Non-farm Enterprises Research Articles

MITIGATION OF FOOD INSECURITY IN ETHIOPIA: PERSONAL, HOUSEHOLD, AND REGIONAL DETERMINANTS

Food insecurity has plagued Ethiopia for decades. The objective of this study is determining which personal attributes, household features, income-generating undertakings, and regional location change the food insecurity of Ethiopian households updating past studies. Furthermore, the study quantifies the probability changes in a household being food insecure in response to changes in personal attributes, household features, income-generating undertakings, and regional location. The data from the 2021/2022 Ethiopian Rural Socioeconomic Survey have been applied to estimate coefficients using the logit technique and calculate the effects of explanatory variables. Results show that being a male household head, education, having non-farm enterprise, and access to electricity lower the likelihood of a household being food insecure. In contrast, the likelihood of being food insecure has been associated with the region where a household was located, or dependence on raising livestock. The regional discrepancies have been substantial. Broadening access to education, stimulating non-farm enterprise, and promoting economic development while accounting for regional differences will reduce the risk of household food insecurity.

A machine learning‐based exploration of resilience and food security

AbstractLeveraging advancements in remote data collection and using the Food Insecurity Experience Scale (FIES) as a proxy measure of resilience, we show that machine learning models (such as Gradient Boosting Classifier, eXtreme Gradient Boosting, and Artificial Neural Networks), can predict resilience with relatively high accuracy (up to 81%). Key household‐level predictors include access to financial institutions, asset ownership, the adoption of agricultural mechanization as evidenced by the use of tractors, the number of crops cultivated, and ownership of nonfarm enterprises. Our analysis offers insights to researchers and policymakers interested in the development of targeted interventions to bolster household resilience.

International remittances and labor supply in Nigeria: Do educational attainment and household income matter?

AbstractThe effect of remittances on the labor supply decisions of recipients remains a subject of contention. To contribute to the debate, we investigate how the educational attainment and household income of remittance recipients shape their decisions to work. Using data from the 2018–2019 living standard measurement survey for over 61,000 Nigerians and applying the instrumental variable probit and Tobit techniques, we find that remittances are associated with an occupational switch from agriculture to nonagricultural (paid jobs and nonfarm enterprises) works. Specifically, the results show that remittance recipients are more likely to exit or reduce the hours worked on the farm, regardless of educational attainment and household income status. On the other hand, remittances promote labor supply to paid jobs and nonfarm enterprises, especially among the less educated in Northern Nigeria. In terms of household income, the positive effect of remittances on nonfarm jobs only holds for individuals in the top income quartile, regardless of their region of residence. Our findings are robust to alternative estimation techniques and hold important cues for policymakers.

Technology application driven farmers’ income enhancement: Evidences for spatial, sectoral and social inclusiveness

Indian farmers have played decisive role in ensuring national food security, however issues about their economic security have been a matter of concern. The study conducted during 2022 with 3648 farmers in 29 districts of Karnataka, exhibited the possibilities for income enhancement through technology-supported productivity-driven, diversification and agri-entrepreneurship promoted by the Krishi Vigyan Kendras (KVKs). The composition of income, estimated through Simpson’s Index of Diversity, testify the inclusiveness in sources of household income. Income enhancement across agro-climatic zones corroborated for the spatial inclusiveness. Evidences across different landholding categories demonstrated the social inclusiveness. Horticultural sector contributed highest to absolute enhancement in farmers’ income, but farm and non-farm enterprises, fisheries and livestock had higher rate of growth. Technology uptake was the catalyser for income enhancement across the sectors. The results provide an empirical framework for stage I impact, driven by productivity enhancement, leading to diversification and entrepreneurship development.

Entrepreneurship and human capital development in children: The case of Tanzania

ABSTRACT This paper examines the contribution of household non-farm enterprises (NFEs) to human capital development in children, measured through child labour and schooling. We use nationally representative panel data from Tanzania and control for observed and time-invariant unobserved factors in pooled least squares and household fixed effects estimations. Both contemporaneous and dynamic analyses are performed separately for boys and girls and for different types of NFEs, including those with and without employees, as well as father- and mother-owned NFEs. We find that father-owned and NFEs without employees are associated with less child labour on average. The impacts on schooling are not consistently estimated, except for girls and father-owned NFEs. Less child labour among boys is associated with father’s NFEs and among girls with NFEs hiring employees. Our findings indicate that NFEs may contribute to reducing the child labour problem, but they may be insufficient for resolving low school attendance.

Gendered Effect Of Non-Farm Enterprises On Household Clean Energy Adaptation In Sierra Leone

Gendered Effect Of Non-Farm Enterprises On Household Clean Energy Adaptation In Sierra Leone

Participation and returns from informal service-oriented non-farm enterprises: Evidence from a survey of Nigerian households.

We investigate the factors that influence the selection and productivity of informal service-oriented family enterprises in Nigeria. Using nationally representative micro-data from the Nigerian General Household Survey (2010-2015), we employed random-effect probit and selectivity-adjusted regression models to estimate and analyze the results. The findings reveal that the location of informal Non-Farm Household Enterprises (NFHEs)-whether home-based or non-home-based-significantly impacts the wholesale, retail, personal, and consultancy service sectors operated by informal NFHEs. This impact remains significant even after accounting for variations in individuals, households, or locational characteristics. Furthermore, when considering selectivity in the earnings equation, we found that home-based informal enterprises exhibit lower productivity compared to non-home-based enterprises, a difference that varies across sectors. Overall, factors such as the gender of business owners, educational levels, geopolitical zones, infrastructure, and business characteristics play a crucial role in determining the locational and productivity disparities among service-oriented enterprises in Nigeria. Key recommendations stemming from this study include addressing gender-based segregation and economic disparities, prioritising financial inclusion for small business development, bridging infrastructure gaps, and implementing policies that acknowledge and bolster the informal sector.

Nexus between participation in nonfarm enterprises and poverty among rural farm households: evidence from Nigeria

PurposeDespite a reduction in poverty the global population in 2015, the incidence of poverty remains very high in Sub-Saharan African countries. Most of the countries in the region are agrarian, with most of their population residing in rural areas, and a majority of the poor in the region are found in Nigeria. This study examined the nexus between participation in nonfarm enterprises (NFEs) and poverty among rural farm households in Nigeria and across the six geopolitical zones.Design/methodology/approachThe Nigerian Living Standard Survey (NLSS) conducted in 2018–2019 by the National Bureau of Statistics was used. We made use of 13,440 farm households with useful information for the purpose of this study. The sample comprises 6,885 households that participated in NFEs and 6,555 nonparticipating households. The data were analyzed with Foster, Greer, and Thorbecke (FGT) (1984) metrics, probit, and fractional probit models at p = 0.05.FindingsThe incidence of poverty was lower among the participating households than in the nonparticipating households. Participation in NFEs had a mitigating effect on poverty. We also established that zonal differentials in poverty rates exist among households in all the analyses. Participation in NFEs was influenced by individual, household, and institutional factors and was also able to explain the depth of poverty among the respondents.Practical implicationsIt is suggested that poverty alleviation policies should be targeted at improving access to nonfarm economic activities by rural farm households residing in vulnerable geopolitical zones.Originality/valueThis study is the first attempt to profile household poverty based on the type of NFEs they are involved in. The study also provides an insight into the effect of the state of residence on zonal poverty models, which is expedient if the country must achieve Sustainable Development Goal 1 on the eradication of poverty everywhere.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-06-2023-0493

Rural Nonfarm Enterprise and Its Impact on Household Livelihood in Ethiopia: Evidence from Gurage Zone

Rural Nonfarm Enterprise and Its Impact on Household Livelihood in Ethiopia: Evidence from Gurage Zone

Households’ entry into non-farm entrepreneurship and the market exit of enterprises in rural Ethiopia

Purpose This paper examines household and community characteristics that influence the entry of rural households into non-farm entrepreneurship and investigates the various factors that influence the market exit of non-farm enterprises (NFEs).Design/methodology/approach The authors use data from three rounds (2011/12, 2013/14 and 2015/16) of the World Bank’s Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). The authors employ panel logit and multilevel logit models to examine the probability of opening one or more enterprises and the enterprise exit rates.Findings Results indicate that the likelihood of starting a NFE is positively associated with primary education attainment, access to credit, experiencing idiosyncratic shocks and availability of formal financial institutions. Age, higher education attainment and rising farm input prices constrain entry into non-farm entrepreneurship. The enterprise exit rate is negatively associated with small-town residence, wealth, access to tar/gravel roads and cellphone communication.Practical implications Policymakers and administrators should strive to address the challenges that communities face in transportation, communication and financial services. Policies aimed at stabilizing prices and increasing access to mobile communication, primary education and road infrastructure could help expand the rural non-farm sector.Originality/value Previous studies primarily examined the determinants of participation in NFEs at a given time using cross-sectional data. The current study uses panel data to study the dynamics of NFE ownership by investigating households’ decisions to enter into or exit from the sector.Peer reviewThe peer review history for this article is available at https://publons.com/publon/10.1108/IJSE-09-2022-0611

The effects of the Indonesian conditional cash transfer program on transition out of agriculture

This study evaluates the effect of a conditional cash transfer (CCT) on the structural transformation process in a developing economy. It uses randomized control trial (RCT) data from Indonesia’s Conditional Cash Transfer program, the Family Hope Program (PKH), to examine whether the PKH program has a significant impact on whether or not agricultural households have moved to other sectors after six years of implementation of the program. The estimates reveal modest impacts of the PKH program on diversification of livelihoods outside agriculture. The treatment group has a 28 percent higher participation in nonfarm wage employment and a 23 percent higher rate of employment in a nonfarm enterprise (NFE) compared to the control group. The heterogeneous impact analysis reveals that distance from a market is a major factor in determining the type of non-agricultural employment. Individuals in households with only a small amount of land who reside near a market are more likely to be casual workers, while individuals in households with only a small amount of land who reside far from a market are more likely to have an NFE. Interestingly, participation in a CCT program has larger effects on households residing in nonindustrial areas than in industrial areas, in terms of both nonfarm wage employment and employment in a nonfarm enterprise.

Enterprise Informality in India: The Blind Spots in Public Policy

AbstractAn essential characteristic of firm size distribution patterns in developing countries including India, is a bimodal distribution with a “missing middle”, which is widely accepted in development economics. We analyse data from the Annual Survey of Industries (ASI), National Sample Survey (NSS) and Economic Census to assess the firm size structure of the whole non-farm sector. The contribution of the paper is that for the first time a comprehensive database is constructed to enable analysis of the size structure of India’s non-farm enterprises. The second contribution is that we find a deep distortion in India, with even a “small”-scale sector being very small, relatively. We examine briefly the policy-related causes that make India an outlier even among Asian economies in respect of size structure of enterprises. Finally, we argue that the historically policy-induced informality of enterprises is being entrenched by the current hiatus in state policy in even recognising the true nature of the problem of micro, small & medium enterprises (MSMEs), which holds back both their growth and employment.

Social Protection and Rural Transformation in Africa

This article develops a conceptual framework on pathways through which noncontributory social protection can support resilient and inclusive agricultural growth in rural Africa. It draws insights from a review of rigorous empirical evidence on the impacts of cash transfers and multifaceted cash plus programs on a range of relevant productive outcomes, including accumulation of productive assets, inputs and farm management practices, off-farm labor and nonfarm enterprises, and farm production and income. This review demonstrates an emerging consensus in the literature: that access to social protection programs contributes positively to increasing the productive asset holdings of rural people, increasing the use of improved inputs and farm practices, and shifting away from casual wage labor arrangements. Moreover, there is limited evidence on heterogeneous effects across different baseline characteristics (income, sex, and labor-constrained households, among others). Finally, the article highlights how social protection programs should be considered an integral part of broader rural and agricultural development strategies in order to achieve a more productive, resilient, and equitable rural transformation in Africa.

The influence of COVID-19 pandemic and coping strategies on work operation of nonfarm household enterprises in Nigeria.

The purpose of this study is to investigate how COVID-19 pandemic including some coping strategies such as hand wash with soap and food consumption influences work operation or performance of nonfarm household enterprises (NHEs) in Nigeria using 2020 Living Standard Measurement Survey data of 1728 sample size. This study departs from existing study in two ways: first, the study employs multinomial logistic regression technique to ascertain the determinants of work performance of nonfarm household enterprises in Nigeria. Second, the study focuses on nonfarm enterprises such as petty trade, road side automobile and cab drivers. The results show that COVID-19 pandemic is significant with negative influence on the work operation of NHEs in Nigeria. The result of the study also reveals that coping strategy such as hand wash with soap during the pandemic is an important driver of work performance or operation of NHEs in Nigeria. Another coping strategy like food consumption by nonfarm household enterprises shows insignificant influence on work operation which implies that there is no relationship between food consumption and work operation by NHEs in Nigeria. The policy recommendation of this study, among others, is that policies should focus on procurement of sanitary material for public use. This can be achieved through public sensitisation in terms of organising workshops and conferences.

What influences village-level access to a bank branch? Evidence from India

PurposeFinancial access is key to achieving several economic goals in developing countries. This paper aims to construct a longitudinal village-level measure of financial access in India and understand the role of RBI's policies and village characteristics in influencing the access.Design/methodology/approachThe authors adopt a spatial approach in developing a metric of financial access. In particular, they measure the distance of each unbanked village in India to the nearest banked-centre from 1951 to 2019. The authors use this measure to conduct two exercises. First, a descriptive study is undertaken to assess how RBI's policies on bank branch expansion from 1951 to 2019 influenced the proximity to bank branches. Second, the authors conduct regression analyses to investigate how socio-economic and demographic characteristics of villages influence their proximity to bank branches.FindingsThe average distance of an unbanked village to the nearest banked-centre has declined from 43.5 km in 1951 to 4.2 km in 2019. The gain in bank access has varied geographically and over time. In 2001, bank branches were relatively distant from villages with under-privileged caste groups and proximate to areas with better infrastructure. This relationship worsened after 2005 when RBI introduced liberalized branch expansion policies. By 2019, proximity responds much more adversely to the presence of underprivileged groups. At the same time, banks have moved closer to economically better-off villages and villages with workforce in non-farm enterprises rather than agriculture.Originality/valueFirst, studies in the Indian context focus on state-level determinants of bank branching, this is the first study to develop a longitudinal measure of financial access at the village level. This helps to understand spatial heterogeneity in bank branch access within states, which other studies are unable to do. Second, the paper analyses the role of village-level socio-economic and demographic characteristics in proximity to bank branches. This analysis helps in discovering micro-foundations of growth of bank branch network. The granularity of the approach adopted here overcomes the confoundedness problems that the studies at a more aggregate level face.

Spending pattern and profit performance: A case study of nonfarm household enterprises in Nigeria

Spending pattern and profit performance: A case study of nonfarm household enterprises in Nigeria

Determinants of Livelihood Diversification of Farm Households in Rural India: Evidence From National Sample Survey

The lives of rural households are predominantly based on agriculture and its allied activities. However, there are signs of an agricultural crisis resulting in dependence on alternative sources of income. This paper analyzes the factors that influence the decision of farm households to participate in non-farm activities for alternative income. The official data for two years on the Situation Assessment Survey of Agricultural Households are explored and a pooled probit regression model is run to examine the determinants of income diversification. Our findings reveal that farm income and irrigated land negatively influence diversification. However, diversification of those having lower access to farm holdings, socioeconomic deprivation, and improved access to education, informal credit, and crop insurance point out positive participation in non-farm enterprises. In addition, the population belonging to hilly and coastal plain regions and the age group 30–64 years are more likely to diversify.

Hybrid livelihoods: Maize and agrarian transformation in Southeast Asia's uplands

Hybrid maize farming has boomed across upland Southeast Asia in the past three decades. Recent studies suggest that the boom has resulted in diverse outcomes across countries. In Thailand, Vietnam, and Laos, the introduction of hybrid maize has often initially been linked to rising incomes and living standards, with little loss or concentration of landholdings. In contrast, recent studies from Myanmar argue that exploitative trader-farmer credit relations are driving rapid agrarian differentiation and dispossession. We analyze patterns of agrarian change associated with hybrid maize farming in southern Shan State, Myanmar, using data from a representative survey of 1562 rural households. Widespread farmer engagement in maize cultivation has contributed to deepening petty commodity production and some economic differentiation, but with little dispossession or negative impacts on food security. Credit provision by traders may benefit some larger farmers but does not actively penalize smaller producers. Hybrid maize is a ‘moderate risk, moderate reward’ crop that households integrate strategically into a broader patchwork of subsistence farming, higher risk cash crop production, and a growing mix of off-farm activities. Employment in non-farm enterprises, salaried work, and migration have significant potential to modify trajectories of differentiation associated with agriculture.

Determinants of Household Poverty in Ethiopia

ABSTRACT The purpose of this study is to investigate the determinants of household poverty in Ethiopia. The study used the national survey data collected by the World Bank during the second phase in 2014. The study employed a binary logistic regression model to identify the determinants of household poverty. Results show that educational level of the household head, family size, dependency ratio, residence of the household, the region in which the household resides, ownership of non-farm enterprises (construction), economic status of the household (high), source of start-up enterprises (credit and saving institutions), and lack of supporting institutions were the factors affecting the probability that a household is poor.

Poverty and Its Correlates among Kenyan Refugees during the COVID-19 Pandemic: A Random Effects Probit Regression Model

Poverty remains a major problem among refugees, and the COVID-19 pandemic seems to have exacerbated its incidences. In Kenya, although refugees ordinarily face serious economic conditions, COVID-19 worsened their economic status. The objective of this paper was to analyze the determinants of poverty dynamics among Kenyan refugees during the COVID-19 pandemic. The data were the COVID-19 rapid response panel data that were collected between May 2020 and June 2021 by the Kenyan National Bureau of Statistics (KNBS), the United Nations High Commissioner for Refugees (UNHCR) and the University of California, Berkeley with technical assistance from the World Bank. The random effects probit regression model was used for data analysis using the absolute and relative poverty lines. The results showed that, using the Kenya’s national poverty lines, 73.03% of the respondents were poor across time, while there was a steady decline in poverty incidences from 76.55 in July–September 2020 to 68.44% in March–June 2021. The results further showed the presence of significant heterogeneity, thereby justifying the panel estimation approach. Poverty significantly declined (p < 0.05) with receipt of food assistance, remittances, gifts, amount of loan, amount realized from sale of assets and agricultural enterprises, while it increased with education, household size, non-farm enterprises, residence in urban areas, and at the Kakuma, Kalobeyei and Shona camps. It was concluded that welfare deprivation among refugees during COVID-19 is pathetic, and post-COVID-19 recovery should, among other things, take cognizance of place and camp of residence, and access to some form of socioeconomic support.