Household Income Diversification and Food Security in Somalia: Role of Urbanization, Displacement, and Household Size

Household Income Diversification and Food Security in Somalia: Role of Urbanization, Displacement, and Household Size | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Household Income Diversification and Food Security in Somalia: Role of Urbanization, Displacement, and Household Size Osman Abdulkadir Nor, Abas Omar Mohamed This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9110419/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 Household well-being and sustainable development depend on food security, but in fragile regions such as Somalia, urbanization, violence, displacement, and climate change continue to affect households. Although income diversification, particularly through regular income, food assistance and remittances, is widely recognized as resilience strategy, existing research frequently overlooks its effectiveness due to regional and demographic factors. This study closes this gap by examining how household size, place of residence, and displacement status affect the relationship between food insecurity and income diversification using the Sustainable Livelihoods Framework and Urbanization Theory. Using nationally representative data from the Somalia Integrated Household Budget Survey, the study estimates linear probability, logit, and probit models to assess the risk of food insecurity across different income sources. According to the research, regular income and food assistance significantly reduce food insecurity, but remittances alone do not consistently improve food outcomes. Additionally, there is notable heterogeneity in effectiveness, as diversification strategies vary across internally displaced households, larger families, and urban dwellers. Overall, the results indicate that, to improve food security in Somalia in a sustainable way, income-based interventions alone will not be sufficient; context-sensitive livelihood policies and targeted social protection are also required. Income Diversification Food Security Urbanization Remittances Somalia Figures Figure 1 1. INTRODUCTION Household income diversification is recognized as a critical adaptation strategy for improving food security in fragile contexts, where protracted conflict, recurrent droughts, and socio-political instability severely affect livelihoods (Waha et al., 2018; Etea et al., 2019; Liyew & Damtie, 2024; Atuoye et al., 2019). Food security comprises four key dimensions, availability, access, utilization, and stability, that collectively ensure sufficient and nutritious food for all individuals. (Clapp et al., 2022). Several household-specific, socioeconomic, and environmental factors play a crucial role in determining the effectiveness of income diversification as a strategy for improving food security. Urbanization shapes these dynamics by shifting livelihoods away from traditional subsistence agriculture toward wage labor and informal sector activities, while household size and displacement introduce additional vulnerabilities within resource-constrained urban environments (Gebresilassie et al., 2025; Abebe, 2024 ). The history of Somalia’s food insecurity spans decades of conflict-induced displacement and drought, culminating in critical famines in 2011, 2026, and 2022, which highlighted glaring deficiencies in resilience and early warning systems (Osman & Abebe, 2023 ). As shown in Fig. 1 , preliminary observations of data collected from approximately 50,000 Somali households across 17 of the 18 Somali regions indicate dire food insecurity across all six indicators, affecting a significant portion of the population. Since then, urban migration has accelerated as displaced rural populations seek refuge and livelihood opportunities in cities like Mogadishu, contributing to rapidly expanding informal settlements that strain food systems (Hussein & Osman, 2024). The significance of this study lies in examining the interplay between remittances as a diversification strategy and demographic moderators shaping household food security outcomes in fragile, urbanizing, and displacement-affected contexts. As a critical household livelihood factor in Somalia, remittance inflows from the diaspora constitute one of the largest sources of household income and serve as crucial financial buffers, enabling families to secure diverse and nutritious food amid shocks and market disruptions (Hillbruner & Moloney, 2012 ). Source: Authors’ calculation using the Somalia Integrated Household Budget Survey data The study is grounded primarily in the Sustainable Livelihoods Framework (SLF), which emphasizes diversifying income sources to enhance household resilience by building and protecting livelihood assets in the face of shocks such as conflict or climate variability (Ye et al., 2022 ). Within this paradigm, remittances serve as vital injections of financial capital that households leverage to stabilize consumption, access markets, and invest in food security (Subramaniam Y, 2022). Complementing SLF, household production theory informs the analysis of how intra-household demographics, including household size, affect resource allocation and the effective utilization of remittance income for food needs (Harris-Fry et al., 2017 ). Larger households may face higher dependency burdens, thus moderating the direct benefits of income diversification (Tadele, 2021). Urbanization theory adds another layer by contextualizing the transitions from rural to urban livelihoods, highlighting both expanded job opportunities and increased cost-of-living burdens that influence food security outcomes (Abebe, 2024 ). The integration of these theories provides a robust conceptual foundation to examine remittance-driven food security under the moderating influences of household size, urban residence, and displacement status. Extensive literature confirms that income diversification positively correlates with food security by spreading risk and smoothing household consumption. Studies from Ghana and Ethiopia illustrate that diversification strategies, including off-farm work and remittances, improve household dietary diversity and calorie intake, directly enhancing nutrition and food stability (Akrasi et al., 2020 ; Adem et al., 2018 ). A consensus emerges that diversification acts as a buffer against agricultural shocks, yet disagreements persist about the extent of benefits in fragile contexts, where limited market access, social exclusion, or displacement complicate the translation of income into food security (Nasung et al., 2019 ). This variability underscores the need to consider moderating factors in the income-food security nexus. For instance, remittances have a significant positive impact on Somalia's total GDP(Mohamed & Enow, 2025 ). This indicates that remittances have a greater impact on Somalia's GDP than both foreign direct investment (FDI) and official development assistance (ODA). This demonstrates how important remittances are to the Somali people as an outside source of funding (Bulut & Mohamed, 2018 ). This inflow not only reduces food insecurity by increasing household purchasing power but also facilitates access to previously unaffordable, diverse food items under subsistence conditions (Poblacion et al., 2017 ). Yet, much of the literature tends to focus on direct effects without adequately considering moderating variables. For example, a larger household size can weaken per capita benefits from remittances, while urban living imposes higher expenditure pressures, thereby influencing the overall impact of remittance income on food security (Chukwu & Chukwu, 2025 ). The urbanization and displacement literature further elaborates on the complexity. Rapid urbanization has been associated with improved livelihood diversification opportunities, allowing rural migrants and IDPs access to wage labor and informal trade (Adzande, 2025 ). However, these benefits are often offset by increased living costs, inadequate infrastructure, and food price volatility (Szabo & Szabo, 2016 ). Displaced populations in Somalia, including roughly 3 million IDPs, face compounded food insecurity risks due to disrupted social networks, limited asset ownership, and dependency on humanitarian aid (Warsame et al., 2024 ). Despite the growing body of research, methodological gaps persist, including insufficient longitudinal data, inconsistent incorporation of displacement and urbanization as moderating variables, and limited empirical studies focusing on Somalia’s distinctive, fragile setting. Expanding on the literature, emerging studies emphasize the role of remittance mechanisms and financial inclusion in enhancing food security. Digital financial services and hawala networks facilitate remittance flows even during conflict, enabling continued support for household food access(Mannan & Farhana, 2023 ). However, challenges such as transfer costs and regulatory barriers limit the full utilization of remittances for food security gains. Furthermore, with increasing climate variability, the role of remittances as adaptive tools has garnered attention, where households use remitted funds to diversify food sources or invest in climate-resilient agricultural inputs (Omer, 2024 ). Yet, this adaptive capacity is contingent on supportive social and policy environments, which are often weak in Somalia. Additional research highlights the differential impact of urbanization contexts. Urban poor and displaced groups often experience food insecurity despite remittance inflows due to heightened competition for resources, inadequate social protection, and food price inflation(Hussein & Osman, 2024). This underscores that the nexus of income diversification and food security cannot be universally applied without accounting for socio-demographic moderators such as household size and displacement status. Studies in other fragile contexts confirm these interactions, suggesting the need for nuanced policy targeting(Adem et al., 2018 ). Hence, this study contributes by explicitly testing these moderating effects using recent Somali household data, bridging gaps in coverage, methodology, and context specificity. Somalia suffers from persistent and severe food insecurity, even as remittances constitute a significant portion of household income. While the beneficial role of remittances in improving food security is well-acknowledged, critical inconsistencies remain regarding how factors such as urbanization, household size, and displacement status affect this relationship. Prior research typically isolates these variables rather than examining their interaction effects, leading to gaps in data coverage, particularly for displaced urban households. To address the limitations of the literature, this study aims to answer the following research questions. How does household income remittance influence food security in Somalia? How do household size, urbanization, and displacement status moderate this nexus? As a result, this study contributes to advancing theoretical understanding by integrating key socio-demographic moderators within the Sustainable Livelihoods Framework in a fragile, conflict-affected context. Empirically, it enriches the limited Somalia-specific evidence on the interactions between food security and income diversification, using recent and representative household survey data. The findings offer actionable insights for policymakers and humanitarian actors aiming to design targeted interventions to strengthen food security resilience, particularly for vulnerable displaced and large urban households. The rest of the paper is organized as follows: Section 2 outlines the methodology and data sources; Section 3 presents the empirical results; Section 4 discusses the theoretical and practical implications; and Section 5 concludes and offers economic policy recommendations for Somalia’s fiscal and public service reform initiatives. 2. METHODS AND MATERIALS This section provides empirical strategy, data, and variables of the study. Following Husein Duale (2018) and Boru and Dilla (2017), the study employed nonlinear probit and logit regression models to investigate Household income diversification and food insecurity in Somalia. This design was deemed appropriate given that the dependent variable, Food insecurity, is binary and measured through discrete categories. The approach facilitated an empirical analysis of how regular income, food aid, and remittances influence food insecurity, thereby moving beyond descriptive statistics to generate policy-relevant insights. 2.1 Data and Variables The study uses the Somalia Integrated Household Budget Survey (SIHBS) dataset, obtained from the Somalia National Bureau of Statistics, which provides detailed data on 7212 Somali households. The data includes information on food insecurity, regular income, food aid, remittances, and other household variables. The household sample encompasses rural, nomadic, and urban areas, where communities are most vulnerable to cyclical Shocks, such as drought, conflict, and economic instability. The dataset also includes key household characteristic variables (e.g., sex, homeownership, IDP status and household size). The dependent variable in this study is measured using a binary indicator of food insecurity. It captures household food security status following the exposure to income-related shocks such as drought, conflict, or market disruptions. It categorizes households based on whether they experienced significant food-related shocks and related welfare impacts. More specifically, it is measured as an index of six food insecurity indicators, including: worrying about food, being unable to eat nutritious food, limiting food variety, skipping meals, eating less, and running out of food. The independent variables represent different sources of household income, including regular income and remittances received. The variable regular income indicates whether the household has a stable source of income, while food aid captures receipt of external food assistance. The variable remittance received indicates whether the household receives remittances as financial support. Additionally, the study controlled for other variables, such as food aid, home ownership, and sex. These independent and confounding variables work together to investigate how household coping mechanisms affect the impact of shocks, as indicated by food security outcomes. 2.2 Empirical Model Specification The empirical framework for the study was specified using three complementary models. First, the Linear Probability Model (LPM) was specified as follows: $${FI}_{i}={\beta}_{0}+{\beta}_{1}{RI}_{i}+{\beta}_{2}{FA}_{i}+{\beta}_{3}{RR}_{i}+{\beta}_{4}{X}_{i}+{E}_{i}\left(1\right)$$ Where \({\text{F}\text{I}}_{i}\) is food insecurity, \({RI}_{i}is\) regular income, \({FA}_{i}\) is a food aid, \({RR}_{i}\) : is remittance received, \({X}_{i}\) for other control variables such as home ownership and sex. \({E}_{i}\) : is the error term. Second, the Logit model was expressed as: $$P\left(FI=1\right)=\frac{\text{exp}\left({\beta}_{0}+{\beta}_{1}{RI}_{i}+{\beta}_{2}{FA}_{i}+{\beta}_{3}{RR}_{i}+{\beta}_{4}{X}_{i}\right)}{1+\text{exp}\left({\beta}_{0}+{\beta}_{1}{RI}_{i}+{\beta}_{2}{FA}_{i}+{\beta}_{3}{RR}_{i}\right)}\left(2\right)$$ $$P\left(FI=1\right)={\int}_{-\infty}^{\left({\beta}_{0}+{\beta}_{1}{RI}_{i}+{\beta}_{2}{FA}_{i}+{\beta}_{2}{RR}_{i}{+\beta}_{4}{X}_{i}\right)}\varnothing\left(z\right)dz\left(3\right)$$ where food insecurity impact is the outcome variable, measured as a binary variable using an index of 6 food insecurity indicators: worrying about food, being unable to eat nutritious food, limiting food variety, skipping meals, eating less, and running out of food. Income diversification is the main explanatory variable, including regular income, food aid, remittances, and household characteristics such as sex and home ownership. Beta represents the coefficients for each category of the dependent variable, and Phi represents the cumulative distribution function of the standard normal distribution in the probit model. The substantial interaction between remittances and displacement status suggests that displaced households gain less from remittances in terms of enhancing food security than non-displaced households do. Additionally, the interaction terms between remittances and urban or nomadic residence show that the relationship between remittances and food insecurity is moderated by location. The impact of income sources on food insecurity is also influenced by household size, suggesting that larger households might be less affected by income. These results generally confirm the significance of moderating factors in influencing food security outcomes. 3. RESULTS In line with the study objectives, this section presents the study's results, which provide insight into the impact of regular income, food aid, remittances, and socio-demographic factors on food insecurity and how these dynamics vary across household characteristics. Moreover, the section provides the moderating effects of displacement, urbanization, and household size on the income-food insecurity nexus. Finally, provide a qualitative interpretation of the results. The section concludes with the marginal effects and odds ratios results. 3.1 Basic Results The first results provided in Table 1 present the basic findings on the impact of regular income, food aid, and remittances on food insecurity, using multiple regression models (LPM, Probit, and Logit). The results show that regular income and food aid are significantly negatively associated with food insecurity, indicating that they help reduce it. Specifically, the coefficients for regular income range from − 0.083 (LPM) to -0.435 (Logit), and for food aid from − 0.044 (LPM) to -0.213 (Logit), all statistically significant at the 1% level. Conversely, remittances, with coefficients ranging from 0.085 (LPM) to 0.456 (Logit), show a positive relationship with food insecurity, suggesting that remittances worsen food security, possibly due to over-reliance on external income sources rather than sustainable local strategies. Additionally, household size and location also significantly affect food security, with larger households and those located in rural or nomadic settings facing greater food insecurity. These findings underscore the critical role of income diversification in improving food security, but also highlight the need for further investigation into factors like location and household composition. Table 1 Basic Results Dependent Variable: Food Insecurity LPM Model Probit Model Logit Model (1) (2) (3) Regular income − .083*** − .255*** − .435*** (.02) (.062) (.105) Food aid − .044*** − .127*** − .213*** (.009) (.026) (.045) Remittances Received .085*** .265*** .456*** (.019) (.058) (.099) IDP .283*** .77*** 1.261*** (.025) (.072) (.118) Rural location .029* .099* .147* (.017) (.052) (.087) Nomadic location .125*** .359*** .59*** (.025) (.073) (.121) Household size .072*** .221*** .369*** (.021) (.065) (.108) Home ownership .002*** .006*** .01*** (0) (.001) (.001) _cons .167** − .986*** -1.631*** (.071) (.218) (.365) Observations 3270 3270 3270 R-squared 0.0802 - - Pseudo R 2 - .064 .064 Standard errors are in parentheses *** p<.01, ** p<.05, * p<.1 3.2 Displacement Moderating Effects on the Remittance-Food Insecurity Nexus Building on the findings in Table 1 , the results in Table 2 further explore how displacement moderates the relationship between remittances and food insecurity. The interaction term between remittances and displacement (IDP) is significant and negative, with coefficients ranging from − 0.158 (LPM) to -0.696 (Logit), suggesting that displaced households benefit less from remittances in terms of food security compared to non-displaced households. This reinforces the idea that displaced persons face compounded vulnerabilities, which may prevent remittances from improving food security as effectively as in stable household contexts. In addition to this interaction, household size and rural location remain significant predictors of food insecurity. These results highlight the need for targeted interventions that consider displacement status and the specific challenges faced by displaced households, such as disrupted social networks and limited access to resources. Table 2 Displacement Moderating Effects on Remittance-Food Security Nexus Dependent Variable: Food Insecurity LPM Model Probit Model Logit Model (1) (2) (3) Regular income − .083*** − .255*** − .432*** (.02) (.062) (.105) Food aid − .043*** − .125*** − .209*** (.009) (.026) (.045) Remittances .229*** .646*** 1.072*** (.021) (.066) (.111) Remittances*IDP − .158*** − .426*** − .696*** (.013) (.039) (.064) 1bn.location1 .032* .109** .166* (.017) (.052) (.087) 3.location1 .127*** .365*** .603*** (.025) (.073) (.121) Household size .07*** .212*** .356*** (.021) (.065) (.108) Home ownership .002*** .006*** .01*** (0) (.001) (.001) _cons .19*** − .907*** -1.49*** (.07) (.217) (.364) Observations 3270 3270 3270 R-squared 0.0832 - - Pseudo R 2 - .066 .065 Standard errors are in parentheses *** p<.01, ** p<.05, * p<.1 3.3 Urbanization Moderating Effects on the Remittance-Food Security Nexus The next results presented in Table 3 extend the analysis by examining how urbanization moderates the effect of remittances on food security. While remittances remain positively correlated with food insecurity across all models, the interaction terms between remittances and urban or nomadic locations are important. For households in rural or nomadic areas, the coefficients for remittance interaction terms are significantly positive (0.073 in LPM to 0.334 in Logit), indicating that these households benefit more from remittances than urban households. Urban households, potentially facing higher living costs and greater competition for resources, experience a smaller positive effect of remittances on food security. The findings in this table emphasize the importance of accounting for urbanization when assessing the impact of remittances, as the dynamics in urban and rural areas differ significantly. This section suggests that while remittances are a critical factor in food security, their effectiveness is moderated by the urban context, where higher living costs might limit their positive impact. Table 3 Urbanization Moderating Effects on Remittance-Food Security Nexus Dependent Variable: Food Insecurity LPM Model Probit Model Logit Model (1) (2) (3) Regular income − .083*** − .255*** − .435*** (.02) (.062) (.105) Food aid − .044*** − .128*** − .214*** (.009) (.026) (.045) Remittance .072*** .223*** .389*** (.019) (.061) (.103) Remittance*Rural .014 .047 .067 (.009) (.029) (.048) Remittance*Nomadic .073*** .204*** .334*** (.014) (.039) (.065) 1bn.IDP .283*** .771*** 1.263*** (.025) (.072) (.118) Lnhhsize .072*** .222*** .37*** (.021) (.065) (.108) Home_ownership .002*** .007*** .011*** (0) (.001) (.001) _cons .19*** − .907*** -1.499*** (.07) (.214) (.359) Observations 3270 3270 3270 R-squared 0.0813 - - Pseudo R 2 - .065 .064 Standard errors are in parentheses *** p<.01, ** p<.05, * p<.1 3.4 Household Size Moderating Effects on Income-Food Security Nexus Furthermore, the analysis provided in Table 4 explores how household size influences the relationship between income sources and food insecurity. The interaction term between income and household size is significant, with coefficients ranging from 0.039 (LPM) to 0.229 (Logit), indicating that larger households benefit less from regular income in terms of food security. This likely occurs because higher dependency ratios in larger households mean the same amount of income is spread more thinly across a greater number of dependents, reducing its overall impact on food security. These results underscore the need to consider household composition when designing food security interventions, as larger households may require additional support to achieve food security levels comparable to those of smaller households. Table 4 Household Size Moderating Effects on Income-Food Security Nexus Dependent Variable: Food Insecurity LPM Model Probit Model Logit Model (1) (2) (3) Regular income − .361*** -1.206*** -2.119*** (.06) (.201) (.358) Income*HHsize .039*** .131*** .229*** (.008) (.026) (.046) Food aid − .042*** − .123*** − .204*** (.009) (.026) (.045) Remittance .079*** .245*** .429*** (.019) (.058) (.099) IDP .266*** .722*** 1.176*** (.025) (.072) (.119) Rural location1 .028 .098* .148* (.017) (.052) (.087) Nomadic location1 .116*** .334*** .549*** (.025) (.072) (.119) Home ownership .002*** .006*** .01*** (0) (.001) (.001) _cons .317*** − .523*** − .881*** (.057) (.174) (.297) Observations 3270 3270 3270 R-squared 0.0833 - - Pseudo R 2 - .067 .067 Standard errors are in parentheses *** p<.01, ** p<.05, * p<.1 3.5 Marginal Effects and Odds Ratio Results Finally, Table 5 provides a detailed analysis through marginal effects and odds ratios, offering a quantifiable assessment of the strength of the relationships between various income sources and food insecurity. The marginal effects confirm that remittances have a significant positive effect on food insecurity (0.496), indicating they are associated with greater food insecurity in the study population. Similarly, regular income and food aid have negative effects on food insecurity, with significant odds ratios showing their beneficial impact. Household size continues to have a significant moderating effect, with larger households facing higher food insecurity, even when accounting for income diversification strategies. These results reinforce previous findings, emphasizing the crucial role of remittances in food insecurity and highlighting the need for more nuanced approaches that account for household size and location to ensure the effectiveness of income diversification strategies in enhancing food security. Table 5 Marginal Effects and Odds Ratio Results Dependent Variable: Food Insecurity Marginal Effects Model Odds Ratio Model (1) (2) (3) (4) Regular income − .081** − .435*** -0.0894*** -0.0918*** (.064) (.105) (0.0216) (0.0221) Food aid − .239*** − .213*** -0.0444*** -0.0449*** (.03) (.045) (0.00924) (0.00938) Remittance .496*** .456*** 0.0926*** 0.0961*** (.068) (.099) (0.0202) (0.0208) 1bn.IDP 1.261*** 0.293*** 0.297*** (.118) (0.0278) (0.0282) Rural location .147* 0.0340* 0.0302* (.087) (0.0178) (0.0179) Nomad location .59*** 0.131*** 0.131*** (.121) (0.0273) (0.0280) HHsize .369*** 0.0772*** 0.0778*** (.108) (0.0227) (0.0227) Home ownership .01*** 0.00226*** 0.00221*** (.001) (0.000319) (0.000313) _cons − .301 -1.631*** (.196) (.365) Observations 6348 3270 3,270 3,270 Pseudo R 2 .016 .064 Standard errors are in parentheses *** p<.01, ** p<.05, * p<.1 4. DISCUSSION The study findings reveal that while regular income and food aid significantly reduce food insecurity, remittances, in isolation, worsen food security, possibly due to an over-reliance on external income sources. Household size, location, and displacement status are also critical factors in shaping food security outcomes. Displaced households, for instance, benefit less from remittances, and urban households experience fewer advantages from them than rural households. These findings underscore the complex interplay between income sources and socio-demographic factors in fragile contexts such as Somalia. Collectively, these findings suggest that while remittances and income diversification strategies have the potential to improve food security, their effectiveness is significantly influenced by household characteristics, including size, location, and displacement status. These findings underscore the importance of developing targeted food security interventions that account for these moderating factors to more effectively address food insecurity in Somalia. The study contributes to the theoretical understanding of food security in the context of income diversification, particularly in fragile settings. The Sustainable Livelihoods Framework (SLF), which emphasizes the importance of diversified income sources, aligns with findings that regular income and food aid improve food security by stabilizing consumption and expanding access to markets. However, the negative relationship between remittances and food security challenges some assumptions within SLF, particularly the adequacy of remittances as a sole strategy for household resilience. Urbanization Theory also supports the study’s findings, suggesting that urbanization complicates the benefits of remittances by increasing living costs and competition for resources. These theoretical frameworks help explain the contradictory effects of income diversification on food security, especially in contexts marked by urbanization, displacement, and large household sizes. Studies such as (Mabrouk & Ã, 2018 ) Support the idea that income diversification, including remittances, benefits food security. However, other studies (Vargas-silva & Vargas-silva, 2016 ), (Thanh et al., 2015 )Emphasize that the benefits of remittances depend on contextual factors, such as household size and displacement status. These contradictions highlight the need for detailed theoretical models that better account for socio-demographic factors. This study makes a significant contribution by incorporating these moderating factors into the analysis. The empirical contribution of this study is important as it provides context-specific insights into the relationship between income diversification and food security in Somalia. The results support the well-established notion that regular income and food aid improve food security, as seen in other contexts, such as Ghana and Ethiopia (Akrasi et al., 2020 ). However, the finding that remittances worsen food security in Somalia is a novel and crucial contribution, challenging much of the existing literature that treats remittances as an unmitigated benefit for food security(Ali et al., 2025 ). This suggests that remittances may not always lead to improved food security in fragile, conflict-affected environments, as highlighted by other studies (Abdulle et al., 2025 ). Additionally, the moderating effects of household size, urbanization, and displacement status reinforce previous research findings that these socio-demographic factors significantly impact food security (Li et al., 2024 ). Empirical studies by Sulemana and Doabil ( 2023 ) and Dessie et al. ( 2022 ) demonstrate that remittances, when combined with other livelihood strategies, can support food security. However, this study suggests that relying solely on remittances may be inadequate. Displacement, in particular, weakens the impact of remittances on food security, consistent with research on IDPs in Somalia (Mumin et al., 2022 ). The study’s findings on urbanization further confirm other regional studies, which indicate that urban poor communities experience greater food insecurity despite income diversification(Warren et al., 2015 ). These results call for policies that take local context into account when evaluating the role of remittances in food security. While this study provides valuable insights into the moderating effects of household size, urbanization, and displacement on income diversification and food security in Somalia, several limitations exist. First, the study relies on cross-sectional data from the Somalia Integrated Household Budget Survey (SIHBS), which limits the ability to make causal inferences. Longitudinal studies could provide more robust evidence on how changes in income sources and household characteristics impact food security over time. Second, the study does not consider other potential income sources, such as remittances from international humanitarian organizations, which may also influence food security. Future research could explore the role of digital financial services, particularly mobile money, in facilitating remittance flows and improving food security. Finally, this study focuses solely on Somalia, and while the findings provide valuable insights, they may not be fully generalizable to other conflict-affected or urbanizing regions. Expanding the study to other countries facing similar challenges would strengthen the empirical evidence on income diversification and food security in fragile settings. 5. CONCLUSION This study analyzes the role of income diversification in improving food security in Somalia, emphasizing the moderating effects of urbanization, displacement, and household size. The findings suggest that regular income and food aid significantly reduce food insecurity, but remittances may worsen food security in Somalia due to over-reliance on external income sources. Additionally, household characteristics, including size, location, and displacement status, play a critical role in determining the effectiveness of income diversification strategies. The study results constitute practical policy recommendations for food security. First, policies should focus on enhancing remittance utilization by reducing costs and barriers, especially in rural and displaced communities, to ensure more efficient transfers. Second, targeted interventions should support rural and nomadic households by improving access to food and income diversification strategies. Third, humanitarian organizations must prioritize direct food aid to address food insecurity, particularly in displacement settings. Fourth, promoting local livelihoods through small-scale agriculture and informal-sector work can reduce dependence on remittances. Fifth, policies in urban areas should focus on improving food security through subsidies, infrastructure improvements, and price stabilization mechanisms. Sixth, displacement-targeted programs should be strengthened to address the specific needs of displaced persons, particularly in terms of food security. Finally, enhancing financial inclusion through mobile money access and expanding social protection programs will help vulnerable households, especially in urban and displaced settings, better manage food security challenges. Declarations Conflict of Interest: The authors declare that they have no financial or non-financial conflicts of interest to disclose. Funding No funding was received for this study. Author Contribution All authors contributed to the study’s conception and the design of the conceptual framework. Osman Abdulkadir Nor carried out the introduction section, empirical specifications, data analysis, interpretation and discussion section although Abas Omar Mohamed was supervising all task of the article specially data analysis and methodology section .All authors participated in the manuscript review, with final editing and proofreading completed by Osman Abdulkadir Nor. Data Availability The study employed the Somalia Integrated Household Budget Survey (SIHBS) dataset sourced from the Somalia National Bureau of Statistics (https://microdata.nbs.gov.so/index.php/catalog/59). References Abebe, M. G. (2024). Impacts of urbanization on food security in Ethiopia . A review with empirical evidence. Journal of Agriculture and Food Research, 15(January), 100997. https://doi.org/10.1016/j.jafr.2024.100997 . Abdulle, A. S., Majid, A., Ibey, Y., Mohamed, A. A., & Omar, M. M. (2025). The impact of trade openness on private consumption in a heavily import-dependent country. Cogent Economics & Finance , 13 (1). https://doi.org/10.1080/23322039.2025.2566950 Abebe, M. G. (2024). Impacts of urbanization on food security in Ethiopia . A review with empirical evidence. Journal of Agriculture and Food Research , 15 (January), 100997. https://doi.org/10.1016/j.jafr.2024.100997 Adem, M., Tadele, E., & Mossie, H. (2018). Income diversification and food security situation in Ethiopia : A review study Income diversification and food security situation in Ethiopia : A review study. Cogent Food & Agriculture , 4 (1), 1–17. https://doi.org/10.1080/23311932.2018.1513354 Adzande, P. (2025). Developing pathways for self-reliance : urban IDPs and the negotiation of livelihood opportunities in Makurdi , Nigeria . XX (Xx), 226–243. https://doi.org/10.1177/09562478251317988 Akrasi, R. O., Eddico, P. N., & Adarkwah, R. (2020). Income Diversification Strategies and Household Food Security among Rice Farmers : Pointers to Note in the North Tongu District of Ghana . 8 (3), 77–88. https://doi.org/10.12691/jfs-8-3-1 Ali, D. A., Mohamed, N. A., & Ismail, A. I. (2025). Modelling the determinants of rural household poverty : empirical evidence from Somalia. Cogent Food & Agriculture , 11 (1). https://doi.org/10.1080/23311932.2024.2445139 Bulut, E., & Mohamed, A. A. (2018). Remittances and Poverty Reduction in Somalia . 2 (3), 1–37. https://doi.org/10.25295/fsecon.2018.03.001 Chukwu, N. O., & Chukwu, J. O. (2025). Impact of household income diversification on household welfare . December . https://doi.org/10.1108/ECON-01-2023-0012 Dessie, Z. G., Zewotir, T., & North, D. (2022). The spatial modification effect of predictors on household level food insecurity in Ethiopia. Scientific Reports , 0123456789 , 1–11. https://doi.org/10.1038/s41598-022-23918-y Harris-fry, H., Shrestha, N., Costello, A., & Saville, N. M. (2017). Determinants of intra-household food allocation between adults in South Asia – a systematic review . 1–21. https://doi.org/10.1186/s12939-017-0603-1 Hillbruner, C., & Moloney, G. (2012). When early warning is not enough — Lessons learned from the 2011 Somalia Famine. Global Food Security , 1 (1), 20–28. https://doi.org/10.1016/j.gfs.2012.08.001 Li, M., Li, J., Id, H., & Nadeem, M. (2024). Agriculture land use transformation : A threat to sustainable food production systems , rural food security , and farmer well-being ? 1–20. https://doi.org/10.1371/journal.pone.0296332 Mabrouk, F., & Ã, M. M. M. (2018). Remittances and Food Security in African Countries . 30 (3), 252–263. https://doi.org/10.1111/1467-8268.12334 Mannan, K. A., & Farhana, K. M. (2023). Digital Financial Inclusion and Remittances : An Empirical Study on Bangladeshi Migrant Households . 680–697. Mohamed, A., & Enow, H. (2025). Evaluating the impact of remittance , FDI and export on economic growth of Somalia : an empirical analysis. Cogent Economics & Finance , 13 (1). https://doi.org/10.1080/23322039.2025.2593737 Mumin, F. I., Wesonga, F. D., Handuleh, J. I. M., White, R. G., & Mor, S. M. (2022). COVID ‑ 19 and its prevention in internally displaced person ( IDP ) camps in Somalia : impact on livelihood , food security and mental health. BMC Public Health , 1–14. https://doi.org/10.1186/s12889-022-14878-z Nasung, K., Antabe, R., Sano, Y., & Luginaah, I. (2019). Household Income Diversification and Food Insecurity in the Upper West Region of Ghana . 144 (2), 899–920. Omer, M. A. (2024). Climate variability and livelihood in Somaliland : a review of the impacts , gaps , and ways forward. Cogent Social Sciences , 10 (1). https://doi.org/10.1080/23311886.2023.2299108 Osman, A. A., & Abebe, G. K. (2023). Rural Displacement and Its Implications on Livelihoods and Food Insecurity : The Case of Inter-Riverine Communities in Somalia . Poblacion, A., Cook, J., Bovell, A., Sheward, R., Pasquariello, J., & Cutts, D. (2017). Can Food Insecurity Be Reduced in the United States by Improving SNAP , WIC , and the Community Eligibility Provision ? 9 (4), 435–455. https://doi.org/10.1002/wmh3.248 Sulemana, I., & Doabil, L. (2023). Migrant Remittances and Food Security in Sub- Saharan Africa : The Role of Income Classi fi cations . 57 (2), 681–706. https://doi.org/10.1177/01979183221107925 Szabo, S., & Szabo, S. (2016). Urbanisation and Food Insecurity Risks : Assessing the Role of Human Development Urbanisation and Food Insecurity Risks : Assessing the Role of Human Development. Oxford Development Studies , 44 (1), 28–48. https://doi.org/10.1080/13600818.2015.1067292 Tadele, H. (2020). Microfinance board and default risk in sub-Saharan Africa. African Journal of Economic and Management Studies , 12 (1), 1–17. https://doi.org/10.1108/AJEMS-01-2020-0040 Thanh, T., Bui, N., Thanh, T., Le, N., & Daly, K. J. (2015). PT SC. Emerging Markets Review . https://doi.org/10.1016/j.ememar.2015.10.001 Vargas-silva, C., & Vargas-silva, C. (2016). Remittances Sent To and From the Forcibly Displaced Remittances Sent To and From the Forcibly Displaced. The Journal of Development Studies , 00 (00), 1–14. https://doi.org/10.1080/00220388.2016.1234040 Warren, E., Hawkesworth, S., & Knai, C. (2015). Investigating the association between urban agriculture and food security , dietary diversity , and nutritional status : A systematic literature review. JOURNAL OF FOOD POLICY , 53 , 54–66. https://doi.org/10.1016/j.foodpol.2015.03.004 Warsame, A. A., Sheik-ali, I. A., Abdirahman, A., & Sarkodie, S. A. (2024). The nexus between climate change , conflicts and food security in Somalia : empirical evidence from time-varying Granger causality. Cogent Food & Agriculture , 10 (1). https://doi.org/10.1080/23311932.2024.2347713 Ye, W., Wang, Y., & Yang, X. (2022). Understanding Sustainable Livelihoods with a Framework Linking Livelihood Vulnerability and Resilience in the Semiarid Loess Plateau of China . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9110419","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":612480362,"identity":"67258576-fbd7-4a88-8dfd-bd7b71000729","order_by":0,"name":"Osman Abdulkadir Nor","email":"data:image/png;base64,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","orcid":"","institution":"Jamhuriya University of science \u0026 technology (JUST)","correspondingAuthor":true,"prefix":"","firstName":"Osman","middleName":"Abdulkadir","lastName":"Nor","suffix":""},{"id":612480363,"identity":"a0963255-00fb-4618-bcb9-5ee1bbc43bb3","order_by":1,"name":"Abas Omar Mohamed","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Abas","middleName":"Omar","lastName":"Mohamed","suffix":""}],"badges":[],"createdAt":"2026-03-13 05:23:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9110419/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9110419/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105582246,"identity":"5c3a6802-10c4-4e43-bdfc-fdc6a73e6c2f","added_by":"auto","created_at":"2026-03-27 14:48:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":49486,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe Prevalence of Food Insecurity in Somalia\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSource: Authors’ calculation using the Somalia Integrated Household Budget Survey data\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9110419/v1/9ba1b202701fb314d0f6b0ee.png"},{"id":105727947,"identity":"091a5f44-8a78-4693-8eee-60d252ecfbe7","added_by":"auto","created_at":"2026-03-30 11:06:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1113676,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9110419/v1/07642119-26e2-42b8-b7fc-897fb1234f20.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Household Income Diversification and Food Security in Somalia: Role of Urbanization, Displacement, and Household Size","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eHousehold income diversification is recognized as a critical adaptation strategy for improving food security in fragile contexts, where protracted conflict, recurrent droughts, and socio-political instability severely affect livelihoods (Waha et al., 2018; Etea et al., 2019; Liyew \u0026amp; Damtie, 2024; Atuoye et al., 2019). Food security comprises four key dimensions, availability, access, utilization, and stability, that collectively ensure sufficient and nutritious food for all individuals. (Clapp et al., 2022). Several household-specific, socioeconomic, and environmental factors play a crucial role in determining the effectiveness of income diversification as a strategy for improving food security. Urbanization shapes these dynamics by shifting livelihoods away from traditional subsistence agriculture toward wage labor and informal sector activities, while household size and displacement introduce additional vulnerabilities within resource-constrained urban environments (Gebresilassie et al., 2025; Abebe, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe history of Somalia\u0026rsquo;s food insecurity spans decades of conflict-induced displacement and drought, culminating in critical famines in 2011, 2026, and 2022, which highlighted glaring deficiencies in resilience and early warning systems (Osman \u0026amp; Abebe, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, preliminary observations of data collected from approximately 50,000 Somali households across 17 of the 18 Somali regions indicate dire food insecurity across all six indicators, affecting a significant portion of the population. Since then, urban migration has accelerated as displaced rural populations seek refuge and livelihood opportunities in cities like Mogadishu, contributing to rapidly expanding informal settlements that strain food systems (Hussein \u0026amp; Osman, 2024). The significance of this study lies in examining the interplay between remittances as a diversification strategy and demographic moderators shaping household food security outcomes in fragile, urbanizing, and displacement-affected contexts. As a critical household livelihood factor in Somalia, remittance inflows from the diaspora constitute one of the largest sources of household income and serve as crucial financial buffers, enabling families to secure diverse and nutritious food amid shocks and market disruptions (Hillbruner \u0026amp; Moloney, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSource: Authors\u0026rsquo; calculation using the Somalia Integrated Household Budget Survey data\u003c/p\u003e \u003cp\u003eThe study is grounded primarily in the Sustainable Livelihoods Framework (SLF), which emphasizes diversifying income sources to enhance household resilience by building and protecting livelihood assets in the face of shocks such as conflict or climate variability (Ye et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Within this paradigm, remittances serve as vital injections of financial capital that households leverage to stabilize consumption, access markets, and invest in food security (Subramaniam Y, 2022). Complementing SLF, household production theory informs the analysis of how intra-household demographics, including household size, affect resource allocation and the effective utilization of remittance income for food needs (Harris-Fry et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Larger households may face higher dependency burdens, thus moderating the direct benefits of income diversification (Tadele, 2021). Urbanization theory adds another layer by contextualizing the transitions from rural to urban livelihoods, highlighting both expanded job opportunities and increased cost-of-living burdens that influence food security outcomes (Abebe, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The integration of these theories provides a robust conceptual foundation to examine remittance-driven food security under the moderating influences of household size, urban residence, and displacement status.\u003c/p\u003e \u003cp\u003eExtensive literature confirms that income diversification positively correlates with food security by spreading risk and smoothing household consumption. Studies from Ghana and Ethiopia illustrate that diversification strategies, including off-farm work and remittances, improve household dietary diversity and calorie intake, directly enhancing nutrition and food stability (Akrasi et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Adem et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). A consensus emerges that diversification acts as a buffer against agricultural shocks, yet disagreements persist about the extent of benefits in fragile contexts, where limited market access, social exclusion, or displacement complicate the translation of income into food security (Nasung et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This variability underscores the need to consider moderating factors in the income-food security nexus. For instance, remittances have a significant positive impact on Somalia's total GDP(Mohamed \u0026amp; Enow, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). This indicates that remittances have a greater impact on Somalia's GDP than both foreign direct investment (FDI) and official development assistance (ODA). This demonstrates how important remittances are to the Somali people as an outside source of funding (Bulut \u0026amp; Mohamed, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This inflow not only reduces food insecurity by increasing household purchasing power but also facilitates access to previously unaffordable, diverse food items under subsistence conditions (Poblacion et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Yet, much of the literature tends to focus on direct effects without adequately considering moderating variables. For example, a larger household size can weaken per capita benefits from remittances, while urban living imposes higher expenditure pressures, thereby influencing the overall impact of remittance income on food security (Chukwu \u0026amp; Chukwu, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe urbanization and displacement literature further elaborates on the complexity. Rapid urbanization has been associated with improved livelihood diversification opportunities, allowing rural migrants and IDPs access to wage labor and informal trade (Adzande, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). However, these benefits are often offset by increased living costs, inadequate infrastructure, and food price volatility (Szabo \u0026amp; Szabo, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Displaced populations in Somalia, including roughly 3\u0026nbsp;million IDPs, face compounded food insecurity risks due to disrupted social networks, limited asset ownership, and dependency on humanitarian aid (Warsame et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Despite the growing body of research, methodological gaps persist, including insufficient longitudinal data, inconsistent incorporation of displacement and urbanization as moderating variables, and limited empirical studies focusing on Somalia\u0026rsquo;s distinctive, fragile setting.\u003c/p\u003e \u003cp\u003eExpanding on the literature, emerging studies emphasize the role of remittance mechanisms and financial inclusion in enhancing food security. Digital financial services and hawala networks facilitate remittance flows even during conflict, enabling continued support for household food access(Mannan \u0026amp; Farhana, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, challenges such as transfer costs and regulatory barriers limit the full utilization of remittances for food security gains. Furthermore, with increasing climate variability, the role of remittances as adaptive tools has garnered attention, where households use remitted funds to diversify food sources or invest in climate-resilient agricultural inputs (Omer, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Yet, this adaptive capacity is contingent on supportive social and policy environments, which are often weak in Somalia.\u003c/p\u003e \u003cp\u003eAdditional research highlights the differential impact of urbanization contexts. Urban poor and displaced groups often experience food insecurity despite remittance inflows due to heightened competition for resources, inadequate social protection, and food price inflation(Hussein \u0026amp; Osman, 2024). This underscores that the nexus of income diversification and food security cannot be universally applied without accounting for socio-demographic moderators such as household size and displacement status. Studies in other fragile contexts confirm these interactions, suggesting the need for nuanced policy targeting(Adem et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Hence, this study contributes by explicitly testing these moderating effects using recent Somali household data, bridging gaps in coverage, methodology, and context specificity.\u003c/p\u003e \u003cp\u003eSomalia suffers from persistent and severe food insecurity, even as remittances constitute a significant portion of household income. While the beneficial role of remittances in improving food security is well-acknowledged, critical inconsistencies remain regarding how factors such as urbanization, household size, and displacement status affect this relationship. Prior research typically isolates these variables rather than examining their interaction effects, leading to gaps in data coverage, particularly for displaced urban households. To address the limitations of the literature, this study aims to answer the following research questions. How does household income remittance influence food security in Somalia? How do household size, urbanization, and displacement status moderate this nexus?\u003c/p\u003e \u003cp\u003eAs a result, this study contributes to advancing theoretical understanding by integrating key socio-demographic moderators within the Sustainable Livelihoods Framework in a fragile, conflict-affected context. Empirically, it enriches the limited Somalia-specific evidence on the interactions between food security and income diversification, using recent and representative household survey data. The findings offer actionable insights for policymakers and humanitarian actors aiming to design targeted interventions to strengthen food security resilience, particularly for vulnerable displaced and large urban households. The rest of the paper is organized as follows: Section 2 outlines the methodology and data sources; Section 3 presents the empirical results; Section 4 discusses the theoretical and practical implications; and Section 5 concludes and offers economic policy recommendations for Somalia\u0026rsquo;s fiscal and public service reform initiatives.\u003c/p\u003e"},{"header":"2. METHODS AND MATERIALS","content":"\u003cp\u003eThis section provides empirical strategy, data, and variables of the study. Following Husein Duale (2018) and Boru and Dilla (2017), the study employed nonlinear probit and logit regression models to investigate Household income diversification and food insecurity in Somalia. This design was deemed appropriate given that the dependent variable, Food insecurity, is binary and measured through discrete categories. The approach facilitated an empirical analysis of how regular income, food aid, and remittances influence food insecurity, thereby moving beyond descriptive statistics to generate policy-relevant insights.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Data and Variables\u003c/h2\u003e \u003cp\u003eThe study uses the Somalia Integrated Household Budget Survey (SIHBS) dataset, obtained from the Somalia National Bureau of Statistics, which provides detailed data on 7212 Somali households. The data includes information on food insecurity, regular income, food aid, remittances, and other household variables. The household sample encompasses rural, nomadic, and urban areas, where communities are most vulnerable to cyclical Shocks, such as drought, conflict, and economic instability. The dataset also includes key household characteristic variables (e.g., sex, homeownership, IDP status and household size). The dependent variable in this study is measured using a binary indicator of food insecurity. It captures household food security status following the exposure to income-related shocks such as drought, conflict, or market disruptions. It categorizes households based on whether they experienced significant food-related shocks and related welfare impacts. More specifically, it is measured as an index of six food insecurity indicators, including: worrying about food, being unable to eat nutritious food, limiting food variety, skipping meals, eating less, and running out of food.\u003c/p\u003e \u003cp\u003eThe independent variables represent different sources of household income, including regular income and remittances received. The variable regular income indicates whether the household has a stable source of income, while food aid captures receipt of external food assistance. The variable remittance received indicates whether the household receives remittances as financial support. Additionally, the study controlled for other variables, such as food aid, home ownership, and sex. These independent and confounding variables work together to investigate how household coping mechanisms affect the impact of shocks, as indicated by food security outcomes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Empirical Model Specification\u003c/h2\u003e \u003cp\u003eThe empirical framework for the study was specified using three complementary models. First, the Linear Probability Model (LPM) was specified as follows:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$${FI}_{i}={\\beta}_{0}+{\\beta}_{1}{RI}_{i}+{\\beta}_{2}{FA}_{i}+{\\beta}_{3}{RR}_{i}+{\\beta}_{4}{X}_{i}+{E}_{i}\\left(1\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\text{F}\\text{I}}_{i}\\)\u003c/span\u003e\u003c/span\u003e is food insecurity, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({RI}_{i}is\\)\u003c/span\u003e\u003c/span\u003eregular income, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({FA}_{i}\\)\u003c/span\u003e\u003c/span\u003e is a food aid, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({RR}_{i}\\)\u003c/span\u003e\u003c/span\u003e: is remittance received, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({X}_{i}\\)\u003c/span\u003e\u003c/span\u003e for other control variables such as home ownership and sex. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({E}_{i}\\)\u003c/span\u003e\u003c/span\u003e: is the error term.\u003c/p\u003e \u003cp\u003eSecond, the Logit model was expressed as:\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$P\\left(FI=1\\right)=\\frac{\\text{exp}\\left({\\beta}_{0}+{\\beta}_{1}{RI}_{i}+{\\beta}_{2}{FA}_{i}+{\\beta}_{3}{RR}_{i}+{\\beta}_{4}{X}_{i}\\right)}{1+\\text{exp}\\left({\\beta}_{0}+{\\beta}_{1}{RI}_{i}+{\\beta}_{2}{FA}_{i}+{\\beta}_{3}{RR}_{i}\\right)}\\left(2\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv id=\"Equc\" class=\"Equation\"\u003e \u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e\n$$P\\left(FI=1\\right)={\\int}_{-\\infty}^{\\left({\\beta}_{0}+{\\beta}_{1}{RI}_{i}+{\\beta}_{2}{FA}_{i}+{\\beta}_{2}{RR}_{i}{+\\beta}_{4}{X}_{i}\\right)}\\varnothing\\left(z\\right)dz\\left(3\\right)$$\u003c/div\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003ewhere food insecurity impact is the outcome variable, measured as a binary variable using an index of 6 food insecurity indicators: worrying about food, being unable to eat nutritious food, limiting food variety, skipping meals, eating less, and running out of food. Income diversification is the main explanatory variable, including regular income, food aid, remittances, and household characteristics such as sex and home ownership. Beta represents the coefficients for each category of the dependent variable, and Phi represents the cumulative distribution function of the standard normal distribution in the probit model. The substantial interaction between remittances and displacement status suggests that displaced households gain less from remittances in terms of enhancing food security than non-displaced households do. Additionally, the interaction terms between remittances and urban or nomadic residence show that the relationship between remittances and food insecurity is moderated by location. The impact of income sources on food insecurity is also influenced by household size, suggesting that larger households might be less affected by income. These results generally confirm the significance of moderating factors in influencing food security outcomes.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. RESULTS","content":"\u003cp\u003eIn line with the study objectives, this section presents the study's results, which provide insight into the impact of regular income, food aid, remittances, and socio-demographic factors on food insecurity and how these dynamics vary across household characteristics. Moreover, the section provides the moderating effects of displacement, urbanization, and household size on the income-food insecurity nexus. Finally, provide a qualitative interpretation of the results. The section concludes with the marginal effects and odds ratios results.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Basic Results\u003c/h2\u003e \u003cp\u003eThe first results provided in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e present the basic findings on the impact of regular income, food aid, and remittances on food insecurity, using multiple regression models (LPM, Probit, and Logit). The results show that regular income and food aid are significantly negatively associated with food insecurity, indicating that they help reduce it. Specifically, the coefficients for regular income range from \u0026minus;\u0026thinsp;0.083 (LPM) to -0.435 (Logit), and for food aid from \u0026minus;\u0026thinsp;0.044 (LPM) to -0.213 (Logit), all statistically significant at the 1% level. Conversely, remittances, with coefficients ranging from 0.085 (LPM) to 0.456 (Logit), show a positive relationship with food insecurity, suggesting that remittances worsen food security, possibly due to over-reliance on external income sources rather than sustainable local strategies. Additionally, household size and location also significantly affect food security, with larger households and those located in rural or nomadic settings facing greater food insecurity. These findings underscore the critical role of income diversification in improving food security, but also highlight the need for further investigation into factors like location and household composition.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBasic Results\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDependent Variable:\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eFood Insecurity\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLPM Model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProbit Model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLogit Model\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegular income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.083***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.255***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.435***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.062)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.105)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFood aid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.044***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.127***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.213***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.009)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.026)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.045)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRemittances Received\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.085***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.265***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.456***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.019)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.058)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.099)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIDP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.283***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.77***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.261***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.025)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.072)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.118)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural location\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.029*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.099*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.147*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.017)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.052)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.087)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNomadic location\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.125***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.359***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.59***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.025)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.073)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.121)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHousehold size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.072***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.221***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.369***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.021)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.065)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.108)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHome ownership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.002***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.006***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.01***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e_cons\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.167**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.986***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.631***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.071)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.218)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.365)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3270\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR-squared\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0802\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePseudo R\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.064\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eStandard errors are in parentheses\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cem\u003e*** p\u0026lt;.01, ** p\u0026lt;.05, * p\u0026lt;.1\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Displacement Moderating Effects on the Remittance-Food Insecurity Nexus\u003c/h2\u003e \u003cp\u003eBuilding on the findings in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the results in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e further explore how displacement moderates the relationship between remittances and food insecurity. The interaction term between remittances and displacement (IDP) is significant and negative, with coefficients ranging from \u0026minus;\u0026thinsp;0.158 (LPM) to -0.696 (Logit), suggesting that displaced households benefit less from remittances in terms of food security compared to non-displaced households. This reinforces the idea that displaced persons face compounded vulnerabilities, which may prevent remittances from improving food security as effectively as in stable household contexts. In addition to this interaction, household size and rural location remain significant predictors of food insecurity. These results highlight the need for targeted interventions that consider displacement status and the specific challenges faced by displaced households, such as disrupted social networks and limited access to resources.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDisplacement Moderating Effects on Remittance-Food Security Nexus\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDependent Variable:\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eFood Insecurity\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLPM Model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProbit Model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLogit Model\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegular income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.083***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.255***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.432***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.062)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.105)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFood aid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.043***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.125***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.209***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.009)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.026)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.045)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRemittances\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.229***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.646***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.072***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.021)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.066)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.111)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRemittances*IDP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.158***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.426***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.696***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.013)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.039)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.064)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1bn.location1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.032*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.109**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.166*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.017)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.052)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.087)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3.location1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.127***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.365***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.603***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.025)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.073)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.121)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHousehold size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.07***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.212***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.356***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.021)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.065)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.108)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHome ownership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.002***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.006***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.01***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e_cons\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.19***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.907***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.49***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.217)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.364)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3270\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR-squared\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0832\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePseudo R\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.065\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eStandard errors are in parentheses\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cem\u003e*** p\u0026lt;.01, ** p\u0026lt;.05, * p\u0026lt;.1\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Urbanization Moderating Effects on the Remittance-Food Security Nexus\u003c/h2\u003e \u003cp\u003eThe next results presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e extend the analysis by examining how urbanization moderates the effect of remittances on food security. While remittances remain positively correlated with food insecurity across all models, the interaction terms between remittances and urban or nomadic locations are important. For households in rural or nomadic areas, the coefficients for remittance interaction terms are significantly positive (0.073 in LPM to 0.334 in Logit), indicating that these households benefit more from remittances than urban households. Urban households, potentially facing higher living costs and greater competition for resources, experience a smaller positive effect of remittances on food security. The findings in this table emphasize the importance of accounting for urbanization when assessing the impact of remittances, as the dynamics in urban and rural areas differ significantly. This section suggests that while remittances are a critical factor in food security, their effectiveness is moderated by the urban context, where higher living costs might limit their positive impact.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUrbanization Moderating Effects on Remittance-Food Security Nexus\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDependent Variable:\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eFood Insecurity\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLPM Model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProbit Model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLogit Model\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegular income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.083***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.255***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.435***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.062)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.105)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFood aid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.044***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.128***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.214***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.009)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.026)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.045)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRemittance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.072***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.223***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.389***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.019)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.061)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.103)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRemittance*Rural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.067\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.009)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.029)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.048)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRemittance*Nomadic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.073***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.204***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.334***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.014)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.039)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.065)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1bn.IDP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.283***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.771***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.263***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.025)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.072)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.118)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLnhhsize\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.072***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.222***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.37***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.021)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.065)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.108)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHome_ownership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.002***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.007***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.011***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e_cons\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.19***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.907***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.499***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.214)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.359)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3270\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR-squared\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0813\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePseudo R\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.064\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eStandard errors are in parentheses\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cem\u003e*** p\u0026lt;.01, ** p\u0026lt;.05, * p\u0026lt;.1\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Household Size Moderating Effects on Income-Food Security Nexus\u003c/h2\u003e \u003cp\u003eFurthermore, the analysis provided in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e explores how household size influences the relationship between income sources and food insecurity. The interaction term between income and household size is significant, with coefficients ranging from 0.039 (LPM) to 0.229 (Logit), indicating that larger households benefit less from regular income in terms of food security. This likely occurs because higher dependency ratios in larger households mean the same amount of income is spread more thinly across a greater number of dependents, reducing its overall impact on food security. These results underscore the need to consider household composition when designing food security interventions, as larger households may require additional support to achieve food security levels comparable to those of smaller households.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHousehold Size Moderating Effects on Income-Food Security Nexus\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDependent Variable:\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eFood Insecurity\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLPM Model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProbit Model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLogit Model\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegular income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.361***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.206***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.119***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.201)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.358)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncome*HHsize\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.039***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.131***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.229***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.008)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.026)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.046)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFood aid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.042***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.123***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.204***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.009)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.026)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.045)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRemittance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.079***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.245***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.429***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.019)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.058)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.099)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIDP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.266***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.722***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.176***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.025)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.072)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.119)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural location1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.098*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.148*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.017)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.052)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.087)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNomadic location1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.116***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.334***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.549***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.025)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.072)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.119)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHome ownership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.002***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.006***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.01***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e_cons\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.317***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.523***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.881***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.057)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.174)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(.297)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3270\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR-squared\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0833\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePseudo R\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.067\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eStandard errors are in parentheses\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cem\u003e*** p\u0026lt;.01, ** p\u0026lt;.05, * p\u0026lt;.1\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Marginal Effects and Odds Ratio Results\u003c/h2\u003e \u003cp\u003eFinally, Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e provides a detailed analysis through marginal effects and odds ratios, offering a quantifiable assessment of the strength of the relationships between various income sources and food insecurity. The marginal effects confirm that remittances have a significant positive effect on food insecurity (0.496), indicating they are associated with greater food insecurity in the study population. Similarly, regular income and food aid have negative effects on food insecurity, with significant odds ratios showing their beneficial impact. Household size continues to have a significant moderating effect, with larger households facing higher food insecurity, even when accounting for income diversification strategies. These results reinforce previous findings, emphasizing the crucial role of remittances in food insecurity and highlighting the need for more nuanced approaches that account for household size and location to ensure the effectiveness of income diversification strategies in enhancing food security.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMarginal Effects and Odds Ratio Results\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDependent Variable:\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eFood Insecurity\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eMarginal Effects Model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eOdds Ratio Model\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(4)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegular income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.081**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.435***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.0894***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.0918***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.064)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.105)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.0216)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.0221)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFood aid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.239***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.213***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.0444***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.0449***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.045)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.00924)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.00938)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRemittance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.496***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.456***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0926***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0961***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.068)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.099)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.0202)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.0208)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1bn.IDP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.261***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.293***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.297***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.118)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.0278)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.0282)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural location\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.147*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0340*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0302*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.087)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.0178)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.0179)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNomad location\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.59***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.131***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.131***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.121)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.0273)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.0280)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHHsize\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.369***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0772***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0778***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.108)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.0227)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.0227)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHome ownership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.01***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00226***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.00221***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.000319)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.000313)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e_cons\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.631***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(.196)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(.365)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6348\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,270\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePseudo R\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eStandard errors are in parentheses\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003e*** p\u0026lt;.01, ** p\u0026lt;.05, * p\u0026lt;.1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003eThe study findings reveal that while regular income and food aid significantly reduce food insecurity, remittances, in isolation, worsen food security, possibly due to an over-reliance on external income sources. Household size, location, and displacement status are also critical factors in shaping food security outcomes. Displaced households, for instance, benefit less from remittances, and urban households experience fewer advantages from them than rural households. These findings underscore the complex interplay between income sources and socio-demographic factors in fragile contexts such as Somalia. Collectively, these findings suggest that while remittances and income diversification strategies have the potential to improve food security, their effectiveness is significantly influenced by household characteristics, including size, location, and displacement status. These findings underscore the importance of developing targeted food security interventions that account for these moderating factors to more effectively address food insecurity in Somalia.\u003c/p\u003e \u003cp\u003eThe study contributes to the theoretical understanding of food security in the context of income diversification, particularly in fragile settings. The Sustainable Livelihoods Framework (SLF), which emphasizes the importance of diversified income sources, aligns with findings that regular income and food aid improve food security by stabilizing consumption and expanding access to markets. However, the negative relationship between remittances and food security challenges some assumptions within SLF, particularly the adequacy of remittances as a sole strategy for household resilience. Urbanization Theory also supports the study\u0026rsquo;s findings, suggesting that urbanization complicates the benefits of remittances by increasing living costs and competition for resources. These theoretical frameworks help explain the contradictory effects of income diversification on food security, especially in contexts marked by urbanization, displacement, and large household sizes.\u003c/p\u003e \u003cp\u003eStudies such as (Mabrouk \u0026amp; \u0026Atilde;, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) Support the idea that income diversification, including remittances, benefits food security. However, other studies (Vargas-silva \u0026amp; Vargas-silva, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), (Thanh et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2015\u003c/span\u003e)Emphasize that the benefits of remittances depend on contextual factors, such as household size and displacement status. These contradictions highlight the need for detailed theoretical models that better account for socio-demographic factors. This study makes a significant contribution by incorporating these moderating factors into the analysis.\u003c/p\u003e \u003cp\u003eThe empirical contribution of this study is important as it provides context-specific insights into the relationship between income diversification and food security in Somalia. The results support the well-established notion that regular income and food aid improve food security, as seen in other contexts, such as Ghana and Ethiopia (Akrasi et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, the finding that remittances worsen food security in Somalia is a novel and crucial contribution, challenging much of the existing literature that treats remittances as an unmitigated benefit for food security(Ali et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). This suggests that remittances may not always lead to improved food security in fragile, conflict-affected environments, as highlighted by other studies (Abdulle et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Additionally, the moderating effects of household size, urbanization, and displacement status reinforce previous research findings that these socio-demographic factors significantly impact food security (Li et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEmpirical studies by Sulemana and Doabil (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and Dessie et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) demonstrate that remittances, when combined with other livelihood strategies, can support food security. However, this study suggests that relying solely on remittances may be inadequate. Displacement, in particular, weakens the impact of remittances on food security, consistent with research on IDPs in Somalia (Mumin et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The study\u0026rsquo;s findings on urbanization further confirm other regional studies, which indicate that urban poor communities experience greater food insecurity despite income diversification(Warren et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). These results call for policies that take local context into account when evaluating the role of remittances in food security.\u003c/p\u003e \u003cp\u003eWhile this study provides valuable insights into the moderating effects of household size, urbanization, and displacement on income diversification and food security in Somalia, several limitations exist. First, the study relies on cross-sectional data from the Somalia Integrated Household Budget Survey (SIHBS), which limits the ability to make causal inferences. Longitudinal studies could provide more robust evidence on how changes in income sources and household characteristics impact food security over time. Second, the study does not consider other potential income sources, such as remittances from international humanitarian organizations, which may also influence food security. Future research could explore the role of digital financial services, particularly mobile money, in facilitating remittance flows and improving food security. Finally, this study focuses solely on Somalia, and while the findings provide valuable insights, they may not be fully generalizable to other conflict-affected or urbanizing regions. Expanding the study to other countries facing similar challenges would strengthen the empirical evidence on income diversification and food security in fragile settings.\u003c/p\u003e"},{"header":"5. CONCLUSION","content":"\u003cp\u003eThis study analyzes the role of income diversification in improving food security in Somalia, emphasizing the moderating effects of urbanization, displacement, and household size. The findings suggest that regular income and food aid significantly reduce food insecurity, but remittances may worsen food security in Somalia due to over-reliance on external income sources. Additionally, household characteristics, including size, location, and displacement status, play a critical role in determining the effectiveness of income diversification strategies. The study results constitute practical policy recommendations for food security. First, policies should focus on enhancing remittance utilization by reducing costs and barriers, especially in rural and displaced communities, to ensure more efficient transfers. Second, targeted interventions should support rural and nomadic households by improving access to food and income diversification strategies. Third, humanitarian organizations must prioritize direct food aid to address food insecurity, particularly in displacement settings. Fourth, promoting local livelihoods through small-scale agriculture and informal-sector work can reduce dependence on remittances. Fifth, policies in urban areas should focus on improving food security through subsidies, infrastructure improvements, and price stabilization mechanisms. Sixth, displacement-targeted programs should be strengthened to address the specific needs of displaced persons, particularly in terms of food security. Finally, enhancing financial inclusion through mobile money access and expanding social protection programs will help vulnerable households, especially in urban and displaced settings, better manage food security challenges.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eConflict of Interest:\u003c/strong\u003e \u003cp\u003eThe authors declare that they have no financial or non-financial conflicts of interest to disclose.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eNo funding was received for this study.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors contributed to the study\u0026rsquo;s conception and the design of the conceptual framework. Osman Abdulkadir Nor carried out the introduction section, empirical specifications, data analysis, interpretation and discussion section although Abas Omar Mohamed was supervising all task of the article specially data analysis and methodology section .All authors participated in the manuscript review, with final editing and proofreading completed by Osman Abdulkadir Nor.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe study employed the Somalia Integrated Household Budget Survey (SIHBS) dataset sourced from the Somalia National Bureau of Statistics (https://microdata.nbs.gov.so/index.php/catalog/59).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbebe, M. G. (2024). Impacts of urbanization on food security in Ethiopia . A review with empirical evidence. Journal of Agriculture and Food Research, 15(January), 100997. https://doi.org/10.1016/j.jafr.2024.100997\u003cu\u003e.\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eAbdulle, A. S., Majid, A., Ibey, Y., Mohamed, A. A., \u0026amp; Omar, M. M. (2025). The impact of trade openness on private consumption in a heavily import-dependent country. \u003cem\u003eCogent Economics \u0026amp; Finance\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e(1). \u003cu\u003ehttps://doi.org/10.1080/23322039.2025.2566950\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eAbebe, M. G. (2024). Impacts of urbanization on food security in Ethiopia . A review with empirical evidence. \u003cem\u003eJournal of Agriculture and Food Research\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e(January), 100997. \u003cu\u003ehttps://doi.org/10.1016/j.jafr.2024.100997\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eAdem, M., Tadele, E., \u0026amp; Mossie, H. (2018). Income diversification and food security situation in Ethiopia : A review study Income diversification and food security situation in Ethiopia : A review study. \u003cem\u003eCogent Food \u0026amp; Agriculture\u003c/em\u003e, \u003cem\u003e4\u003c/em\u003e(1), 1\u0026ndash;17. \u003cu\u003ehttps://doi.org/10.1080/23311932.2018.1513354\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eAdzande, P. (2025). \u003cem\u003eDeveloping pathways for self-reliance : urban IDPs and the negotiation of livelihood opportunities in Makurdi , Nigeria\u003c/em\u003e. \u003cem\u003eXX\u003c/em\u003e(Xx), 226\u0026ndash;243. \u003cu\u003ehttps://doi.org/10.1177/09562478251317988\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eAkrasi, R. O., Eddico, P. N., \u0026amp; Adarkwah, R. (2020). \u003cem\u003eIncome Diversification Strategies and Household Food Security among Rice Farmers : Pointers to Note in the North Tongu District of Ghana\u003c/em\u003e. \u003cem\u003e8\u003c/em\u003e(3), 77\u0026ndash;88. \u003cu\u003ehttps://doi.org/10.12691/jfs-8-3-1\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eAli, D. A., Mohamed, N. A., \u0026amp; Ismail, A. I. (2025). Modelling the determinants of rural household poverty : empirical evidence from Somalia. \u003cem\u003eCogent Food \u0026amp; Agriculture\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(1). \u003cu\u003ehttps://doi.org/10.1080/23311932.2024.2445139\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eBulut, E., \u0026amp; Mohamed, A. A. (2018). \u003cem\u003eRemittances and Poverty Reduction in Somalia\u003c/em\u003e. \u003cem\u003e2\u003c/em\u003e(3), 1\u0026ndash;37. \u003cu\u003ehttps://doi.org/10.25295/fsecon.2018.03.001\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eChukwu, N. O., \u0026amp; Chukwu, J. O. (2025). \u003cem\u003eImpact of household income diversification on household welfare\u003c/em\u003e. \u003cem\u003eDecember\u003c/em\u003e. \u003cu\u003ehttps://doi.org/10.1108/ECON-01-2023-0012\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eDessie, Z. G., Zewotir, T., \u0026amp; North, D. (2022). The spatial modification effect of predictors on household level food insecurity in Ethiopia. \u003cem\u003eScientific Reports\u003c/em\u003e, \u003cem\u003e0123456789\u003c/em\u003e, 1\u0026ndash;11. \u003cu\u003ehttps://doi.org/10.1038/s41598-022-23918-y\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eHarris-fry, H., Shrestha, N., Costello, A., \u0026amp; Saville, N. M. (2017). \u003cem\u003eDeterminants of intra-household food allocation between adults in South Asia \u0026ndash; a systematic review\u003c/em\u003e. 1\u0026ndash;21.\u003cu\u003e https://doi.org/10.1186/s12939-017-0603-1\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eHillbruner, C., \u0026amp; Moloney, G. (2012). When early warning is not enough \u0026mdash; Lessons learned from the 2011 Somalia Famine. \u003cem\u003eGlobal Food Security\u003c/em\u003e, \u003cem\u003e1\u003c/em\u003e(1), 20\u0026ndash;28. \u003cu\u003ehttps://doi.org/10.1016/j.gfs.2012.08.001\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eLi, M., Li, J., Id, H., \u0026amp; Nadeem, M. (2024). \u003cem\u003eAgriculture land use transformation : A threat to sustainable food production systems , rural food security , and farmer well-being ?\u003c/em\u003e 1\u0026ndash;20.\u003cu\u003e https://doi.org/10.1371/journal.pone.0296332\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eMabrouk, F., \u0026amp; \u0026Atilde;, M. M. M. (2018). \u003cem\u003eRemittances and Food Security in African Countries\u003c/em\u003e. \u003cem\u003e30\u003c/em\u003e(3), 252\u0026ndash;263. \u003cu\u003ehttps://doi.org/10.1111/1467-8268.12334\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eMannan, K. A., \u0026amp; Farhana, K. M. (2023). \u003cem\u003eDigital Financial Inclusion and Remittances : An Empirical Study on Bangladeshi Migrant Households\u003c/em\u003e. 680\u0026ndash;697.\u003c/li\u003e\n\u003cli\u003eMohamed, A., \u0026amp; Enow, H. (2025). Evaluating the impact of remittance , FDI and export on economic growth of Somalia : an empirical analysis. \u003cem\u003eCogent Economics \u0026amp; Finance\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e(1). \u003cu\u003ehttps://doi.org/10.1080/23322039.2025.2593737\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eMumin, F. I., Wesonga, F. D., Handuleh, J. I. M., White, R. G., \u0026amp; Mor, S. M. (2022). COVID ‑ 19 and its prevention in internally displaced person ( IDP ) camps in Somalia : impact on livelihood , food security and mental health. \u003cem\u003eBMC Public Health\u003c/em\u003e, 1\u0026ndash;14. \u003cu\u003ehttps://doi.org/10.1186/s12889-022-14878-z\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eNasung, K., Antabe, R., Sano, Y., \u0026amp; Luginaah, I. (2019). \u003cem\u003eHousehold Income Diversification and Food Insecurity in the Upper West Region of Ghana\u003c/em\u003e. \u003cem\u003e144\u003c/em\u003e(2), 899\u0026ndash;920.\u003c/li\u003e\n\u003cli\u003eOmer, M. A. (2024). Climate variability and livelihood in Somaliland : a review of the impacts , gaps , and ways forward. \u003cem\u003eCogent Social Sciences\u003c/em\u003e, \u003cem\u003e10\u003c/em\u003e(1). \u003cu\u003ehttps://doi.org/10.1080/23311886.2023.2299108\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eOsman, A. A., \u0026amp; Abebe, G. K. (2023). \u003cem\u003eRural Displacement and Its Implications on Livelihoods and Food Insecurity : The Case of Inter-Riverine Communities in Somalia\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003ePoblacion, A., Cook, J., Bovell, A., Sheward, R., Pasquariello, J., \u0026amp; Cutts, D. (2017). \u003cem\u003eCan Food Insecurity Be Reduced in the United States by Improving SNAP , WIC , and the Community Eligibility Provision ?\u003c/em\u003e \u003cem\u003e9\u003c/em\u003e(4), 435\u0026ndash;455. \u003cu\u003ehttps://doi.org/10.1002/wmh3.248\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eSulemana, I., \u0026amp; Doabil, L. (2023). \u003cem\u003eMigrant Remittances and Food Security in Sub- Saharan Africa : The Role of Income Classi fi cations\u003c/em\u003e. \u003cem\u003e57\u003c/em\u003e(2), 681\u0026ndash;706. \u003cu\u003ehttps://doi.org/10.1177/01979183221107925\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eSzabo, S., \u0026amp; Szabo, S. (2016). Urbanisation and Food Insecurity Risks : Assessing the Role of Human Development Urbanisation and Food Insecurity Risks : Assessing the Role of Human Development. \u003cem\u003eOxford Development Studies\u003c/em\u003e, \u003cem\u003e44\u003c/em\u003e(1), 28\u0026ndash;48. \u003cu\u003ehttps://doi.org/10.1080/13600818.2015.1067292\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eTadele, H. (2020). Microfinance board and default risk in sub-Saharan Africa. \u003cem\u003eAfrican Journal of Economic and Management Studies\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(1), 1\u0026ndash;17. \u003cu\u003ehttps://doi.org/10.1108/AJEMS-01-2020-0040\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eThanh, T., Bui, N., Thanh, T., Le, N., \u0026amp; Daly, K. J. (2015). PT SC. \u003cem\u003eEmerging Markets Review\u003c/em\u003e. \u003cu\u003ehttps://doi.org/10.1016/j.ememar.2015.10.001\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eVargas-silva, C., \u0026amp; Vargas-silva, C. (2016). Remittances Sent To and From the Forcibly Displaced Remittances Sent To and From the Forcibly Displaced. \u003cem\u003eThe Journal of Development Studies\u003c/em\u003e, \u003cem\u003e00\u003c/em\u003e(00), 1\u0026ndash;14. \u003cu\u003ehttps://doi.org/10.1080/00220388.2016.1234040\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eWarren, E., Hawkesworth, S., \u0026amp; Knai, C. (2015). Investigating the association between urban agriculture and food security , dietary diversity , and nutritional status : A systematic literature review. \u003cem\u003eJOURNAL OF FOOD POLICY\u003c/em\u003e, \u003cem\u003e53\u003c/em\u003e, 54\u0026ndash;66. \u003cu\u003ehttps://doi.org/10.1016/j.foodpol.2015.03.004\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eWarsame, A. A., Sheik-ali, I. A., Abdirahman, A., \u0026amp; Sarkodie, S. A. (2024). The nexus between climate change , conflicts and food security in Somalia : empirical evidence from time-varying Granger causality. \u003cem\u003eCogent Food \u0026amp; Agriculture\u003c/em\u003e, \u003cem\u003e10\u003c/em\u003e(1).\u003cu\u003e https://doi.org/10.1080/23311932.2024.2347713\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eYe, W., Wang, Y., \u0026amp; Yang, X. (2022). \u003cem\u003eUnderstanding Sustainable Livelihoods with a Framework Linking Livelihood Vulnerability and Resilience in the Semiarid Loess Plateau of China\u003c/em\u003e.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Income Diversification, Food Security, Urbanization, Remittances, Somalia","lastPublishedDoi":"10.21203/rs.3.rs-9110419/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9110419/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHousehold well-being and sustainable development depend on food security, but in fragile regions such as Somalia, urbanization, violence, displacement, and climate change continue to affect households. Although income diversification, particularly through regular income, food assistance and remittances, is widely recognized as resilience strategy, existing research frequently overlooks its effectiveness due to regional and demographic factors. This study closes this gap by examining how household size, place of residence, and displacement status affect the relationship between food insecurity and income diversification using the Sustainable Livelihoods Framework and Urbanization Theory. Using nationally representative data from the Somalia Integrated Household Budget Survey, the study estimates linear probability, logit, and probit models to assess the risk of food insecurity across different income sources. According to the research, regular income and food assistance significantly reduce food insecurity, but remittances alone do not consistently improve food outcomes. Additionally, there is notable heterogeneity in effectiveness, as diversification strategies vary across internally displaced households, larger families, and urban dwellers. Overall, the results indicate that, to improve food security in Somalia in a sustainable way, income-based interventions alone will not be sufficient; context-sensitive livelihood policies and targeted social protection are also required.\u003c/p\u003e","manuscriptTitle":"Household Income Diversification and Food Security in Somalia: Role of Urbanization, Displacement, and Household Size","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-27 14:48:28","doi":"10.21203/rs.3.rs-9110419/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":"6b533b3c-01da-4609-a0c6-78436e691725","owner":[],"postedDate":"March 27th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-27T14:48:28+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-27 14:48:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9110419","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9110419","identity":"rs-9110419","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}