Endogenous Switching Regression Model Research Articles

Credit Constraints on Farm Household Welfare in Rural China: Evidence from Fujian Province

This study investigates the effect of demographic factors on formal and informal borrowing households in rural Fujian Province. The study tests whether credit constraint affects rural farmers’ welfare in the studied region, using a probit regression and endogenous switching regression model to analyse data collected in 2017 from 960 farm households. Analysis shows that age, poverty, household size, and farmland size operate to constrain credit in formal borrowing. Results also indicate that level of education, farm land size and age have significant impacts on rural household borrowing from informal sources. The results from the endogenous switching model approach suggest that credit constraint does have a significant impact on rural farmers’ consumption and welfare in Fujian province.

Land Ownership, Youth and Agricultural Performance Among Maize Farmers in Republic of Benin

Access to land plays a major role in the low performance of the food production system in developing countries. The present study analysed the effect of land ownership on young and old farmers’ performance and the potential yield difference among the two groups by using Endogenous Switching Regression Model, based on a random survey of 354 maize farmers. One-third of the farmers interviewed were young. Availability of family land and experience in farming affected young and old farmers differently. Old farmers who have personal or family land ownership have higher yield compared to farmers who rent their farms. Land ownership did not affect the youth yield, meaning only the availability of the land is important for youth, the incremental cost of getting the land does not matter. Land ownership is important in farmers’ performance; therefore, government should take measure to protect agricultural land against land grabbing.

Productivity and production risk effects of adopting drought-tolerant maize varieties in Zambia

PurposeProductivity and production risks affect the use of agricultural production practices and inputs, particularly in developing countries. This paper aims to investigate the effects of adopting drought-tolerant maize varieties (DTMVs) on farm productivity, yield variance and downside risk exposure of maize growing households of Zambia.Design/methodology/approachThe study uses household survey data collected from 11 maize producing districts of Eastern, Southern and Copperbelt provinces of Zambia using a structured questionnaire. The Antle’s flexible moment-based approach was used in specifying, estimating and testing a stochastic production function. The study further applied an endogenous switching regression model to control for both observable and unobservable sources of bias.FindingsThe study revealed that DTMV adoption increases maize yield by 15 per cent and reduces the risk of crop failure: reducing yield variance by 38 per cent and exposure to downside risk by 36 per cent.Originality/valueThis study establishes the benefits of DTMV adoption in Zambia with regards to productivity, yield stability and downside risk in the face of climate change. Results from this study underscore the need for more concerted efforts to scale-out DTMVs for both maize productivity enhancement and for risk mitigation against weather shocks.

Farm Machine Use and Pesticide Expenditure in Maize Production: Health and Environment Implications.

Although chemical pesticide use has increased agricultural productivity, it has caused adverse effects on human health and the environment. For example, pesticide exposure may result in the incidence of a human health condition (e.g., heart disease, immune disorders, cancer, and damaged skin) and it can pollute air, water, and soil conditions and damage biodiversity. Mitigating the negative externalities associated with pesticide use is essential to improve human health and environmental performance. In this study, we are trying to explore whether farm machine use reduces pesticide expenditure by analyzing farm household survey data collected from 493 maize farmers in China. An endogenous switching regression model is employed to address the sample selection bias issue associated with voluntary farm machine use. The empirical results reveal that farm machine use exerts a negative and statistically significant impact on pesticide expenditure. The findings highlight the important role of farm machines in helping reduce pesticide expenditure, which is, in turn, beneficial for improving human health conditions and environmental performance.

Inclusiveness and effectiveness of agricultural cooperatives: recent evidence from Ethiopia

PurposeUsing a recent rural farm household survey, the purpose of this paper is to investigate inclusiveness and effectiveness of agricultural cooperatives in Ethiopia.Design/methodology/approachThe study employs a logit model to examine inclusiveness and an endogenous switching regression (ESR) model to evaluate the effectiveness of agricultural cooperatives.FindingsThe results show that agricultural cooperatives are less inclusive of land-poor and illiterate households. On the other hand, the estimated results indicate that cooperatives effectively improved agricultural performance and welfare of its member households – i.e. membership in cooperatives increases yield and income by 1.37 quintal/hectare and 1,804 birr, respectively. Moreover, the result shows that marketing cooperatives effectively increased marketed surplus of their members by 34 percent.Research limitations/implicationsThe study has important implications regarding the ways to improve the effectiveness and/or inclusiveness of agricultural cooperatives.Originality/valueWhile accounting for the collective behavior of cooperatives, this study uses multiple outcome variables in examining the effectiveness of cooperatives in Ethiopia. Furthermore, this paper employs the ESR model and accounts for potential problems in estimating impact using non-experimental data.

Heterogeneous credit constraints and smallholder farming productivity in the Senegal River Valley

ABSTRACT Credit constraints come in various forms, to the extent that they translate ex ante into market entry barriers (mostly transaction cost, price, and risk constraints) or ex post into credit application rejection (quantity constraints). This article is concerned with the underlying generating mechanisms of such heterogeneity in credit constraints and the implications for farmers’ productivity in the Senegal River Valley. Results from an endogenous switching regression model based on farm-level data indeed indicate that both pre- and postapplication constraints are holding back farmers’ performance, with differential impact depending on whether the latter is based on the average treatment on the credit beneficiaries or on the nonbeneficiaries and on the productivity measure. This is in addition to significant differences in the generating factors of market entry barriers and credit application outcome. These results are suggestive of various policy options that would not only increase market participation and bring about its beneficial impact, but also contribute to improve smallholder farmers’ credit-worthiness.

An Empirical Assessment of the Impact of Access to Credit on Farm Output: A Case Study of Sefwi-Wiawso Municipality Ghana

The study examined the socio-demographic features of farmers and credit accessibility in the Sefwi-Wiawso Municipality Ghana. It also identifies the sources and factors influencing access to credit in the Sefwi-Wiawso Municipality. Primary data were obtained from 1,200 households and farmers within the Sefwi-Wiawso Municipal. The empirical analysis employed a logistic regression technique, the Tobit model and Endogenous Switching Regression Model (ESRM) to explore the accessibility of credit on productivity in the agriculture sector. The results revealed that age and gender are statistically significant in determining access to credit from both the logit and the endogenous regression models. The endogenous switching regression model further reveals that educational status, land ownership, access to knowledge on credit significantly influences the amount of credit received by a particular farmer within the Sefwi-Wiawso Municipality. These findings have practical implications for the modernizations of the Agriculture sector in Ghana. It is therefore important for various stakeholders to increase financial literacy among farming communities and the financial institutions to increase the credit accessibility by the Agriculture sector. It is therefore recommended that extension services provision, diversification of agriculture production and easy access to credit from financial institutions in the Municipality be established to ensure increased agriculture production.

Rural Credit Constraint and Informal Rural Credit Accessibility in China

This paper investigates the effects of rural households’ demographic characteristics on formal credit constraint, and explores the relationship between informal and formal lending in rural China. Using 2013 China’s Household Finance survey data, the authors apply probit regression models to investigate the effects of demographic factors on formal credit constraint and the household’s decision to borrow from informal credit sources. In addition, the endogenous switching regression model is applied to evaluate the impact of credit constraint on the welfare of rural farm households. The empirical evidence confirms that age, family size, annual household nonagricultural income, level of education, and history of informal borrowing have significant influence over credit constraint. Moreover, annual household nonagricultural income, the presence of children, borrowing from social networks and monthly communication expenses significantly impact rural households’ decision to utilise informal borrowing. Results from the endogenous switching regression model suggest that credit constraint by formal credit sources has no impact on household consumption.

Impact of green control techniques on family farms' welfare

Using survey data of 375 family farms in five provinces of the Huang-Huai-Hai Plain, this paper conducts a comprehensive measurement of family farms' welfare within the framework of the capability approach theory. Furthermore, using an endogenous switching regression model and a multinomial treatment effects model, this paper evaluates the impact of the adoption or non-adoption of green control techniques on family farms' welfare and estimate the welfare effects of the degree and timing of adoption. This research finds that the average treatment effect on family farm welfare with and without adopting green control techniques is significant, at 0.084 and 0.046, respectively. Therefore, green control techniques help to improve the welfare level of family farms. Compared with family farms that do not adopt green control techniques, the welfare level of family farms adopting a high or low degree of green control techniques increases by 22.63% and 16.42%, respectively, and the welfare level of family farms given the early or late adoption of green control techniques increases by 5.87% and 7.57%, respectively. Therefore, the welfare effect of a high degree of adoption on family farms is greater, and the welfare level of family farms with late adoption is higher.

Impact of Credit Demand on the Productivity of Rice Farmers in South West Nigeria

Employing cross-sectional data from 360 rice farmers selected from three states in South West Nigeria, the study analyzes the impact of credit demand on the productivity of rice farmers. An Endogenous Switching Regression Model (ESRM) that accounts for both heterogeneity and sample selection biases were used to estimate the impact of credit demand on rice productivity in South West Nigeria. In addition, a Tobit regression model was employed to measure the level of participation of rice farmers in the credit market. The result of the first stage (probit model) of the ESRM revealed that household assets, access to service, climate variables, regional variables, and transaction cost are statistically significant in influencing farmers’ credit demand decision. The results of the second stage of the ESRM indicate factors such as household assets and access to service were statistically significant in explaining variations in rice productivity among participants and non-participants in the credit market. Furthermore, the results of the Tobit model showed that the farmers’ location income from rice farming experience, interest rate, and distance to the source of credit are statistically significant determinants of the amount of credit received. These findings suggest that facilitating farmers’ access to credit will improve rice productivity. Therefore, it is imperative for government and development partner to work together in order to improve the conditions for suitable agricultural credit access to rice farmers, especially a review of interest rates. A necessary addition should be developed to the assistance already being provided under Nigeria Incentive-Based Risk Sharing System for Agricultural Lending (NIRSAL) in the form of loan guarantees and other risk-sharing incentives, such as a regulatory environment that supports the modern contractual obligations that are characteristic of well-functioning agricultural financing. This would not only contribute to the intensification of rice production in Nigeria to meet its increasing rice demand, but also improve rice farmers’ productivity and their households’ incomes.

Fertilizer Subsidy and Rice Productivity in Ghana: A Microeconomic Study

Across Africa, agricultural productivity continues to decline due to poor soil fertility. Smallholder farmers have less access to fertilizers to improve yields. Past and present governments in Ghana have made some efforts to raise productivity and to deepen the economic and social potentials of the agricultural sector by implementing fertilizer subsidy programs. Using data from 543 smallholder rice farmers in northern Ghana, we estimated both endogenous switching regression and treatment effect models to examine the factors that influenced participation in fertilizer subsidy programs, and rice productivity differences among beneficiary and non-beneficiary farmers. This was to address heterogeneity and biases stemming from unobservable characteristics at farm and farmer levels. Farmers’ participation in fertilizer subsidy programs was influenced by age, sex, education, farm size, membership of Farmer-Based Organization (FBO), access to media, knowledge of integrated soil and water conservation (SWC) practices, farm to market distance and herbicides application. Productivity of rice was mainly influenced by age, knowledge of integrated SWC, seed and herbicides usage. The outcomes from the treatment effect model revealed a negatively and significant effect of fertilizer subsidy on rice productivity. It is recommended that ways to improve the effectiveness of the fertilizer subsidy policy and distributional mechanisms to farmers should be given much attention to unlock the agricultural potential of Ghana.

Adoption and Impact of the Improved Fallow Technique on Cotton Productivity and Income in Zambia

An improved fallow is a soil fertility agroforestry technique that has commonly been used in the staple maize production systems of Zambia and sub-Saharan Africa. Several studies have assessed the adoption and impact of the improved fallow on maize production. Generally, it has been observed that though the improved fallow does increase maize yields, its efficacy on welfare in terms of increased income is low. The use of the technique on cash crops that could significantly contribute to household welfare has rarely been investigated. This study assessed the factors affecting the adoption and impact of improved fallows on a commonly grown cash crop, cotton, in the cotton growing provinces of Zambia. The study used a sub sample (N=1206) of the nationally representative 2014/15 Rural Agricultural Livelihoods Survey (RALS) data which was randomly collected by the Indaba Agricultural Policy Research Institute (IAPRI) and Central Statistical Office (CSO) of Zambia. The determinants of improved fallow adoption among the cotton farmers were examined through the use of the probit model while the impact of the technique on cotton production and income was evaluated by using the propensity score matching and the endogenous switching regression models. Among the socioeconomic factors significantly increasing the probability of improved fallow adoption included: increases in age, education level, and per capita productive assets of the farmer, in addition to the area under cotton production and the distance of the homestead to the market. Institutional factors found to increase the farmer’s likelihood of adopting the improved fallow in the cotton production systems included; farmer membership to a cooperative, receiving improved fallow seedlings from the government projects and having information on agroforestry tree species. On the other hand, an increase in land size per capita was found to negatively affect the likelihood of improved tree fallow adoption. Impact estimates showed significant cotton yield and income increases as a result of adopting the technique. The continuous provision of information on relatively new techniques such as the improved fallows preferably in farmer organized groups, and support towards the provision of the technique’s planting materials are some of the areas requiring government and NGOs attention. In addition, the study recommends that the farmers’ formal education level should be enhanced and that improved tree fallows should also be explicitly promoted on cash crops that have similar agronomic requirements to maize such as cotton.

Teleworkers in Italy: who are they? Do they make more?

PurposeThe purpose of this paper is to investigate the determinants of the probability of being a teleworker and the extent of earnings differentials between teleworkers and traditional employees.Design/methodology/approachThe analysis is grounded on a theoretical framework depicting endogenous telework assignment and wage variations based on individual bargaining. The empirical strategy allows for non-random telework assignment, generating from individual- and job-specific observed as well as unobserved factors.FindingsResults are based on the Italian labor force survey and uncover a key role of gender, higher education and family composition as determinants of the probability of teleworking. Furthermore, teleworkers enjoy a wage premium ranging between 2.7 and 8 percent.Originality/valueAccounting for observed individual and job-specific effects, by both standard linear regression and propensity score matching, largely reduces the extent of wage premium emerging from unconditional descriptives; the results of an endogenous switching regression model however suggest that failing to properly care for unobserved factors leads to the underestimation of returns to telework.

Impact of traditional versus modern dairy value chains on food security: Evidence from India’s dairy sector

The Indian government has made significant efforts to promote dairy cooperatives to link the milk producers with consumers. Despite this, milk marketing is still dominated by traditional outlets. This paper examines the impact of modern dairy value chains on food security indicators such as net returns from dairying and consumption expenditures. Using a large, national, farm-level dataset from India and a multinomial endogenous switching regression model, results reveal that Indian dairy farmers’ integration with the modern dairy value chain has a positive and significant impact on their food security (measured by net returns and household consumption expenditures). Participation in modern milk-marketing outlets significantly increases net returns per year, regardless of whether farmers choose one outlet or a combination.

Investment Sensitivity to Inter-enterprises Payment Deadlines

This paper investigates the determinants of firms investment financing constraints. Using an endogenous switching regression model on French Provence-Alpes Cote d'Azur region firms data collected between 2005-2014, we provide a novel evidence of the role of inter-enterprises payment deadlines which are days receivable outstanding and days payable outstanding, as factors determining rms investment nancing constraints. We also show that there is a non-negligible number of firms switching each year either from constrained regime to unconstrained regime or unconstrained regime to constrained one. By developing a model, we highlight the factors determining firms regime change.

Effect Of Credit Constraints On Intensity Of Fertilzer Adoption And Agriclutural Productivity In Amhara Region, Ethiopia: An Endogenous Switching Regression Analysis

Access to finance to the rural households is a powerful intervention to facilitate the adoption of farm inputs and boost agricultural productivity in developing countries like Ethiopia. Credit constraints limit the ability of households to use inputs at optimal level and thereby stifles agricultural productivity. However, evaluation of the impact of credit constraints on agricultural technology adoption and productivity have faced methodological problems and most of the existing studies have failed to explicitly measure and analyze the amount of productivity loss and the magnitude increase in intensity of fertilizer adoption if the farm households are found credit unconstrained. This study has examined the possible effect of credit constraint on the intensity of fertilizer adoption and productivity among households who vary in their credit constraint status. The study used cross sectional farm household level data collected in 2013 from 1165 randomly sampled households. An endogenous switching regression model is used for analytical purpose so as to account for selection bias and heterogeneity problem. The result evidence that intensity of fertilizer adoption and agriculture productivity would be higher among farm households who are found to be credit unconstrained. The result revealed that factors that affect the intensity of fertilizer adoption and agriculture productivity among credit constrained farm households are different from their counterparts. Age and age square of the household head, primary cooperative membership, number of Oxen, ownership of TV, hired labor as dummy and use of manure have significant effect on the intensity of fertilizer adoption among credit unconstrained regimes. Whereas, household size, altitude of land, ownership of land, way of land cultivation, and being risk averse household have significant effect on the intensity of fertilizer adoption in the credit constrained regimes. The result shown that size of land has negative and significant effect on the intensity of fertilizer adoption in the constrained regime while it has positive and significant effect on the intensity of adoption in the unconstrained regime. Age and age square of the household head, TLU, hired labor as dummy are the factors that significantly affect the productivity in the unconstrained regimes. The number of oxen and distance of farm land from residence also affect the productivity. Land size has found the significant and negative effect on the productivity in the constrained regime, but it has the positive and significant effect in the credit constrained regime. The policy implication is that the policy makers should account the credit constraint heterogeneity among farm households when they design agricultural policy to increase intensity of fertilizer adoption and thereby boost productivity of agriculture.

Analysis of Taxpayers’ Intention to Use Tax E-Filing System in Tanzania: Controlling for Self-Selection Based Endogeneity

This paper aims at analysing factors that influence taxpayers’ intention to use electronic tax filing system. The paper employs Technology Acceptance Model (TAM) framework. We first estimated traditional TAM model using OLS. Using econometric tests we observed self-selection endogeneity bias in intention to use e-filing system. To account for this bias we estimated endogenous switching regression model. Results of endogenous switching model show that risk, social influence and performance expectancy have significant effects on intention to use e-filing. Further, we found that these factors affect users and non-users intentions differently, calling for differentiated strategies in influencing e-filing use intention. Lastly, we recommended both administrative and technical issues to be considered for enhanced intention to use and adoption of e-filing system.

Effect of off-farm work on agricultural productivity: empirical evidence from northern Ghana

Abstract. In recent years, there has been increasing recognition of the importance of income diversification to agrarian households in developing countries. Empirical evidence of the effect of farm household income diversification on agricultural productivity remains scanty and inconclusive. An important policy question concerns the effect that farmer participation in off-farm work has on agricultural productivity. This paper answers that question by examining the factors that explain the decision of farm household heads to work off-farm and how this impacts farm productivity using a sample of 300 rice producing households in northern Ghana. Endogenous switching regression model supported by a treatment effect model was used to empirically assess the effect of off-farm work on agricultural productivity. Results show that engagement in off-farm work has a robust and positive impact on rice productivity. Farmers’ choice to work outside the farm thus contributed significantly to rice productivity of smallholders, confirming the role of income diversification in contributing to agricultural productivity of agrarian households.

Economic Impact of Improved Cattle Feeding Practice on Performance Dairy Farms and Household Welfare in Northern Ethiopia

In this paper, efforts were made to estimate the impact of stall feeding (SF) technology on households’ milk production and consumption, market participation as well as land conservation in rural Northern Ethiopia using data obtained from a survey of 518 rural farmers. Using endogenous switching regression models, we estimate different outcome indicators for both adopters from adopting SF (ATT), and non-adopters had they adopted (ATU). The values of ATT and ATU show that SF adoption increased milk production, consumption expenditure, number of plantation and of physical construction, propensity of participating in animal market sale and growing trees in their plots.

Analysis of maize biomass use in Ethiopia and its implications for food security and the bioeconomy

Using Ethiopia’s maize production as a case study, this paper examines the uses of maize biomass as a bioeconomy crop, and its implications and challenges for household food security. In the context of this study, bioeconomy refers to the production and utilization of biological resources or biomass to provide products, processes and services. The study followed a mixed methods approach that involved a household survey covering 322 randomly selected farmers, key informant interviews and focus group discussions in Ethiopia. We examined the implication of intensity of biomass use on farm household food security using an endogenous switching regression model. The study found multiple areas of use of maize biomass, although many of them were underdeveloped and underutilized. Model results further showed a positive and significant effect of diversification of use of biomass on the food security of farm households. Raising the quantity of maize biomass is important to enhance farm household food security as it allows farm households to increase the amount of biomass allocated for individual use and also to use it for diverse purposes. Yet, a broad set of factors including lack of market access, limited information and extension support on the uses of biomass, and a lack of biomass value-adding technologies have restricted the full potential of biomass utilization. Therefore, this study highlights the importance of provision of these factors in order to unlock the potential of biomass for food security and advance the development of the bioeconomy.