Remittances and household financial behavior in Rajshahi Division, Bangladesh: examining consumption and investment patterns

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Mominul Islam This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7264115/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 study explores the impact of remittances on household spending and investment decisions in Rajshahi Division, Bangladesh. It is based on a cross-sectional survey of 235 remittance-receiving households. For analyzing survey data from households that receive remittances, the research employs multiple regression models to examine spending behaviors. The sample includes households randomly selected from Pabna, Sirajganj, and Kushtia districts. The study focuses on key factors such as financial literacy, migration duration, and income levels to understand their influence on remittance utilization. Findings indicate that most households prioritize consumption over investment. The regression results reveal that financial literacy and remittance amount significantly and positively affect household investment ratio, while migration duration is the strongest predictor of business investment percentage. Interestingly, income levels do not appear to have a significant moderating effect on remittance-driven investment behavior. This study shows how financial knowledge promotes beneficial remittance expenditure. The study's unique focus on migration duration and business investment illuminates remittance-driven financial behavior. Based on these findings, the study recommends promoting household-level financial literacy programs and supporting long-term migrants' investment initiatives to improve the productive use of remittances. Such targeted measures can help maximize remittance benefits for household stability and local economic development, especially in rural regions like Rajshahi Division. Remittances Migration and economic development Household finance Consumption vs. Investment behavior Financial literacy Figures Figure 1 Introduction Background of the study Remittances play a crucial role in Bangladesh’s economy, serving as a lifeline for millions of households. Bangladesh ranks among the top ten remittance-receiving countries globally, with remittance inflows reaching $23.9 billion in FY 2023-24 (Bangladesh Bank 2023). Remittances contribute 5.1% of the country’s GDP, reducing poverty and improving household financial stability (World Bank 2023). The country’s migration trend is primarily driven by economic necessity, with around 12 million Bangladeshi migrants working abroad, particularly in Middle Eastern countries such as Saudi Arabia, the UAE, Qatar, Oman, and Kuwait (BMET 2023). In 2022 alone, over 1.1 million Bangladeshi workers migrated, setting a record for overseas employment (Prothom Alo 2023). While these national-level figures are important, there is limited understanding of how remittances affect household-level consumption and investment decisions, particularly in rural regions. Among the major remittance-receiving regions in Bangladesh, the Rajshahi Division—including districts such as Pabna, Sirajganj, and Kushtia—accounts for a substantial portion of migration to Middle Eastern countries. The prevalence of migration from these districts stems from high unemployment rates, limited economic opportunities, and rural poverty, which push many individuals to seek better financial prospects abroad (Khan 2021). This study focuses on Rajshahi Division to understand how households in economically vulnerable areas utilize remittances, addressing a critical regional gap in existing research. The majority of Bangladeshi migrants are engaged in low-skilled and semi-skilled jobs, including construction, manufacturing, domestic work, and sales. Around 75% of Bangladeshi expatriate workers fall into this category, earning relatively low wages but sending a significant portion of their income back home (ILO 2018). These remittances are often the primary source of income for families left behind, helping them meet basic needs such as food, healthcare, and education. However, the extent to which remittances are channeled into productive investments, such as business ventures and asset accumulation, remains a critical policy concern. Understanding this household-level allocation is essential for designing targeted interventions to improve the long-term economic impact of remittances. Migration has increased in Bangladesh due to economic hardship, widespread unemployment, and low rural wages. Agriculture-based households in Pabna, Sirajganj, and Kushtia districts depend on remittances. Remittances into rural areas improve living conditions, reduce credit dependence, and enable investment in land, housing, and small companies (Naimul et al. 2017). Mainly employed for productive investments or short-term spending, remittances are a serious concern. Remittances significantly impact household spending. Food and healthcare are priorities for migrant families, improving well-being (Raihan, Uddin, and Ahmmed 2022). Education is another important expense since families regard it as a chance to improve their children's futures. Although these benefits exist, investment in productive assets like enterprises and real estate is limited (World Economic Forum 2025). This raises questions about what factors encourage households to shift from short-term consumption to long-term investment, a focus that this study directly addresses. Remittances provide financial stability and improve living conditions for households. Families use remittances for daily expenses, education, healthcare, debt repayment, housing improvements, and small investments. Remittance-receiving households had stronger consumption and financial resilience than non-receiving households, according to empirical studies. Remittances boost short-term financial security, but how households use them determines their long-term economic benefit. Some families spend remittances on short-term necessities, while others invest in entrepreneurship, land purchase, and business expansion to boost economic growth. Financial literacy and banking access could improve remittance use, ensuring long-term financial stability and development. This study, therefore, seeks to understand how financial literacy, income levels, and migration duration influence remittance utilization at the household level, using data specifically collected from Rajshahi Division. Research aim and objectives The primary aim of this study is to examine the impact of remittances on household consumption and investment patterns in the Rajshahi Division—including districts such as Pabna, Sirajganj, and Kushtia, Bangladesh. Given the increasing reliance of Bangladeshi households on remittances, this research seeks to explore how these financial inflows shape economic behavior, particularly in terms of essential expenditures such as food, education, and healthcare, as well as long-term investment decisions like land acquisition, business ventures, and savings. The study also examines how financial literacy and income categories moderate remittance use for financial stability and economic growth. To achieve this aim, the study is guided by the following objectives: To assess the relationship between remittances and household consumption patterns, focusing on the extent to which remittances are allocated to daily expenses such as food, education, and healthcare. To examine the impact of remittances on household investment behavior, focusing on the percentage of inflows allocated to productive activities including business expansion, land acquisitions, and long-term savings. To evaluate the role of financial literacy in influencing remittance utilization, determining whether households with better financial knowledge allocate remittances more efficiently toward investment rather than consumption. To investigate the moderating effect of income levels on remittance-investment relationships, identifying whether higher-income households demonstrate more productive use of remittances compared to lower-income groups. To analyze how migration duration influences remittance allocation, particularly whether long-term migrants contribute more toward business investments compared to short-term migrants. By addressing these objectives, this study aims to contribute to the existing body of literature by offering empirical insights into how remittances are managed at the household level and identifying key factors that optimize their economic benefits. Research gap and significance of the study Despite the vast body of research on remittances and their economic impact, there remains a crucial gap in understanding how these financial inflows shape household consumption and investment decisions in specific regional contexts in Bangladesh. Much of the existing literature has focused on the macroeconomic effects of remittances, such as their contributions to GDP, poverty reduction, and foreign exchange reserves. However, studies that provide granular insights into the micro-level financial behaviors of remittance-receiving households are relatively limited, especially within rural economies that depend heavily on migration income. A key limitation in prior studies is the lack of differentiation between consumption and investment behavior. While remittances undeniably improve household welfare by reducing financial vulnerability and enhancing access to education and healthcare, the extent to which they contribute to productive investment remains highly debated. Many studies assume that remittances automatically lead to business development, but empirical findings are mixed. Some argue that remittances foster entrepreneurship and asset accumulation, while others suggest that most funds are spent on daily needs rather than being invested in income-generating activities (Adams Jr and Cuecuecha 2013). The role of financial literacy, migration duration, and income level in shaping these decisions remains underexplored, particularly in developing economies like Bangladesh. Another research gap involves the moderating effect of household income on remittance utilization. While prior studies acknowledge that lower-income families rely more on remittances for consumption, few have examined whether higher-income households are more likely to allocate remittances toward business investment, land acquisition, or savings. Understanding this relationship is critical for targeting financial policies that encourage long-term wealth creation among remittance-dependent households. Furthermore, there is limited empirical research on how financial literacy influences remittance spending. Although studies highlight the importance of financial education in wealth management and savings behavior, empirical evidence specific to remittance-receiving households in rural Bangladesh is scarce. A deeper examination of how financial awareness affects remittance-based investment decisions is necessary for designing more effective financial inclusion programs in Bangladesh. In addition, migration duration has been widely acknowledged as a determinant of remittance flow stability, but its effect on household investment decisions remains unclear. Some studies suggest that short-term migrants remit larger amounts in the early years to support immediate household needs, while long-term migrants provide more stable financial support that facilitates investment in education, business, and property. However, there is insufficient empirical evidence on whether longer migration durations lead to greater investment in productive assets. This study is highly significant as it will address these gaps by providing empirical evidence from Rajshahi Division—including districts such as Pabna, Sirajganj, and Kushtia, rural regions that heavily depends on Middle Eastern labor migration. The findings will be policy-relevant, offering guidance for governments, financial institutions, and development agencies on designing strategies that encourage sustainable economic development through remittance utilization. Policymakers can use the insights from this study to develop customized financial literacy programs, enhance access to formal banking and investment services, and implement targeted interventions that maximize the long-term economic benefits of remittances for rural communities. By investigating household financial behavior, investment choices, and the role of financial literacy, this research will contribute substantially to the discourse on remittance economics in Bangladesh. The findings will provide valuable inputs for designing policies that encourage productive investments, ultimately helping households transition from dependency on remittances to financial self-sufficiency. Furthermore, this study will serve as a foundation for future research on how migration and remittances interact with financial behaviors in other developing economies facing similar migration-driven financial structures. This study is divided into several sections. The introduction explains the study's purpose and why remittances matter. The literature review examines past studies on remittances, consumption, and investment while identifying research gaps. The methodology describes data collection, sample selection, and analysis techniques. The results present key findings from statistical analysis. The discussion interprets the results and compares them to previous studies. The conclusion and recommendations summarize key points, suggest policy measures, highlight study limitations, and propose future research directions. Literature review Concept of remittances & economic impact Remittances play a key role in economic stability. They provide financial support to families in developing countries. Theories such as the Permanent Income Hypothesis (Friedman 2018) and the Life Cycle Hypothesis (Kurihara 2013) suggest that remittances are used based on long-term expectations, not just immediate needs. Some studies show that remittances boost household consumption (Ratha 2013). Others argue that they help families invest in businesses, land, or education (Adams Jr 2011). In South Asia, remittances have reduced poverty and increased financial access (Gupta, Pattillo, and Wagh 2009). However, some studies warn that remittances can make families dependent and reduce their motivation to work (Chami, Fullenkamp, and Jahjah 2005). Household consumption vs. investment framework Households receiving remittances often allocate them based on their immediate needs and financial priorities. Several studies highlight that a significant portion of remittances is used for daily consumption, including food and healthcare. Adams Jr & Cuecuecha (2013) found that in developing countries, remittance-receiving households spend more on food and basic necessities than non-recipient households. Similarly, Gupta et al. (2009) showed that remittances help improve nutrition and healthcare access, particularly in low-income families. Education is another critical area where remittances are spent. Evidence suggests that households with remittance income invest more in children's education than those without. Yang (2008) found that remittances in the Philippines increased school enrollment rates and reduced child labor, allowing families to prioritize education. Acosta et al. (2008) reported similar findings in Latin America, showing that remittance-receiving households allocate more funds to education, reducing dropout rates. Studies show that 40% of remittances go to household consumption and 35% to health and education (Bangladesh Bank 2021). Business investments, real estate, and savings receive less. This shows that remittances may give quick financial relief but not permanent economic growth. Many households fail to employ remittances to create long-term income, limiting their economic benefits. Remittance use depends on financial literacy and banking availability. Many households employ informal saving because they lack financial management knowledge (Lusardi and Mitchell 2014). Only 35% of Bangladeshi remittance-receiving households save in formal banks, while the remainder employ informal methods, according to a survey. Families without financial expertise may miss opportunities to invest remittances in ways that boost long-term stability. Investment in business is less common but still plays a role. Some studies suggest that remittances contribute to small-scale entrepreneurship and self-employment. Woodruff and Zenteno (2007) found that remittance-receiving households in Mexico were more likely to start businesses. However, in many developing countries, business investment remains a secondary priority, as families often use remittances for consumption rather than capital accumulation (Ratha 2013). A World Bank (2008) report found that most remittances are spent on daily expenses rather than capital investments. Some studies also suggest that high remittance dependence reduces workforce participation, as families rely on external income instead of local employment (Upadhyaya, Dhakal, and Thapa 2013). The debate on remittances centers on whether they contribute to long-term economic growth or short-term consumption. Some scholars argue that remittances discourage productive labor and create dependency (Chami et al. 2005), while others suggest they provide an alternative source of capital, especially in weak financial systems (Giuliano and Ruiz-Arranz 2009). Income level moderates remittance-investment decisions Income typically determines how recipients use remittances. Low-income households spend most of their remittances on food, housing, and utilities (Adams Jr 2011). Middle-income households invest more in education, entrepreneurship, and real estate, showing a longer-term financial outlook (Dustmann and Mestres 2010). Wealthier households invest remittances in long-term investments that develop financial assets (Giuliano and Ruiz-Arranz 2009). However, lower-income households depend on remittances for daily survival, limiting their savings and investment (Chami et al. 2005). This shows how financial position affects remittance usage. Remittance recipients often lack financial planning abilities, wasting funds (Giuliano and Ruiz-Arranz 2009). Remittance use also depends on household income. Lower-income households spend most of their remittances on basic needs, while higher-income households invest in enterprises, land, or savings. Additionally, migration duration matters. Short-term migrants cover everyday costs, while long-term migrants save and invest (Dustmann and Kirchkamp 2002). Duration of migration and business investment Migrants' remittance usage also depends on their stay overseas. Long-term migrants save more and invest in businesses as they become financially stable (Woodruff and Zenteno 2007). Long-term expatriates are more inclined to send money for investment than consumption (Dustmann and Kirchkamp 2002). The New Economics of Labor Migration theory (Stark and Bloom 1985) outlooks migration as a thoughtful household decision to reduce financial risks and improve living conditions. Long-term migrants generally learn commercial and financial skills, which helps them invest in income-generating businesses (Vaaler 2011). Summary of literature, gaps, and contribution Table 1 below shows the summary of the literature, gaps, and contributions of the study. Table 1 Summary of literature, gaps, and contribution Existing Studies' Key Themes & Gaps Authors and Date My Contribution in the Current Study Existing studies analyze the impact of remittances on household consumption but often fail to differentiate their effects across various household structures and income levels. (Ratha 2013), (Adams Jr and Cuecuecha 2013), (Chami et al. 2005) This study examines remittance allocation based on income categories and financial literacy, offering a more nuanced analysis of household financial behavior. The investment potential of remittances is acknowledged, but prior research largely overlooks the moderating effect of financial literacy and income levels. (Adams Jr 2011), (Giuliano and Ruiz-Arranz 2009), (Woodruff and Zenteno 2007) This study introduces financial literacy and income level as key moderators, showing how they shape remittance utilization. Studies on remittances and financial literacy are mostly conducted in developed economies, with limited research focused on South Asia. (Lusardi and Mitchell 2014), (Hastings et al. 2012), (Klapper, Lusardi, and Van Oudheusden 2015), This study provides empirical evidence from Bangladesh, offering insights into a developing economy where remittances play a crucial role. The relationship between migration duration and investment is discussed, but previous studies do not account for variations in business investment decisions. (Woodruff and Zenteno 2007), (Dustmann and Kirchkamp 2002), (Vaaler 2011) This study examines how migration duration affects business investment decisions, contributing new evidence on the long-term impact of migration. Previous studies focus on the macroeconomic impact of remittances rather than household-level decision-making. (Adams Jr 2011), (Dustmann and Mestres 2010), (Giuliano and Ruiz-Arranz 2009) This study shifts the focus to microeconomic decision-making by analyzing household remittance allocation at an individual level. Most research does not properly capture the household-level interplay between financial literacy, income, and remittance use. Additionally, migration duration's impact on firm investment is unknown. By using financial knowledge and income as moderators, my work fills these gaps and provides a better understanding of remittance allocation in underdeveloped economies. The findings provide a paradigm for household remittance-driven financial decisions, which informs policy and scholarly literature. Conceptual framework and hypotheses development Conceptual framework This study examines how remittances influence household consumption and investment, integrating financial literacy, income level, and migration duration as moderating factors. The Permanent Income Hypothesis (Friedman 2018) and Life Cycle Hypothesis (Kurihara 2013) explain that households plan income allocation over time. However, in developing economies, remittances often fund immediate consumption rather than investment (Stark and Bloom 1985). The Dual Sector Model (Lewis 1954) suggests remittances can transition households from subsistence living to entrepreneurship. The conceptual model positions remittance amount as the key independent variable, influencing consumption (daily expenses) and investment (business, education, savings), with financial literacy, income level, and migration duration moderating the relationships. Hypotheses H1 Households receiving remittances allocate a significant portion toward consumption rather than investment. The Keynesian Consumption Function (Keynes 1936) suggests that an increase in income leads to higher spending. Remittance-dependent families often prioritize food, rent, and healthcare (Ratha 2013). Research shows that in low-income economies, remittances are mainly used for consumption (Adams Jr and Cuecuecha 2013). While remittances help stabilize households, excessive spending may reduce investment opportunities. The Permanent Income Hypothesis (PIH) (Friedman 2018) suggests that people plan their spending over time. However, in low-income households, remittances are often used for daily expenses rather than investment. This study modifies the hypothesis to highlight the heavy reliance on remittances for food, healthcare, and other needs instead of business or asset investment. H2 There is a positive relationship between remittance inflow and household investment in education. The Human Capital Theory (Becker 2009) explains that investment in education improves future income. Studies show that remittances help families afford school fees and supplies. This study examines how much of remittance income is used for education in recipient households. H3 Households with higher financial literacy allocate more remittances toward investment than consumption. Behavioral Economics explains that financially literate individuals make better financial decisions (Lusardi and Mitchell 2014). Households with financial knowledge are more likely to invest remittances in businesses, real estate, or savings. Without financial literacy, households may struggle to use remittances effectively, reducing long-term benefits. The Financial Literacy Theory states that better financial knowledge improves money management. Research suggests that financially educated households save and invest more (Atkinson and Messy 2012). This study explores whether financial literacy influences remittance spending decisions. H4 Households with long-term migrants invest more in business than those with recent migrants. The Migration Investment Framework (Dustmann and Mestres 2010) suggests that migration duration affects remittance usage. Short-term migrants send money for immediate needs, while long-term migrants contribute to investments (Mansuri 2006). This study assesses whether remittance spending patterns change over time. H5 Household income influences the link between remittances and investment. Income levels determine how remittances are used. Higher-income families are more likely to invest, while lower-income households rely on remittances for survival (Raihan et al. 2022). This study evaluates whether household income shapes remittance investment decisions. Research methodology This study examines how households use remittances for consumption and investment. It focuses on three districts of Rajshahi division in Bangladesh: Pabna, Sirajganj, and Kushtia, where many people migrate to Middle Eastern countries for work. The study follows a quantitative approach using survey data to understand spending patterns. The total sample size is 235 households. The sample is equally distributed across the three districts, with about one-third of households taken from each district. A cross-sectional household survey was conducted through face-to-face interviews using structured questionnaires. A random sampling method was used to select remittance-receiving households. This ensures that different income levels and financial backgrounds are included. The survey included both male and female respondents, focusing on the main household decision-makers. This method allows consistency in responses but limits detailed personal opinions. The questionnaire included closed-ended questions on remittance usage, financial literacy, and investment decisions. The study considers multiple key variables. The dependent variables include the Consumption Ratio, which measures the proportion of remittances spent on household needs, and the Investment Ratio, which reflects the share allocated to savings, business, or asset accumulation. The independent variables include the Remittance Amount, which represents the total remittances received by the household, Household Income (excluding remittances), Financial Literacy (a dummy variable where 1 = High and 0 = Low), and Migration Duration, which is categorized into four groups: less than 1 year, 1-3 years, 3-5 years, and more than 5 years. Additional household-level characteristics were included as control variables in the regression models to reduce omitted variable bias. These include age, gender, education level, and dependency ratio of the remittance recipient. Control variables were chosen based on prior literature and economic reasoning. Age and education of the household head can influence financial decision-making. Household size affects expenditure needs. Gender and occupation also shape remittance utilization patterns. To avoid bias from combining ratio variables and absolute numbers in the models, all continuous variables were checked for scale compatibility and normalized where necessary before analysis. This ensured that variables such as remittance amount (absolute value) and investment ratio (proportion) were appropriately handled in the regression models. Some variables in this study are ratios (like investment and consumption ratios), while others are absolute values (such as remittance amount). To avoid issues from combining these different types of variables, all continuous variables were reviewed for scale compatibility. Where necessary, they were normalized before regression analysis. This step ensured that ratio variables and absolute numbers could be used together without bias. Variable definitions and measurements were guided by the structured questionnaire, which asked respondents to report both exact remittance amounts and the percentage allocation to specific uses such as education, consumption, and business investment. The study also includes a moderating variable, Income Category, categorized as Low, Medium, and High, to test whether income level influences remittance utilization. An interaction term was created: Remittance × Income Category, to determine whether income level moderates the relationship between remittance inflows and household investment decisions. Econometric models To analyze these relationships, various linear regression models were used. Effect of remittances on consumption ratio: Consumption Ratioi=β0+β1×Remittance Amounti+β2×Household Controlsi+ϵi Effect of remittances on education investment: Education Investmenti=β0+β1×Remittance Amounti +β2×Household Controlsi+ϵi Effect of remittances and financial literacy on investment ratio: Investment Ratioi=β0+β1×Remittance Amounti+β2×Financial Literacyi+β3×Household Controlsi+ϵi Effect of migration duration and remittance amount on business investment: Business Investmenti=β0+β1×Migration Durationi+β2×Remittance Amounti+β3×Household Controlsi+ϵi Moderation model for income level in investment decisions: Investment Ratioi=β0+β1×Remittance Amounti+β2×Income Categoryi+β3 ×(Remittance Amount×Income Category) +ϵi Each of these models provides an econometric framework to analyze the dynamics of remittance allocation in recipient households. Household control variables include age, education level, household size, and dependency ratio. By estimating these equations using regression analysis, we can determine the strength and significance of these economic relationships, thereby offering valuable insights for policymakers and financial institutions. Results Demographic information The majority of migrants are male (90.2%), while females account for only 9.8% of the total. Regarding the migrant's relationship with the household, husbands (41.3%) send the most remittances, followed by sons (40%) and brothers (13.6%). Educational attainment among household members varies, with 19.6% having no formal education, while 20.4% have a bachelor’s degree or higher. These findings suggest that a significant portion of households still lacks higher education, which may influence financial decision-making. The destination of migration also plays a key role in remittance inflows. Most migrants are in Saudi Arabia (14%), UAE (14%), Kuwait (20.9%), and Oman (12.8%), while a smaller portion is in Bahrain (11.5%) and Qatar (9.4%). The method of remittance transfer varies, with the majority relying on bank transfers (61.7%), followed by mobile financial services (30.2%), while a small percentage still uses informal Hundi channels (8.1%). These trends indicate that formal banking channels dominate remittance inflows, reducing the risks associated with informal transfer methods. Descriptive statistics Table 2 Descriptive statistics Descriptive Statistics N Minimum Maximum Mean Std. deviation Remittance amount 235 20017 99901 60968.41 23411.286 Education expense percentage 235 .26 10.77 6.1226 2.45379 Business investment percentage 235 .20 2.33 1.2248 .65721 Consumption ratio 235 .40 .85 .6489 .12607 Investment ratio 235 .06 .29 .1702 .04801 Valid N (list-wise) 235 Table 2 shows the descriptive statistics. In terms of financial distribution, households receive an average remittance of 60,968.41 BDT, with values ranging between 20,017 BDT to 99,901 BDT. A large portion of these remittances is used for daily consumption needs (64.89%), while investment in business remains low (1.22%). The education expense percentage is 6.12%, indicating that only a small portion of remittances is allocated to educational development. The investment ratio is 17.02%, suggesting that while some households invest in long-term financial stability, a significant portion of remittances is used for immediate needs rather than asset accumulation. Further analysis of financial stability indicators shows that 53.6% of households have not started a business, while 46.4% have. Among those who invest in businesses, 27.7% are engaged in agriculture, 26.8% in transport, and 23% in retail shops, highlighting the sectors where remittance-fueled investments are directed. However, 42.1% of households report investment difficulties, mainly due to financial constraints. Meanwhile, 51.1% of households indicate financial stability, and 48.9% have reduced loans using remittance money. Despite this, 51.9% of households remain highly dependent on remittances, raising concerns about their ability to sustain themselves without external financial support. Correlation Table 3 Correlations Correlations Migration duration Remittance amount Education expense percentage Business investment percentage Financial literature Consumption ratio Investment ratio Income category Migration duration Pearson Correlation 1 .142 * .138 * .964 ** .051 .102 .078 -.121 Sig. (2-tailed) .030 .034 .000 .434 .119 .235 .063 Remittance amount Pearson Correlation .142 * 1 .909 ** .146 * .475 ** .683 ** .674 ** -.086 Sig. (2-tailed) .030 .000 .025 .000 .000 .000 .187 Education expense percentage Pearson Correlation .138 * .909 ** 1 .145 * .409 ** .602 ** .601 ** -.132 * Sig. (2-tailed) .034 .000 .027 .000 .000 .000 .044 Business investment percentage Pearson Correlation .964 ** .146 * .145 * 1 .053 .103 .086 -.131 * Sig. (2-tailed) .000 .025 .027 .419 .115 .188 .044 Financial literature Pearson Correlation .051 .475 ** .409 ** .053 1 -.031 .814 ** -.017 Sig. (2-tailed) .434 .000 .000 .419 .642 .000 .791 Consumption ratio Pearson Correlation .102 .683 ** .602 ** .103 -.031 1 .066 -.079 Sig. (2-tailed) .119 .000 .000 .115 .642 .316 .227 Investment ratio Pearson Correlation .078 .674 ** .601 ** .086 .814 ** .066 1 -.058 Sig. (2-tailed) .235 .000 .000 .188 .000 .316 .373 Income category Pearson Correlation -.121 -.086 -.132 * -.131 * -.017 -.079 -.058 1 Sig. (2-tailed) .063 .187 .044 .044 .791 .227 .373 *. Correlation is significant at the 0.05 level (2-tailed). **. Correlation is significant at the 0.01 level (2-tailed). In Table 3, the correlation analysis highlights key relationships between remittance usage, financial literacy, migration duration, and income levels. Migration duration is strongly linked to business investment (r=0.964, p<0.01r = 0.964, p < 0.01r=0.964, p<0.01), indicating that longer migration leads to higher business investment. Remittance amount is positively correlated with both consumption (r=0.683, p<0.01r = 0.683, p < 0.01r=0.683, p<0.01) and investment (r=0.674, p<0.01r = 0.674, p < 0.01r=0.674, p<0.01), confirming that households with higher remittances allocate funds for both immediate needs and future gains. Financial literacy is moderately linked to education expenses (r=0.409, p<0.01r = 0.409, p < 0.01r=0.409, p<0.01), but not significantly associated with business investment or consumption. Income category has a weak negative correlation with business investment and education spending, suggesting that wealthier households allocate remittances differently. These findings support the study’s hypotheses and provide a foundation for further regression analysis. Multicollinearity The analysis validates the hypotheses related to remittance utilization. Remittance Amount, Income Category, Financial Literacy, and Migration Duration significantly influence consumption and investment decisions. The Variance Inflation Factor (VIF) values (1.021–1.322) and Tolerance values (>0.7) confirm no multicollinearity, ensuring the reliability of the regression model. This indicates that each independent variable contributes uniquely to explaining remittance allocation, reinforcing the importance of financial awareness and economic stability in shaping remittance usage. Analysis Impact of remittance amount on consumption ratio Table 4 Effect of remittances on consumption ratio Coefficients a Model Unstandardized coefficients Standardized coefficients Beta t Sig. B Std. error (Constant) 0.424 0.036 11.740 .000 Age 0.004 0.004 0.004 0.092 .927 Education Level 0.005 0.004 0.055 1.128 .260 Household Members -0.003 0.003 -0.007 -1.135 .893 Dependents -0.002 0.004 -0.025 -0.520 .604 Remittance Amount 3.638E-6 .000 0.676 13.849 .000 a. Dependent variable: Consumption ratio Table 4 presents the results of the regression analysis exploring the effect of remittance inflows on the household consumption ratio, while controlling for age, number of dependents, household size, and education level. The analysis reveals a statistically significant positive relationship between remittance amount and consumption ratio. The model reports an R-value of 0.686, indicating a strong positive correlation between the predictors and the dependent variable. The R-squared value of 0.470 suggests that approximately 47% of the variation in household consumption ratio is explained by the model. The adjusted R² of 0.459 confirms the model's explanatory power after accounting for the number of predictors included. The ANOVA test demonstrates the overall significance of the model, with an F-statistic of 40.657 and a p-value < 0.001, indicating that the model provides a statistically significant fit to the data. As shown in Table 4, the remittance amount has a significant positive effect on the consumption ratio (B = 3.638E-6, p < 0.001), with a standardized beta coefficient of 0.676, signifying a strong effect size. This implies that higher remittance inflows are associated with increased household spending, supporting the hypothesis that remittances are largely allocated toward consumption needs. Among the control variables, none are statistically significant at the 5% level. Age (p = 0.927), education level (p = 0.260), household size (p = 0.893), and number of dependents (p = 0.604) do not exhibit a meaningful impact on the household consumption ratio in this model. Nevertheless, their inclusion ensures a robust estimation of the effect of remittances. These findings emphasize that remittances play a critical role in shaping household consumption behavior, with implications for financial planning and welfare policies targeting remittance-receiving families. Impacts of remittance amount on education expense The regression analysis explores the relationship between remittance inflows and the proportion of household spending allocated to education. The dependent variable is the percentage of household expenses dedicated to education. The model includes control variables such as age, education level, household size, and number of dependents. The model demonstrates a strong overall fit, with an R-value of 0.911, indicating a high positive correlation between remittance amount and education expense. The R² value of 0.830 suggests that approximately 83.0% of the variance in education spending can be explained by the combined effect of remittance inflows and the control variables. The adjusted R² of 0.826 confirms the robustness of the model after accounting for sample size. Additionally, the standard error of the estimate is 1.02304, indicating a relatively small dispersion of observed values around the regression line. The ANOVA table confirms the overall significance of the model, with an F-statistic of 223.438 (p < 0.001), affirming that the predictors collectively explain a significant portion of the variance in education expenses. Table 5 Effect of remittances on education investment Coefficients a Model Unstandardized coefficients Standardized coefficients Beta t Sig. B Std. error (Constant) -0.182 0.399 — -0.457 0.648 Age 0.007 0.006 0.036 1.318 0.189 Education Level -0.013 0.048 -0.007 -0.265 0.791 Household Members 0.052 0.034 0.133 1.507 0.133 Dependents -0.053 0.047 -0.031 -1.135 0.257 Remittance Amount 5.593E-5 0.000 0.915 33.113 0.000 a. Dependent variable: Education expense percentage Table 5 presents the detailed regression coefficients. The remittance amount is found to be a statistically significant predictor (B = 5.593E-5, p < 0.001), with a standardized beta coefficient of 0.915. This demonstrates a strong positive association, indicating that as remittances increase, households tend to allocate a larger proportion of their budget to education. In contrast, the control variables (age, education level, household size, and dependents) do not show statistically significant relationships with education expenditure, suggesting that remittance inflows are the principal driver of increased education spending. These findings underscore the critical role of remittances in facilitating educational investment among recipient households. The results align with the hypothesis that remittance inflows provide financial resources that directly support long-term human capital development. Impact of remittances and financial literacy on investment ratio Table 6 Effect of remittances and financial literacy on investment ratio Coefficients a Model Unstandardized coefficients Standardized coefficients Beta t Sig. B Std. error (Constant) 0.097 0.010 10.181 .000 Age 0.000 0.000 .026 0.814 .417 Education Level -0.001 0.001 -.028 -0.874 .383 Household Members 0.001 0.001 .026 0.805 .422 Dependents -0.001 0.001 -.031 -0.978 .329 Remittance Amount 7.649E-7 0.000 .373 10.177 .000 Financial Literacy 0.062 0.003 .643 17.728 .000 Migration Duration -0.001 0.001 -.007 -0.223 .824 a. Dependent variable: Investment ratio Table 6 presents the results of the multiple linear regression model estimating the effect of remittance amount and financial literacy on the household investment ratio, controlling for relevant demographic and household-level factors. The model includes control variables such as migration duration, education level, number of dependents, household size, and age of the household head. The regression model explains approximately 77.3% of the variation in the investment ratio (R² = 0.773), with an adjusted R² of 0.766 and a standard error of 0.02325. The ANOVA results confirm the model’s overall statistical significance (F = 110.144, p < 0.001), indicating that the independent variables jointly have a strong influence on the investment ratio. Among the predictors, remittance amount (B = 7.649E-7, β = 0.373, p < 0.001) and financial literacy (B = 0.062, β = 0.643, p < 0.001) have statistically significant and positive effects on investment ratio. This implies that households receiving higher remittances and exhibiting greater financial literacy are more likely to allocate a larger proportion of their income towards investment purposes. Conversely, control variables such as age, education level, number of household members, number of dependents, and migration duration did not show significant individual effects (p > 0.05), although they contribute to the model's overall explanatory power. These findings reinforce the critical role of both remittance inflows and financial literacy in promoting household-level investments. Financial literacy, in particular, appears to have a stronger standardized impact, suggesting its influence in improving financial decision-making and efficient allocation of resources. Impact of remittance amount and migration duration on business investment percentage Table 7 Effect of migration duration, remittance amount, and household-level controls on business investment Coefficients a Model Unstandardized coefficients Standardized coefficients Beta t Sig. B Std. error (Constant) -0.235 0.073 – -3.223 0.001 Age 0.001 0.001 0.015 0.864 0.388 Education level 0.006 0.008 0.012 0.690 0.491 Household members -0.003 0.006 -0.008 -0.473 0.637 Dependents 0.009 0.009 0.019 1.089 0.277 Remittance amount 3.625E-7 0.000 0.001 0.639 0.524 Migration duration 0.565 0.010 0.964 54.347 0.000 Debt payment -0.005 0.023 -0.004 -0.203 0.839 Financial literacy 0.012 0.026 0.009 0.453 0.651 Investment difficulties -0.042 0.018 -0.240 -2.290 0.023 a. Dependent variable: Business investment percentage Table 7 presents the results from a multiple linear regression model that investigates the influence of migration duration and remittance amount on business investment behavior, while controlling for a set of household-level socioeconomic and financial variables. The model is statistically significant (F = 342.064, p < 0.001), and the R² value of 0.932 indicates that approximately 93.2% of the variance in business investment percentage is explained by the independent variables included in the model. Among the predictors, migration duration emerges as the most influential variable (B = 0.565, β = 0.964, p < 0.001), suggesting that households with migrants who spend longer periods abroad are significantly more likely to invest a greater proportion of remittances into business activities. This finding aligns with the hypothesis that prolonged migration enables individuals to accumulate financial capital and entrepreneurial knowledge, thereby fostering investment readiness. While remittance amount shows a positive coefficient (B = 3.625E-7), it is not statistically significant (p = 0.524), indicating that the sheer volume of remittance inflows does not independently predict business investment once migration duration and other household factors are considered. Among the control variables, investment difficulties is the only statistically significant factor (B = -0.042, β = -0.240, p = 0.023). The negative coefficient highlights that households encountering greater challenges in accessing or utilizing investment opportunities tend to allocate a smaller portion of remittances to business activities. This underscores the importance of institutional and infrastructural support in facilitating productive investment. Other variables, including age, education level, number of household members, number of dependents, debt payment, and financial literacy, do not exhibit statistically significant effects (p > 0.05). Their inclusion was guided by theoretical relevance and prior empirical findings, but their effects may be absorbed by stronger predictors in this model. Overall, the results reinforce the pivotal role of migration experience, particularly duration, in shaping household investment behavior, while also acknowledging the obstructive role of practical investment challenges. This highlights the need for targeted support mechanisms that ease investment processes for remittance-receiving households, especially those with substantial migration histories. Moderation analysis The regression analysis examines the moderating effect of income category on the relationship between remittance amount and investment ratio. The model summary indicates an R² value of 0.4548, suggesting that approximately 45.48% of the variance in investment ratio can be explained by the independent variables, including the interaction term. The F-statistic (64.2394, p < 0.001) confirms that the overall model is statistically significant. Table 8 Moderation model for income level in investment decisions Coefficients a Model Coefficient SE t Sig. (Constant) .1702 .0023 72.8870 .0000 Remittance amount .0000 .0000 13.8139 .0000 Income category .0000 .0021 .0017 .9987 Interaction term .0000 .0000 .2144 .8304 a. Dependent variable: Investment ratio The coefficients Table 8 shows that remittance amount has a significant positive effect on investment ratio (B = 0.0000, t = 13.8139, p < 0.001), indicating that higher remittances contribute to increased investments. However, the interaction term (Remittance amount × Income category) is not significant (B = 0.0000, t = 0.2144, p = 0.8304), suggesting that income category does not significantly moderate the relationship between remittances and investment. The graphical representation in Figure 1 further supports these findings, showing that the slopes of the regression lines for different income categories are nearly identical, indicating no substantial difference in investment behavior across income groups. This suggests that regardless of income level, remittances play a crucial role in shaping investment decisions, with no significant moderating effect from income category. Discussion Impact of remittance inflows on household consumption The regression analysis shows that remittance inflows have a significant positive effect on household consumption. The standardized beta coefficient of 0.676 suggests that a one-unit increase in remittance leads to a 67.6% rise in household consumption. This result aligns with the findings of Adams and Cuecuecha (2013) and Gupta et al. (2009) who reported that remittances are primarily used for food, healthcare, and daily necessities. The R² value of 0.470 indicates that remittances explain 47.0% of the variation in consumption, confirming that household spending largely depends on remittance income. The adjusted R² of 0.459 confirms the explanatory power of the model after accounting for control variables. The statistical significance of the model (p < 0.001) further strengthens the conclusion that remittances play a vital role in sustaining household expenses. While previous research suggests that remittances can also support business investment and long-term financial stability (Woodruff and Zenteno 2007), this study finds that the primary allocation is toward immediate consumption. This supports Keynesian economic theory, which argues that income increases drive consumption growth. The remaining 53.0% of variation in household consumption is explained by other factors such as local income, employment conditions, and financial literacy. Among the control variables—age, education level, household size, and number of dependents—none were statistically significant in this model, indicating that remittances are the primary driver of consumption behavior in remittance-receiving households. The findings confirm that while remittances provide financial stability in the short run, they may not necessarily contribute to long-term asset accumulation, as also debated by Ratha (2013). This highlights the need for policies that encourage remittance-receiving households to allocate a portion of funds toward investment and savings for future economic security. Relationship between remittance amount and education expenses The regression results indicate a strong and statistically significant relationship between remittance inflows and household spending on education. The model reports an R² value of 0.830, indicating that 83.0% of the variation in education expenses is explained by the included predictors, primarily remittance inflows. This suggests that remittances are a primary financial resource for educational investments. The standardized beta coefficient of 0.915 suggests that a one-unit increase in remittance amount leads to a 91.5% increase in household spending on education. This reinforces the argument that remittances serve as a crucial driver of human capital formation. This aligns with the Human Capital Theory (Becker 2009), which posits that individuals and households view education as an investment in future earning potential. Empirical studies further support this link, with Yang (2008) and Acosta (2011) demonstrating that remittances enhance school enrollment rates and reduce dropout rates, particularly in developing countries. The findings contrast with research suggesting that remittances are primarily consumed rather than invested (Ratha, 2021). While previous studies highlight a strong inclination toward immediate consumption needs such as food and healthcare (Adams Jr and Cuecuecha 2013), this study indicates that education is a key spending priority for remittance-receiving households. The remittance variable shows a statistically significant coefficient (B = 5.593E-5, p < 0.001), with a strong effect size, highlighting that families prioritize education when remittance income increases. This reinforces earlier findings by Acosta (2011) that remittances act as a financial buffer for households, enabling them to support children's schooling without disruption. The non-significant constant term (B = -0.182, p = 0.648) indicates that in the absence of remittance inflows, education expenses are not automatically guaranteed, reflecting financial constraints in non-remittance-receiving households. While remittances facilitate access to education, other factors may still influence household education spending decisions. Economic conditions, parental financial literacy, and government support programs may further shape educational investments. Some scholars argue that remittances are more likely to be allocated toward education when financial literacy levels are higher, as informed households recognize the long-term benefits of human capital investment (Lusardi and Mitchell 2014). The findings of this study support policies that encourage productive utilization of remittances, particularly through financial education initiatives that enhance household decision-making in favor of long-term investments such as education. The role of remittances and financial literacy in investment decisions The regression results show that both remittances and financial literacy influence household investment. The model explains approximately 77.3% of the variation in the investment ratio (R² = 0.773), with an adjusted R² of 0.766 and a standard error of 0.02325.This supports past research that highlights financial literacy as key to better financial decisions (Lusardi and Mitchell 2014). The findings suggest that remittances increase investment, but the impact is small. However, both remittance amount (B = 7.649E-7, β = 0.373, p < 0.001) and financial literacy (B = 0.062, β = 0.643, p < 0.001) are statistically significant predictors of investment ratio. Financial literacy has a much stronger effect. Households with financial knowledge are more likely to invest remittances in business or savings. Similar studies found that financial education helps people make better investment choices (Hastings et al. 2012; Klapper et al. 2015). Research also shows that financially aware households prioritize long-term investments. Atkinson and Messy (2012) found that such households spend less on daily needs and more on wealth-building activities. Islam et al. (2012) noted that in Bangladesh, financially literate families use remittances for business and asset growth. Demirgüç-Kunt (2008) showed that financial literacy increases banking and microfinance participation. Conversely, control variables such as age, education level, number of household members, number of dependents, and migration duration were not individually significant (p > 0.05), though they contribute to the overall explanatory power of the model. Despite its benefits, financial literacy remains low in many developing countries. Expanding financial education can help remittance-receiving households use their money wisely and build a stable future. Migration duration and business investment The regression results show that migration duration strongly affects business investment. The model explains 93.2% of the variation in business investment, indicating that migration experience plays a critical role in shaping investment behavior. The findings confirm that longer migration leads to higher business investment. The standardized beta coefficient of 0.565 shows that migration duration accounts for 96.4% of the changes in business investment. This means that as migration duration increases, business investment rises significantly. This supports Cumulative Causation Theory, which suggests that long-term migration improves financial stability and business skills, leading to higher investments in businesses. The results also show that remittance amount positively affects business investment, although its influence is comparatively weaker than that of migration duration. The regression coefficient (B = 3.625, p = 0.524) is not statistically significant, implying that remittance inflows alone may not be a strong driver of business investment when other factors are controlled. However, migration duration has a much stronger impact than remittances. These findings agree with studies showing that long-term migrants are more likely to invest in businesses (Woodruff and Zenteno 2007). Furthermore, investment difficulties emerged as the only control variable with a statistically significant effect (B = -0.042, β = -0.240, p = 0.023), indicating that households encountering greater barriers to investment may allocate fewer remittance resources toward entrepreneurial ventures. This highlights the need to address institutional or structural barriers to enhance remittance utilization in business development. Income category as a moderator in the remittance-investment relationship The results reveal that income category does not significantly moderate the relationship between remittances and investment decisions. The model explains 45.48% of the variation in investment, showing that remittance inflows have a notable impact. However, the interaction effect is not statistically significant, meaning that investment behavior remains unchanged across different income groups. This contradicts the Relative Income Hypothesis, which suggests that higher-income households are more likely to invest while lower-income households prioritize consumption. Previous studies have shown that income levels influence remittance allocation, with wealthier families investing more in business and assets. However, these findings suggest that remittances enable investment regardless of income level, possibly because remittance-receiving households—regardless of their pre-existing income—see remittances as a unique financial resource dedicated to future security. The coefficient for Remittance Amount is significant, confirming that remittances drive investment, but Income Category itself is not statistically significant, meaning income differences do not alter investment behavior. The insignificant interaction effect suggests that all income groups—low, middle, and high—respond similarly to remittances in terms of investment. Graphical representation in figure 1 further supports this, showing that the regression lines for different income categories are nearly parallel, meaning there is no significant moderating effect. This finding challenges the traditional assumption that investment decisions are largely dictated by household wealth levels. Instead, it suggests that remittance recipients, regardless of income, recognize the importance of investment, possibly due to limited local earning opportunities or economic uncertainty. This result highlights the need for further investigation into the factors shaping remittance utilization beyond just income levels. Conclusion This study explores how remittances affect household financial decisions, including spending, education, business, financial literacy, and income moderation. The findings show that remittances are vital to household expenditure and economic well-being. The findings support that remittance-receiving households spend more than invest. This shows a positive and significant association between remittance inflows and consumption, indicating that remittance-receiving households use these cash for food, healthcare, and utilities rather than long-term wealth formation. The dependency theory indicates that remittances are a financial safety net rather than an investment instrument in emerging economies. Education expenses increase strongly with remittance inflows, confirming their importance in enhancing education access and human capital development. These findings support the Human Capital Theory, which claims that education investment pays off over time. Financial literacy enhances the possibility of investing remittances. Financially literate households invest more of their remittances than consume, indicating that financial education improves financial decision-making. This research supports behavioral economics by demonstrating that knowledge and awareness improve financial outcomes. Longer migration periods bring to more financial resources, experience, and confidence, which increases investment. According to the Cumulative Causation Theory, longer migratory experiences strengthen economic links and investment prospects. Moreover, migration duration appears to have a stronger and more consistent effect on business investment compared to remittance volume alone, suggesting that experience gained through long-term migration improves household entrepreneurial capacity. This study shows that remittances influence household financial decisions, particularly consumption and education investment. The results show that financial literacy improves remittance allocation to productive investments, but migration duration strongly influences business investment decisions. Furthermore, the effect of remittance amount on investment becomes statistically insignificant when controlling for household characteristics, highlighting the need to address structural constraints that hinder effective remittance utilization. Remittances appear to stabilize investment behavior regardless of income group, suggesting they stabilize the economy. These findings add to remittance use discussions and support the idea that financial knowledge and long-term migration boost economic development. Policymakers should encourage financial literacy and structured remittance investment plans to optimize development impact. Policy Implications This study has major policy implications for governments, financial institutions, and development groups looking to maximize remittance benefits. Financial literacy programs could help remittance-receiving households make better financial decisions and manage funds more efficiently. Structured financial training can help families invest rather than spend. By expanding mobile banking and microfinance, households may better manage remittances. Governments should promote accessible financial literacy campaigns through community centers, mobile apps, and digital platforms to reach migrants and their families at scale. This study is important for remittance-dependent economies around the world. Policymakers must ensure constructive use of global remittance flows. Remittances serve as a primary income source for millions in South Asia, Africa, and Latin America; yet they are often allocated more towards current expenditures than long-term investments. This study highlights the importance of financial literacy and the duration of migration, providing a framework that governments and financial institutions can adopt to enhance remittance utilization. Special focus should be given to low-income and rural households, where financial literacy levels are typically lower and the risk of remittance misuse is higher. This research offers practical measures for economic growth. Unlike earlier research, it emphasizes financial literacy in diverting remittance spending to productive activity. The study also examines how migration duration affects investment decisions, revealing how remittances benefit businesses. We found that long-term migration boosts financial capability and business investments, which has major policy implications for reintegrating returning migrants. Governments should develop reintegration packages for returnees with investment coaching, start-up support, and tax incentives for remittance-financed enterprises. Education is another area where remittances can provide long-term advantages. Policymakers should establish scholarship programs for migrant workers’ children. Financial organizations can offer savings programs based on remittances for education finance. These activities will assist families in using remittances to enhance human capital, hence increasing economic chances. Linking remittances with conditional education investments (e.g., matched savings for tuition) could further strengthen long-term educational outcomes. Governments in remittance-receiving nations should incorporate financial literacy into their migration strategies. Many migrants lack financial education, which influences how they handle remittances. Countries that employ migrant workers, such as those in the Middle East and Europe, should partner with financial institutions to give financial literacy training before migration. This would ensure that remittances meet both short-term demands and long-term development. In addition, embassies and labor attachés can facilitate pre-departure financial training in coordination with host country employers. Global financial agencies such as the IMF and the UN can use these insights to link remittances to economic growth objectives. Microfinance initiatives and remittance-backed loans have the potential to transform remittance inflows into long-term economic growth. Encouraging banks to establish remittance-based lending products will help migrant families invest more in their businesses. Partnering with fintech companies to design user-friendly remittance-linked financial products can improve access and reduce transaction costs, especially for underserved populations. This study suggests practical approaches to increase remittance use. Remittances can help to improve long-term financial stability by fostering financial literacy, increasing access to financial services, and promoting productive investments. Future studies should look for new ways to optimize remittance potential by integrating behavioral insights and tailoring interventions based on household characteristics. Limitations and future study This study provides useful insights about remittance utilization; however, many limitations must be acknowledged. Its focus on Bangladesh areas may limit its applicability. To compare remittance usage across regions, future research should cover more regions. The study uses cross-sectional data to examine remittance impacts at one period. A longitudinal study might better capture causal relationships and explain changes in remittance utilization over time. Additionally, the study focuses on how remittances, financial literacy, and migration duration affect household financial decisions. However, other macroeconomic variables such as labor market conditions, government policy shifts, inflation rates, and financial access infrastructure may also influence remittance behavior. Further research should include more variables for a more complete analysis. Financial literacy measurement is another issue. The survey classifies financial literacy as high or low, which may not convey the complexity of financial decision-making. Further research should create a more comprehensive financial literacy index to assess financial understanding and decision-making. The study uses self-reported data, which may be prone to recall or social desirability bias. To verify findings and assure accuracy, future studies should integrate multiple data sources, including bank transaction records and remittance platform analytics. Research should also evaluate financial literacy programs and remittance utilization policies. Experimental or quasi-experimental methods could assess the causal impact of financial training and migration experience on remittance investment behavior. Future research should assess the impact of financial literacy programs and policy interventions designed to improve remittance utilization. For example, randomized trials of community-based financial education, digital financial tools, or remittance-linked savings products could reveal what strategies work best in specific contexts. Case studies of successful remittance-driven investment programs could provide further insights into best practices for policymakers. Furthermore, comparative studies across different migrant-sending countries would help validate whether the observed effects of migration duration and financial literacy generalize beyond Bangladesh. Declarations Ethics Approval and Consent to Participate This study was conducted with human participants in compliance with the ethical principles outlined in the Declaration of Helsinki (2013). There is no mandatory centralized ethical approval process for studies at my University that pose minimal risk to participants. However, ethical considerations were strictly followed to ensure participants' rights, confidentiality, and voluntary participation. Written consent was obtained from all the participants involved in the study. Consent for Publication Not applicable. Funding This research received no external funding. 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Mominul Islam","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyUlEQVRIiWNgGAWjYDCCAyDCgIGHjb0BxLAgXoscHw+IZSBBrBYGBmM5iQQQTYQWvtunEx/dKLiT2Cb5/OqGHwUSDPzt3Ql4tUiey91snGPwLLFNOqfsZg/QYRJnzm7Aq8XgDO826RyDwyAtaTd4gFoMJHKJ1SJ5Ju3mH1K0GLNJsB+7TZQtkmd4QX45LMfGk8N2W8ZAgoegX/jO8G58nPPnMI98+/FnN9/8sZHjb+/FrwUJ8BiASWKVgwD7A1JUj4JRMApGwQgCADZrRxa1vRxzAAAAAElFTkSuQmCC","orcid":"","institution":"","correspondingAuthor":true,"prefix":"","firstName":"Md.","middleName":"Mominul","lastName":"Islam","suffix":""}],"badges":[],"createdAt":"2025-07-31 16:08:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7264115/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7264115/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107437096,"identity":"b7ec4080-ecc8-4f6b-bef1-7916fd8c5f01","added_by":"auto","created_at":"2026-04-21 13:27:22","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":44890,"visible":true,"origin":"","legend":"\u003cp\u003eModerating effect of income levels on remittance-investment relationships\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7264115/v1/82f3bbae511a0a52225f9731.jpg"},{"id":107437183,"identity":"2efd621b-95c0-45e2-9535-22fa64ba751c","added_by":"auto","created_at":"2026-04-21 13:27:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1178778,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7264115/v1/0e8a9b03-cf8e-4733-b43e-9776e8ab8834.pdf"},{"id":107437095,"identity":"740fe989-8b6d-4c6e-a245-3e570380d540","added_by":"auto","created_at":"2026-04-21 13:27:22","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":16848,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix.docx","url":"https://assets-eu.researchsquare.com/files/rs-7264115/v1/0f44d20c3a6164564a01ebe7.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Remittances and household financial behavior in Rajshahi Division, Bangladesh: examining consumption and investment patterns","fulltext":[{"header":"Introduction","content":"\u003cp\u003e\u003cstrong\u003eBackground of the study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRemittances play a crucial role in Bangladesh\u0026rsquo;s economy, serving as a lifeline for millions of households. Bangladesh ranks among the top ten remittance-receiving countries globally, with remittance inflows reaching $23.9 billion in FY 2023-24 (Bangladesh Bank 2023). Remittances contribute 5.1% of the country\u0026rsquo;s GDP, reducing poverty and improving household financial stability (World Bank 2023). The country\u0026rsquo;s migration trend is primarily driven by economic necessity, with around 12 million Bangladeshi migrants working abroad, particularly in Middle Eastern countries such as Saudi Arabia, the UAE, Qatar, Oman, and Kuwait (BMET 2023). In 2022 alone, over 1.1 million Bangladeshi workers migrated, setting a record for overseas employment (Prothom Alo 2023). While these national-level figures are important, there is limited understanding of how remittances affect household-level consumption and investment decisions, particularly in rural regions.\u003c/p\u003e\n\u003cp\u003eAmong the major remittance-receiving regions in Bangladesh, the Rajshahi Division\u0026mdash;including districts such as Pabna, Sirajganj, and Kushtia\u0026mdash;accounts for a substantial portion of migration to Middle Eastern countries. The prevalence of migration from these districts stems from high unemployment rates, limited economic opportunities, and rural poverty, which push many individuals to seek better financial prospects abroad (Khan 2021). This study focuses on Rajshahi Division to understand how households in economically vulnerable areas utilize remittances, addressing a critical regional gap in existing research.\u003c/p\u003e\n\u003cp\u003eThe majority of Bangladeshi migrants are engaged in low-skilled and semi-skilled jobs, including construction, manufacturing, domestic work, and sales. Around 75% of Bangladeshi expatriate workers fall into this category, earning relatively low wages but sending a significant portion of their income back home (ILO 2018). These remittances are often the primary source of income for families left behind, helping them meet basic needs such as food, healthcare, and education. However, the extent to which remittances are channeled into productive investments, such as business ventures and asset accumulation, remains a critical policy concern.\u0026nbsp;Understanding this household-level allocation is essential for designing targeted interventions to improve the long-term economic impact of remittances.\u003c/p\u003e\n\u003cp\u003eMigration has increased in Bangladesh due to economic hardship, widespread unemployment, and low rural wages. Agriculture-based households in Pabna, Sirajganj, and Kushtia districts depend on remittances. Remittances into rural areas improve living conditions, reduce credit dependence, and enable investment in land, housing, and small companies (Naimul et al. 2017). Mainly employed for productive investments or short-term spending, remittances are a serious concern.\u003c/p\u003e\n\u003cp\u003eRemittances significantly impact household spending. Food and healthcare are priorities for migrant families, improving well-being (Raihan, Uddin, and Ahmmed 2022). Education is another important expense since families regard it as a chance to improve their children\u0026apos;s futures. Although these benefits exist, investment in productive assets like enterprises and real estate is limited (World Economic Forum 2025).\u0026nbsp;This raises questions about what factors encourage households to shift from short-term consumption to long-term investment, a focus that this study directly addresses.\u003c/p\u003e\n\u003cp\u003eRemittances provide financial stability and improve living conditions for households. Families use remittances for daily expenses, education, healthcare, debt repayment, housing improvements, and small investments. Remittance-receiving households had stronger consumption and financial resilience than non-receiving households, according to empirical studies.\u003c/p\u003e\n\u003cp\u003eRemittances boost short-term financial security, but how households use them determines their long-term economic benefit. Some families spend remittances on short-term necessities, while others invest in entrepreneurship, land purchase, and business expansion to boost economic growth. Financial literacy and banking access could improve remittance use, ensuring long-term financial stability and development. This study, therefore, seeks to understand how financial literacy, income levels, and migration duration influence remittance utilization at the household level, using data specifically collected from Rajshahi Division.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResearch aim and objectives\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe primary aim of this study is to examine the impact of remittances on household consumption and investment patterns in the Rajshahi Division\u0026mdash;including districts such as Pabna, Sirajganj, and Kushtia, Bangladesh. Given the increasing reliance of Bangladeshi households on remittances, this research seeks to explore how these financial inflows shape economic behavior, particularly in terms of essential expenditures such as food, education, and healthcare, as well as long-term investment decisions like land acquisition, business ventures, and savings. The study also examines how financial literacy and income categories moderate remittance use for financial stability and economic growth.\u003c/p\u003e\n\u003cp\u003eTo achieve this aim, the study is guided by the following objectives:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eTo assess the relationship between remittances and household consumption patterns, focusing on the extent to which remittances are allocated to daily expenses such as food, education, and healthcare.\u003c/li\u003e\n \u003cli\u003eTo examine the impact of remittances on household investment behavior, focusing on the percentage of inflows allocated to productive activities including business expansion, land acquisitions, and long-term savings.\u003c/li\u003e\n \u003cli\u003eTo evaluate the role of financial literacy in influencing remittance utilization, determining whether households with better financial knowledge allocate remittances more efficiently toward investment rather than consumption.\u003c/li\u003e\n \u003cli\u003eTo investigate the moderating effect of income levels on remittance-investment relationships, identifying whether higher-income households demonstrate more productive use of remittances compared to lower-income groups.\u003c/li\u003e\n \u003cli\u003eTo analyze how migration duration influences remittance allocation, particularly whether long-term migrants contribute more toward business investments compared to short-term migrants.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eBy addressing these objectives, this study aims to contribute to the existing body of literature by offering empirical insights into how remittances are managed at the household level and identifying key factors that optimize their economic benefits.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResearch gap and significance of the study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDespite the vast body of research on remittances and their economic impact, there remains a crucial gap in understanding how these financial inflows shape household consumption and investment decisions in specific regional contexts in Bangladesh. Much of the existing literature has focused on the macroeconomic effects of remittances, such as their contributions to GDP, poverty reduction, and foreign exchange reserves. However, studies that provide granular insights into the micro-level financial behaviors of remittance-receiving households are relatively limited, especially within rural economies that depend heavily on migration income.\u003c/p\u003e\n\u003cp\u003eA key limitation in prior studies is the lack of differentiation between consumption and investment behavior. While remittances undeniably improve household welfare by reducing financial vulnerability and enhancing access to education and healthcare, the extent to which they contribute to productive investment remains highly debated. Many studies assume that remittances automatically lead to business development, but empirical findings are mixed. Some argue that remittances foster entrepreneurship and asset accumulation, while others suggest that most funds are spent on daily needs rather than being invested in income-generating activities (Adams Jr and Cuecuecha 2013). The role of financial literacy, migration duration, and income level in shaping these decisions remains underexplored, particularly in developing economies like Bangladesh.\u003c/p\u003e\n\u003cp\u003eAnother research gap involves the moderating effect of household income on remittance utilization. While prior studies acknowledge that lower-income families rely more on remittances for consumption, few have examined whether higher-income households are more likely to allocate remittances toward business investment, land acquisition, or savings. Understanding this relationship is critical for targeting financial policies that encourage long-term wealth creation among remittance-dependent households.\u003c/p\u003e\n\u003cp\u003eFurthermore, there is limited empirical research on how financial literacy influences remittance spending. Although studies highlight the importance of financial education in wealth management and savings behavior, empirical evidence specific to remittance-receiving households in rural Bangladesh is scarce. A deeper examination of how financial awareness affects remittance-based investment decisions is necessary for designing more effective financial inclusion programs in Bangladesh.\u003c/p\u003e\n\u003cp\u003eIn addition, migration duration has been widely acknowledged as a determinant of remittance flow stability, but its effect on household investment decisions remains unclear. Some studies suggest that short-term migrants remit larger amounts in the early years to support immediate household needs, while long-term migrants provide more stable financial support that facilitates investment in education, business, and property. However, there is insufficient empirical evidence on whether longer migration durations lead to greater investment in productive assets.\u003c/p\u003e\n\u003cp\u003eThis study is highly significant as it will address these gaps by providing empirical evidence from Rajshahi Division\u0026mdash;including districts such as Pabna, Sirajganj, and Kushtia, rural regions that heavily depends on Middle Eastern labor migration. The findings will be policy-relevant, offering guidance for governments, financial institutions, and development agencies on designing strategies that encourage sustainable economic development through remittance utilization. Policymakers can use the insights from this study to develop customized financial literacy programs, enhance access to formal banking and investment services, and implement targeted interventions that maximize the long-term economic benefits of remittances for rural communities.\u003c/p\u003e\n\u003cp\u003eBy investigating household financial behavior, investment choices, and the role of financial literacy, this research will contribute substantially to the discourse on remittance economics in Bangladesh. The findings will provide valuable inputs for designing policies that encourage productive investments, ultimately helping households transition from dependency on remittances to financial self-sufficiency. Furthermore, this study will serve as a foundation for future research on how migration and remittances interact with financial behaviors in other developing economies facing similar migration-driven financial structures.\u003c/p\u003e\n\u003cp\u003eThis study is divided into several sections. The introduction explains the study\u0026apos;s purpose and why remittances matter. The literature review examines past studies on remittances, consumption, and investment while identifying research gaps. The methodology describes data collection, sample selection, and analysis techniques. The results present key findings from statistical analysis. The discussion interprets the results and compares them to previous studies. The conclusion and recommendations summarize key points, suggest policy measures, highlight study limitations, and propose future research directions.\u003c/p\u003e"},{"header":"Literature review ","content":"\u003cp\u003e\u003cstrong\u003eConcept of remittances \u0026amp; economic impact\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRemittances play a key role in economic stability. They provide financial support to families in developing countries. Theories such as the Permanent Income Hypothesis (Friedman 2018) and the Life Cycle Hypothesis (Kurihara 2013) suggest that remittances are used based on long-term expectations, not just immediate needs.\u003c/p\u003e\n\u003cp\u003eSome studies show that remittances boost household consumption (Ratha 2013). Others argue that they help families invest in businesses, land, or education (Adams Jr 2011). In South Asia, remittances have reduced poverty and increased financial access (Gupta, Pattillo, and Wagh 2009). However, some studies warn that remittances can make families dependent and reduce their motivation to work (Chami, Fullenkamp, and Jahjah 2005).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHousehold consumption vs. investment framework\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHouseholds receiving remittances often allocate them based on their immediate needs and financial priorities. Several studies highlight that a significant portion of remittances is used for daily consumption, including food and healthcare. Adams Jr \u0026amp; Cuecuecha (2013) found that in developing countries, remittance-receiving households spend more on food and basic necessities than non-recipient households. Similarly, Gupta et al. (2009) showed that remittances help improve nutrition and healthcare access, particularly in low-income families.\u003c/p\u003e\n\u003cp\u003eEducation is another critical area where remittances are spent. Evidence suggests that households with remittance income invest more in children\u0026apos;s education than those without. Yang (2008) found that remittances in the Philippines increased school enrollment rates and reduced child labor, allowing families to prioritize education. Acosta et al. (2008) reported similar findings in Latin America, showing that remittance-receiving households allocate more funds to education, reducing dropout rates.\u003c/p\u003e\n\u003cp\u003eStudies show that 40% of remittances go to household consumption and 35% to health and education (Bangladesh Bank 2021). Business investments, real estate, and savings receive less. This shows that remittances may give quick financial relief but not permanent economic growth. Many households fail to employ remittances to create long-term income, limiting their economic benefits.\u003c/p\u003e\n\u003cp\u003eRemittance use depends on financial literacy and banking availability. Many households employ informal saving because they lack financial management knowledge (Lusardi and Mitchell 2014). Only 35% of Bangladeshi remittance-receiving households save in formal banks, while the remainder employ informal methods, according to a survey. Families without financial expertise may miss opportunities to invest remittances in ways that boost long-term stability.\u003c/p\u003e\n\u003cp\u003eInvestment in business is less common but still plays a role. Some studies suggest that remittances contribute to small-scale entrepreneurship and self-employment. Woodruff and Zenteno (2007) found that remittance-receiving households in Mexico were more likely to start businesses. However, in many developing countries, business investment remains a secondary priority, as families often use remittances for consumption rather than capital accumulation (Ratha 2013).\u003c/p\u003e\n\u003cp\u003eA World Bank (2008) report found that most remittances are spent on daily expenses rather than capital investments. Some studies also suggest that high remittance dependence reduces workforce participation, as families rely on external income instead of local employment (Upadhyaya, Dhakal, and Thapa 2013).\u003c/p\u003e\n\u003cp\u003eThe debate on remittances centers on whether they contribute to long-term economic growth or short-term consumption. Some scholars argue that remittances discourage productive labor and create dependency (Chami et al. 2005), while others suggest they provide an alternative source of capital, especially in weak financial systems (Giuliano and Ruiz-Arranz 2009).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIncome level moderates remittance-investment decisions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIncome typically determines how recipients use remittances. Low-income households spend most of their remittances on food, housing, and utilities (Adams Jr 2011). Middle-income households invest more in education, entrepreneurship, and real estate, showing a longer-term financial outlook (Dustmann and Mestres 2010).\u003c/p\u003e\n\u003cp\u003eWealthier households invest remittances in long-term investments that develop financial assets (Giuliano and Ruiz-Arranz 2009). However, lower-income households depend on remittances for daily survival, limiting their savings and investment (Chami et al. 2005). This shows how financial position affects remittance usage.\u003c/p\u003e\n\u003cp\u003eRemittance recipients often lack financial planning abilities, wasting funds (Giuliano and Ruiz-Arranz 2009). Remittance use also depends on household income. Lower-income households spend most of their remittances on basic needs, while higher-income households invest in enterprises, land, or savings. Additionally, migration duration matters. Short-term migrants cover everyday costs, while long-term migrants save and invest (Dustmann and Kirchkamp 2002).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDuration of migration and business investment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMigrants\u0026apos; remittance usage also depends on their stay overseas. Long-term migrants save more and invest in businesses as they become financially stable (Woodruff and Zenteno 2007). Long-term expatriates are more inclined to send money for investment than consumption (Dustmann and Kirchkamp 2002).\u003c/p\u003e\n\u003cp\u003eThe New Economics of Labor Migration theory (Stark and Bloom 1985) outlooks migration as a thoughtful household decision to reduce financial risks and improve living conditions. Long-term migrants generally learn commercial and financial skills, which helps them invest in income-generating businesses (Vaaler 2011).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSummary of literature, gaps, and contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 1 below shows the summary of the literature, gaps, and contributions of the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e Summary of literature, gaps, and contribution\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eExisting Studies\u0026apos; Key Themes \u0026amp; Gaps\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAuthors and Date\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMy Contribution in the Current Study\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eExisting studies analyze the impact of remittances on household consumption but often fail to differentiate their effects across various household structures and income levels.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e(Ratha 2013),\u0026nbsp;(Adams Jr and Cuecuecha 2013),\u0026nbsp;(Chami et al. 2005)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eThis study examines remittance allocation based on income categories and financial literacy, offering a more nuanced analysis of household financial behavior.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eThe investment potential of remittances is acknowledged, but prior research largely overlooks the moderating effect of financial literacy and income levels.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e(Adams Jr 2011),\u0026nbsp;(Giuliano and Ruiz-Arranz 2009),\u0026nbsp;(Woodruff and Zenteno 2007)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eThis study introduces financial literacy and income level as key moderators, showing how they shape remittance utilization.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStudies on remittances and financial literacy are mostly conducted in developed economies, with limited research focused on South Asia.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e(Lusardi and Mitchell 2014),\u0026nbsp;(Hastings et al. 2012),\u0026nbsp;(Klapper, Lusardi, and Van Oudheusden 2015),\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eThis study provides empirical evidence from Bangladesh, offering insights into a developing economy where remittances play a crucial role.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eThe relationship between migration duration and investment is discussed, but previous studies do not account for variations in business investment decisions.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e(Woodruff and Zenteno 2007),\u0026nbsp;(Dustmann and Kirchkamp 2002),\u0026nbsp;(Vaaler 2011)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eThis study examines how migration duration affects business investment decisions, contributing new evidence on the long-term impact of migration.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePrevious studies focus on the macroeconomic impact of remittances rather than household-level decision-making.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e(Adams Jr 2011),\u0026nbsp;(Dustmann and Mestres 2010),\u0026nbsp;(Giuliano and Ruiz-Arranz 2009)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eThis study shifts the focus to microeconomic decision-making by analyzing household remittance allocation at an individual level.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eMost research does not properly capture the household-level interplay between financial literacy, income, and remittance use. Additionally, migration duration\u0026apos;s impact on firm investment is unknown. By using financial knowledge and income as moderators, my work fills these gaps and provides a better understanding of remittance allocation in underdeveloped economies. The findings provide a paradigm for household remittance-driven financial decisions, which informs policy and scholarly literature.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConceptual framework and hypotheses development\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConceptual framework\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study examines how remittances influence household consumption and investment, integrating financial literacy, income level, and migration duration as moderating factors. The Permanent Income Hypothesis (Friedman 2018) and Life Cycle Hypothesis (Kurihara 2013) explain that households plan income allocation over time. However, in developing economies, remittances often fund immediate consumption rather than investment (Stark and Bloom 1985). The Dual Sector Model (Lewis 1954) suggests remittances can transition households from subsistence living to entrepreneurship.\u003c/p\u003e\n\u003cp\u003eThe conceptual model positions remittance amount as the key independent variable, influencing consumption (daily expenses) and investment (business, education, savings), with financial literacy, income level, and migration duration moderating the relationships.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHypotheses\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eH1\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;Households receiving remittances allocate a significant portion toward consumption rather than investment.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe Keynesian Consumption Function (Keynes 1936) suggests that an increase in income leads to higher spending. Remittance-dependent families often prioritize food, rent, and healthcare (Ratha 2013). Research shows that in low-income economies, remittances are mainly used for consumption (Adams Jr and Cuecuecha 2013). While remittances help stabilize households, excessive spending may reduce investment opportunities.\u003c/p\u003e\n\u003cp\u003eThe Permanent Income Hypothesis (PIH) (Friedman 2018) suggests that people plan their spending over time. However, in low-income households, remittances are often used for daily expenses rather than investment. This study modifies the hypothesis to highlight the heavy reliance on remittances for food, healthcare, and other needs instead of business or asset investment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eH2\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;There is a positive relationship between remittance inflow and household investment in education.\u003c/em\u003e\u003cbr\u003eThe Human Capital Theory (Becker 2009) explains that investment in education improves future income. Studies show that remittances help families afford school fees and supplies. This study examines how much of remittance income is used for education in recipient households.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eH3\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;Households with higher financial literacy allocate more remittances toward investment than consumption.\u003c/em\u003e\u003cbr\u003eBehavioral Economics explains that financially literate individuals make better financial decisions (Lusardi and Mitchell 2014). Households with financial knowledge are more likely to invest remittances in businesses, real estate, or savings. Without financial literacy, households may struggle to use remittances effectively, reducing long-term benefits.\u003c/p\u003e\n\u003cp\u003eThe Financial Literacy Theory states that better financial knowledge improves money management. Research suggests that financially educated households save and invest more (Atkinson and Messy 2012). This study explores whether financial literacy influences remittance spending decisions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eH4\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;Households with long-term migrants invest more in business than those with recent migrants.\u003c/em\u003e\u003cbr\u003eThe Migration Investment Framework (Dustmann and Mestres 2010) suggests that migration duration affects remittance usage. Short-term migrants send money for immediate needs, while long-term migrants contribute to investments (Mansuri 2006). This study assesses whether remittance spending patterns change over time.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eH5\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;Household income influences the link between remittances and investment.\u003c/em\u003e\u003cbr\u003eIncome levels determine how remittances are used. Higher-income families are more likely to invest, while lower-income households rely on remittances for survival (Raihan et al. 2022). This study evaluates whether household income shapes remittance investment decisions.\u003c/p\u003e"},{"header":"Research methodology","content":"\u003cp\u003eThis study examines how households use remittances for consumption and investment. It focuses on three districts of Rajshahi division in Bangladesh: Pabna, Sirajganj, and Kushtia, where many people migrate to Middle Eastern countries for work. The study follows a quantitative approach using survey data to understand spending patterns.\u0026nbsp;The total sample size is 235 households. The sample is equally distributed across the three districts, with about one-third of households taken from each district. A cross-sectional household survey was conducted through face-to-face interviews using structured questionnaires.\u003c/p\u003e\n\u003cp\u003eA random sampling method was used to select remittance-receiving households. This ensures that different income levels and financial backgrounds are included. The survey included both male and female respondents, focusing on the main household decision-makers. This method allows consistency in responses but limits detailed personal opinions. The questionnaire included closed-ended questions on remittance usage, financial literacy, and investment decisions.\u003c/p\u003e\n\u003cp\u003eThe study considers multiple key variables. The dependent variables include the Consumption Ratio, which measures the proportion of remittances spent on household needs, and the Investment Ratio, which reflects the share allocated to savings, business, or asset accumulation. The independent variables include the Remittance Amount, which represents the total remittances received by the household, Household Income (excluding remittances), Financial Literacy (a dummy variable where 1 = High and 0 = Low), and Migration Duration, which is categorized into four groups: less than 1 year, 1-3 years, 3-5 years, and more than 5 years. Additional household-level characteristics were included as control variables in the regression models to reduce omitted variable bias. These include age, gender, education level, and dependency ratio of the remittance recipient. Control variables were chosen based on prior literature and economic reasoning. Age and education of the household head can influence financial decision-making. Household size affects expenditure needs. Gender and occupation also shape remittance utilization patterns.\u003c/p\u003e\n\u003cp\u003eTo avoid bias from combining ratio variables and absolute numbers in the models, all continuous variables were checked for scale compatibility and normalized where necessary before analysis. This ensured that variables such as remittance amount (absolute value) and investment ratio (proportion) were appropriately handled in the regression models.\u003c/p\u003e\n\u003cp\u003eSome variables in this study are ratios (like investment and consumption ratios), while others are absolute values (such as remittance amount). To avoid issues from combining these different types of variables, all continuous variables were reviewed for scale compatibility. Where necessary, they were normalized before regression analysis. This step ensured that ratio variables and absolute numbers could be used together without bias. Variable definitions and measurements were guided by the structured questionnaire, which asked respondents to report both exact remittance amounts and the percentage allocation to specific uses such as education, consumption, and business investment.\u003c/p\u003e\n\u003cp\u003eThe study also includes a moderating variable, Income Category, categorized as Low, Medium, and High, to test whether income level influences remittance utilization. An interaction term was created: Remittance \u0026times; Income Category, to determine whether income level moderates the relationship between remittance inflows and household investment decisions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEconometric models\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo analyze these relationships, various linear regression models were used.\u003c/p\u003e\n\u003cp\u003eEffect of remittances on consumption ratio:\u003c/p\u003e\n\u003cp\u003eConsumption Ratioi=\u0026beta;0+\u0026beta;1\u0026times;Remittance Amounti+\u0026beta;2\u0026times;Household Controlsi+ϵi\u003c/p\u003e\n\u003cp\u003eEffect of remittances on education investment:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEducation Investmenti=\u0026beta;0+\u0026beta;1\u0026times;Remittance Amounti +\u0026beta;2\u0026times;Household Controlsi+ϵi\u003c/p\u003e\n\u003cp\u003eEffect of remittances and financial literacy on investment ratio:\u003c/p\u003e\n\u003cp\u003eInvestment Ratioi=\u0026beta;0+\u0026beta;1\u0026times;Remittance Amounti+\u0026beta;2\u0026times;Financial Literacyi+\u0026beta;3\u0026times;Household Controlsi+ϵi\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEffect of migration duration and remittance amount on business investment:\u003c/p\u003e\n\u003cp\u003eBusiness Investmenti=\u0026beta;0+\u0026beta;1\u0026times;Migration Durationi+\u0026beta;2\u0026times;Remittance Amounti+\u0026beta;3\u0026times;Household Controlsi+ϵi\u003c/p\u003e\n\u003cp\u003eModeration model for income level in investment decisions:\u003c/p\u003e\n\u003cp\u003eInvestment Ratioi=\u0026beta;0+\u0026beta;1\u0026times;Remittance Amounti+\u0026beta;2\u0026times;Income Categoryi+\u0026beta;3 \u0026times;(Remittance Amount\u0026times;Income Category) +ϵi\u003c/p\u003e\n\u003cp\u003eEach of these models provides an econometric framework to analyze the dynamics of remittance allocation in recipient households. Household control variables include age, education level, household size, and dependency ratio. By estimating these equations using regression analysis, we can determine the strength and significance of these economic relationships, thereby offering valuable insights for policymakers and financial institutions.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Results ","content":"\u003cp\u003e\u003cstrong\u003eDemographic information\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe majority of migrants are male (90.2%), while females account for only 9.8% of the total. Regarding the migrant\u0026apos;s relationship with the household, husbands (41.3%) send the most remittances, followed by sons (40%) and brothers (13.6%). Educational attainment among household members varies, with 19.6% having no formal education, while 20.4% have a bachelor\u0026rsquo;s degree or higher. These findings suggest that a significant portion of households still lacks higher education, which may influence financial decision-making.\u003c/p\u003e\n\u003cp\u003eThe destination of migration also plays a key role in remittance inflows. Most migrants are in Saudi Arabia (14%), UAE (14%), Kuwait (20.9%), and Oman (12.8%), while a smaller portion is in Bahrain (11.5%) and Qatar (9.4%). The method of remittance transfer varies, with the majority relying on bank transfers (61.7%), followed by mobile financial services (30.2%), while a small percentage still uses informal Hundi channels (8.1%). These trends indicate that formal banking channels dominate remittance inflows, reducing the risks associated with informal transfer methods.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDescriptive statistics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e Descriptive statistics\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"620\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDescriptive Statistics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMinimum\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaximum\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStd. deviation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003eRemittance amount\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e20017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e99901\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e60968.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e23411.286\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003eEducation expense percentage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e10.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e6.1226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e2.45379\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003eBusiness investment percentage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e2.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e1.2248\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e.65721\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003eConsumption ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e.6489\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e.12607\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003eInvestment ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e.1702\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e.04801\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003eValid N (list-wise)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 2 shows the descriptive statistics. In terms of financial distribution, households receive an average remittance of 60,968.41 BDT, with values ranging between 20,017 BDT to 99,901 BDT. A large portion of these remittances is used for daily consumption needs (64.89%), while investment in business remains low (1.22%). The education expense percentage is 6.12%, indicating that only a small portion of remittances is allocated to educational development. The investment ratio is 17.02%, suggesting that while some households invest in long-term financial stability, a significant portion of remittances is used for immediate needs rather than asset accumulation.\u003c/p\u003e\n\u003cp\u003eFurther analysis of financial stability indicators shows that 53.6% of households have not started a business, while 46.4% have. Among those who invest in businesses, 27.7% are engaged in agriculture, 26.8% in transport, and 23% in retail shops, highlighting the sectors where remittance-fueled investments are directed. However, 42.1% of households report investment difficulties, mainly due to financial constraints. Meanwhile, 51.1% of households indicate financial stability, and 48.9% have reduced loans using remittance money. Despite this, 51.9% of households remain highly dependent on remittances, raising concerns about their ability to sustain themselves without external financial support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrelation\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u0026nbsp;\u003c/strong\u003eCorrelations\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"678\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCorrelations\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003eMigration duration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003eRemittance amount\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eEducation expense percentage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eBusiness investment percentage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003eFinancial literature\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003eConsumption ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eInvestment \u0026nbsp;ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003eIncome category\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eMigration duration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003ePearson Correlation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e.142\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e.138\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e.964\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e.051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e.102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e-.121\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eSig. (2-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e.434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e.119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e.235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e.063\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eRemittance amount\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003ePearson Correlation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e.142\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e.909\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e.146\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e.475\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e.683\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e.674\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e-.086\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eSig. (2-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e.187\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eEducation expense percentage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003ePearson Correlation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e.138\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e.909\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e.145\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e.409\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e.602\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e.601\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e-.132\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eSig. (2-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e.044\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eBusiness investment percentage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003ePearson Correlation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e.964\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e.146\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e.145\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e.103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e.086\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e-.131\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eSig. (2-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e.419\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e.115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e.188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e.044\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eFinancial literature\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003ePearson Correlation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e.051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e.475\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e.409\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e-.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e.814\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e-.017\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eSig. (2-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e.434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e.419\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e.642\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e.791\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eConsumption ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003ePearson Correlation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e.102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e.683\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e.602\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e.103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e-.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e.066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e-.079\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eSig. (2-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e.119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e.115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e.642\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e.316\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e.227\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eInvestment \u0026nbsp; \u0026nbsp; ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003ePearson Correlation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e.674\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e.601\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e.086\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e.814\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e.066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e-.058\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eSig. (2-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e.235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e.188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e.316\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e.373\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eIncome category\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003ePearson Correlation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e-.121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e-.086\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e-.132\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e-.131\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e-.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e-.079\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e-.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003eSig. (2-tailed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e.187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e.791\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e.227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e.373\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*. Correlation is significant at the 0.05 level (2-tailed).\u003c/p\u003e\n\u003cp\u003e**. Correlation is significant at the 0.01 level (2-tailed).\u003c/p\u003e\n\u003cp\u003eIn Table 3, the correlation analysis highlights key relationships between remittance usage, financial literacy, migration duration, and income levels. Migration duration is strongly linked to business investment (r=0.964, p\u0026lt;0.01r = 0.964, p \u0026lt; 0.01r=0.964, p\u0026lt;0.01), indicating that longer migration leads to higher business investment. Remittance amount is positively correlated with both consumption (r=0.683, p\u0026lt;0.01r = 0.683, p \u0026lt; 0.01r=0.683, p\u0026lt;0.01) and investment (r=0.674, p\u0026lt;0.01r = 0.674, p \u0026lt; 0.01r=0.674, p\u0026lt;0.01), confirming that households with higher remittances allocate funds for both immediate needs and future gains. Financial literacy is moderately linked to education expenses (r=0.409, p\u0026lt;0.01r = 0.409, p \u0026lt; 0.01r=0.409, p\u0026lt;0.01), but not significantly associated with business investment or consumption. Income category has a weak negative correlation with business investment and education spending, suggesting that wealthier households allocate remittances differently. These findings support the study\u0026rsquo;s hypotheses and provide a foundation for further regression analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMulticollinearity\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe analysis validates the hypotheses related to remittance utilization. Remittance Amount, Income Category, Financial Literacy, and Migration Duration significantly influence consumption and investment decisions. The Variance Inflation Factor (VIF) values (1.021\u0026ndash;1.322) and Tolerance values (\u0026gt;0.7) confirm no multicollinearity, ensuring the reliability of the regression model. This indicates that each independent variable contributes uniquely to explaining remittance allocation, reinforcing the importance of financial awareness and economic stability in shaping remittance usage.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImpact of remittance amount on consumption ratio\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u003c/strong\u003e Effect of remittances on consumption ratio\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"681\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 681px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoefficients \u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnstandardized coefficients\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eStandardized coefficients\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eBeta\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003et\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eStd. error\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e(Constant)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.424\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11.740\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.092\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.927\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEducation Level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.260\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHousehold Members\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-1.135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.893\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDependents\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.520\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.604\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRemittance Amount\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.638E-6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.676\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13.849\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ea. Dependent variable: Consumption ratio\u003c/p\u003e\n\u003cp\u003eTable 4 presents the results of the regression analysis exploring the effect of remittance inflows on the household consumption ratio, while controlling for age, number of dependents, household size, and education level. The analysis reveals a statistically significant positive relationship between remittance amount and consumption ratio.\u003c/p\u003e\n\u003cp\u003eThe model reports an R-value of 0.686, indicating a strong positive correlation between the predictors and the dependent variable. The R-squared value of 0.470 suggests that approximately 47% of the variation in household consumption ratio is explained by the model. The adjusted R\u0026sup2; of 0.459 confirms the model\u0026apos;s explanatory power after accounting for the number of predictors included. The ANOVA test demonstrates the overall significance of the model, with an F-statistic of 40.657 and a p-value \u0026lt; 0.001, indicating that the model provides a statistically significant fit to the data.\u003c/p\u003e\n\u003cp\u003eAs shown in Table 4, the remittance amount has a significant positive effect on the consumption ratio (B = 3.638E-6, p \u0026lt; 0.001), with a standardized beta coefficient of 0.676, signifying a strong effect size. This implies that higher remittance inflows are associated with increased household spending, supporting the hypothesis that remittances are largely allocated toward consumption needs. Among the control variables, none are statistically significant at the 5% level. Age (p = 0.927), education level (p = 0.260), household size (p = 0.893), and number of dependents (p = 0.604) do not exhibit a meaningful impact on the household consumption ratio in this model. Nevertheless, their inclusion ensures a robust estimation of the effect of remittances. These findings emphasize that remittances play a critical role in shaping household consumption behavior, with implications for financial planning and welfare policies targeting remittance-receiving families.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImpacts of remittance amount on education expense\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe regression analysis explores the relationship between remittance inflows and the proportion of household spending allocated to education. The dependent variable is the percentage of household expenses dedicated to education. The model includes control variables such as age, education level, household size, and number of dependents.\u003c/p\u003e\n\u003cp\u003eThe model demonstrates a strong overall fit, with an R-value of 0.911, indicating a high positive correlation between remittance amount and education expense. The R\u0026sup2; value of 0.830 suggests that approximately 83.0% of the variance in education spending can be explained by the combined effect of remittance inflows and the control variables. The adjusted R\u0026sup2; of 0.826 confirms the robustness of the model after accounting for sample size. Additionally, the standard error of the estimate is 1.02304, indicating a relatively small dispersion of observed values around the regression line. The ANOVA table confirms the overall significance of the model, with an F-statistic of 223.438 (p \u0026lt; 0.001), affirming that the predictors collectively explain a significant portion of the variance in education expenses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5\u003c/strong\u003e Effect of remittances on education investment\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"679\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 679px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoefficients \u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnstandardized coefficients\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eStandardized coefficients\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eBeta\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003et\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eStd. error\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e(Constant)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.399\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.457\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.648\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.318\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.189\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eEducation Level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.791\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHousehold Members\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.507\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDependents\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-1.135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.257\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRemittance Amount\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.593E-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.915\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e33.113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ea. Dependent variable: Education expense percentage\u003c/p\u003e\n\u003cp\u003eTable 5 presents the detailed regression coefficients. The remittance amount is found to be a statistically significant predictor (B = 5.593E-5, p \u0026lt; 0.001), with a standardized beta coefficient of 0.915. This demonstrates a strong positive association, indicating that as remittances increase, households tend to allocate a larger proportion of their budget to education. In contrast, the control variables (age, education level, household size, and dependents) do not show statistically significant relationships with education expenditure, suggesting that remittance inflows are the principal driver of increased education spending. These findings underscore the critical role of remittances in facilitating educational investment among recipient households. The results align with the hypothesis that remittance inflows provide financial resources that directly support long-term human capital development.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImpact of remittances and financial literacy on investment ratio\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6\u003c/strong\u003e Effect of remittances and financial literacy on investment ratio\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCoefficients \u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"629\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnstandardized coefficients\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eStandardized coefficients\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eBeta\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003et\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eStd. error\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e(Constant)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.097\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10.181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.814\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.417\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eEducation Level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.874\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.383\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHousehold Members\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.805\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.422\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDependents\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.978\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.329\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRemittance Amount\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.649E-7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.373\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10.177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eFinancial Literacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17.728\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMigration Duration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.223\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e.824\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ea. Dependent variable: Investment ratio\u003c/p\u003e\n\u003cp\u003eTable 6 presents the results of the multiple linear regression model estimating the effect of remittance amount and financial literacy on the household investment ratio, controlling for relevant demographic and household-level factors. The model includes control variables such as migration duration, education level, number of dependents, household size, and age of the household head.\u003c/p\u003e\n\u003cp\u003eThe regression model explains approximately 77.3% of the variation in the investment ratio (R\u0026sup2; = 0.773), with an adjusted R\u0026sup2; of 0.766 and a standard error of 0.02325. The ANOVA results confirm the model\u0026rsquo;s overall statistical significance (F = 110.144, p \u0026lt; 0.001), indicating that the independent variables jointly have a strong influence on the investment ratio.\u003c/p\u003e\n\u003cp\u003eAmong the predictors, remittance amount (B = 7.649E-7, \u0026beta; = 0.373, p \u0026lt; 0.001) and financial literacy (B = 0.062, \u0026beta; = 0.643, p \u0026lt; 0.001) have statistically significant and positive effects on investment ratio. This implies that households receiving higher remittances and exhibiting greater financial literacy are more likely to allocate a larger proportion of their income towards investment purposes. Conversely, control variables such as age, education level, number of household members, number of dependents, and migration duration did not show significant individual effects (p \u0026gt; 0.05), although they contribute to the model\u0026apos;s overall explanatory power.\u003c/p\u003e\n\u003cp\u003eThese findings reinforce the critical role of both remittance inflows and financial literacy in promoting household-level investments. Financial literacy, in particular, appears to have a stronger standardized impact, suggesting its influence in improving financial decision-making and efficient allocation of resources.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImpact of remittance amount and migration duration on business investment percentage\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 7\u003c/strong\u003e Effect of migration duration, remittance amount, and household-level controls on business investment\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCoefficients \u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnstandardized coefficients\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eStandardized coefficients\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eBeta\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003et\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eStd. error\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e(Constant)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-3.223\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.864\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.388\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eEducation level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.690\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.491\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHousehold members\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.473\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.637\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDependents\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.089\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.277\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRemittance amount\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.625E-7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.639\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.524\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMigration duration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.565\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.964\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e54.347\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDebt payment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.203\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.839\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eFinancial literacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.453\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.651\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eInvestment difficulties\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.240\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-2.290\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ea. Dependent variable: Business investment percentage\u003c/p\u003e\n\u003cp\u003eTable 7 presents the results from a multiple linear regression model that investigates the influence of migration duration and remittance amount on business investment behavior, while controlling for a set of household-level socioeconomic and financial variables. The model is statistically significant (F = 342.064, p \u0026lt; 0.001), and the R\u0026sup2; value of 0.932 indicates that approximately 93.2% of the variance in business investment percentage is explained by the independent variables included in the model. Among the predictors, migration duration emerges as the most influential variable (B = 0.565, \u0026beta; = 0.964, p \u0026lt; 0.001), suggesting that households with migrants who spend longer periods abroad are significantly more likely to invest a greater proportion of remittances into business activities. This finding aligns with the hypothesis that prolonged migration enables individuals to accumulate financial capital and entrepreneurial knowledge, thereby fostering investment readiness.\u003c/p\u003e\n\u003cp\u003eWhile remittance amount shows a positive coefficient (B = 3.625E-7), it is not statistically significant (p = 0.524), indicating that the sheer volume of remittance inflows does not independently predict business investment once migration duration and other household factors are considered.\u003c/p\u003e\n\u003cp\u003eAmong the control variables, investment difficulties is the only statistically significant factor (B = -0.042, \u0026beta; = -0.240, p = 0.023). The negative coefficient highlights that households encountering greater challenges in accessing or utilizing investment opportunities tend to allocate a smaller portion of remittances to business activities. This underscores the importance of institutional and infrastructural support in facilitating productive investment.\u003c/p\u003e\n\u003cp\u003eOther variables, including age, education level, number of household members, number of dependents, debt payment, and financial literacy, do not exhibit statistically significant effects (p \u0026gt; 0.05). Their inclusion was guided by theoretical relevance and prior empirical findings, but their effects may be absorbed by stronger predictors in this model.\u003c/p\u003e\n\u003cp\u003eOverall, the results reinforce the pivotal role of migration experience, particularly duration, in shaping household investment behavior, while also acknowledging the obstructive role of practical investment challenges. This highlights the need for targeted support mechanisms that ease investment processes for remittance-receiving households, especially those with substantial migration histories.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eModeration analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe regression analysis examines the moderating effect of income category on the relationship between remittance amount and investment ratio. The model summary indicates an R\u0026sup2; value of 0.4548, suggesting that approximately 45.48% of the variance in investment ratio can be explained by the independent variables, including the interaction term. The F-statistic (64.2394, p \u0026lt; 0.001) confirms that the overall model is statistically significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 8\u003c/strong\u003e Moderation model for income level in investment decisions\u003c/p\u003e\n\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"600\"\u003e\n \u003ctbody\u003e\n\u003ctr\u003e\n \u003ctd valign=\"top\" colspan=\"5\" style=\"width: 623px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoefficients \u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoefficient\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003et\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e(Constant)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e.1702\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e.0023 \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e72.8870 \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eRemittance amount\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e13.8139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eIncome category\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e.0021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e.0017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e.9987 \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eInteraction term\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e.2144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e.8304\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ea. Dependent variable: Investment ratio\u003c/p\u003e\n\u003cp\u003eThe coefficients Table 8 shows that remittance amount has a significant positive effect on investment ratio (B = 0.0000, t = 13.8139, p \u0026lt; 0.001), indicating that higher remittances contribute to increased investments. However, the interaction term (Remittance amount \u0026times; Income category) is not significant (B = 0.0000, t = 0.2144, p = 0.8304), suggesting that income category does not significantly moderate the relationship between remittances and investment.\u003c/p\u003e\n\u003cp\u003eThe graphical representation in Figure 1 further supports these findings, showing that the slopes of the regression lines for different income categories are nearly identical, indicating no substantial difference in investment behavior across income groups. This suggests that regardless of income level, remittances play a crucial role in shaping investment decisions, with no significant moderating effect from income category.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cstrong\u003eImpact of remittance inflows on household consumption\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe regression analysis shows that remittance inflows have a significant positive effect on household consumption. The standardized beta coefficient of 0.676 suggests that a one-unit increase in remittance leads to a 67.6% rise in household consumption. This result aligns with the findings of Adams and Cuecuecha (2013) and Gupta et al. (2009) who reported that remittances are primarily used for food, healthcare, and daily necessities. The R\u0026sup2; value of 0.470 indicates that remittances explain 47.0% of the variation in consumption, confirming that household spending largely depends on remittance income. The adjusted R\u0026sup2; of 0.459 confirms the explanatory power of the model after accounting for control variables. The statistical significance of the model (p \u0026lt; 0.001) further strengthens the conclusion that remittances play a vital role in sustaining household expenses.\u003c/p\u003e\n\u003cp\u003eWhile previous research suggests that remittances can also support business investment and long-term financial stability (Woodruff and Zenteno 2007), this study finds that the primary allocation is toward immediate consumption. This supports Keynesian economic theory, which argues that income increases drive consumption growth. The remaining 53.0% of variation in household consumption is explained by other factors such as local income, employment conditions, and financial literacy. Among the control variables\u0026mdash;age, education level, household size, and number of dependents\u0026mdash;none were statistically significant in this model, indicating that remittances are the primary driver of consumption behavior in remittance-receiving households. The findings confirm that while remittances provide financial stability in the short run, they may not necessarily contribute to long-term asset accumulation, as also debated by Ratha (2013). This highlights the need for policies that encourage remittance-receiving households to allocate a portion of funds toward investment and savings for future economic security.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRelationship between remittance amount and education expenses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe regression results indicate a strong and statistically significant relationship between remittance inflows and household spending on education. The model reports an R\u0026sup2; value of 0.830, indicating that 83.0% of the variation in education expenses is explained by the included predictors, primarily remittance inflows. This suggests that remittances are a primary financial resource for educational investments. The standardized beta coefficient of 0.915 suggests that a one-unit increase in remittance amount leads to a 91.5% increase in household spending on education. This reinforces the argument that remittances serve as a crucial driver of human capital formation. This aligns with the Human Capital Theory (Becker 2009), which posits that individuals and households view education as an investment in future earning potential. Empirical studies further support this link, with Yang (2008) and Acosta (2011) demonstrating that remittances enhance school enrollment rates and reduce dropout rates, particularly in developing countries.\u003c/p\u003e\n\u003cp\u003eThe findings contrast with research suggesting that remittances are primarily consumed rather than invested (Ratha, 2021). While previous studies highlight a strong inclination toward immediate consumption needs such as food and healthcare (Adams Jr and Cuecuecha 2013), this study indicates that education is a key spending priority for remittance-receiving households. The remittance variable shows a statistically significant coefficient (B = 5.593E-5, p \u0026lt; 0.001), with a strong effect size, highlighting that families prioritize education when remittance income increases. This reinforces earlier findings by Acosta (2011) that remittances act as a financial buffer for households, enabling them to support children\u0026apos;s schooling without disruption. The non-significant constant term (B = -0.182, p = 0.648) indicates that in the absence of remittance inflows, education expenses are not automatically guaranteed, reflecting financial constraints in non-remittance-receiving households.\u003c/p\u003e\n\u003cp\u003eWhile remittances facilitate access to education, other factors may still influence household education spending decisions. Economic conditions, parental financial literacy, and government support programs may further shape educational investments. Some scholars argue that remittances are more likely to be allocated toward education when financial literacy levels are higher, as informed households recognize the long-term benefits of human capital investment (Lusardi and Mitchell 2014). The findings of this study support policies that encourage productive utilization of remittances, particularly through financial education initiatives that enhance household decision-making in favor of long-term investments such as education.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe role of remittances and financial literacy in investment decisions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe regression results show that both remittances and financial literacy influence household investment. The model explains approximately 77.3% of the variation in the investment ratio (R\u0026sup2; = 0.773), with an adjusted R\u0026sup2; of 0.766 and a standard error of 0.02325.This supports past research that highlights financial literacy as key to better financial decisions (Lusardi and Mitchell 2014).\u003c/p\u003e\n\u003cp\u003eThe findings suggest that remittances increase investment, but the impact is small. However, both remittance amount (B = 7.649E-7, \u0026beta; = 0.373, p \u0026lt; 0.001) and financial literacy (B = 0.062, \u0026beta; = 0.643, p \u0026lt; 0.001) are statistically significant predictors of investment ratio. Financial literacy has a much stronger effect. Households with financial knowledge are more likely to invest remittances in business or savings. Similar studies found that financial education helps people make better investment choices (Hastings et al. 2012; Klapper et al. 2015).\u003c/p\u003e\n\u003cp\u003eResearch also shows that financially aware households prioritize long-term investments. Atkinson and Messy (2012) found that such households spend less on daily needs and more on wealth-building activities. Islam et al. (2012) noted that in Bangladesh, financially literate families use remittances for business and asset growth. Demirg\u0026uuml;\u0026ccedil;-Kunt (2008) showed that financial literacy increases banking and microfinance participation. Conversely, control variables such as age, education level, number of household members, number of dependents, and migration duration were not individually significant (p \u0026gt; 0.05), though they contribute to the overall explanatory power of the model. Despite its benefits, financial literacy remains low in many developing countries. Expanding financial education can help remittance-receiving households use their money wisely and build a stable future.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMigration duration and business investment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe regression results show that migration duration strongly affects business investment. The model explains 93.2% of the variation in business investment, indicating that migration experience plays a critical role in shaping investment behavior. The findings confirm that longer migration leads to higher business investment. The standardized beta coefficient of 0.565 shows that migration duration accounts for 96.4% of the changes in business investment. This means that as migration duration increases, business investment rises significantly. This supports Cumulative Causation Theory, which suggests that long-term migration improves financial stability and business skills, leading to higher investments in businesses.\u003c/p\u003e\n\u003cp\u003eThe results also show that remittance amount positively affects business investment, although its influence is comparatively weaker than that of migration duration. The regression coefficient (B = 3.625, p = 0.524) is not statistically significant, implying that remittance inflows alone may not be a strong driver of business investment when other factors are controlled. However, migration duration has a much stronger impact than remittances. These findings agree with studies showing that long-term migrants are more likely to invest in businesses (Woodruff and Zenteno 2007).\u003c/p\u003e\n\u003cp\u003eFurthermore, investment difficulties emerged as the only control variable with a statistically significant effect (B = -0.042, \u0026beta; = -0.240, p = 0.023), indicating that households encountering greater barriers to investment may allocate fewer remittance resources toward entrepreneurial ventures. This highlights the need to address institutional or structural barriers to enhance remittance utilization in business development.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIncome category as a moderator in the remittance-investment relationship\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results reveal that income category does not significantly moderate the relationship between remittances and investment decisions. The model explains 45.48% of the variation in investment, showing that remittance inflows have a notable impact. However, the interaction effect is not statistically significant, meaning that investment behavior remains unchanged across different income groups. This contradicts the Relative Income Hypothesis, which suggests that higher-income households are more likely to invest while lower-income households prioritize consumption. Previous studies have shown that income levels influence remittance allocation, with wealthier families investing more in business and assets. However, these findings suggest that remittances enable investment regardless of income level, possibly because remittance-receiving households\u0026mdash;regardless of their pre-existing income\u0026mdash;see remittances as a unique financial resource dedicated to future security.\u003c/p\u003e\n\u003cp\u003eThe coefficient for Remittance Amount is significant, confirming that remittances drive investment, but Income Category itself is not statistically significant, meaning income differences do not alter investment behavior. The insignificant interaction effect suggests that all income groups\u0026mdash;low, middle, and high\u0026mdash;respond similarly to remittances in terms of investment. Graphical representation in figure 1 further supports this, showing that the regression lines for different income categories are nearly parallel, meaning there is no significant moderating effect. This finding challenges the traditional assumption that investment decisions are largely dictated by household wealth levels. Instead, it suggests that remittance recipients, regardless of income, recognize the importance of investment, possibly due to limited local earning opportunities or economic uncertainty. This result highlights the need for further investigation into the factors shaping remittance utilization beyond just income levels.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study explores how remittances affect household financial decisions, including spending, education, business, financial literacy, and income moderation. The findings show that remittances are vital to household expenditure and economic well-being. The findings support that remittance-receiving households spend more than invest. This shows a positive and significant association between remittance inflows and consumption, indicating that remittance-receiving households use these cash for food, healthcare, and utilities rather than long-term wealth formation. The dependency theory indicates that remittances are a financial safety net rather than an investment instrument in emerging economies. Education expenses increase strongly with remittance inflows, confirming their importance in enhancing education access and human capital development. These findings support the Human Capital Theory, which claims that education investment pays off over time. Financial literacy enhances the possibility of investing remittances. Financially literate households invest more of their remittances than consume, indicating that financial education improves financial decision-making. This research supports behavioral economics by demonstrating that knowledge and awareness improve financial outcomes. Longer migration periods bring to more financial resources, experience, and confidence, which increases investment. According to the Cumulative Causation Theory, longer migratory experiences strengthen economic links and investment prospects.\u0026nbsp;Moreover, migration duration appears to have a stronger and more consistent effect on business investment compared to remittance volume alone, suggesting that experience gained through long-term migration improves household entrepreneurial capacity.\u003c/p\u003e\n\u003cp\u003eThis study shows that remittances influence household financial decisions, particularly consumption and education investment. The results show that financial literacy improves remittance allocation to productive investments, but migration duration strongly influences business investment decisions. Furthermore, the effect of remittance amount on investment becomes statistically insignificant when controlling for household characteristics, highlighting the need to address structural constraints that hinder effective remittance utilization. Remittances appear to stabilize investment behavior regardless of income group, suggesting they stabilize the economy. These findings add to remittance use discussions and support the idea that financial knowledge and long-term migration boost economic development. Policymakers should encourage financial literacy and structured remittance investment plans to optimize development impact.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePolicy Implications\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study has major policy implications for governments, financial institutions, and development groups looking to maximize remittance benefits. Financial literacy programs could help remittance-receiving households make better financial decisions and manage funds more efficiently. Structured financial training can help families invest rather than spend. By expanding mobile banking and microfinance, households may better manage remittances. Governments should promote accessible financial literacy campaigns through community centers, mobile apps, and digital platforms to reach migrants and their families at scale.\u003c/p\u003e\n\u003cp\u003eThis study is important for remittance-dependent economies around the world. Policymakers must ensure constructive use of global remittance flows. Remittances serve as a primary income source for millions in South Asia, Africa, and Latin America; yet they are often allocated more towards current expenditures than long-term investments. This study highlights the importance of financial literacy and the duration of migration, providing a framework that governments and financial institutions can adopt to enhance remittance utilization. Special focus should be given to low-income and rural households, where financial literacy levels are typically lower and the risk of remittance misuse is higher.\u003c/p\u003e\n\u003cp\u003eThis research offers practical measures for economic growth. Unlike earlier research, it emphasizes financial literacy in diverting remittance spending to productive activity. The study also examines how migration duration affects investment decisions, revealing how remittances benefit businesses. We found that long-term migration boosts financial capability and business investments, which has major policy implications for reintegrating returning migrants. Governments should develop reintegration packages for returnees with investment coaching, start-up support, and tax incentives for remittance-financed enterprises.\u003c/p\u003e\n\u003cp\u003eEducation is another area where remittances can provide long-term advantages. Policymakers should establish scholarship programs for migrant workers\u0026rsquo; children. Financial organizations can offer savings programs based on remittances for education finance. These activities will assist families in using remittances to enhance human capital, hence increasing economic chances. Linking remittances with conditional education investments (e.g., matched savings for tuition) could further strengthen long-term educational outcomes.\u003c/p\u003e\n\u003cp\u003eGovernments in remittance-receiving nations should incorporate financial literacy into their migration strategies. Many migrants lack financial education, which influences how they handle remittances. Countries that employ migrant workers, such as those in the Middle East and Europe, should partner with financial institutions to give financial literacy training before migration. This would ensure that remittances meet both short-term demands and long-term development. In addition, embassies and labor attach\u0026eacute;s can facilitate pre-departure financial training in coordination with host country employers.\u003c/p\u003e\n\u003cp\u003eGlobal financial agencies such as the IMF and the UN can use these insights to link remittances to economic growth objectives. Microfinance initiatives and remittance-backed loans have the potential to transform remittance inflows into long-term economic growth. Encouraging banks to establish remittance-based lending products will help migrant families invest more in their businesses. Partnering with fintech companies to design user-friendly remittance-linked financial products can improve access and reduce transaction costs, especially for underserved populations.\u003c/p\u003e\n\u003cp\u003eThis study suggests practical approaches to increase remittance use. Remittances can help to improve long-term financial stability by fostering financial literacy, increasing access to financial services, and promoting productive investments. Future studies should look for new ways to optimize remittance potential by integrating behavioral insights and tailoring interventions based on household characteristics.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitations and future study\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study provides useful insights about remittance utilization; however, many limitations must be acknowledged. Its focus on Bangladesh areas may limit its applicability. To compare remittance usage across regions, future research should cover more regions. The study uses cross-sectional data to examine remittance impacts at one period. A longitudinal study might better capture causal relationships and explain changes in remittance utilization over time. Additionally, the study focuses on how remittances, financial literacy, and migration duration affect household financial decisions. However, other macroeconomic variables such as labor market conditions, government policy shifts, inflation rates, and financial access infrastructure may also influence remittance behavior. Further research should include more variables for a more complete analysis.\u003c/p\u003e\n\u003cp\u003eFinancial literacy measurement is another issue. The survey classifies financial literacy as high or low, which may not convey the complexity of financial decision-making. Further research should create a more comprehensive financial literacy index to assess financial understanding and decision-making. The study uses self-reported data, which may be prone to recall or social desirability bias. To verify findings and assure accuracy, future studies should integrate multiple data sources, including bank transaction records and remittance platform analytics. Research should also evaluate financial literacy programs and remittance utilization policies. Experimental or quasi-experimental methods could assess the causal impact of financial training and migration experience on remittance investment behavior.\u003c/p\u003e\n\u003cp\u003eFuture research should assess the impact of financial literacy programs and policy interventions designed to improve remittance utilization. For example, randomized trials of community-based financial education, digital financial tools, or remittance-linked savings products could reveal what strategies work best in specific contexts. Case studies of successful remittance-driven investment programs could provide further insights into best practices for policymakers. Furthermore, comparative studies across different migrant-sending countries would help validate whether the observed effects of migration duration and financial literacy generalize beyond Bangladesh.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted with human participants in compliance with the ethical principles outlined in the Declaration of Helsinki (2013). There is no mandatory centralized ethical approval process for studies at my University that pose minimal risk to participants. However, ethical considerations were strictly followed to ensure participants\u0026apos; rights, confidentiality, and voluntary participation. Written consent was obtained from all the participants involved in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no external funding.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAcosta, Pablo. 2011. \u0026ldquo;School Attendance, Child Labour, and Remittances from International Migration in El Salvador.\u0026rdquo; \u003cem\u003eJournal of Development Studies\u003c/em\u003e 47(6):913\u0026ndash;36. doi: 10.1080/00220388.2011.563298.\u003c/li\u003e\n\u003cli\u003eAcosta, Pablo, Pablo Fajnzylber, and J. Humberto L\u0026oacute;pez. 2008. \u0026ldquo;How Important Are Remittances in Latin America.\u0026rdquo; \u003cem\u003eRemittances and Development. Lessons from Latin America\u003c/em\u003e 21\u0026ndash;49.\u003c/li\u003e\n\u003cli\u003eAdams Jr, Richard H. 2011. \u0026ldquo;Evaluating the Economic Impact of International Remittances on Developing Countries Using Household Surveys: A Literature Review.\u0026rdquo; \u003cem\u003eJournal of Development Studies\u003c/em\u003e 47(6):809\u0026ndash;28.\u003c/li\u003e\n\u003cli\u003eAdams Jr, Richard H., and Alfredo Cuecuecha. 2013. \u0026ldquo;The Impact of Remittances on Investment and Poverty in Ghana.\u0026rdquo; \u003cem\u003eWorld Development\u003c/em\u003e 50:24\u0026ndash;40.\u003c/li\u003e\n\u003cli\u003eAtkinson, Adele, and Flore-Anne Messy. 2012. \u0026ldquo;Measuring Financial Literacy.\u0026rdquo; \u003cem\u003eJournal of Consumer Affairs\u003c/em\u003e 44(2):296\u0026ndash;316.\u003c/li\u003e\n\u003cli\u003eBangladesh Bank. 2021. \u003cem\u003eChapter-8: Annual Report 2021: The Impact of Remittances on the Economy\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eBangladesh Bank. 2023. \u003cem\u003eMonthly Report on Workers\u0026rsquo; Remittance Inflows in Bangladesh-December, 2024\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eBecker, GS. 2009. \u003cem\u003eHuman Capital: A Theoretical and Empirical Analysis, with Special Reference to Education\u003c/em\u003e. University of Chicago press.\u003c/li\u003e\n\u003cli\u003eBMET. 2023. \u003cem\u003eMigration from Bangladesh and Overseas Employment Policy\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eChami, Ralph, Connel Fullenkamp, and Samir Jahjah. 2005. \u003cem\u003eAre Immigrant Remittance Flows a Source of Capital for Development?\u003c/em\u003e Vol. 52. 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Here\u0026rsquo;s Why.\u0026rdquo; Retrieved February 19, 2025 (https://www.weforum.org/stories/2025/01/cross-border-payments-economic-growth/).\u003c/li\u003e\n\u003cli\u003eYang, Dean. 2008. \u0026ldquo;International Migration, Remittances and Household Investment: Evidence from Philippine Migrants\u0026rsquo; Exchange Rate Shocks.\u0026rdquo; \u003cem\u003eThe Economic Journal\u003c/em\u003e 118(528):591\u0026ndash;630.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"Remittances, Migration and economic development, Household finance, Consumption vs. Investment behavior, Financial literacy","lastPublishedDoi":"10.21203/rs.3.rs-7264115/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7264115/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"This study explores the impact of remittances on household spending and investment decisions in Rajshahi Division, Bangladesh. It is based on a cross-sectional survey of 235 remittance-receiving households. For analyzing survey data from households that receive remittances, the research employs multiple regression models to examine spending behaviors. The sample includes households randomly selected from Pabna, Sirajganj, and Kushtia districts. The study focuses on key factors such as financial literacy, migration duration, and income levels to understand their influence on remittance utilization. Findings indicate that most households prioritize consumption over investment. The regression results reveal that financial literacy and remittance amount significantly and positively affect household investment ratio, while migration duration is the strongest predictor of business investment percentage. Interestingly, income levels do not appear to have a significant moderating effect on remittance-driven investment behavior. This study shows how financial knowledge promotes beneficial remittance expenditure. The study's unique focus on migration duration and business investment illuminates remittance-driven financial behavior. Based on these findings, the study recommends promoting household-level financial literacy programs and supporting long-term migrants' investment initiatives to improve the productive use of remittances. Such targeted measures can help maximize remittance benefits for household stability and local economic development, especially in rural regions like Rajshahi Division.","manuscriptTitle":"Remittances and household financial behavior in Rajshahi Division, Bangladesh: examining consumption and investment patterns","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-21 13:26:22","doi":"10.21203/rs.3.rs-7264115/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":"b84a0821-eeb3-4e49-a6ca-e7004a179d0f","owner":[],"postedDate":"April 21st, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-21T13:26:22+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-21 13:26:22","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7264115","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7264115","identity":"rs-7264115","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}