Assessing Agribusiness as an Investment Choice for Return Migrants in Rural Nepal

Assessing Agribusiness as an Investment Choice for Return Migrants in Rural Nepal | 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 Article Assessing Agribusiness as an Investment Choice for Return Migrants in Rural Nepal Bipin Khanal, Tsuyoshi Sumita, Eustadius Francis Magezi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9024066/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract In the context of globalization, while Nepal has benefited from foreign labor markets, it also faces challenges regarding the investment decisions of returning migrant workers after their return. This study examines household investment in agribusiness and livelihood diversification in rural Nepal using multinomial logit estimates based on data across eight districts from two provinces. The results indicate that return migrants strongly drive agribusiness investment, either exclusively or in combination with other businesses, whereas households with members currently abroad, although engaged in agribusiness, are more inclined toward non-agribusiness activities or no investment at all. This suggests that remittances are not properly reinvested in agribusiness, highlighting that remittances are mostly used for consumption purposes, and households with migrant members are better off without investing in agribusiness, thereby challenging assumptions that migration stimulates rural entrepreneurship. However, household education and networks promote diversification in businesses significantly, while agriculture-specific skills support sole agribusiness investment. Further, more active members, with greater labour force availability, are more likely to diversify through non-farm activities, and individually managed farms also diversify to reduce risks. In contrast, female-headed households are reluctant to invest in agribusiness despite being active in subsistence agriculture. In this context, policies should encourage returnee engagement in agribusiness, improve rural infrastructure, strengthen market linkages, and expand financial access to foster diversification and resilience in rural economies. Business and commerce/Economics Social science/Economics Earth and environmental sciences/Environmental social sciences Diversification Entrepreneurship Social-Networks Non-farm Activities Figures Figure 1 1. Introduction Countries benefit from integrated labor markets, and Nepal is no exception, as the economy becomes increasingly interconnected; however, a key challenge lies in the livelihood strategies of returning migrants. Return migrants often face difficulties in identifying suitable investment choices due to unfamiliarity with the domestic economic environment after their return, despite having accumulated resources from abroad, such as financial capital, knowledge, and skills. Business activities and entrepreneurial decisions are shaped by these resources, along with household characteristics such as education, age, and prior experience (González-Leonardo et al. 2022 ; Wei & Zhu 2020 ; Yin et al. 2021 ). Nevertheless, return-migrant entrepreneurship is not automatic and depends on institutional support, access to finance, and an enabling local environment (Naudé et al. 2015 ; Silva et al. 2023 ; Sinatti 2022 ; Zhou et al. 2024 ). In the Nepalese context, foreign employment is viewed as lucrative, leading many to abandon agriculture as a mainstay in favor of working abroad, especially for newer generations (Agrawal 2021 ), and the absentee population is about 2.3 million, highlighting the current situation of the country (NSO 2021). The country’s socio-economic environment is deeply influenced by factors related to labor migration, particularly encouraging individuals from low and middle-income households to migrate abroad, and these influencing factors are a lack of employment opportunities, socioeconomic inequalities, poor education systems, and a desire for better income and living standards (Adhikari et al. 2023 ). Foreign opportunities serve as a necessary evil with positive impacts on food security, though people are encouraged to seek foreign work due to low agricultural incomes and land fragmentation (Timilsina et al. 2019 ). Labor migration in Nepal is a continuous and dynamic process; some permanently leave the country in search of better opportunities, but others return with newly acquired skills and capital. These returnees have the potential to channelize local resources into rural entrepreneurial activities to create jobs and revive the rural economy through a favorable business environment (Devkota 2016 ). Entrepreneurship developed by returnees is vital for rural development, which includes employment generation, income diversification, poverty reduction, and agricultural production, particularly with agribusiness activities (Bao et al. 2022 ; Liu and Qiao 2025 ; Miao et al. 2021 ; Naminse et al. 2018 ). Several scholars show that return migrants are more likely to engage in entrepreneurship than non-migrants due to the financial capital, skills, and experience accumulated abroad (Batista et al. 2017 ; Lara et al. 2021 ; Silva et al. 2023 ). Further, remittances and agricultural productivity show a positive association, possibly through agricultural investment, and remittances serve as a key resource for investment (Kapre and Ghimire 2020). However, a study by Maharajan et al. (2012) explicitly stated that migration did not help to move subsistence agriculture into commercial agriculture. Fragmented policies and weak institutional support, especially in countries lacking dedicated reintegration institutions, can shrink the possible developmental impact of returnee entrepreneurship despite their potential to become entrepreneurs (Riaño 2023 ; Spitzer and Piper 2014 ). Though Poudel and Poudel (2022) have studied the returnees' engagement in agriculture, it did not specifically indicate the engagement in agriculture as business or subsistence oriented. Further, Carter and Khadka ( 2021 ) found that agriculture in the mid-hills has been revived through innovation, especially adopted by returnee migrants. Our study aims to assess whether households with returnees are more likely to invest in local business activities, including agribusiness, compared to households without returnees. It further examines business strategies developed by different households, whether returnee households differ from migrant households (with members currently abroad) in their investment behaviour, including whether they engage exclusively in agribusiness or combine it with other forms of business as part of a broader diversification strategy. Despite studies on migration and agriculture being conducted by several scholars; comprehensive analysis of returnee investment in agribusiness compared to non-returnee and migrants is lacking. Specifically, this study has three main objectives. First, it assesses whether returnee households are more likely to invest in local enterprises, including agribusiness, than non-returnee households. Second, it examines the extent to which households with family members currently abroad are inclined to invest in agribusiness. Third, based on these findings, the study provides conclusive evidence-based policy insights by identifying which household categories contribute most significantly to agribusiness, and by emphasizing the need for supportive measures such as improved access to direct or indirect financial assistance in order to promote and sustain agribusiness development across household types. 2. Literature Review A study by Silva et al. ( 2023 ) discovered that the probability of entrepreneurship among returnee migrants is high and suggested that there is an increasing chance of mobilizing their accumulated resources by migrants after returning to the home country. It also emphasized that when personal preferences align with a supportive local environment, returnees are engaging capital in entrepreneurial activities; however, not all return migrants are interested in becoming entrepreneurs (Naudé et al. 2015 ). Due to the capital and skills acquired abroad, there is a positive correlation between return migrants and involvement in entrepreneurial activities (Lara et al. 2021 ), and migrants workers with support from their families, communities, and government are encouraged often to pool their savings and engage in entrepreneurial activities, and this is the evidence from the Philippines, where the National Reintegration Centre provides seminars to migrant workers and their families to encourage entrepreneurship (Spitzer and Piper 2014 ). However, in Nepal, there is no specialized body dedicated to supporting returnee migrants. Instead, various ministries and local government programs have incorporated certain support measures for returnee migrants. Entrepreneurship is an important basis of economic development, and rural migrants returning home to start businesses can promote employment, alleviate poverty, and drive rural economic transformation (Bao et al. 2022 ). The participation of farmers in commercial activities has been gradually increasing, and they are now considered an important part of the entrepreneurial community (Miao et al. 2021 ). This not only helps increase farmers’ income but also invigorates the rural economy through job creation and poverty reduction (Naminse et al. 2018 ). Liu and Qiao ( 2025 ) found that return migrants have a positive impact on increasing agricultural productivity, especially for voluntary return. Migration itself generates social and economic benefits for both home and host countries (Hausmann and Nedelkoska 2018 ). Studies have also shown that returnees’ investment decisions and entrepreneurial dynamics strongly influence their occupational choices, and also reveal a higher probability of entrepreneurship among return migrants compared to non-migrants (Batista et al. 2017 ). Further, returnees can serve as catalysts to foster rural entrepreneurship; they need financial support and targeted education (Zhou et al. 2024 ). A study by Yin et al. ( 2021 ) underlined that investment decisions are influenced by education and past work experience; similarly, Wei and Zhu ( 2020 ) found that migrants’ work experiences and household attributes significantly affect entrepreneurial choices. Further, migrants’ own experiences, social determinants, and government support are crucial for successful entrepreneurship development after their return (Sinatti 2022 ). Moreover, individual characteristics such as age, gender, and education also significantly influence entrepreneurial outcomes (Syafitri et al. 2024 ). Key factors identified by González-Leonardo et al. ( 2022 ) that are shaping the role of returnees in revitalizing rural economies include human capital and financial resources. Institutional arrangements, infrastructure, and facilities are key pull factors for return migration, which ultimately support urbanization through returnee-led entrepreneurial ventures (Yu and Liu 2024). Return migrants are more transformational entrepreneurs than subsistence-oriented, are more objective, prefer formal credit markets, and invest their savings more than those without migration experience (Ding et al. 2025 ). Nevertheless, despite their motivation and entrepreneurial spirit, return migrants are often portrayed as automatic agents of development; in reality, this is different and affected by many socio-economic factors, and demonstrates that conflicts and weak state support can undermine return-led development (Riaño 2023 ). In contrast, Nepal, once affected by domestic conflicts that displaced rural communities, is now relatively stable, and such conflicts or social barriers no longer pose major obstacles to entrepreneurship development. 3. Methodology 3.1 Study Site and Data The household survey in 2025, which included a total of 791 randomly selected households from eight municipalities in two provinces of Nepal, served as the primary data for this study (Fig. 1 ). To gather household-level information, both structured and semi-structured questionnaires were used. Figure 1 illustrates the distribution of the sample collection sites across two provinces. From each province, four municipalities (one municipality from one district) were selected: two from the Terai or Inner Terai districts and two from the hilly districts. Red markers on the map indicate selected municipalities. Demographic and climatic characteristics of the selected study sites are presented in Table 1. Table 1 : Table 1 : Brief information about data collection area and collected sample size Province Districts Municipality Ecological belt No. of households in the municipality Sample size collected per municipality Lumbini Rupendehi Kanchan Terai (Tropical) 10,440 98 Lumbini Kapilbastu Shivaraj Terai (Tropical) 16,241 98 Lumbini Arghakhanchi Malarani Hill (Sub-tropical) 6,780 99 Lumbini Pyuthan Jhimruk Hill (Sub-tropical) 6,534 98 Bagmati Chitwan Madi Inner-terai (Tropical) 10,120 100 Bagmati Makwanpur Makwanpurgadhi Inner-terai (Tropical) 5,285 100 Bagmati Kavreplanchok Panauti Hill (Sub-tropical) 12,806 100 Bagmati Sindupalchok Melamchi Hill (Sub-tropical) 11,180 98 Total 79,386 791 Note: The number of households per municipality was obtained from Nepal’s National Statistics Office (NSO) based on the 2021 Population and Housing Census 3.2 Estimation Model To analyze drivers of investment decisions, we employ the Multinomial Logit Model (MNL). We assume that households behave rationally and choose an investment portfolio k from a set of mutually exclusive alternatives to maximize their utility. The underlying latent utility U ik that household i derives from choosing alternative k is composed of a deterministic component and a stochastic random error component \(\:\epsilon\:\) ik . The utility function is expressed as: $$\:{U}_{ik}={V}_{ik}+{\epsilon\:}_{ik}={\beta\:}_{0k}+{\beta\:}_{k}{X}_{i}+{\epsilon\:}_{ik}$$ 1 where X i represents a vector of observed household characteristics. The primary variables of interest include migration status — captured by dummy variables for permanent returnees and households with members currently living abroad — alongside control variables such as the age and education level of the household head. The summary statistics for all variables used in this study are presented in Table 2 . The vector β k denotes the coefficients to be estimated for category k , while \(\:\epsilon\:\) ik accounts for unobserved factors influencing the investment choice. Table 2 : Summary Statistics of the Variables Mean Std. Dev Min Max Obs Investment category (dummy) 0.516 0.751 0 2 791 Household with permanent returnee (dummy) 0.197 0.398 0 1 791 Household with members living abroad (dummy) 0.418 0.494 0 1 791 Household head with at least sec. education (dummy) 0.312 0.464 0 1 791 Female-headed household (dummy) 0.111 0.315 0 1 791 Age of household head (years) 53.244 12.718 25 92 791 Joint family (dummy) 0.155 0.363 0 1 791 At least one agriculture is commercialized (dummy) 0.255 0.436 0 1 791 Number of working-age adult household members 3.365 1.372 0 9 791 Local household (dummy) 0.742 0.438 0 1 791 Ownership/individual farm (dummy) 0.249 0.433 0 1 791 Networking status of households with returnees (dummy) 0.104 0.305 0 1 791 At least one member with agricultural skills in the households (dummy) 0.225 0.418 0 1 791 Total share of irrigated land (percent) 28.728 38.356 0 100 791 Total asset value in million (rupees) 3.862 5.690 0 70.95 791 Formal channel loan (dummy) 0.091 0.288 0 1 791 Subsidy (dummy) 0.152 0.359 0 1 791 Rupendehi district (dummy) 0.124 0.329 0 1 791 Kapilbastu district (dummy) 0.124 0.329 0 1 791 Arghakhanchi district (dummy) 0.125 0.331 0 1 791 Pyuthan district (dummy) 0.124 0.329 0 1 791 Kavreplanchok district (dummy) 0.126 0.333 0 1 791 Sindhupalchok district (dummy) 0.124 0.329 0 1 791 Makwanpur district (dummy) 0.126 0.332 0 1 791 Note: As of 30 January 2026, 1 US dollar = 146.84 Nepalese Rupees (NRs). The dependent variable ( Y i ) categorizes households into three distinct investment groups. The first category, Agribusiness Only ( k = 1), comprises households engaged in commercial agriculture activities, such as crop production, livestock, and agro-processing, with the primary aim of selling commodities. The second category, Mixed business ( k = 2) represents households that diversify their income by combining agribusiness with non-agricultural activities like trading, groceries or other non-agriculture production-related activities. The third category, No Agribusiness ( k = 3), serves as the reference group (base outcome) and includes households engaged solely in non-agribusiness ventures or those with no business activities at all. To estimate the model, we assume the error terms \(\:\epsilon\:\) ik follow an independent and identically distributed (i.i.d.), and the probability that household i selects alternative k is given by: $$\:P\left({Y}_{i}=k\right)=\frac{exp\left({\beta\:}_{0k}+{\beta\:}_{k}{X}_{i}\right)}{{\sum\:}_{j=1}^{3}exp\left({\beta\:}_{0j}+{\beta\:}_{j}{X}_{i}\right)}$$ 2 For model identification, the coefficients for the reference category (No Agribusiness) are normalized to zero (β 3 = 0). Thus, the estimated coefficients represent the impact of the explanatory variables on the utility of choosing the category relative to the base category. 4. Result 4.1. Descriptive Results Table 3 presents the investment-related descriptive characteristics of households across three categories: Agribusiness (category 1), Mixed business (category 2), and No-agribusiness (control group). We examine the mean difference outcomes with a pair-wise t-test of households categorized as agriculture investors and mixed investors against the control group. The analysis examines whether households engaged in agribusiness (category 1) or mixed business activities (category 2) differ significantly from households with no agribusiness investment. In several key attributes, the result indicates that agribusiness households and mixed business households differ significantly from the control group. Households that are mainly engaged in agribusiness show significantly different socioeconomic and agribusiness characteristics across multiple dimensions compared to households that are not engaged in any form of agribusiness, and this category 1 of households is more likely to include permanent returnees, have heads with at least secondary education, and maintain a larger proportion of working-age members. Moreover, households with agribusiness-only investment show a greater engagement in commercial agriculture and substantially higher utilization of subsidies and formal credit. Further, they also depict stronger social networks, enhanced agricultural skills, and higher asset value. Table 3 : Comparison of key variables by household status in agribusiness participation Variables Agribusiness Mixed No-agribusiness Differences (1) (2) (3) (1-3) (2-3) Household with permanent returnee (dummy) 0.375 0.290 0.118 0.257*** 0.172*** Household with members living abroad (dummy) 0.381 0.266 0.467 -0.086* -0.201*** Household head with at least sec. education (dummy) 0.381 0.403 0.268 0.113*** 0.135*** Female-headed household (dummy) 0.081 0.081 0.128 -0.047 -0.048 Age of household head (years) 54.294 52.153 53.179 1.114 -1.026 Joint family (dummy) 0.144 0.145 0.162 -0.018 -0.017 At least one agriculture is commercialized (dummy) 0.975 0.226 0.036 0.939*** 0.190*** Number of working-age adult household members 3.763 3.492 3.209 0.553*** 0.283** Local household (dummy) 0.650 0.685 0.785 -0.135*** -0.100** Ownership/individual farm (dummy) 0.944 0.226 0.036 0.908*** 0.190*** Networking status of households with returnees (dummy) 0.269 0.194 0.030 0.239*** 0.164*** At least one member with agricultural skills in the households (dummy) 0.425 0.113 0.189 0.236*** -0.076** Total share of irrigated land (percent) 30.719 21.225 29.934 0.784 -8.709** Total asset value in million (rupees) 5.343 4.609 3.212 2.131*** 1.398*** Formal channel loan (dummy) 0.263 0.234 0.002 0.261*** 0.232*** Subsidy (dummy) 0.613 0.105 0.018 0.595*** 0.087*** Rupendehi district (dummy) 0.175 0.258 0.075 0.100*** 0.183*** Kapilbastu district (dummy) 0.069 0.081 0.152 -0.083*** -0.071** Arghakhanchi district (dummy) 0.106 0.097 0.138 -0.032 -0.041 Pyuthan district (dummy) 0.050 0.105 0.152 -0.102*** -0.047 Kavreplanchok district (dummy) 0.181 0.113 0.112 0.069** 0.000 Sindhupalchok district (dummy) 0.119 0.169 0.114 0.004 0.055* Makawanpur district (dummy) 0.131 0.048 0.144 -0.013 -0.096*** Observations (households) 160 124 507 Source: Authors. Notes: (i) *** denotes significant at 1%, ** significant at 5%, and * significant at 10% in t-test comparison between the labelled categories. By contrast, households with diversified business also present certain advantages relative to household who are not engaged in agriculture, including fewer members abroad, slightly better-educated household heads, a larger number of working-age adults, and greater involvement in commercial agriculture but lesser agricultural skills. Further, their access to financial resources, particularly formal loans, remains comparatively low compared to households with agricultural investments. Similarly, subsidy also been well utilized by households with agribusiness or mixed businesses. Further, households led by locally born individuals are less likely to engage in agribusiness, signaling that local people have more endurance and adaptive characteristics and show less interest in agribusiness or mixed businesses. Moreover, their inclination towards non-agribusiness or no investment, or specialize outside agriculture. Moreover, households from different districts also differ significantly in their investment choices. Similarly, household with diversified businesses occupies a midway position between household who are solely involved in agribusiness and households without any agribusiness. Overall, the descriptive evidence indicates that households with agribusiness or mixed business are significantly different from the base category households. 4.2 Estimation Results The marginal effects from the multinomial logit model, presented in Table 4 , highlight the factors affecting household investment decisions in different business categories. Households with a permanent return migrant are more likely to invest in both mixed businesses and agribusiness, with a strong inclination toward business diversification than investment in agribusiness alone, as shown by the estimates, thereby suggesting return migrants act as a positive driver of agribusiness engagement in rural Nepal. However, returnee households are less likely to invest exclusively in non-agribusiness activities, indicating a tendency toward diversified livelihood strategies rather than specialization beyond agriculture. Table 4 : Factors influencing business investment choices (marginal effects based on multinomial logit estimates) VARIABLES Agribusiness Mixed No-agribusiness Household with permanent returnee (dummy) 0.018** 0.055*** -0.073*** [0.018] [0.031] [0.029] Household with members living abroad (dummy) 0.019** -0.073*** 0.054*** [0.017] [0.027] [0.027] Household head with at least sec. education (dummy) -0.009 0.052*** -0.042** [0.018] [0.029] [0.027] Female-headed household (dummy) -0.028** -0.010 0.038** [0.027] [0.039] [0.032] Age of household head (years) -0.001 0.000 0.000 [0.001] [0.001] [0.001] Joint family (dummy) -0.013 -0.004 0.017 [0.023] [0.041] [0.036] At least one agriculture is commercialized (dummy) 0.672*** -0.554*** -0.118** [0.065] [0.110] [0.098] Number of working-age adult household members 0.006** 0.016** -0.022*** [0.006] [0.011] [0.010] Local household (dummy) -0.034*** -0.029** 0.063** [0.019] [0.041] [0.042] Ownership/ individual farm (dummy) -0.448*** 0.545*** -0.097** [0.059] [0.115] [0.102] Networking status of household with returnees (dummy) -0.015** 0.104*** -0.089*** [0.022] [0.041] [0.045] At least one member with agricultural skills in the households (dummy) 0.046*** -0.056** 0.011 [0.025] [0.042] [0.036] Total share of irrigated land (percent) 0.000** -0.001*** 0.001*** [0.000] [0.000] [0.000] Total asset value in million (rupees) 0.001 -0.001** 0.001 [0.002] [0.002] [0.002] Formal channel loan (dummy) 0.084*** 0.409*** -0.493*** [0.029] [0.077] [0.091] Subsidy (dummy) 0.067*** 0.098*** -0.165*** [0.019] [0.039] [0.038] Rupendehi district (dummy) -0.027** -0.059** 0.086** [0.029] [0.052] [0.052] Kapilbastu district (dummy) 0.030** -0.165*** 0.135*** [0.034] [0.060] [0.053] Arghakhanchi district (dummy) 0.009 -0.158*** 0.149*** [0.035] [0.052] [0.050] Pyuthan district (dummy) 0.070*** -0.155*** 0.086*** [0.033] [0.051] [0.043] Kavreplanchok district (dummy) 0.096*** -0.082*** -0.013 [0.040] [0.048] [0.041] Sindhupalchok district (dummy) 0.022 -0.013 -0.009 [0.033] [0.042] [0.038] Makawanpur district (dummy) 0.069*** -0.154*** 0.084** [0.027] [0.060] [0.053] Observations (households) 160 124 507 Source: Authors’ estimations. Notes: (i) Robust standard errors in brackets. (ii) *** denotes significant at 1%, ** significant at 5%, and * significant at 10%. Additionally, the increasing age of the household head is associated with a declining probability of investing in agribusiness alone, signifying the role of the head in the agribusiness investment decision, and a larger number of adult household members increases the likelihood of business diversification. Households engaged in the commercialization of a specific commodity are more likely to invest exclusively in agribusiness, reflecting a preference for specialization. However, households with joint members tend to favour non-agribusiness activities or no investment, indicating more involvement in non-farm activities, which is favoured by a large number of household members. Social networking plays a crucial role in business diversification, underscoring its importance as a risk-mitigation strategy, particularly through connections with return migrants. While agricultural skills encourage investment in agribusiness alone, this shows that skills lead to specialization of businesses in one specific area. Interestingly, higher household asset values do not show a significant effect on agribusiness or mixed business choices. Furthermore, an increase in the share of irrigated land positively influences the probability of agribusiness investment; the magnitude of this effect is relatively small, and it negatively affects mixed business choices. Subsidies and access to formal credit significantly enhance the likelihood of agribusiness investment. Finally, there are significant inter-district differences in investment choice decisions due to heterogeneity present in socio-economic and climatic conditions. 5. Discussion This study aims to assess whether agribusiness is a preferred investment choice for returnees. We found that returnees are well-positioned to invest in agribusiness. We also found that diversification of business is their main strategy to cope with unexpected loss from a single agribusiness investment, and this could be further studied to identify factors that motivate such investments. Households with at least secondary education are more likely to diversify their businesses and are inclined to minimize the risks associated with agribusiness. In contrast, female-headed households do not show any significant investment in any businesses, and this is in contrast with the study by Graskemper et al. ( 2021 ), which found that women are more involved in diversification in Germany. However, the results of our study are in line with FAO (2017), which reported that in developing countries, women mostly stay in rural areas and are engaged in agriculture; engaging in agriculture doesn’t necessarily mean participation in agricultural investment. Our study found that households with family members abroad are relatively more distant from agribusiness investment, and this is in line with López-Feldman and Escalona ( 2017 ), who found that remittance-receiving households benefited from increased disposable income, which provided them with greater leisure opportunities and moved them away from low-return agricultural activities. Joint families, on the other hand, are more likely to invest in non-agribusiness or no businesses, and this emphasizes that a larger labour force in the household may diversify their income by engaging in other non-farm activities, which has also been mentioned in different studies (Patidar and Chothodi 2021 ; Kolog et al. 2024 ). An increase in the number of working-age members (18–58 years) within a household raises the likelihood of business diversification, while reducing the probability of investing only in agribusiness or only in non-agribusiness activities. Gebreyesus ( 2016 ) study in Ethiopia found that the larger the household size, the greater the diversification ability to adopt diversified livelihood strategies, which helps increase household income by optimizing labor force availability. Locally born members headed households are more inclined to engage in non-agribusiness activities alone or to refrain from any business investment. Migration is often viewed as a way to cope with the uneven spatial distribution of resources such as natural assets, markets, and job opportunities. It has therefore become increasingly recognized as an important element of livelihood strategies, and highlighted the importance of migration and diversification of livelihood strategies (Tacoli and Mabala 2010 ). Haggblade et al. ( 2010 ) stated that about 35–50% of rural household income among developing countries depends on rural non-farm activities, and this livelihood diversifying strategy is to reduce the risk associated with farm activities. Similarly, individually managed firms are more likely to be diversified, non-agribusiness-oriented, or entirely uninvolved in business ventures. Strong household networking with other returnees fosters business diversification. Etriya et al. ( 2019 ) emphasized that diverse networks have increased the performance of entrepreneurship and have more innovative ties and technology ties, which not only improve the innovativeness of entrepreneurship but also better financial performance. Moreover, networks have positive impacts on the performance of agribusiness owned by women in Ghana (Dossou et al. 2024 ). Further, households with at least one member possessing agricultural skills beyond traditional knowledge are more likely to invest exclusively in agribusiness. Samuel and Godâ ( 2023 ) found that there is no significant difference between graduates and experienced farmers who have agriculture skills for entrepreneurship, which highlights the importance of skills required for entrepreneurial activities. We find that an increase in household asset value does not show any significant effect on the choice of businesses. However, Dzanku ( 2015 ) found that there is a positive association between assets and livelihood diversification. Rising asset values do not necessarily lead to higher income, and non-farm activities in rural areas are also important because these activities help to diversify the income (Grzelak 2022 ). Furthermore, we also find that households that have access to subsidies in agriculture and access to formal credit are more likely to show interest in agribusiness, and Ding et al. ( 2025 ) in their study stated the importance of formal credit for return migrants. Further, Kolog et al. ( 2024 ) found that credit accessibility helps to diversify the livelihood of rural farm households. Additionally, financial accessibility, such as subsidies and formal loans, significantly increases the likelihood of agribusiness-only investment and reduces the probability of having no investment. Agrawal ( 2021 ), in support of evidence-based policy development, emphasized that promotion of community-based financial institutions supporting credit and micro-credit is essential to ensure farmers’ easy access to finance, while simultaneously expanding formal banking services, which support agriculture loans and government assistance, is of the utmost importance. Further, agricultural restructuring plays a crucial role in shaping household income, while the transformation of agriculture from a subsistence-based system to a market-based, commercial-oriented production is essential for strengthening the rural economy (Hu et al. 2023 ). Moreover, Yu et al. ( 2024 ) found that immigrant remittances support agribusiness investment and asset accumulation. However, in our study, households with migrated family members who are potential remittance receivers are not particularly interested in agricultural investment, although asset accumulation among returnee migrants and households with migrated family members is significantly higher. Thus, our study is both aligned with and contradictory to theirs in different aspects. From the above results and discussion, and from the different literature, the findings we obtained have both supportive and contradictory aspects. However, most studies highlight that migrants are less likely to engage in agriculture-related activities and are more reliant on the remittances they receive. This supports the idea that there is always a trade-off between choices, and in line with this, economic theories suggest that people behave rationally to maximize utility and welfare, which stimulates the efficient allocation of labor and resources. 6. Conclusion and Recommendation This study, when compared with existing studies, highlights the complex interplay of migration and investment decisions. Education, household composition, age of the household head, assets, and institutional support, such as government assistance, play an important role in shaping agribusiness engagement and diversification in rural Nepal. The empirical analysis shows that households with returnee members are more likely to invest in mixed businesses, although agribusiness-only investment is also a choice compared to other households. Return migrants emerge as a positive driver of business diversification, while households with members abroad are more closely associated with non-agribusiness activities or no investment rather than agribusiness investment, and this implies that remittance income is rarely reinvested in farming enterprises. This suggests that remittances primarily serve as a source of income rather than investment-based financing. Further analysis shows that returnees diversify businesses to cope with uncertainty in agribusiness. In contrast, households with migrant members are more persuaded toward non-agribusiness activities or choose not to invest in any agribusiness activities. Trade-offs among alternatives and rational household decision-making can explain this behaviour. In some cases, households may perceive themselves as better off without investing in any business, as remittances serve as a source of income. Moreover, household features also influence investment decisions. For example, as the age of the household’s head increases, the probability of investing exclusively in agribusiness decreases, and this echoes the physically demanding nature of agribusiness and the slow progress of agricultural mechanization. Moreover, farms with single ownership tend to be more diversified, as the risk-averse nature of small holders who seek to reduce vulnerability through livelihood diversification. Since individual farms are typically small in capacity, they are more inclined to engage in a combination of farm and non-farm activities. Additionally, households with a larger labour force are better positioned to pursue off-farm activities, which serve as an important strategy for livelihood diversification. Furthermore, investing in agribusiness or diversifying business seems less favourable for female-headed households, which highlights the difficulties related to household work faced by women in rural areas. This underlined the difficulty faced by women in managing both household responsibilities and business activities simultaneously. Further, the importance of women's engagement in agriculture is highlighted by several studies and cannot be ignored. Until and unless the involvement of women in agribusiness seems less possible without a reduction in women's dodgery with effective policy ratification. Further, higher education levels, stronger networks, more active members, and access to credit are important household characteristics that illustrate a greater propensity for business diversification, underscoring the importance of human, social, and financial capital in rural entrepreneurship. Other household characters also play a critical role, as such, with larger families more likely to diversify income sources by engaging in both farm and non-farm activities. Additionally, subsidies and broader financial instruments are essential to support small and medium investors when they typically operate in rural areas. Hence, the Government of Nepal should focus on policies that support the economic integration of return migrants through entrepreneurship development. Returnee migrants serve not only as investors in agribusiness but also as key agents of business diversification, as multiple business activities can act as a form of self-insurance, allowing households to offset losses in one enterprise with gains in another, which serves as household resilience and income stabilization. Further, households with migrant members abroad are also potential investors and encourage them to diversify their livelihood strategy through policy endorsement, and such policies are as easy access to credit facilities, cooperative-based financing, and insurance services, because these investors are generally motivated by risk-aversion strategies. As returnees use diversification strategies to cope with uncertainty, government policies should support these strategies and endorse the policies that motivate migrant households to channel remittance resources toward business investment and diversification, thereby reducing the national economy’s dependence on remittances. Moreover, improved access to markets, market information, and market-related rural infrastructure is fundamental for promoting agribusiness in rural areas. Further, the government should prioritise the development of a dedicated institution to support returnee migrants. Finally, it is important to note the geographical limitations of our study, as it was only conducted in two provinces of Nepal, covering the plain and hilly regions. We did not include the mountainous region primarily due to the resource constraints involved in reaching remote, sparsely populated areas. Additionally, the mountainous region has a distinct socioeconomic profile where, unlike in the surveyed areas, mostly livelihoods are driven by tourism and trekking rather than agribusiness activities studied here. Declarations Acknowledgement Authors contribution Corresponding authors conceptualized the idea, collected the data, and wrote the original draft ; contributing authors supervised the research, helped in data curation and methodology, reviewed, and edited the draft. Funding Data availability Competing interests We do not have competing interests regarding this paper and the work reported in this paper. Use of AI tools Artificial Intelligence (AI) tools were utilized in this manuscript solely for language editing, proofreading, and ensuring stylistic consistency. Ethical Approval The data were collected in accordance with established ethical standards and codes of conduct. Although the study involved human participation through a household survey, it did not include any invasive procedures or the collection of biological samples, thereby posing minimal risk to participants. An ethical approval waiver was duly obtained from the Department of Agricultural Economics. Informed Consent Participants were fully informed about the intended use of their data and the measures implemented to protect their confidentiality and privacy. References Adhikari J, Rai MK, Baral C, Subedi M (2023) Labor Migration from Nepal: Trends and Explanations. Migration in South Asia: IMISCOE Regional Reader. Springer International Publishing, Cham, pp 67–81. https://doi.org/10.1007/978-3-031-34194-6 . Agrawal S (2021) Return and Reintegration: Exploring challenges and opportunities of COVID-19 migrant returnees in small scale Agri-businesses. Daayitwa- Fusemachines Nepal Public Policy Fellow 2021 https:// . 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Space Cult India 9(3):32–44 DOI 10.20896/saci.v9i3.1206 Riaño Y (2023) Migrant Entrepreneurs as agents of development? Geopolitical context and transmobility strategies of Colombian migrants returning from Venezuela. J Int Migration Integr 24(Suppl 2):539–562. https://doi.org/10.1007/s12134-022-00959-w Samuel OE, Godâ S (2023) Entrepreneurial Skills Acquired by Agribusiness Graduates in the Management of Small-Scale Agribusiness Ventures in Bayelsa State, Nigeria. Int J Econ Financial Res 9(3):20–26. 10.32861/ijefr.93.20.26 Sinatti G (2022) Return migration, entrepreneurship and development. In: Russel K and Katie K(ed) Handbook of return migration (pp. 344–357). Edward Elgar Publishing, UK, 2022. https://www.e-elgar.com/shop/gbp/handbook-of-return-migration-9781839100048.html . Accessed 15 Sept 2025 Silva BG, Nguyen N, Andriese NC, Combs J (2023) Returnee-Migrant Entrepreneurship: A Systematic Review. In Academy of Management Proceedings, vol. 2023, No. 1, p. 10415. 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Asian Popul Stud 16(1):61–81. https://doi.org/10.1080/17441730.2020.1718358 Yin J, Huang X, Dong Y, Zhao M, Tan W (2021) Dual-level impact of regional context and individual attributes on entrepreneurship among return migrants in China. Growth Change 52(2):1099–1116. https://doi.org/10.1111/grow.12480 Yu L, Li Z, Liu D (2024) Return-migrant urbanisation in inland China: The case of Hubei Province. Land 13(2):190. https://doi.org/10.3390/land13020190 Yu Z, Zhang K, Wang Z, Liu C (2024) Immigration remittances, agricultural investment, and household wealth accumulation. Finance Res Lett 68:105991. https://doi.org/10.1016/j.frl.2024.105991 Zhou J, Zhang X, Korkmaz AG, Ding X, Yue P (2024) Mirroring the urban exodus: The impact of return migration on rural entrepreneurship. Finance Res Lett 66:105619. https://doi.org/10.1016/j.frl.2024.105619 Additional Declarations No competing interests reported. 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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-9024066","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":621580535,"identity":"78ac0b28-2e82-44b8-a366-ac2003e991aa","order_by":0,"name":"Bipin Khanal","email":"data:image/png;base64,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","orcid":"","institution":"Tohoku University","correspondingAuthor":true,"prefix":"","firstName":"Bipin","middleName":"","lastName":"Khanal","suffix":""},{"id":621580536,"identity":"a637a3f2-a9d5-4b6c-86b1-bf1f53273a36","order_by":1,"name":"Tsuyoshi Sumita","email":"","orcid":"","institution":"Tohoku University","correspondingAuthor":false,"prefix":"","firstName":"Tsuyoshi","middleName":"","lastName":"Sumita","suffix":""},{"id":621580537,"identity":"22cae3f1-dcd9-48e7-861f-3e039c700ac1","order_by":2,"name":"Eustadius Francis Magezi","email":"","orcid":"","institution":"Tohoku University","correspondingAuthor":false,"prefix":"","firstName":"Eustadius","middleName":"Francis","lastName":"Magezi","suffix":""}],"badges":[],"createdAt":"2026-03-03 22:53:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9024066/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9024066/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106811371,"identity":"c66eb293-2b3b-4ab6-a71f-cbb89b9e7187","added_by":"auto","created_at":"2026-04-13 16:20:54","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":170530,"visible":true,"origin":"","legend":"\u003cp\u003eMap shows the data collection area of eight municipalities\u003c/p\u003e\n\u003cp\u003e(Source: Authors, using publicly available shapefiles)\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9024066/v1/a4055d5eeab2c4872330a853.jpg"},{"id":106994113,"identity":"159ae882-6fd7-49ad-8bd5-1d860fcbfa46","added_by":"auto","created_at":"2026-04-15 15:04:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1003995,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9024066/v1/ec83e72c-5a4e-474f-a525-b04eefecdbbd.pdf"},{"id":106811373,"identity":"c3208309-1429-4d44-b1f8-4c1d731d33fb","added_by":"auto","created_at":"2026-04-13 16:20:55","extension":"zip","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":402898,"visible":true,"origin":"","legend":"","description":"","filename":"Surveydatainvestmentanalysis.zip","url":"https://assets-eu.researchsquare.com/files/rs-9024066/v1/a8e74a981a42e1534c47a192.zip"},{"id":106811374,"identity":"26c99d3c-ea96-4f3f-9803-d750b21b57bf","added_by":"auto","created_at":"2026-04-13 16:20:55","extension":"zip","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":76134,"visible":true,"origin":"","legend":"","description":"","filename":"Analyisdofilefinaldata.zip","url":"https://assets-eu.researchsquare.com/files/rs-9024066/v1/c5a8af0e09e67e28ed14efe9.zip"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assessing Agribusiness as an Investment Choice for Return Migrants in Rural Nepal","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eCountries benefit from integrated labor markets, and Nepal is no exception, as the economy becomes increasingly interconnected; however, a key challenge lies in the livelihood strategies of returning migrants. Return migrants often face difficulties in identifying suitable investment choices due to unfamiliarity with the domestic economic environment after their return, despite having accumulated resources from abroad, such as financial capital, knowledge, and skills. Business activities and entrepreneurial decisions are shaped by these resources, along with household characteristics such as education, age, and prior experience (Gonz\u0026aacute;lez-Leonardo et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Wei \u0026amp; Zhu \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Yin et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Nevertheless, return-migrant entrepreneurship is not automatic and depends on institutional support, access to finance, and an enabling local environment (Naud\u0026eacute; et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Silva et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Sinatti \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zhou et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the Nepalese context, foreign employment is viewed as lucrative, leading many to abandon agriculture as a mainstay in favor of working abroad, especially for newer generations (Agrawal \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and the absentee population is about 2.3\u0026nbsp;million, highlighting the current situation of the country (NSO 2021). The country\u0026rsquo;s socio-economic environment is deeply influenced by factors related to labor migration, particularly encouraging individuals from low and middle-income households to migrate abroad, and these influencing factors are a lack of employment opportunities, socioeconomic inequalities, poor education systems, and a desire for better income and living standards (Adhikari et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Foreign opportunities serve as a necessary evil with positive impacts on food security, though people are encouraged to seek foreign work due to low agricultural incomes and land fragmentation (Timilsina et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Labor migration in Nepal is a continuous and dynamic process; some permanently leave the country in search of better opportunities, but others return with newly acquired skills and capital. These returnees have the potential to channelize local resources into rural entrepreneurial activities to create jobs and revive the rural economy through a favorable business environment (Devkota \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEntrepreneurship developed by returnees is vital for rural development, which includes employment generation, income diversification, poverty reduction, and agricultural production, particularly with agribusiness activities (Bao et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Liu and Qiao \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Miao et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Naminse et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Several scholars show that return migrants are more likely to engage in entrepreneurship than non-migrants due to the financial capital, skills, and experience accumulated abroad (Batista et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Lara et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Silva et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Further, remittances and agricultural productivity show a positive association, possibly through agricultural investment, and remittances serve as a key resource for investment (Kapre and Ghimire 2020). However, a study by Maharajan et al. (2012) explicitly stated that migration did not help to move subsistence agriculture into commercial agriculture. Fragmented policies and weak institutional support, especially in countries lacking dedicated reintegration institutions, can shrink the possible developmental impact of returnee entrepreneurship despite their potential to become entrepreneurs (Ria\u0026ntilde;o \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Spitzer and Piper \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThough Poudel and Poudel (2022) have studied the returnees' engagement in agriculture, it did not specifically indicate the engagement in agriculture as business or subsistence oriented. Further, Carter and Khadka (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) found that agriculture in the mid-hills has been revived through innovation, especially adopted by returnee migrants. Our study aims to assess whether households with returnees are more likely to invest in local business activities, including agribusiness, compared to households without returnees. It further examines business strategies developed by different households, whether returnee households differ from migrant households (with members currently abroad) in their investment behaviour, including whether they engage exclusively in agribusiness or combine it with other forms of business as part of a broader diversification strategy. Despite studies on migration and agriculture being conducted by several scholars; comprehensive analysis of returnee investment in agribusiness compared to non-returnee and migrants is lacking.\u003c/p\u003e \u003cp\u003eSpecifically, this study has three main objectives. First, it assesses whether returnee households are more likely to invest in local enterprises, including agribusiness, than non-returnee households. Second, it examines the extent to which households with family members currently abroad are inclined to invest in agribusiness. Third, based on these findings, the study provides conclusive evidence-based policy insights by identifying which household categories contribute most significantly to agribusiness, and by emphasizing the need for supportive measures such as improved access to direct or indirect financial assistance in order to promote and sustain agribusiness development across household types.\u003c/p\u003e"},{"header":"2. Literature Review","content":"\u003cp\u003eA study by Silva et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) discovered that the probability of entrepreneurship among returnee migrants is high and suggested that there is an increasing chance of mobilizing their accumulated resources by migrants after returning to the home country. It also emphasized that when personal preferences align with a supportive local environment, returnees are engaging capital in entrepreneurial activities; however, not all return migrants are interested in becoming entrepreneurs (Naud\u0026eacute; et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Due to the capital and skills acquired abroad, there is a positive correlation between return migrants and involvement in entrepreneurial activities (Lara et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and migrants workers with support from their families, communities, and government are encouraged often to pool their savings and engage in entrepreneurial activities, and this is the evidence from the Philippines, where the National Reintegration Centre provides seminars to migrant workers and their families to encourage entrepreneurship (Spitzer and Piper \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). However, in Nepal, there is no specialized body dedicated to supporting returnee migrants. Instead, various ministries and local government programs have incorporated certain support measures for returnee migrants.\u003c/p\u003e \u003cp\u003eEntrepreneurship is an important basis of economic development, and rural migrants returning home to start businesses can promote employment, alleviate poverty, and drive rural economic transformation (Bao et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The participation of farmers in commercial activities has been gradually increasing, and they are now considered an important part of the entrepreneurial community (Miao et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This not only helps increase farmers\u0026rsquo; income but also invigorates the rural economy through job creation and poverty reduction (Naminse et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Liu and Qiao (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) found that return migrants have a positive impact on increasing agricultural productivity, especially for voluntary return. Migration itself generates social and economic benefits for both home and host countries (Hausmann and Nedelkoska \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Studies have also shown that returnees\u0026rsquo; investment decisions and entrepreneurial dynamics strongly influence their occupational choices, and also reveal a higher probability of entrepreneurship among return migrants compared to non-migrants (Batista et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Further, returnees can serve as catalysts to foster rural entrepreneurship; they need financial support and targeted education (Zhou et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). A study by Yin et al. (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) underlined that investment decisions are influenced by education and past work experience; similarly, Wei and Zhu (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) found that migrants\u0026rsquo; work experiences and household attributes significantly affect entrepreneurial choices. Further, migrants\u0026rsquo; own experiences, social determinants, and government support are crucial for successful entrepreneurship development after their return (Sinatti \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Moreover, individual characteristics such as age, gender, and education also significantly influence entrepreneurial outcomes (Syafitri et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Key factors identified by Gonz\u0026aacute;lez-Leonardo et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) that are shaping the role of returnees in revitalizing rural economies include human capital and financial resources. Institutional arrangements, infrastructure, and facilities are key pull factors for return migration, which ultimately support urbanization through returnee-led entrepreneurial ventures (Yu and Liu 2024). Return migrants are more transformational entrepreneurs than subsistence-oriented, are more objective, prefer formal credit markets, and invest their savings more than those without migration experience (Ding et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNevertheless, despite their motivation and entrepreneurial spirit, return migrants are often portrayed as automatic agents of development; in reality, this is different and affected by many socio-economic factors, and demonstrates that conflicts and weak state support can undermine return-led development (Ria\u0026ntilde;o \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In contrast, Nepal, once affected by domestic conflicts that displaced rural communities, is now relatively stable, and such conflicts or social barriers no longer pose major obstacles to entrepreneurship development.\u003c/p\u003e"},{"header":"3. Methodology","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n\u003ch2\u003e3.1 Study Site and Data\u003c/h2\u003e\n\u003cp\u003eThe household survey in 2025, which included a total of 791 randomly selected households from eight municipalities in two provinces of Nepal, served as the primary data for this study (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). To gather household-level information, both structured and semi-structured questionnaires were used.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates the distribution of the sample collection sites across two provinces. From each province, four municipalities (one municipality from one district) were selected: two from the Terai or Inner Terai districts and two from the hilly districts. Red markers on the map indicate selected municipalities. Demographic and climatic characteristics of the selected study sites are presented in Table\u0026nbsp;1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e: Brief information about data collection area and collected sample size\u003c/p\u003e\n\u003ctable width=\"879\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003eProvince\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"152\"\u003e\n\u003cp\u003eDistricts\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"125\"\u003e\n\u003cp\u003eMunicipality\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eEcological belt\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"161\"\u003e\n\u003cp\u003eNo. of households in the municipality\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eSample size collected per municipality\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003eLumbini\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"152\"\u003e\n\u003cp\u003eRupendehi\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"125\"\u003e\n\u003cp\u003eKanchan\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eTerai (Tropical)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"161\"\u003e\n\u003cp\u003e10,440\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e98\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003eLumbini\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"152\"\u003e\n\u003cp\u003eKapilbastu\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"125\"\u003e\n\u003cp\u003eShivaraj\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eTerai (Tropical)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"161\"\u003e\n\u003cp\u003e16,241\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e98\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003eLumbini\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"152\"\u003e\n\u003cp\u003eArghakhanchi\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"125\"\u003e\n\u003cp\u003eMalarani\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eHill (Sub-tropical)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"161\"\u003e\n\u003cp\u003e6,780\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e99\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003eLumbini\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"152\"\u003e\n\u003cp\u003ePyuthan\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"125\"\u003e\n\u003cp\u003eJhimruk\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eHill (Sub-tropical)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"161\"\u003e\n\u003cp\u003e6,534\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e98\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003eBagmati\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"152\"\u003e\n\u003cp\u003eChitwan\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"125\"\u003e\n\u003cp\u003eMadi\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eInner-terai (Tropical)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"161\"\u003e\n\u003cp\u003e10,120\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e100\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003eBagmati\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"152\"\u003e\n\u003cp\u003eMakwanpur\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"125\"\u003e\n\u003cp\u003eMakwanpurgadhi\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eInner-terai (Tropical)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"161\"\u003e\n\u003cp\u003e5,285\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e100\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003eBagmati\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"152\"\u003e\n\u003cp\u003eKavreplanchok\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"125\"\u003e\n\u003cp\u003ePanauti\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eHill (Sub-tropical)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"161\"\u003e\n\u003cp\u003e12,806\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e100\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003eBagmati\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"152\"\u003e\n\u003cp\u003eSindupalchok\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"125\"\u003e\n\u003cp\u003eMelamchi\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eHill (Sub-tropical)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"161\"\u003e\n\u003cp\u003e11,180\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e98\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"139\"\u003e\n\u003cp\u003eTotal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"152\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"125\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"161\"\u003e\n\u003cp\u003e79,386\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e791\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: The number of households per municipality was obtained from Nepal\u0026rsquo;s National Statistics Office (NSO) based on the 2021 Population and\u003c/p\u003e\n\u003cp\u003eHousing Census\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n\u003ch2\u003e3.2 Estimation Model\u003c/h2\u003e\n\u003cp\u003eTo analyze drivers of investment decisions, we employ the Multinomial Logit Model (MNL). We assume that households behave rationally and choose an investment portfolio \u003cem\u003ek\u003c/em\u003e from a set of mutually exclusive alternatives to maximize their utility. The underlying latent utility \u003cem\u003eU\u003c/em\u003e\u003csub\u003e\u003cem\u003eik\u003c/em\u003e\u003c/sub\u003e that household \u003cem\u003ei\u003c/em\u003e derives from choosing alternative \u003cem\u003ek\u003c/em\u003e is composed of a deterministic component and a stochastic random error component \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\epsilon\\:\\)\u003c/span\u003e\u003c/span\u003e\u003csub\u003e\u003cem\u003eik\u003c/em\u003e\u003c/sub\u003e. The utility function is expressed as:\u003c/p\u003e\n\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\n\u003cdiv id=\"FileID_Equ1\" class=\"mathdisplay\"\u003e$$\\:{U}_{ik}={V}_{ik}+{\\epsilon\\:}_{ik}={\\beta\\:}_{0k}+{\\beta\\:}_{k}{X}_{i}+{\\epsilon\\:}_{ik}$$\u003c/div\u003e\n\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003ewhere \u003cem\u003eX\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e represents a vector of observed household characteristics. The primary variables of interest include migration status \u0026mdash; captured by dummy variables for permanent returnees and households with members currently living abroad \u0026mdash; alongside control variables such as the age and education level of the household head. The summary statistics for all variables used in this study are presented in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. The vector \u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003ek\u003c/em\u003e\u003c/sub\u003e denotes the coefficients to be estimated for category \u003cem\u003ek\u003c/em\u003e, while \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\epsilon\\:\\)\u003c/span\u003e\u003c/span\u003e\u003csub\u003e\u003cem\u003eik\u003c/em\u003e\u003c/sub\u003e accounts for unobserved factors influencing the investment choice.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e: Summary Statistics of the Variables\u003c/p\u003e\n\u003ctable border=\"1\" width=\"665\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"331\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003eMean\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003eStd. Dev\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003eMin\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"57\"\u003e\n\u003cp\u003eMax\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"60\"\u003e\n\u003cp\u003eObs\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"331\"\u003e\n\u003cp\u003eInvestment category (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0.516\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.751\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"57\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"60\"\u003e\n\u003cp\u003e791\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"331\"\u003e\n\u003cp\u003eHousehold with permanent returnee (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0.197\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.398\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"57\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"60\"\u003e\n\u003cp\u003e791\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"331\"\u003e\n\u003cp\u003eHousehold with members living abroad (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0.418\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.494\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"57\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"60\"\u003e\n\u003cp\u003e791\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"331\"\u003e\n\u003cp\u003eHousehold head with at least sec. education (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0.312\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.464\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"57\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"60\"\u003e\n\u003cp\u003e791\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"331\"\u003e\n\u003cp\u003eFemale-headed household (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0.111\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.315\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"57\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"60\"\u003e\n\u003cp\u003e791\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"331\"\u003e\n\u003cp\u003eAge of household head (years)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e53.244\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e12.718\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"57\"\u003e\n\u003cp\u003e92\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"60\"\u003e\n\u003cp\u003e791\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"331\"\u003e\n\u003cp\u003eJoint family (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0.155\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.363\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"57\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"60\"\u003e\n\u003cp\u003e791\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"331\"\u003e\n\u003cp\u003eAt least one agriculture is commercialized (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0.255\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.436\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"57\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"60\"\u003e\n\u003cp\u003e791\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"331\"\u003e\n\u003cp\u003eNumber of working-age adult household members\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e3.365\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e1.372\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"57\"\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"60\"\u003e\n\u003cp\u003e791\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"331\"\u003e\n\u003cp\u003eLocal household (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0.742\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.438\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"57\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"60\"\u003e\n\u003cp\u003e791\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"331\"\u003e\n\u003cp\u003eOwnership/individual farm (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0.249\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.433\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"57\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"60\"\u003e\n\u003cp\u003e791\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 48px;\"\u003e\n\u003ctd style=\"height: 48px;\" width=\"331\"\u003e\n\u003cp\u003eNetworking status of households with returnees (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 48px;\" width=\"66\"\u003e\n\u003cp\u003e0.104\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 48px;\" width=\"85\"\u003e\n\u003cp\u003e0.305\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 48px;\" width=\"66\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 48px;\" width=\"57\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 48px;\" width=\"60\"\u003e\n\u003cp\u003e791\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 48px;\"\u003e\n\u003ctd style=\"height: 48px;\" width=\"331\"\u003e\n\u003cp\u003eAt least one member with agricultural skills in the households (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 48px;\" width=\"66\"\u003e\n\u003cp\u003e0.225\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 48px;\" width=\"85\"\u003e\n\u003cp\u003e0.418\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 48px;\" width=\"66\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 48px;\" width=\"57\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 48px;\" width=\"60\"\u003e\n\u003cp\u003e791\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"331\"\u003e\n\u003cp\u003eTotal share of irrigated land (percent)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e28.728\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e38.356\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"57\"\u003e\n\u003cp\u003e100\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"60\"\u003e\n\u003cp\u003e791\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"331\"\u003e\n\u003cp\u003eTotal asset value in million (rupees)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e3.862\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e5.690\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"57\"\u003e\n\u003cp\u003e70.95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"60\"\u003e\n\u003cp\u003e791\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"331\"\u003e\n\u003cp\u003eFormal channel loan (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0.091\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.288\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"57\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"60\"\u003e\n\u003cp\u003e791\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"331\"\u003e\n\u003cp\u003eSubsidy (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0.152\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.359\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"57\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"60\"\u003e\n\u003cp\u003e791\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"331\"\u003e\n\u003cp\u003eRupendehi district (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0.124\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.329\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"57\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"60\"\u003e\n\u003cp\u003e791\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"331\"\u003e\n\u003cp\u003eKapilbastu district (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0.124\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.329\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"57\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"60\"\u003e\n\u003cp\u003e791\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"331\"\u003e\n\u003cp\u003eArghakhanchi district (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0.125\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.331\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"57\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"60\"\u003e\n\u003cp\u003e791\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"331\"\u003e\n\u003cp\u003ePyuthan district (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0.124\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.329\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"57\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"60\"\u003e\n\u003cp\u003e791\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"331\"\u003e\n\u003cp\u003eKavreplanchok district (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0.126\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.333\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"57\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"60\"\u003e\n\u003cp\u003e791\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"331\"\u003e\n\u003cp\u003eSindhupalchok district (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0.124\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.329\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"57\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"60\"\u003e\n\u003cp\u003e791\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"331\"\u003e\n\u003cp\u003eMakwanpur district (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0.126\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.332\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"66\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"57\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"60\"\u003e\n\u003cp\u003e791\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: As of 30 January 2026, 1 US dollar = 146.84 Nepalese Rupees (NRs).\u003c/p\u003e\n\u003cbr /\u003e\n\u003cp\u003eThe dependent variable (\u003cem\u003eY\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e) categorizes households into three distinct investment groups. The first category, Agribusiness Only (\u003cem\u003ek\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1), comprises households engaged in commercial agriculture activities, such as crop production, livestock, and agro-processing, with the primary aim of selling commodities. The second category, Mixed business (\u003cem\u003ek\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2) represents households that diversify their income by combining agribusiness with non-agricultural activities like trading, groceries or other non-agriculture production-related activities. The third category, No Agribusiness (\u003cem\u003ek\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3), serves as the reference group (base outcome) and includes households engaged solely in non-agribusiness ventures or those with no business activities at all.\u003c/p\u003e\n\u003cp\u003eTo estimate the model, we assume the error terms \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\epsilon\\:\\)\u003c/span\u003e\u003c/span\u003e\u003csub\u003e\u003cem\u003eik\u003c/em\u003e\u003c/sub\u003e follow an independent and identically distributed (i.i.d.), and the probability that household \u003cem\u003ei\u003c/em\u003e selects alternative \u003cem\u003ek\u003c/em\u003e is given by:\u003c/p\u003e\n\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\n\u003cdiv id=\"FileID_Equ2\" class=\"mathdisplay\"\u003e$$\\:P\\left({Y}_{i}=k\\right)=\\frac{exp\\left({\\beta\\:}_{0k}+{\\beta\\:}_{k}{X}_{i}\\right)}{{\\sum\\:}_{j=1}^{3}exp\\left({\\beta\\:}_{0j}+{\\beta\\:}_{j}{X}_{i}\\right)}$$\u003c/div\u003e\n\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003eFor model identification, the coefficients for the reference category (No Agribusiness) are normalized to zero (\u0026beta;\u003csub\u003e3\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0). Thus, the estimated coefficients represent the impact of the explanatory variables on the utility of choosing the category relative to the base category.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Result","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n\u003ch2\u003e4.1. Descriptive Results\u003c/h2\u003e\n\u003cp\u003eTable\u0026nbsp;3 presents the investment-related descriptive characteristics of households across three categories: Agribusiness (category 1), Mixed business (category 2), and No-agribusiness (control group). We examine the mean difference outcomes with a pair-wise t-test of households categorized as agriculture investors and mixed investors against the control group. The analysis examines whether households engaged in agribusiness (category 1) or mixed business activities (category 2) differ significantly from households with no agribusiness investment. In several key attributes, the result indicates that agribusiness households and mixed business households differ significantly from the control group. Households that are mainly engaged in agribusiness show significantly different socioeconomic and agribusiness characteristics across multiple dimensions compared to households that are not engaged in any form of agribusiness, and this category 1 of households is more likely to include permanent returnees, have heads with at least secondary education, and maintain a larger proportion of working-age members. Moreover, households with agribusiness-only investment show a greater engagement in commercial agriculture and substantially higher utilization of subsidies and formal credit. Further, they also depict stronger social networks, enhanced agricultural skills, and higher asset value.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e: Comparison of key variables by household status in agribusiness participation\u003c/p\u003e\n\u003ctable border=\"1\" width=\"913\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"411\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"137\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"411\"\u003e\n\u003cp\u003eVariables\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003eAgribusiness\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003eMixed\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"137\"\u003e\n\u003cp\u003eNo-agribusiness\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"177\"\u003e\n\u003cp\u003eDifferences\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"411\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e(1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e(2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"137\"\u003e\n\u003cp\u003e(3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e(1-3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e(2-3)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"411\"\u003e\n\u003cp\u003eHousehold with permanent returnee (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.375\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e0.290\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"137\"\u003e\n\u003cp\u003e0.118\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e0.257***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e0.172***\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"411\"\u003e\n\u003cp\u003eHousehold with members living abroad (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.381\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e0.266\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"137\"\u003e\n\u003cp\u003e0.467\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e-0.086*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e-0.201***\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"411\"\u003e\n\u003cp\u003eHousehold head with at least sec. education (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.381\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e0.403\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"137\"\u003e\n\u003cp\u003e0.268\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e0.113***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e0.135***\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"411\"\u003e\n\u003cp\u003eFemale-headed household (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.081\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e0.081\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"137\"\u003e\n\u003cp\u003e0.128\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e-0.047\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e-0.048\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"411\"\u003e\n\u003cp\u003eAge of household head (years)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e54.294\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e52.153\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"137\"\u003e\n\u003cp\u003e53.179\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e1.114\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e-1.026\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"411\"\u003e\n\u003cp\u003eJoint family (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.144\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e0.145\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"137\"\u003e\n\u003cp\u003e0.162\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e-0.018\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e-0.017\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"411\"\u003e\n\u003cp\u003eAt least one agriculture is commercialized (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.975\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e0.226\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"137\"\u003e\n\u003cp\u003e0.036\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e0.939***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e0.190***\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"411\"\u003e\n\u003cp\u003eNumber of working-age adult household members\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e3.763\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e3.492\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"137\"\u003e\n\u003cp\u003e3.209\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e0.553***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e0.283**\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"411\"\u003e\n\u003cp\u003eLocal household (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.650\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e0.685\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"137\"\u003e\n\u003cp\u003e0.785\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e-0.135***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e-0.100**\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"411\"\u003e\n\u003cp\u003eOwnership/individual farm (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.944\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e0.226\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"137\"\u003e\n\u003cp\u003e0.036\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e0.908***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e0.190***\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"411\"\u003e\n\u003cp\u003eNetworking status of households with returnees (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.269\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e0.194\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"137\"\u003e\n\u003cp\u003e0.030\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e0.239***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e0.164***\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"411\"\u003e\n\u003cp\u003eAt least one member with agricultural skills in the households (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.425\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e0.113\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"137\"\u003e\n\u003cp\u003e0.189\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e0.236***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e-0.076**\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"411\"\u003e\n\u003cp\u003eTotal share of irrigated land (percent)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e30.719\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e21.225\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"137\"\u003e\n\u003cp\u003e29.934\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e0.784\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e-8.709**\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"411\"\u003e\n\u003cp\u003eTotal asset value in million (rupees)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e5.343\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e4.609\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"137\"\u003e\n\u003cp\u003e3.212\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e2.131***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e1.398***\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"411\"\u003e\n\u003cp\u003eFormal channel loan (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.263\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e0.234\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"137\"\u003e\n\u003cp\u003e0.002\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e0.261***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e0.232***\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"411\"\u003e\n\u003cp\u003eSubsidy (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.613\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e0.105\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"137\"\u003e\n\u003cp\u003e0.018\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e0.595***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e0.087***\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"411\"\u003e\n\u003cp\u003eRupendehi district (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.175\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e0.258\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"137\"\u003e\n\u003cp\u003e0.075\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e0.100***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e0.183***\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"411\"\u003e\n\u003cp\u003eKapilbastu district (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.069\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e0.081\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"137\"\u003e\n\u003cp\u003e0.152\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e-0.083***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e-0.071**\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"411\"\u003e\n\u003cp\u003eArghakhanchi district (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.106\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e0.097\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"137\"\u003e\n\u003cp\u003e0.138\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e-0.032\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e-0.041\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"411\"\u003e\n\u003cp\u003ePyuthan district (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.050\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e0.105\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"137\"\u003e\n\u003cp\u003e0.152\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e-0.102***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e-0.047\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"411\"\u003e\n\u003cp\u003eKavreplanchok district (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.181\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e0.113\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"137\"\u003e\n\u003cp\u003e0.112\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e0.069**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"411\"\u003e\n\u003cp\u003eSindhupalchok district (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.119\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e0.169\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"137\"\u003e\n\u003cp\u003e0.114\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e0.004\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e0.055*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"411\"\u003e\n\u003cp\u003eMakawanpur district (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.131\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e0.048\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"137\"\u003e\n\u003cp\u003e0.144\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e-0.013\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e-0.096***\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"411\"\u003e\n\u003cp\u003eObservations (households)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e160\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"79\"\u003e\n\u003cp\u003e124\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"137\"\u003e\n\u003cp\u003e507\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSource: Authors. Notes: (i) *** denotes significant at 1%, ** significant at 5%, and * significant at 10% in t-test comparison between the labelled categories.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBy contrast, households with diversified business also present certain advantages relative to household who are not engaged in agriculture, including fewer members abroad, slightly better-educated household heads, a larger number of working-age adults, and greater involvement in commercial agriculture but lesser agricultural skills. Further, their access to financial resources, particularly formal loans, remains comparatively low compared to households with agricultural investments. Similarly, subsidy also been well utilized by households with agribusiness or mixed businesses. Further, households led by locally born individuals are less likely to engage in agribusiness, signaling that local people have more endurance and adaptive characteristics and show less interest in agribusiness or mixed businesses. Moreover, their inclination towards non-agribusiness or no investment, or specialize outside agriculture. Moreover, households from different districts also differ significantly in their investment choices. Similarly, household with diversified businesses occupies a midway position between household who are solely involved in agribusiness and households without any agribusiness. Overall, the descriptive evidence indicates that households with agribusiness or mixed business are significantly different from the base category households.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n\u003ch2\u003e4.2 Estimation Results\u003c/h2\u003e\n\u003cp\u003eThe marginal effects from the multinomial logit model, presented in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e, highlight the factors affecting household investment decisions in different business categories. Households with a permanent return migrant are more likely to invest in both mixed businesses and agribusiness, with a strong inclination toward business diversification than investment in agribusiness alone, as shown by the estimates, thereby suggesting return migrants act as a positive driver of agribusiness engagement in rural Nepal. However, returnee households are less likely to invest exclusively in non-agribusiness activities, indicating a tendency toward diversified livelihood strategies rather than specialization beyond agriculture.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u003c/strong\u003e: Factors influencing business investment choices (marginal effects based on multinomial logit estimates)\u003c/p\u003e\n\u003ctable width=\"663\"\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\n\u003cp\u003eVARIABLES\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003eAgribusiness\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003eMixed\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003eNo-agribusiness\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\n\u003cp\u003eHousehold with permanent returnee (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e0.018**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e0.055***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e-0.073***\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e[0.018]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e[0.031]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e[0.029]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\n\u003cp\u003eHousehold with members living abroad (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e0.019**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e-0.073***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e0.054***\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e[0.017]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e[0.027]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e[0.027]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\n\u003cp\u003eHousehold head with at least sec. education (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e-0.009\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e0.052***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e-0.042**\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e[0.018]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e[0.029]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e[0.027]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\n\u003cp\u003eFemale-headed household (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e-0.028**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e-0.010\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e0.038**\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e[0.027]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e[0.039]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e[0.032]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\n\u003cp\u003eAge of household head (years)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e-0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e[0.001]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e[0.001]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e[0.001]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\n\u003cp\u003eJoint family (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e-0.013\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e-0.004\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e0.017\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e[0.023]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e[0.041]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e[0.036]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\n\u003cp\u003eAt least one agriculture is commercialized (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e0.672***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e-0.554***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e-0.118**\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e[0.065]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e[0.110]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e[0.098]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\n\u003cp\u003eNumber of working-age adult household members\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e0.006**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e0.016**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e-0.022***\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e[0.006]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e[0.011]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e[0.010]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\n\u003cp\u003eLocal household (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e-0.034***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e-0.029**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e0.063**\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e[0.019]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e[0.041]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e[0.042]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\n\u003cp\u003eOwnership/ individual farm (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e-0.448***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e0.545***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e-0.097**\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e[0.059]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e[0.115]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e[0.102]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\n\u003cp\u003eNetworking status of household with returnees (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e-0.015**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e0.104***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e-0.089***\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e[0.022]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e[0.041]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e[0.045]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\n\u003cp\u003eAt least one member with agricultural skills in the households (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e0.046***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e-0.056**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e0.011\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e[0.025]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e[0.042]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e[0.036]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\n\u003cp\u003eTotal share of irrigated land (percent)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e0.000**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e-0.001***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e0.001***\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e[0.000]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e[0.000]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e[0.000]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\n\u003cp\u003eTotal asset value in million (rupees)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e-0.001**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e[0.002]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e[0.002]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e[0.002]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\n\u003cp\u003eFormal channel loan (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e0.084***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e0.409***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e-0.493***\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e[0.029]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e[0.077]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e[0.091]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\n\u003cp\u003eSubsidy (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e0.067***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e0.098***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e-0.165***\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e[0.019]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e[0.039]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e[0.038]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\n\u003cp\u003eRupendehi district (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e-0.027**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e-0.059**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e0.086**\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e[0.029]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e[0.052]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e[0.052]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\n\u003cp\u003eKapilbastu district (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e0.030**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e-0.165***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e0.135***\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e[0.034]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e[0.060]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e[0.053]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\n\u003cp\u003eArghakhanchi district (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e0.009\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e-0.158***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e0.149***\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e[0.035]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e[0.052]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e[0.050]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\n\u003cp\u003ePyuthan district (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e0.070***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e-0.155***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e0.086***\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e[0.033]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e[0.051]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e[0.043]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\n\u003cp\u003eKavreplanchok district (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e0.096***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e-0.082***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e-0.013\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e[0.040]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e[0.048]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e[0.041]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\n\u003cp\u003eSindhupalchok district (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e0.022\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e-0.013\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e-0.009\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e[0.033]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e[0.042]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e[0.038]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\n\u003cp\u003eMakawanpur district (dummy)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e0.069***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e-0.154***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e0.084**\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e[0.027]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e[0.060]\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e[0.053]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"397\"\u003e\n\u003cp\u003eObservations (households)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"97\"\u003e\n\u003cp\u003e160\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"82\"\u003e\n\u003cp\u003e124\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"87\"\u003e\n\u003cp\u003e507\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSource: Authors\u0026rsquo; estimations. Notes: (i) Robust standard errors in brackets. (ii) *** denotes significant at 1%, ** significant at 5%, and * significant at 10%.\u003c/p\u003e\n\u003cp\u003eAdditionally, the increasing age of the household head is associated with a declining probability of investing in agribusiness alone, signifying the role of the head in the agribusiness investment decision, and a larger number of adult household members increases the likelihood of business diversification. Households engaged in the commercialization of a specific commodity are more likely to invest exclusively in agribusiness, reflecting a preference for specialization. However, households with joint members tend to favour non-agribusiness activities or no investment, indicating more involvement in non-farm activities, which is favoured by a large number of household members. Social networking plays a crucial role in business diversification, underscoring its importance as a risk-mitigation strategy, particularly through connections with return migrants. While agricultural skills encourage investment in agribusiness alone, this shows that skills lead to specialization of businesses in one specific area. Interestingly, higher household asset values do not show a significant effect on agribusiness or mixed business choices.\u003c/p\u003e\n\u003cp\u003eFurthermore, an increase in the share of irrigated land positively influences the probability of agribusiness investment; the magnitude of this effect is relatively small, and it negatively affects mixed business choices. Subsidies and access to formal credit significantly enhance the likelihood of agribusiness investment. Finally, there are significant inter-district differences in investment choice decisions due to heterogeneity present in socio-economic and climatic conditions.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"5. Discussion","content":"\u003cp\u003eThis study aims to assess whether agribusiness is a preferred investment choice for returnees. We found that returnees are well-positioned to invest in agribusiness. We also found that diversification of business is their main strategy to cope with unexpected loss from a single agribusiness investment, and this could be further studied to identify factors that motivate such investments. Households with at least secondary education are more likely to diversify their businesses and are inclined to minimize the risks associated with agribusiness. In contrast, female-headed households do not show any significant investment in any businesses, and this is in contrast with the study by Graskemper et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), which found that women are more involved in diversification in Germany. However, the results of our study are in line with FAO (2017), which reported that in developing countries, women mostly stay in rural areas and are engaged in agriculture; engaging in agriculture doesn\u0026rsquo;t necessarily mean participation in agricultural investment. Our study found that households with family members abroad are relatively more distant from agribusiness investment, and this is in line with L\u0026oacute;pez-Feldman and Escalona (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), who found that remittance-receiving households benefited from increased disposable income, which provided them with greater leisure opportunities and moved them away from low-return agricultural activities. Joint families, on the other hand, are more likely to invest in non-agribusiness or no businesses, and this emphasizes that a larger labour force in the household may diversify their income by engaging in other non-farm activities, which has also been mentioned in different studies (Patidar and Chothodi \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Kolog et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). An increase in the number of working-age members (18\u0026ndash;58 years) within a household raises the likelihood of business diversification, while reducing the probability of investing only in agribusiness or only in non-agribusiness activities. Gebreyesus (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) study in Ethiopia found that the larger the household size, the greater the diversification ability to adopt diversified livelihood strategies, which helps increase household income by optimizing labor force availability. Locally born members headed households are more inclined to engage in non-agribusiness activities alone or to refrain from any business investment. Migration is often viewed as a way to cope with the uneven spatial distribution of resources such as natural assets, markets, and job opportunities. It has therefore become increasingly recognized as an important element of livelihood strategies, and highlighted the importance of migration and diversification of livelihood strategies (Tacoli and Mabala \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Haggblade et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) stated that about 35\u0026ndash;50% of rural household income among developing countries depends on rural non-farm activities, and this livelihood diversifying strategy is to reduce the risk associated with farm activities. Similarly, individually managed firms are more likely to be diversified, non-agribusiness-oriented, or entirely uninvolved in business ventures. Strong household networking with other returnees fosters business diversification. Etriya et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) emphasized that diverse networks have increased the performance of entrepreneurship and have more innovative ties and technology ties, which not only improve the innovativeness of entrepreneurship but also better financial performance. Moreover, networks have positive impacts on the performance of agribusiness owned by women in Ghana (Dossou et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Further, households with at least one member possessing agricultural skills beyond traditional knowledge are more likely to invest exclusively in agribusiness. Samuel and God\u0026acirc; (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) found that there is no significant difference between graduates and experienced farmers who have agriculture skills for entrepreneurship, which highlights the importance of skills required for entrepreneurial activities. We find that an increase in household asset value does not show any significant effect on the choice of businesses. However, Dzanku (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) found that there is a positive association between assets and livelihood diversification. Rising asset values do not necessarily lead to higher income, and non-farm activities in rural areas are also important because these activities help to diversify the income (Grzelak \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFurthermore, we also find that households that have access to subsidies in agriculture and access to formal credit are more likely to show interest in agribusiness, and Ding et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) in their study stated the importance of formal credit for return migrants. Further, Kolog et al. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) found that credit accessibility helps to diversify the livelihood of rural farm households. Additionally, financial accessibility, such as subsidies and formal loans, significantly increases the likelihood of agribusiness-only investment and reduces the probability of having no investment. Agrawal (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), in support of evidence-based policy development, emphasized that promotion of community-based financial institutions supporting credit and micro-credit is essential to ensure farmers\u0026rsquo; easy access to finance, while simultaneously expanding formal banking services, which support agriculture loans and government assistance, is of the utmost importance. Further, agricultural restructuring plays a crucial role in shaping household income, while the transformation of agriculture from a subsistence-based system to a market-based, commercial-oriented production is essential for strengthening the rural economy (Hu et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMoreover, Yu et al. (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) found that immigrant remittances support agribusiness investment and asset accumulation. However, in our study, households with migrated family members who are potential remittance receivers are not particularly interested in agricultural investment, although asset accumulation among returnee migrants and households with migrated family members is significantly higher. Thus, our study is both aligned with and contradictory to theirs in different aspects. From the above results and discussion, and from the different literature, the findings we obtained have both supportive and contradictory aspects. However, most studies highlight that migrants are less likely to engage in agriculture-related activities and are more reliant on the remittances they receive. This supports the idea that there is always a trade-off between choices, and in line with this, economic theories suggest that people behave rationally to maximize utility and welfare, which stimulates the efficient allocation of labor and resources.\u003c/p\u003e"},{"header":"6. Conclusion and Recommendation","content":"\u003cp\u003eThis study, when compared with existing studies, highlights the complex interplay of migration and investment decisions. Education, household composition, age of the household head, assets, and institutional support, such as government assistance, play an important role in shaping agribusiness engagement and diversification in rural Nepal. The empirical analysis shows that households with returnee members are more likely to invest in mixed businesses, although agribusiness-only investment is also a choice compared to other households. Return migrants emerge as a positive driver of business diversification, while households with members abroad are more closely associated with non-agribusiness activities or no investment rather than agribusiness investment, and this implies that remittance income is rarely reinvested in farming enterprises. This suggests that remittances primarily serve as a source of income rather than investment-based financing.\u003c/p\u003e \u003cp\u003eFurther analysis shows that returnees diversify businesses to cope with uncertainty in agribusiness. In contrast, households with migrant members are more persuaded toward non-agribusiness activities or choose not to invest in any agribusiness activities. Trade-offs among alternatives and rational household decision-making can explain this behaviour. In some cases, households may perceive themselves as better off without investing in any business, as remittances serve as a source of income. Moreover, household features also influence investment decisions. For example, as the age of the household\u0026rsquo;s head increases, the probability of investing exclusively in agribusiness decreases, and this echoes the physically demanding nature of agribusiness and the slow progress of agricultural mechanization. Moreover, farms with single ownership tend to be more diversified, as the risk-averse nature of small holders who seek to reduce vulnerability through livelihood diversification. Since individual farms are typically small in capacity, they are more inclined to engage in a combination of farm and non-farm activities. Additionally, households with a larger labour force are better positioned to pursue off-farm activities, which serve as an important strategy for livelihood diversification.\u003c/p\u003e \u003cp\u003eFurthermore, investing in agribusiness or diversifying business seems less favourable for female-headed households, which highlights the difficulties related to household work faced by women in rural areas. This underlined the difficulty faced by women in managing both household responsibilities and business activities simultaneously. Further, the importance of women's engagement in agriculture is highlighted by several studies and cannot be ignored. Until and unless the involvement of women in agribusiness seems less possible without a reduction in women's dodgery with effective policy ratification. Further, higher education levels, stronger networks, more active members, and access to credit are important household characteristics that illustrate a greater propensity for business diversification, underscoring the importance of human, social, and financial capital in rural entrepreneurship. Other household characters also play a critical role, as such, with larger families more likely to diversify income sources by engaging in both farm and non-farm activities.\u003c/p\u003e \u003cp\u003eAdditionally, subsidies and broader financial instruments are essential to support small and medium investors when they typically operate in rural areas. Hence, the Government of Nepal should focus on policies that support the economic integration of return migrants through entrepreneurship development. Returnee migrants serve not only as investors in agribusiness but also as key agents of business diversification, as multiple business activities can act as a form of self-insurance, allowing households to offset losses in one enterprise with gains in another, which serves as household resilience and income stabilization. Further, households with migrant members abroad are also potential investors and encourage them to diversify their livelihood strategy through policy endorsement, and such policies are as easy access to credit facilities, cooperative-based financing, and insurance services, because these investors are generally motivated by risk-aversion strategies. As returnees use diversification strategies to cope with uncertainty, government policies should support these strategies and endorse the policies that motivate migrant households to channel remittance resources toward business investment and diversification, thereby reducing the national economy\u0026rsquo;s dependence on remittances. Moreover, improved access to markets, market information, and market-related rural infrastructure is fundamental for promoting agribusiness in rural areas. Further, the government should prioritise the development of a dedicated institution to support returnee migrants.\u003c/p\u003e \u003cp\u003eFinally, it is important to note the geographical limitations of our study, as it was only conducted in two provinces of Nepal, covering the plain and hilly regions. We did not include the mountainous region primarily due to the resource constraints involved in reaching remote, sparsely populated areas. Additionally, the mountainous region has a distinct socioeconomic profile where, unlike in the surveyed areas, mostly livelihoods are driven by tourism and trekking rather than agribusiness activities studied here.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors contribution\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorresponding authors conceptualized the idea, collected the data, and wrote the original draft\u003cstrong\u003e;\u0026nbsp;\u003c/strong\u003econtributing authors supervised the research, helped in data curation and methodology, reviewed, and edited the draft.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe do not have competing interests regarding this paper and the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUse of AI tools\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eArtificial Intelligence (AI) tools were utilized in this manuscript solely for language editing, proofreading, and ensuring stylistic consistency.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data were collected in accordance with established ethical standards and codes of conduct. Although the study involved human participation through a household survey, it did not include any invasive procedures or the collection of biological samples, thereby posing minimal risk to participants. An ethical approval waiver was duly obtained from the Department of Agricultural Economics.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants were fully informed about the intended use of their data and the measures implemented to protect their confidentiality and privacy.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAdhikari J, Rai MK, Baral C, Subedi M (2023) Labor Migration from Nepal: Trends and Explanations. Migration in South Asia: IMISCOE Regional Reader. Springer International Publishing, Cham, pp 67\u0026ndash;81. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/978-3-031-34194-6\u003c/span\u003e\u003cspan address=\"10.1007/978-3-031-34194-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAgrawal S (2021) Return and Reintegration: Exploring challenges and opportunities of COVID-19 migrant returnees in small scale Agri-businesses. Daayitwa- Fusemachines Nepal Public Policy Fellow 2021\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ehttps://\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003c/span\u003e\u003cspan address=\"http://www.daayitwa.org/public/storage/archives/1657596970.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. 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Finance Res Lett 66:105619. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.frl.2024.105619\u003c/span\u003e\u003cspan address=\"10.1016/j.frl.2024.105619\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"humanities-and-social-sciences-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"palcomms","sideBox":"Learn more about [Humanities \u0026 Social Sciences Communications](http://www.nature.com/palcomms/)","snPcode":"41599","submissionUrl":"https://submission.springernature.com/new-submission/41599/3","title":"Humanities and Social Sciences Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Diversification, Entrepreneurship, Social-Networks, Non-farm Activities","lastPublishedDoi":"10.21203/rs.3.rs-9024066/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9024066/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn the context of globalization, while Nepal has benefited from foreign labor markets, it also faces challenges regarding the investment decisions of returning migrant workers after their return. This study examines household investment in agribusiness and livelihood diversification in rural Nepal using multinomial logit estimates based on data across eight districts from two provinces. The results indicate that return migrants strongly drive agribusiness investment, either exclusively or in combination with other businesses, whereas households with members currently abroad, although engaged in agribusiness, are more inclined toward non-agribusiness activities or no investment at all. This suggests that remittances are not properly reinvested in agribusiness, highlighting that remittances are mostly used for consumption purposes, and households with migrant members are better off without investing in agribusiness, thereby challenging assumptions that migration stimulates rural entrepreneurship. However, household education and networks promote diversification in businesses significantly, while agriculture-specific skills support sole agribusiness investment. Further, more active members, with greater labour force availability, are more likely to diversify through non-farm activities, and individually managed farms also diversify to reduce risks. In contrast, female-headed households are reluctant to invest in agribusiness despite being active in subsistence agriculture. In this context, policies should encourage returnee engagement in agribusiness, improve rural infrastructure, strengthen market linkages, and expand financial access to foster diversification and resilience in rural economies.\u003c/p\u003e","manuscriptTitle":"Assessing Agribusiness as an Investment Choice for Return Migrants in Rural Nepal","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-13 16:20:45","doi":"10.21203/rs.3.rs-9024066/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"73579282952359763038258184291449303442","date":"2026-05-01T05:42:47+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-07T05:50:52+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-31T04:08:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-25T09:32:05+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-23T13:35:27+00:00","index":"","fulltext":""},{"type":"submitted","content":"Humanities and Social Sciences Communications","date":"2026-03-23T10:20:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"humanities-and-social-sciences-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"palcomms","sideBox":"Learn more about [Humanities \u0026 Social Sciences Communications](http://www.nature.com/palcomms/)","snPcode":"41599","submissionUrl":"https://submission.springernature.com/new-submission/41599/3","title":"Humanities and Social Sciences Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"46a5e1a1-e876-4c3c-bd35-40c54458161f","owner":[],"postedDate":"April 13th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"73579282952359763038258184291449303442","date":"2026-05-01T05:42:47+00:00","index":35,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":66148416,"name":"Business and commerce/Economics"},{"id":66148417,"name":"Social science/Economics"},{"id":66148418,"name":"Earth and environmental sciences/Environmental social sciences"}],"tags":[],"updatedAt":"2026-04-13T16:20:45+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-13 16:20:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9024066","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9024066","identity":"rs-9024066","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}