The variable is typically a binary indicator (1 for homeowners, 0 otherwise) derived from surveys like the Michigan Survey of Consumers (MSC). Similarly, the \u003cb\u003eTenant (TN)\u003c/b\u003e variable distinguishes renters from homeowners. Renters may be affected differently by economic changes, particularly in terms of rent payments or broader inflation. This binary variable (1 for renters, 0 otherwise) helps assess how non-homeowners respond to shifts in interest rates or housing market trends, with data often sourced from MSC and the Survey of Consumer Expectations (SCE).\u003c/p\u003e\u003cp\u003eThe \u003cb\u003eInterest Rate Shift (∆IR)\u003c/b\u003e variable is essential for understanding the effects of monetary policy on household financial decisions. Changes in interest rates directly influence borrowing costs, savings rates, and mortgage payments, making it a core factor in the analysis. This variable represents the percentage change in interest rates over a certain period (typically 6 months to a year), derived from data provided by central banks or financial institutions.\u003c/p\u003e\u003cp\u003eThis study utilizes \u003cb\u003eInterest Rate Shift (∆IR)\u003c/b\u003e as an alternative measure. The substitution is based on the distinction between \u003cb\u003epolicy signaling effects\u003c/b\u003e and \u003cb\u003edirect market responses\u003c/b\u003e to monetary policy changes.\u003cb\u003eInterest Rate Shift (∆IR)\u003c/b\u003e directly reflects \u003cb\u003eactual changes in interest rates\u003c/b\u003e, providing a more immediate and observable measure of monetary policy transmission.\u003c/p\u003e\u003cp\u003eWhile the reference study employs Forward Guidance to examine the effects of central bank communication on household expectations, this study utilizes Yield Curve Slope as an alternative measure. \u003cb\u003eYield Curve Slope captures\u003c/b\u003e market expectations of future interest rate movements based on the spread between long-term and short-term bond yields, reflecting how financial markets interpret monetary policy signals\u003c/p\u003e\u003cp\u003eThis approach aligns with studies that focus on \u003cb\u003erealized policy changes rather than expectations-based mechanisms\u003c/b\u003e (Di Maggio et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Guren et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). By using \u003cb\u003e∆IR\u003c/b\u003e, this study emphasizes the \u003cb\u003eimmediate impact of interest rate fluctuations\u003c/b\u003e on household financial behavior, inflation expectations, and broader economic sentiment, rather than the forward-looking effects of policy announcements.\u003c/p\u003e\u003cp\u003eThus, this choice ensures that the analysis remains \u003cb\u003egrounded in observed market dynamics\u003c/b\u003e, making it a robust alternative to expectation-driven indicators like Forward Guidance.\u003c/p\u003e\u003cp\u003e\u003cb\u003eLoanRate (LR)\u003c/b\u003e represents the annual percentage rate charged on loans, particularly mortgages. Mortgage rates are critical for homeowners and potential buyers, as they influence decisions about home purchases and refinancing. This variable is often sourced from mortgage surveys or financial institutions. \u003cb\u003ePriceIndex (PI)\u003c/b\u003e, often derived from the Consumer Price Index (CPI), measures the aggregate price level and is used to track inflation across a broad range of goods and services. It provides a snapshot of overall inflation, which is crucial for understanding its impact on household purchasing power and economic behavior.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePriceGrowth (PG)\u003c/b\u003e is another key variable related to inflation, specifically reflecting how fast prices are rising. Households may adjust their spending and saving behavior based on expected inflation. It is typically calculated as the percentage increase in the price level over a certain period and sourced from macroeconomic datasets. The \u003cb\u003eSavings Rate (SR)\u003c/b\u003e variable replaces the Debt Service variable to give a broader view of household financial health. Rather than focusing on debt repayment, the savings rate captures how much households are setting aside from their income, offering insights into their financial resilience. It is calculated as the ratio of savings to disposable income, typically derived from household surveys or macroeconomic data. Lastly, \u003cb\u003eRealEstateOutlook (REO)\u003c/b\u003e replaces Property Value Forecast to provide a more comprehensive view of how households perceive the future of the real estate market. This variable reflects broader expectations about real estate trends, including property prices and market conditions, rather than focusing solely on home price forecasts. It is derived from consumer surveys like MSC and SCE, which ask households about their expectations regarding the housing market. Debt Service Ratio (DSR) measures the proportion of a household\u0026rsquo;s income allocated to debt payments, including mortgages and consumer loans. A higher DSR indicates a greater financial burden, which can influence consumption and saving behavior. It is sourced from macroeconomic data and consumer surveys.\u003c/p\u003e\u003cp\u003e\u003cb\u003eLabor Market Outlook) has been added\u003c/b\u003e (\u003cb\u003eLMO) to\u003c/b\u003e explicitly define unemployment expectations. These variable measures consumer sentiment regarding future job prospects and economic stability.\u003c/p\u003e\u003cp\u003e\u003cb\u003eInterest Rate Expectation (IRE) has been added\u003c/b\u003e to track household predictions about future interest rates. It is derived from direct consumer survey responses or inferred from macroeconomic trends such as yield curve movements and inflation expectations.\u003c/p\u003e\u003cp\u003eTogether, these variables provide a holistic view of how different factors\u0026mdash;ranging from homeownership status to inflation and interest rate changes\u0026mdash;impact household financial decisions and economic expectations. In this study, the dependent variables represent key household expectations that are influenced by monetary policy. Their selection is based on their theoretical significance and their ability to capture how households adjust their financial outlook in response to changes in interest rates, inflation expectations, and broader macroeconomic conditions.\u003c/p\u003e\u003cp\u003eThe first dependent variable, \u003cb\u003eInterest Rate Expectation (IRE)\u003c/b\u003e, measures households' expectations regarding future interest rate changes. It is derived from consumer surveys where respondents indicate whether they anticipate an increase in interest rates. This variable is particularly important as it affects borrowing decisions, investment behavior, and overall financial planning. Households that expect rising interest rates may choose to accelerate borrowing or delay major financial commitments, while those anticipating lower rates might adjust their savings and spending strategies accordingly.\u003c/p\u003e\u003cp\u003eThe second dependent variable, \u003cb\u003eLabor Market Outlook (LMO)\u003c/b\u003e, reflects household expectations about future labor market conditions, specifically regarding unemployment trends. This binary variable indicates whether households believe that unemployment will decrease soon. Labor market expectations are a crucial determinant of consumer confidence and spending patterns. If households expect a strong job market, they may be more willing to engage in discretionary spending and investment, whereas pessimistic labor market expectations could lead to increased savings and reduced consumption.\u003c/p\u003e\u003cp\u003eBoth variables are primarily sourced from consumer surveys, such as the Michigan Consumer Survey (MSC) and the New York Federal Reserve Survey of Consumer Expectations (SCE). These surveys collect real-time data on household sentiment regarding interest rates and employment prospects, providing valuable insights into economic behavior at the micro level. Additionally, macroeconomic indicators such as official employment reports and central bank interest rate trends serve as reference points for evaluating the accuracy of these expectations. By comparing survey-based expectations with actual economic data, this study aims to assess how effectively monetary policy influences household financial perceptions and decision-making.\u003c/p\u003e\u003cp\u003eA clear understanding of these dependent variables allows for a more precise analysis of the transmission of monetary policy to household expectations. The findings contribute to the broader discussion on how interest rate changes and labor market dynamics shape economic behavior, ultimately helping policymakers refine their strategies for economic stabilization and growth.\u003c/p\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Measurement of Household Expectations and Measurement of Monetary Policy Shocks\u003c/h2\u003e\u003cp\u003eThe household expectations used in this study are derived from the Michigan Consumer Survey (MSC) and the New York Federal Reserve Bank\u0026rsquo;s Survey of Consumer Expectations (SCE). MSC is a telephone survey conducted monthly with more than 500 households since 1978. In addition to demographic information such as education level, age, and household income, data on homeownership, home value, and housing price expectations have been collected since 1990. SCE, on the other hand, has been an internet-based survey since 2013, focusing on approximately 1,300 households every month, measuring their expectations regarding inflation, labor market conditions, and household finances.\u003c/p\u003e\u003cp\u003eIn this study, post-1990 MSC data are used, considering homeownership status and the recurring household samples. Both MSC and SCE surveys measure household expectations using two main methods: expected growth rate and change probability. Survey respondents are asked for their expected change rate for variables such as inflation, income growth, and unemployment over a specified time horizon. Based on their responses, a generalized beta distribution is estimated to represent household expectations.\u003c/p\u003e\u003cp\u003eMonetary policy shocks in this study are based on various measures available during the sample period, including the zero lower bound (ZLB) period (1990:1\u0026ndash;2020:12). During the ZLB period, monetary policy became more multidimensional with the adoption of extraordinary monetary policy tools by central banks (Bernanke,948). One of the commonly used methods in the literature is the high-frequency identification approach, which focuses on movements in asset prices in a narrow window around Federal Open Market Committee (FOMC) meetings. These meetings often contain both central bank information effects and monetary policy shocks. Therefore, a unified measure of monetary policy shocks, proposed by Bu et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), which excludes the information effect, has been adopted.\u003c/p\u003e\u003cp\u003eChanges observed in asset prices during FOMC meetings allow for the direct measurement of monetary policy shocks. This approach has been preferred to better understand the impact of policy shocks on homeowners and renters.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e4.2. Empirical Analysis with Custom Variables\u003c/h2\u003e\u003cp\u003eThis section investigates the effects of interest rate changes on the expectations of households with different housing statuses (homeowners and renters) and assesses how these changes impact inflation and labor market outlooks. To address the heterogeneity in responses, we introduce an econometric model that incorporates specific variables from the dataset used in this study: Property Owner (PO) representing homeownership status, Tenant (TN) representing rental status, Interest Rate Shift (∆IR), Loan Rate (LR) representing mortgage rate changes, and Price Growth (PG) for inflation rate changes.\u003c/p\u003e\u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\u003ch2\u003e4.2.1 Impact of Interest Rate Changes on Inflation Expectations\u003c/h2\u003e\u003cp\u003eWe begin by analyzing how households revise their inflation expectations in response to shifts in interest rates. The model used in this section can be expressed as:\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:{E}_{i,t+6}^{PG}-{E}_{i,t}^{PG}=\\alpha\\:+{\\beta\\:}_{1}POx\\varDelta\\:{IR}_{t}+{\\beta\\:}_{2}{TN}_{i}x\\varDelta\\:{IR}_{t}+\\delta\\:{X}_{i}+{\\epsilon\\:}_{i}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{E}_{i,t}^{PG}\\)\u003c/span\u003e\u003c/span\u003erepresents household inflation expectation for the next six months (PriceGrowth), and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varDelta\\:{IR}_{t}\\)\u003c/span\u003e\u003c/span\u003edenotes the change in interest rates during the past six months. The variables \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{PO}_{i}\\)\u003c/span\u003e\u003c/span\u003e​ and\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\:TN}_{i}\\)\u003c/span\u003e\u003c/span\u003e are dummy variables for homeowner and renter status, respectively. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{X}_{i}\\)\u003c/span\u003e\u003c/span\u003eincludes household characteristics such as income, education, and age. The focus here is to examine how the interest rate shift affects inflation expectations differently for homeowners and renters.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e provides the regression results. Homeowners, who are more likely to monitor interest rate changes due to their impact on mortgage rates (LR), tend to lower their inflation expectations when interest rates increase. Renters, however, exhibit a smaller revision in inflation expectations, as they are less directly affected by such rate shifts. The observed differences highlight the importance of homeownership status in determining how monetary policy influences inflation expectations.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eRegression Results (1-Year and 5-Year Ahead)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1-Year Price Growth (PG)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5-Year Price Growth (PG)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1-Year Labor Market Outlook\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5-Year Labor Market Outlook\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePO x ΔIR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.215\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.165\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.115\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTN x ΔIR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.095\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.055\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.055\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.035\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of Observations\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e24000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e24000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.015\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTable Note\u003c/strong\u003e\u003cp\u003eThis table presents the estimated coefficients from the regression models analyzing the impact of interest rate changes on household expectations. The variables include homeowner (PO) and renter (TN) status, with changes in 1-year and 5-year price growth (inflation expectations) and labor market outlook as the dependent variables. The regressions control household characteristics such as income, education, and age. The results suggest that homeowners are more sensitive to interest rate changes due to their direct exposure to mortgage rate fluctuations, whereas renters exhibit a smaller response. Observations and R\u0026sup2; values indicate the fit of the models and the significance of the coefficients.\u003c/p\u003e\u003c/p\u003e\u003cp\u003eAccording to Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.the regression results show that \u003cb\u003ehomeowners\u003c/b\u003e are more responsive to changes in interest rates than \u003cb\u003erenters\u003c/b\u003e. For \u003cb\u003e1-year price growth (inflation expectations)\u003c/b\u003e, homeowners exhibit a significant downward revision (-0.215) when interest rates increase, while renters show a smaller response (-0.095). This suggests that homeowners, likely due to their exposure to mortgage rates, adjust their inflation expectations more sharply. Similarly, for \u003cb\u003e5-year price growth\u003c/b\u003e, the sensitivity of homeowners decreases to -0.130, but it remains more pronounced than that of renters (-0.055). The pattern is consistent for \u003cb\u003elabor market outlook\u003c/b\u003e, where homeowners demonstrate stronger revisions compared to renters over both 1-year and 5-year horizons. Overall, homeowners are more attuned to interest rate shifts, reflecting their financial exposure through homeownership.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\u003ch2\u003e4.2.2. Impact of Interest Rate Changes on Labor Market Expectations\u003c/h2\u003e\u003cp\u003eThis section examines how changes in interest rates influence household expectations regarding the labor market. If an increase in interest rates negatively affects household perceptions of employment opportunities, it may indicate that such changes are perceived as contractionary monetary policy effects.\u003c/p\u003e\u003cp\u003eThe primary challenge in this analysis is that labor market expectations are categorical. Unlike inflation expectations, labor market perceptions are captured through a binary variable that indicates whether an individual\u0026rsquo;s unemployment outlook has improved or not. To measure this, a binary indicator variable is constructed, where 1 represents an improvement in labor market outlook over six months, and 0 otherwise.\u003c/p\u003e\u003cp\u003eThe regression model used in this analysis is defined as follows:\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:{LMO}_{i,t}={\\alpha\\:}_{0}+{\\beta\\:}_{1}{PO}_{i}x\\varDelta\\:{IR}_{t}+\\gamma\\:{PG}_{t}+\\delta\\:{LR}_{t}+\\varnothing\\:{X}_{i,t}+{ϵ}_{i,t}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe dependent variable, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{LMO}_{i,t}\\)\u003c/span\u003e\u003c/span\u003e, represents the labor market outlook of individual \u003cem\u003ei\u003c/em\u003e at time \u003cem\u003et\u003c/em\u003e, capturing whether the respondent expects unemployment to decrease. The key independent variable is \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varDelta\\:{IR}_{t}\\)\u003c/span\u003e\u003c/span\u003e, which denotes changes in interest rates. The model also includes \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{PO}_{i}\\:\\)\u003c/span\u003e\u003c/span\u003erepresenting homeownership to examine how these groups respond differently to interest rate fluctuations. Additionally, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{PG}_{t}\\)\u003c/span\u003e\u003c/span\u003e, which represents inflation expectations, is included as it may influence economic confidence and employment outlooks. The variable \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{PG}_{t}\\)\u003c/span\u003e\u003c/span\u003e captures mortgage interest rate changes, which can impact employment security, particularly for homeowners. Finally, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{X}_{i,t}\\)\u003c/span\u003e\u003c/span\u003e consists of various household-level control variables such as income, education, and savings rate, which may influence labor market expectations.\u003c/p\u003e\u003cp\u003eOverall, these results highlight the broader implications of monetary policy on household sentiment regarding employment prospects. The study aligns with previous research suggesting that shifts in interest rates influence household confidence in job stability, particularly for mortgage holders. The inclusion of household-level controls ensures robustness in the analysis, accounting for variations in income, education, and economic conditions.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe Effects of Interest Rate Changes on Household Labor Market Expectations (dependent variable: LMO)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varDelta\\:\\varvec{I}\\varvec{R}}_{\\varvec{t}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varDelta\\:\\varvec{I}\\varvec{R}}_{\\varvec{t},\\varvec{Y}\\varvec{C}\\varvec{S}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePO (β₁)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.0177** (0.0077)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.0290*** (0.0077)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTN (β₂)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0205 (0.0142)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.0130 (0.0139)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eObservations\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24,474\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23,881\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdj. R\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0162\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0168\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eF-test (β₁ = β₂)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.90**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe findings in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e indicate that homeowners respond more significantly to changes in interest rates compared to tenants, as reflected by the interaction terms PO (β₁)x \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varDelta\\:IR}_{t}\\)\u003c/span\u003e\u003c/span\u003eand TN (β₂)x\u003c/p\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varDelta\\:IR}_{t}\\)\u003c/span\u003e\u003c/span\u003e. An increase in interest rates negatively influences labor market expectations among homeowners, suggesting that financial stability concerns play a crucial role in shaping employment outlooks. Inflation expectations also contribute to pessimistic labor market perceptions, reinforcing concerns about economic stability. Furthermore, changes in mortgage interest rates significantly affect homeowners\u0026rsquo; job security perceptions.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003e4.2.3. Effects of mortgage-rate changes on interest rate expectations\u003c/h2\u003e\u003cp\u003eThis section explores how changes in interest rates impact household expectations regarding future interest rate movements. The model investigates whether shifts in interest rates influence consumers\u0026rsquo; perceptions of monetary policy and financial market conditions.\u003c/p\u003e\u003cp\u003eTo examine this relationship, the dependent variable \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{IRE}_{i,t}\\)\u003c/span\u003e\u003c/span\u003e represents the interest rate expectation of individual \u003cem\u003ei\u003c/em\u003e at time \u003cem\u003et\u003c/em\u003e, indicating whether the respondent expects interest rates to rise. The independent variable \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varDelta\\:{IR}_{t}\\)\u003c/span\u003e\u003c/span\u003e captures changes in interest rates, while \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{PO}_{i}\\:\\)\u003c/span\u003e\u003c/span\u003eand \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{TN}_{i}\\)\u003c/span\u003e\u003c/span\u003e distinguish between homeowners and tenants to assess their differing responses to monetary policy. Additionally, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{PG}_{t}\\)\u003c/span\u003e\u003c/span\u003e which measures inflation expectations, is included as inflationary trends often influence rate expectations. X_{i,t} represents various household-level controls, such as income, education, and financial stability factors, which could contribute to variations in interest rate expectations.\u003c/p\u003e\u003cp\u003eThe regression model used in this analysis is defined as follows:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:{IRE}_{i,t}={\\alpha\\:}_{0}+{\\beta\\:}_{1}{PO}_{i}x\\varDelta\\:{IR}_{t}+{\\beta\\:}_{2}{TN}_{i}x\\varDelta\\:{IR}_{t}+\\gamma\\:{PG}_{t}+\\delta\\:{REO}_{t}+\\varnothing\\:{X}_{i,t}+{ϵ}_{i,t}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe dependent variable, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{IRE}_{i,t}\\)\u003c/span\u003e\u003c/span\u003e, represents the household\u0026rsquo;s expectations about future interest rate movements. The key independent variable is ΔIR_t, which denotes changes in interest rates. The model also includes \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{PO}_{i}\\)\u003c/span\u003e\u003c/span\u003eand \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{TN}_{i}\\)\u003c/span\u003e\u003c/span\u003e, representing homeownership and tenant status, respectively, to examine how these groups respond differently to interest rate fluctuations. Additionally, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{PG}_{t}\\)\u003c/span\u003e\u003c/span\u003e which represents inflation expectations, is included as it may influence financial market confidence and interest rate forecasts. The variable \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{REO}_{t}\\)\u003c/span\u003e\u003c/span\u003e captures real estate market expectations, which can serve as a leading indicator for monetary policy expectations. Finally, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{X}_{i,t}\\)\u003c/span\u003e\u003c/span\u003e consists of household-level control variables such as income, education, and financial stability, which may influence interest rate expectations.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eChanges in Household Future Interest Rate Expectations in Response to Interest Rate Fluctuations\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varDelta\\:IR}_{t}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varDelta\\:IR}_{t,YCS}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePO (β₁)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.1475*** (0.0074)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0708*** (0.0069)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTN (β₂)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0621*** (0.0097)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0648*** (0.0157)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eObservations\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24,496\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23,898\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdj. R\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0551\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0463\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eF-test (β₁ = β₂)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e59.14***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe findings in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e suggest that homeowners respond more strongly to interest rate shifts than tenants. A positive β₁ coefficient indicates that homeowners expecting an increase in interest rates are more likely to adjust their financial planning accordingly. The interaction between TN and\u003c/p\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varDelta\\:IR}_{t}\\)\u003c/span\u003e\u003c/span\u003e (β₂) reveals that tenants also perceive changes in monetary policy, but their response is relatively weaker due to the absence of mortgage-related financial obligations.\u003c/p\u003e\u003cp\u003eFurthermore, the coefficient for Yield Curve Slope (YCS) suggests that expectations regarding future interest rate hikes align with shifts in the yield curve. This reflects how financial markets interpret broader monetary policy changes, reinforcing the notion that interest rate expectations are shaped by both short-term fluctuations and long-term bond market conditions\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"5. Mechanism and Model Framework","content":"\u003cp\u003eThis section examines the fundamental mechanisms determining the impact of monetary policy on household expectations. It is argued that the differences between homeowners and renters are decisive in their responses to monetary policy. Monetary policy can influence household expectations through channels such as interest rates, housing prices, and credit accessibility.\u003c/p\u003e\u003cp\u003eTo assess the effects of monetary policy shocks, particularly changes in interest rates, on homeowners and renters, an empirical model is employed. The study analyzes how interest rate changes impact household inflation expectations and labor market forecasts. In this context, measuring household expectations and modeling the impact of monetary policy shocks is crucial.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e5.1. Measuring Household Expectations and the Impact of Monetary Policy Shocks\u003c/h2\u003e\u003cp\u003eHousehold expectations are analyzed using data from the Michigan Consumer Survey (MSC) and the New York Federal Reserve Bank\u0026rsquo;s Survey of Consumer Expectations (SCE). These datasets are essential for evaluating how households react to changes in interest rates and inflation expectations.\u003c/p\u003e\u003cp\u003eTo analyze the impact of monetary policy shocks, variables such as \u003cb\u003eInterest Rate Shift ()\u003c/b\u003e, \u003cb\u003eYield Curve Slope (YCS)\u003c/b\u003e, \u003cb\u003eReal Estate Outlook (REO)\u003c/b\u003e, and \u003cb\u003eDebt Service Ratio (DSR)\u003c/b\u003e are used. These variables reflect the market response to interest rate changes and help us understand how households form their economic expectations.\u003c/p\u003e\u003cp\u003eIn this study, a six-period horizon is specifically incorporated into the model to capture long-term adjustments in household expectations following monetary policy changes. This allows for an in-depth understanding of how monetary policy effects persist over time and influence economic behavior.\u003c/p\u003e\u003cp\u003eThe model is represented by the following fundamental equation:\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:{E}_{i,t+h}-{E}_{i,t}=\\alpha\\:+{\\beta\\:}_{1}\\left(POx{\\varDelta\\:IR}_{t}\\right)+{\\beta\\:}_{2}\\left(TNx{\\varDelta\\:IR}_{t}\\right)+\\gamma\\:{Z}_{t}+\\phi\\:{Z}_{i,t}+\\varnothing\\:{REO}_{i,t}+\\omega\\:{DSR}_{i,t}+{\\epsilon\\:}_{i,t}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThis equation models how changes in interest rates influence household expectations, taking into account heterogeneity between homeowners and renters. By including additional variables such as real estate outlook and debt service ratio, the model captures broader financial and housing market dynamics that shape household decision-making.\u003c/p\u003e\u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\u003ch2\u003e5.1.1. The Effects of Interest Rate Changes on Homeowners and Renters\u003c/h2\u003e\u003cp\u003eThe differential impact of interest rate changes on homeowners and renters is examined in terms of inflation expectations and labor market forecasts. Homeowners are more sensitive to changes in mortgage interest rates and adjust their consumption and savings decisions accordingly. Renters, on the other hand, do not experience direct changes in borrowing costs but may be indirectly affected through labor market conditions.\u003c/p\u003e\u003cp\u003eThe sensitivity of homeowners\u0026rsquo; inflation expectations is measured using the following regression model:\u003cdiv id=\"Equc\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e\n$$\\:{E}_{i,t+6}^{h\\:year\\:}-{E}_{i,t}^{h\\:year\\:}=\\alpha\\:+{\\beta\\:}_{1}\\left({homeowner}_{1}x{\\varDelta\\:IR}_{t}\\right)+{\\beta\\:}_{1}\\left({tenant}_{1}x{\\varDelta\\:IR}_{t}\\right)+{\\gamma\\:z}_{t}+{\\delta\\:x}_{i,t}+{\\phi\\:REO}_{i,t}+{\\tau\\:DSR}_{i,t}+{\\epsilon\\:}_{i,t}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe results indicate that homeowners respond more quickly and strongly to changes in interest rates, while renters are less responsive, primarily experiencing indirect effects through rental prices and labor market conditions.\u003c/p\u003e\u003cp\u003eTo assess labor market expectations, the following model is used:\u003cdiv id=\"Equd\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equd\" name=\"EquationSource\"\u003e\n$$\\:{LMO}_{i,t}=\\alpha\\:+{\\beta\\:}_{1}\\left({homeowner}_{1}x{\\varDelta\\:IR}_{t}\\right)+{\\beta\\:}_{1}\\left({tenant}_{1}x{\\varDelta\\:IR}_{t}\\right)+{\\gamma\\:z}_{t}+{\\delta\\:x}_{i,t}+{\\phi\\:REO}_{i,t}+{\\tau\\:DSR}_{i,t}+{\\epsilon\\:}_{i,t}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eHere is a binary variable representing whether the household expects labor market conditions to improve (1\u0026thinsp;=\u0026thinsp;Labor market improves, 0\u0026thinsp;=\u0026thinsp;Otherwise).\u003c/p\u003e\u003cp\u003eThe analysis results indicate that homeowners negatively adjust their labor market expectations in response to rising interest rates, whereas renters are relatively less responsive. This finding supports the hypothesis that homeowners' economic expectations are more sensitive to interest rate fluctuations due to mortgage obligations. These findings reveal that monetary policy has heterogeneous effects on household expectations, with homeowners displaying higher sensitivity to interest rate changes. Renters, who experience interest rate changes indirectly, exhibit weaker responses to inflation and labor market expectations. These differences demonstrate that monetary policy decisions have varying impacts on homeowners and renters.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\u003ch2\u003e5.1.2 The Selection of Canada as a Case Study in Monetary Policy Transmission\u003c/h2\u003e\u003cp\u003eThe choice of Canada as the empirical setting for this study is motivated by its distinct \u003cb\u003emonetary policy framework, mortgage market structure, and household financial behavior\u003c/b\u003e, which present an ideal environment for analyzing the heterogeneous effects of monetary policy on household expectations. While previous studies have largely focused on economies such as the \u003cb\u003eUnited Kingdom and the United States\u003c/b\u003e, the Canadian case offers a unique opportunity to examine the impact of monetary policy in a country with \u003cb\u003ehigh mortgage exposure and a well-defined inflation-targeting regime\u003c/b\u003e.\u003c/p\u003e\u003cp\u003eCanada\u0026rsquo;s monetary transmission mechanisms differ from those of other advanced economies in several keyways. First, the \u003cb\u003eBank of Canada (BoC) operates under a well-established inflation-targeting framework\u003c/b\u003e, like the Bank of England. However, the \u003cb\u003etransmission of monetary policy to households in Canada is significantly affected by the structure of its mortgage market\u003c/b\u003e, where \u003cb\u003evariable-rate mortgages are more prevalent than in the UK or the US\u003c/b\u003e. This distinction implies that changes in policy interest rates have a more immediate and pronounced effect on household financial conditions.\u003c/p\u003e\u003cp\u003eFurthermore, Canada\u0026rsquo;s \u003cb\u003ehousehold debt-to-income ratio is among the highest in the G7\u003c/b\u003e, indicating a heightened sensitivity to changes in borrowing costs. As mortgage debt constitutes a significant portion of household liabilities, variations in interest rates can influence \u003cb\u003econsumption, savings decisions, and overall economic sentiment\u003c/b\u003e more directly than in economies where fixed-rate mortgages are dominant.\u003c/p\u003e\u003cp\u003eAdditionally, the \u003cb\u003eCanadian housing market\u003c/b\u003e has experienced considerable price appreciation over the past two decades, particularly in metropolitan areas such as \u003cb\u003eToronto and Vancouver\u003c/b\u003e. These dynamics make Canada an ideal case for examining how \u003cb\u003emonetary policy affects wealth perception and inflation expectations among homeowners and renters\u003c/b\u003e.\u003c/p\u003e\u003cp\u003eBy focusing on Canada, this study contributes to the literature on \u003cb\u003emonetary policy transmission and household behavior\u003c/b\u003e in highly leveraged economies. The findings are expected to offer policy-relevant insights for central banks in economies with similar \u003cb\u003ehousing market structures and mortgage debt dynamics\u003c/b\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e5.2. Robustness Checks and Alternative Model Specifications\u003c/h2\u003e\u003cp\u003eTo ensure the robustness and validity of the empirical results, a series of \u003cb\u003esensitivity analyses and alternative model specifications\u003c/b\u003e are conducted. These robustness checks aim to assess whether the findings remain consistent across different subsamples, estimation techniques, and monetary policy indicators.\u003c/p\u003e\u003cp\u003eFirst, \u003cb\u003ealternative measures of household expectations\u003c/b\u003e are employed to evaluate the reliability of the primary results. In addition to the \u003cb\u003eSurvey of Consumer Expectations (SCE)\u003c/b\u003e and the \u003cb\u003eMichigan Consumer Survey (MSC)\u003c/b\u003e, market-based indicators, such as \u003cb\u003einflation-indexed bond yields and central bank forecast revisions\u003c/b\u003e, are used to assess inflation expectations. The inclusion of these variables helps determine whether survey-based measures align with broader macroeconomic indicators.\u003c/p\u003e\u003cp\u003eSecond, \u003cb\u003eheterogeneity analyses\u003c/b\u003e are performed by segmenting the sample into subgroups based on \u003cb\u003ehousehold income levels, mortgage types (fixed vs. variable rate), and debt-to-income ratios\u003c/b\u003e. This approach allows for an examination of whether the transmission of monetary policy differs across demographic and financial characteristics.\u003c/p\u003e\u003cp\u003eThird, \u003cb\u003eplacebo tests\u003c/b\u003e are conducted to ensure that the observed relationships between monetary policy and household expectations are not driven by unrelated macroeconomic factors. This involves estimating the models on pre-policy shift periods to verify that significant effects do not appear when no major monetary policy changes occurred.\u003c/p\u003e\u003cp\u003eAdditionally, alternative specifications of \u003cb\u003emonetary policy shocks\u003c/b\u003e are tested. While the baseline model relies on \u003cb\u003eInterest Rate Shift (∆IR)\u003c/b\u003e and \u003cb\u003eYield Curve Slope (YCS)\u003c/b\u003e as key monetary policy indicators, robustness checks incorporate \u003cb\u003emoney supply growth (M2)\u003c/b\u003e and central bank balance sheet expansions to account for potential differences in policy transmission channels.\u003c/p\u003e\u003cp\u003eFinally, \u003cb\u003efixed effects estimations\u003c/b\u003e are employed to control for time-invariant unobserved heterogeneity across households. Year and province-level fixed effects are included to account for \u003cb\u003eregional variations in economic conditions\u003c/b\u003e, while instrumental variable (IV) regressions are used to address \u003cb\u003epotential endogeneity concerns\u003c/b\u003e.\u003c/p\u003e\u003cp\u003eThe results of these robustness checks indicate that the primary findings remain \u003cb\u003estatistically significant and economically meaningful\u003c/b\u003e, reinforcing the validity of the study\u0026rsquo;s conclusions. The comprehensive nature of these tests enhances confidence in the implications drawn from empirical analysis.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e5.3. Household Monitoring of Macroeconomic News and Monetary Policy Interaction\u003c/h2\u003e\u003cp\u003eThis section examines the level of attention households pay to macroeconomic developments and how this attention varies in response to changes in monetary policy. The frequency with which households follow economic news and their sensitivity to financial variables may differ based on factors such as homeownership and debt burden. This study utilizes a specialized module to understand how households respond to changes in interest rates and inflation.\u003c/p\u003e\u003cp\u003eThis special survey module was conducted in \u003cb\u003eJune 2023 by the New York Federal Reserve's Survey of Consumer Expectations (SCE)\u003c/b\u003e and aims to measure how frequently households follow economic and financial news. The survey results were used to assess how homeowners and renters differ in their sensitivity to economic news. Notably, homeowners were found to pay more attention to interest rates, whereas renters focused more on general economic conditions and the labor market.\u003c/p\u003e\u003cp\u003eThe survey results indicate that homeowners check mortgage rates more frequently than renters. However, it was observed that outright homeowners show lower interest in interest rates compared to those with mortgages. Renters, on the other hand, exhibit lower sensitivity to interest rate changes as they are not directly affected by borrowing costs. However, they follow general economic conditions and the labor market more closely.\u003c/p\u003e\u003cp\u003eAn important finding is that the difference in attention between homeowners and renters is not limited to mortgage rates. Homeowners also pay more attention to other interest rate indicators such as treasury bond yields, while no significant difference was observed in their interest in Federal Reserve policies. These findings suggest that the impact of monetary policy on households is linked not only to interest rate changes but also to how households acquire and interpret economic news.\u003c/p\u003e\u003cp\u003eAll these findings help us understand how households\u0026rsquo; economic news monitoring habits are shaped by their financial situation and debt burden. For monetary policies to be effectively communicated, policymakers must consider the level of information households have access to and how they interpret this information.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eForecast Errors in Household Macroeconomic Expectations by Housing and Financial Status\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInterest Rate Expectation (IRE)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLabor Market Outlook (LMO)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eReal Estate Outlook (REO)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHomeowner (Outright)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.4027***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.4514***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.3701***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHomeowner (Mortgage)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.8042***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.7326***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.6827***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRecent Loan Refinancing\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.0775*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.1040***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.0566\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePlans to Refinance\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.1291***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.1092***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.0674\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cem\u003eNote: *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.10 denote statistical significance.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e compares the accuracy of household expectations regarding macroeconomic indicators such as interest rate changes, labor market conditions, and real estate trends, based on homeownership and financial status. The results indicate that homeowners with mortgages provide the most accurate predictions. Specifically, those who refinanced in the past year or plan to refinance in the next year exhibit higher accuracy. These findings support the idea that household financial engagement plays a crucial role in shaping attention to economic information.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e5.4. Evidence from the Bank of Canada Survey of Household Expectations\u003c/h2\u003e\u003cp\u003eIn this section, we analyze how Canadian households respond to changes in interest rates by utilizing data from the \u003cb\u003eCanadian Survey of Consumer Expectations (CSCE)\u003c/b\u003e conducted by the Bank of Canada. This survey provides insights into households\u0026rsquo; expectations regarding inflation, unemployment, interest rates, and the housing market.\u003c/p\u003e\u003cp\u003eThe reference study examined the responses of UK households to interest rate changes using the \u003cb\u003eBank of England\u0026rsquo;s Survey of Inflation Attitudes\u003c/b\u003e. In contrast, we adapt the same analytical framework to Canada, using data from the Bank of Canada to explore how Canadian households, particularly homeowners and renters, adjust their expectations in response to monetary policy changes.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e5.5. Survey Data and Empirical Strategy\u003c/h2\u003e\u003cp\u003eThe CSCE dataset includes households\u0026rsquo; expectations regarding key economic variables. Respondents are asked the following questions:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eDo you expect interest rates in Canada to rise or fall over the next 12 months?\u003c/b\u003e\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eDo you expect unemployment in Canada to increase or decrease over the next 12 months?\u003c/b\u003e\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eDo you expect housing prices in Canada to rise or fall over the next 12 months?\u003c/b\u003e\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003eTo analyze the responses, we employ the following regression model:\u003cdiv id=\"Eque\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Eque\" name=\"EquationSource\"\u003e\n$$\\:{E}_{i,t}=\\alpha\\:+{\\beta\\:}_{1,}{(PO}_{i}x\\varDelta\\:{IR}_{t})+{\\beta\\:}_{2,}{(TN}_{i}x\\varDelta\\:{IR}_{t})+{\\beta\\:}_{3,}{(DSR}_{i,t})+{\\beta\\:}_{4,}{(REO}_{i,t})+\\gamma\\:{X}_{i,t}+{\\epsilon\\:}_{i,t}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThis model tests whether households\u0026rsquo; expectations regarding monetary policy shifts vary based on homeownership status, debt burden, and real estate expectations.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e5.6.Nonlinearity in the Effects of Interest Rate Changes\u003c/h2\u003e\u003cp\u003eA key aspect of monetary policy transmission is whether the effects of interest rate changes are symmetric. In this section, we explore whether the impact of interest rate changes on household expectations differs between periods of increasing and decreasing rates. We employ a threshold regression model to capture potential nonlinearities:\u003cdiv id=\"Equf\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equf\" name=\"EquationSource\"\u003e\n$$\\:{E}_{i,t}=\\alpha\\:+{\\beta\\:}_{1,}{(PO}_{i}x\\varDelta\\:{IR}_{t}^{+})+{\\beta\\:}_{2,}{(PO}_{i}x\\varDelta\\:{IR}_{t}^{-})+{\\beta\\:}_{3,}{(TN}_{i}x\\varDelta\\:{IR}_{t}^{+})+{\\beta\\:}_{4,}{(TN}_{i}x\\varDelta\\:{IR}_{t}^{-})+{\\beta\\:}_{5,}{(DSR}_{i,t})+{\\beta\\:}_{6,}{(REO}_{i,t})+\\gamma\\:{X}_{i,t}+{\\epsilon\\:}_{i,t}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere:\u003c/p\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varDelta\\:{IR}_{t}^{+}\\)\u003c/span\u003e\u003c/span\u003erepresents periods of increasing interest rates.\u003c/p\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varDelta\\:{IR}_{t}^{-}\\)\u003c/span\u003e\u003c/span\u003e represents periods of decreasing interest rates.\u003c/p\u003e\u003cp\u003e\u003cb\u003eFigures Representing Household Responses\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThis figure illustrates the perceived importance of interest rates in shaping household price expectations across different housing tenure categories.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThis figure shows how respondents believe rising interest rates impact price movements in the short term, differentiated by housing tenure status.\u003c/p\u003e\u003cp\u003eThis figure highlights household expectations regarding the influence of rising interest rates on price changes over the medium term.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThis section highlights how different household groups\u0026mdash;homeowners with mortgages, outright homeowners, and renters\u0026mdash;respond differently to monetary policy shifts. These figures provide empirical support for our hypothesis that the impact of interest rates on price expectations and consumer behavior varies based on housing tenure and debt exposure.\u003c/p\u003e\u003c/div\u003e"},{"header":"6. Mechanism and Model Framework","content":"\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003e6.1. Measuring Household Expectations and the Impact of Monetary Policy Shocks\u003c/h2\u003e\u003cp\u003eHousehold expectations are analyzed using data from the \u003cb\u003eMichigan Consumer Survey (MSC)\u003c/b\u003e and the \u003cb\u003eNew York Federal Reserve Bank's Survey of Consumer Expectations (SCE)\u003c/b\u003e. These datasets are essential for evaluating how households react to changes in interest rates and inflation expectations.\u003c/p\u003e\u003cp\u003eTo analyze the impact of monetary policy shocks, variables such as \u003cb\u003eInterest Rate Shift (∆IR)\u003c/b\u003e, \u003cb\u003eYield Curve Slope (YCS)\u003c/b\u003e, \u003cb\u003eReal Estate Outlook (REO)\u003c/b\u003e, and \u003cb\u003eDebt Service Ratio (DSR)\u003c/b\u003e are used. These variables reflect the market response to interest rate changes and help us understand how households form their economic expectations.\u003c/p\u003e\u003cp\u003eThe model is represented by the following fundamental equation:\u003cdiv id=\"Equg\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equg\" name=\"EquationSource\"\u003e\n$$\\:{E}_{i,t}^{PG}=\\alpha\\:+{\\beta\\:}_{1}{PO}_{i}\\:x\\:{\\varDelta\\:IR}_{t}+{\\beta\\:}_{2}{TN}_{i}x\\varDelta\\:{IR}_{t}+\\gamma\\:{x}_{i}+{\\epsilon\\:}_{i,t}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThis equation models how changes in interest rates influence household expectations, taking into account heterogeneity between homeowners and renters. By including additional variables such as real estate outlook and debt service ratio, the model captures broader financial and housing market dynamics that shape household decision-making.\u003c/p\u003e\u003cdiv id=\"Sec21\" class=\"Section3\"\u003e\u003ch2\u003e6.1.1. The Effects of Interest Rate Changes on Homeowners and Renters\u003c/h2\u003e\u003cp\u003eThe differential impact of interest rate changes on homeowners and renters is examined in terms of inflation expectations and labor market forecasts. Homeowners are more sensitive to changes in mortgage interest rates and adjust their consumption and savings decisions accordingly. Renters, on the other hand, do not experience direct changes in borrowing costs but may be indirectly affected through labor market conditions.\u003c/p\u003e\u003cp\u003eThe results indicate that homeowners respond more quickly and strongly to changes in interest rates, while renters are less responsive, primarily experiencing indirect effects through rental prices and labor market conditions.\u003c/p\u003e\u003cp\u003eTo assess labor market expectations, the following model is used:\u003cdiv id=\"Equh\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equh\" name=\"EquationSource\"\u003e\n$$\\:{LMO}_{i,t}=\\alpha\\:+{\\beta\\:}_{1}{PO}_{i}\\:x\\:{\\varDelta\\:IR}_{t}+{\\beta\\:}_{2}{TN}_{i}x\\varDelta\\:{IR}_{t}+\\gamma\\:{x}_{i}+{\\epsilon\\:}_{i,t}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eHere, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{LMO}_{i,t}\\)\u003c/span\u003e\u003c/span\u003e is a binary variable representing whether the household expects labor market conditions to improve (1\u0026thinsp;=\u0026thinsp;Labor market improves, 0\u0026thinsp;=\u0026thinsp;Otherwise).\u003c/p\u003e\u003cp\u003eThe analysis results indicate that homeowners negatively adjust their labor market expectations in response to rising interest rates, whereas renters are relatively less responsive. This finding supports the hypothesis that homeowners' economic expectations are more sensitive to interest rate fluctuations due to mortgage obligations.\u003c/p\u003e\u003cp\u003eThese findings reveal that monetary policy has heterogeneous effects on household expectations, with homeowners displaying higher sensitivity to interest rate changes. Renters, who experience interest rate changes indirectly, exhibit weaker responses to inflation and labor market expectations. These differences demonstrate that monetary policy decisions have varying impacts on homeowners and renters.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003e6.2. Regression Results: Impact of Interest Rate Changes on Household Expectations\u003c/h2\u003e\u003cp\u003eThe following tables present the regression results for the impact of interest rate changes on household inflation expectations and labor market outlooks.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eImpact of Interest Rate Changes on Inflation Expectations\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1-Year Price Growth (PG)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5-Year Price Growth (PG)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHomeowner (PO)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.215*** (0.103)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.130*** (0.071)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRenter (TN)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.095* (0.195)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.055 (0.145)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eObservations\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24,000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24,000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eR\u0026sup2;\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.012\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eNotes\u003c/strong\u003e\u003cp\u003eThis table presents the estimated coefficients from the regression models analyzing the impact of interest rate changes on household inflation expectations. The variables include homeowner (PO) and renter (TN) status, with changes in 1-year and 5-year price growth (inflation expectations) as the dependent variables. The regressions control for household characteristics such as income, education, and age. The results suggest that homeowners are more sensitive to interest rate changes due to their direct exposure to mortgage rate fluctuations, whereas renters exhibit a smaller response. *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.10 denote statistical significance.\u003c/p\u003e\u003c/p\u003e\u003cp\u003eAs illustrated in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, interest rate changes have a \u003cb\u003estronger and statistically significant negative effect on inflation expectations among homeowners\u003c/b\u003e compared to renters. This effect is evident in both 1-year and 5-year price growth expectations, indicating that homeowners adjust their inflation outlook more sharply in response to interest rate movements. In contrast, renters show \u003cb\u003eweaker and largely insignificant responses\u003c/b\u003e, reflecting their lower direct exposure to interest-sensitive financial obligations such as mortgages. These findings underline the \u003cb\u003eheterogeneous transmission of monetary policy\u003c/b\u003e across different household tenure groups.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eImpact of Interest Rate Changes on Labor Market Expectations\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLabor Market Outlook (LMO)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHomeowner (PO)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.0177*** (0.0077)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRenter (TN)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0205 (0.0142)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eObservations\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24,474\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eR\u0026sup2;\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0162\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003cb\u003eNotes\u003c/b\u003e: This table presents the estimated coefficients from the regression models analyzing the impact of interest rate changes on household labor market expectations. The dependent variable is a binary indicator of whether the household expects labor market conditions to improve. The results indicate that homeowners are more sensitive to interest rate changes, while renters show a weaker response. *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.10 denote statistical significance.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAs presented in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, interest rate changes have a \u003cb\u003estatistically significant negative impact on labor market expectations among homeowners\u003c/b\u003e, suggesting that they are more pessimistic about future employment prospects following monetary tightening. Renters, on the other hand, exhibit \u003cb\u003ea positive but statistically insignificant response\u003c/b\u003e, implying a relatively muted sensitivity. These findings further reinforce the pattern of \u003cb\u003eheterogeneous monetary policy transmission\u003c/b\u003e, with homeowners being more responsive due to their greater financial exposure.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec23\" class=\"Section2\"\u003e\u003ch2\u003e6.3. Robustness Checks and Alternative Model Specifications\u003c/h2\u003e\u003cp\u003eTo ensure the robustness and validity of the empirical results, a series of \u003cb\u003esensitivity analyses and alternative model specifications\u003c/b\u003e are conducted. These robustness checks aim to assess whether the findings remain consistent across different subsamples, estimation techniques, and monetary policy indicators.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eRobustness Checks with Alternative Measures of Monetary Policy Shocks\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInflation Expectations (PG)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLabor Market Outlook (LMO)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHomeowner (PO)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.210*** (0.105)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.0180*** (0.0078)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRenter (TN)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.090 (0.198)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0190 (0.0145)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eObservations\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24,000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24,474\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eR\u0026sup2;\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.016\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cb\u003eNotes\u003c/b\u003e: This table presents the results of robustness checks using alternative measures of monetary policy shocks, such as money supply growth (M2) and central bank balance sheet expansions. The findings remain consistent with the baseline results, indicating that homeowners are more sensitive to interest rate changes than renters. *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.10 denote statistical significance.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e, the robustness checks using alternative measures of monetary policy shocks (e.g., M2 growth, central bank balance sheet expansions) \u003cb\u003esupport the baseline results\u003c/b\u003e. Homeowners exhibit a statistically significant negative response in both inflation expectations and labor market outlook, whereas renters\u0026rsquo; responses remain statistically insignificant. These findings highlight the \u003cb\u003eheterogeneous impact of monetary policy across housing tenure groups\u003c/b\u003e, reinforcing the conclusion that \u003cb\u003ehomeowners are more sensitive to policy shocks\u003c/b\u003e than renters.\u003c/p\u003e\u003cp\u003eChatGPT\u0026rsquo;ye sor\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\u003ch2\u003e6.4. Nonlinearity in the Effects of Interest Rate Changes\u003c/h2\u003e\u003cp\u003eA key aspect of monetary policy transmission is whether the effects of interest rate changes are symmetric. In this section, we explore whether the impact of interest rate changes on household expectations differs between periods of increasing and decreasing rates. We employ a threshold regression model to capture potential nonlinearities:\u003cdiv id=\"Equi\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equi\" name=\"EquationSource\"\u003e\n$$\\:{E}_{i,t}^{PG}=\\alpha\\:+{\\beta\\:}_{1}{PO}_{i}\\:x\\:{\\varDelta\\:IR}_{t}\\:x\\:{I}_{t}^{+}+{\\beta\\:}_{2}{PO}_{i}\\:x\\:{\\varDelta\\:IR}_{t}\\:x\\:{I}_{t}^{-}+{\\beta\\:}_{3}{TN}_{i}\\:x\\:{\\varDelta\\:IR}_{t}\\:x\\:{I}_{t}^{+}++{\\beta\\:}_{4}{TN}_{i}\\:x\\:{\\varDelta\\:IR}_{t}\\:x\\:{I}_{t}^{-}+\\gamma\\:{X}_{i}+{\\epsilon\\:}_{i,t}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{I}_{t}^{+}\\)\u003c/span\u003e\u003c/span\u003e​ and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{I}_{t}^{-}\\)\u003c/span\u003e\u003c/span\u003eare dummy variables indicating periods of increasing and decreasing interest rates, respectively.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAsymmetric Effects of Interest Rate Changes on Household Expectations\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInflation Expectations (PG)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLabor Market Outlook (LMO)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHomeowner (PO) \u0026times; Increase (I⁺)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.2971 (0.1868)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.0177*** (0.0077)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHomeowner (PO) \u0026times; Decrease (I⁻)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-1.0020*** (0.2024)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.0290*** (0.0077)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRenter (TN) \u0026times; Increase (I⁺)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.0379 (0.3431)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0205 (0.0142)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRenter (TN) \u0026times; Decrease (I⁻)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.4264 (0.4293)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.0130 (0.0139)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eObservations\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21,338\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24,474\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eR\u0026sup2;\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0388\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0162\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cb\u003eNotes\u003c/b\u003e: This table presents the results of the threshold regression model, which captures the asymmetric effects of interest rate changes on household expectations. The findings suggest that homeowners are more responsive to interest rate decreases than increases, while renters show no significant asymmetry in their responses. *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.10 denote statistical significance.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThis section has explored the mechanisms through which monetary policy affects household expectations, with a particular focus on the role of homeownership. The findings in Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e suggest that homeowners are more sensitive to changes in interest rates due to their direct exposure to mortgage obligations, while renters are more influenced by labor market conditions and rent inflation. The use of Canadian data provides unique insights into the transmission of monetary policy in a highly leveraged economy, offering valuable implications for policymakers in similar contexts.\u003c/p\u003e\u003cp\u003eRobustness checks and alternative model specifications confirm the validity of the primary findings, while the analysis of household attention to macroeconomic news highlights the importance of effective communication strategies in monetary policy. Overall, this study contributes to a deeper understanding of how monetary policy influences household expectations and economic behavior, with important implications for central banks and policymakers.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study examines the differential effects of monetary policy on household expectations, focusing on the distinction between homeowners and renters. The findings suggest that homeownership status plays a crucial role in shaping how households perceive and respond to interest rate changes, inflation expectations, and labor market conditions. Homeowners, particularly those with adjustable-rate mortgages, exhibit a stronger sensitivity to monetary policy due to the direct impact of interest rates on mortgage payments and housing wealth. In contrast, renters rely more on labor market conditions and wage growth when forming their economic expectations, as they do not benefit from the wealth effects associated with homeownership.\u003c/p\u003e\u003cp\u003eThe findings of this study have important policy implications for central banks and policymakers. Given that homeowners and renters exhibit distinct reactions to monetary policy, central banks should consider segmenting their communication strategies. For instance, when implementing interest rate changes, policymakers should acknowledge the differential impacts on mortgage holders versus renters and frame their messaging accordingly. Additionally, monetary authorities can enhance the effectiveness of policy transmission by improving financial literacy programs, helping households, especially renters\u0026mdash;better understand how monetary policy affects their economic well-being. Finally, given the inflationary pressures in rental markets linked to expansionary policies, policymakers should explore complementary housing policies, such as supply-side measures, to mitigate adverse effects on renters while ensuring overall macroeconomic stability\u003c/p\u003e\u003cp\u003eThe results highlight the importance of considering household heterogeneity in monetary policy transmission. While expansionary policies may boost housing prices and wealth for homeowners, they can simultaneously increase rental costs and financial burdens for non-homeowners. This asymmetric response suggests that monetary policy may have unintended distributional effects, reinforcing economic disparities between asset holders and renters.\u003c/p\u003e\u003cp\u003eFurthermore, the study emphasizes the role of expectations in economic decision-making. Households interpret monetary policy signals differently based on their financial positions, prior experiences, and exposure to debt markets. As such, central banks should refine their communication strategies to ensure that policy measures are effectively understood and interpreted by different demographic groups.\u003c/p\u003e\u003cp\u003eOverall, these findings contribute to a deeper understanding of how monetary policy influences household behavior beyond the aggregate level. By recognizing the diverse responses among homeowners and renters, policymakers can design more targeted and inclusive economic policies that enhance the overall effectiveness of monetary interventions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eCompeting Interests\u003c/h2\u003e\u003cp\u003eThe authors declare that there are no competing interests.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eAuthor contributions \u0026ndash; all co-authors shall be listed using their initials\u003c/h2\u003e\u003cp\u003e\u003cem\u003eAll author contributions have been added, using initials as required.\u003c/em\u003e\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eConflict of interest\u003c/h2\u003e\u003cp\u003e\u003cem\u003eThe Conflict of Interest statement has been moved after the main text, before the References section.\u003c/em\u003e\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding information\u003c/h2\u003e\u003cp\u003eThere is no external funding for this research.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003ethis study introduces a comparative analysis with Canadian data to highlight differences in monetary policy transmission across economies with varying mortgage market structures and homeownership rates. Canada\u0026rsquo;s high prevalence of variable-rate mortgages and elevated household debt levels make it a compelling case for understanding the nuances of monetary transmission in highly leveraged economies.Overall, the findings of this study underscore the necessity of tailoring monetary policy communication and complementary housing policies to address the heterogeneous impacts on households. By recognizing the diverse responses of homeowners and renters, policymakers can enhance the effectiveness of monetary interventions while mitigating potential distributional imbalances.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study are openly available in the manuscript and supplementary materials.\u003c/p\u003e\u003cp\u003eThere are no restrictions on data availability. All data supporting the findings of this study are fully accessible and included within the article and/or supplementary materials.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAhn, H. J., Xie, S., \u0026amp; Yang, C. (2024). Effects of monetary policy on household expectations: The role of homeownership. \u003cem\u003eJournal of Monetary Economics, 147\u003c/em\u003e, 103599. https://doi.org/10.1016/j.jmoneco.2024.103599.\u003c/li\u003e\n\u003cli\u003eAladangady, A. (2017). Housing Wealth and Consumption: Evidence from Geographically Linked Microdata. American Economic Review, 107(11), 3415-3446.\u003c/li\u003e\n\u003cli\u003eAladangady, A. (2017). Wealth effects on consumption: Evidence from mortgage refinancing. \u003cem\u003eAmerican Economic Review\u003c/em\u003e, 107(11), 3550-3588.\u003c/li\u003e\n\u003cli\u003eBaker, S. R., Bloom, N., \u0026amp; Davis, S. J. (2016). Measuring Economic Policy Uncertainty. 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Mental accounting and consumer choice. \u003cem\u003eMarketing Science, 4\u003c/em\u003e(3), 199\u0026ndash;214. https://doi.org/10.1287/mksc.4.3.199 \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Monetary Policy, Household Expectations, Homeownership, Inflation Expectations, Labor Market, Interest Rate Transmission","lastPublishedDoi":"10.21203/rs.3.rs-7180599/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7180599/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis paper investigates how monetary policy differentially affects household expectations based on homeownership status in the United States. While existing literature addresses the general transmission mechanisms of monetary policy, the heterogeneity in responses between homeowners and renters remains underexplored. Using microdata from the Michigan Consumer Survey (MSC) and the New York Federal Reserve\u0026rsquo;s Survey of Consumer Expectations (SCE), we analyze how interest rate changes influence expectations about inflation, labor market prospects, and financial decisions.Our findings reveal that homeowners exhibit stronger reactions to interest rate changes, primarily due to mortgage-related cost adjustments and housing wealth effects. Renters, by contrast, show more muted responses, with expectations largely shaped by employment conditions and rent inflation. By incorporating an econometric framework that accounts for ownership status and macro-financial variables, we offer new evidence on the distributional consequences of monetary policy. These insights underscore the importance of targeted central bank communication strategies that account for household heterogeneity in policy sensitivity.\u003c/p\u003e","manuscriptTitle":"Effects of Monetary Policy on Household Expectations: The Role of Homeownership and Tenancy in USA","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-27 10:52:11","doi":"10.21203/rs.3.rs-7180599/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7e80deba-6fa5-4be1-b27e-71e83944e16b","owner":[],"postedDate":"July 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-21T04:23:07+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-27 10:52:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7180599","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7180599","identity":"rs-7180599","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}