Switching Regression Research Articles

The welfare impact of improved seed variety adoption in Ghana

Despite government support to boost domestic production, tomato consumption in Ghana is heavily dependent on imports. Improved tomato seed varieties (ITSV) are considered inputs to increase productivity, but their contribution to household welfare is quite unknown. We examined the impact of ITSV adoption on household welfare in three agro-ecological zones of Ghana. Primary data was collected from a random sample of 508 tomato farmers using a semi-structured questionnaire. The study corrected for endogeneity bias in farmer adoption decisions using the multinomial endogenous switching regression model. The results show that the farmers' adoption of the improved varieties (Pectomech, Power Roma or both) was high and significantly influenced by sex, farm income, extension contact, credit access, perception of varietal characteristics (mainly yield), and farmers' residence in FSTZ, compared with the local variety (“Techiman”). Regarding household welfare, the adoption of Pectomech, Power Roma or both increased household expenditure and assets. Additionally, farmers gained more income by adopting Pectomech and both Pectomech and Power Roma. The findings suggest the need for research institutions like CSIR and the universities to step up the production of improved seed varieties with high-yielding capabilities and tolerance to pest, spoilage, and bad weather, while government and NGOs assist to increase farmers’ access to credit and extension services. The conceptual framework for the study is presented in Fig 3.4. Smyth (2004) defined a conceptual framework as a deep thinking or conceptualization of the processes or linkages or systems that can be used to simplify the understanding of a particular study. A conceptual framework tries to explain the linkages that exist among various concepts or variables used in the study. It starts from an inductive viewpoint to a deductive or from a simple to complex model below.

The Impact of Farmers’ Adaptation to Climate Change on Rice Yields: Implications for Sustainable Food Systems

Remarkable agricultural productivity gains have been achieved during the last several decades as a result of green revolution (GR) technologies that have greatly increased food production and reduced hunger. However, climate change threatens to reverse the progress made so far in the fight against food insecurity. The agricultural sector in many developing countries, including the rice and wheat producers such as in Punjab (Pakistan and India), is highly vulnerable to climate change, which has serious implications for rural livelihoods and food security. Adaptation is considered a key tool to tackle climate challenges at the farm level and is, therefore, the focus of this study in terms of its impact on rice yields. A household survey was conducted in the Punjab province of Pakistan, and farmers were interviewed face-to-face. We employed a simultaneous equations model to assess the differential impacts of climate change adaptation on adapting and non-adapting farmers’ rice yields. Using the cross-sectional data of 480 rice growers, an endogenous switching regression model provided a means to estimate the selection bias of farmers’ attributes. The results show a significant positive impact of adaptations on rice yields. Specifically, the yield of farmers who adapted to climate change was 24% higher than the non-adapting farmers. The results further indicate that non-adapters can also benefit from the adaptation strategies if they decide to adapt. We also found a significant positive effect of farmers’ climate risk perceptions, literacy level, access to irrigation, ownership of livestock, and availability of farm advisory services on their adaptation decisions. These results, therefore, suggest that policymakers should take into account farmers’ local adaptation knowledge and farming practices when formulating adaptation policies.

Adoption of multiple sustainable land management practices and its effects on productivity of smallholder maize farmers in Nigeria

The problem of land degradation has resulted into low agricultural productivity over the last two decades in Nigeria thus encouraging sustainable land management practices. Thus, we examined the determinants of choice of sustainable land management practices and the factors influencing the adoption of multiple sustainable land management practices including the effects of adoption of sustainable land management practices on maize productivity using endogenous switching regression model (ESRM) in Nigeria. The result of the multivariate probit model found that gender, household size, marital status, farming experience, farm size, years of formal education, access to extension contacts, access to credit and owning a land influenced the maize farmers’ decision to choose between the different sustainable land management practices. The result of the ordered probit model showed that gender, marital status, farming experience, access to extension contacts, access to credit and owning a land influenced farmers decision to adopt multiple sustainable land management practices. Furthermore, the results of the effect of variables such as age, gender, marital status, farming experience, farm size, membership in association and access to extension services translates into increased maize productivity for the maize farmers who adopted sustainable land management practices. The result of the IPWRA showed that adoption of SLMP improves the productivity of the maize farmers. Enacting policy measures that will promote the adoption of SLMP where there is an improvement in farmers having access to financial support and improved extension services towards the smallholder farmers is required. • The negative impact of land degradation has been severe in sub-Saharan Africa (SSA) countries including Nigeria. • Many lands remain uncultivable due to land degradation problems in Nigeria. • Adoption of Sustainable land management practices is of necessity to address the negative impact of land degradation. • Productivity of maize can be enhanced through appropriate adoption of sustainable land management practices.

Understanding the impact of sustainable land-scape management practices on farm productivity under intensifying tropical cyclones: Evidence from Southern Malawi

Southern Malawi is continuously affected by tropical cyclone-related floods (TCRFs), which have negative consequences on households' livelihoods, thereby displacing most households to neighbouring communities of Mozambique. The TCRFs have further threatened national, regional, community, and household food security agenda, which is already constrained by poverty, poor agricultural practices, low use of improved varieties, unaffordable inorganic fertilizers, and fragmenting landholding sizes. Accordingly, households have indigenously engineered resilience-based Sustainable Landscape Management (SLM) practices, like intercropping, agroforestry, cover cropping, and soil and water conservation practices, against the adverse effects of TCRFs on-farm productivity. Hence, this study examines the effect of TCRFs and SLM adoption on-farm productivity. While using rigorous endogenous switching regression econometric tools, the study finds TCRFs reducing farm productivity by 27 percent. After SLM adoption, the study observes farm productivity enhancement by 29–126 percent when households adopt at least one SLM practices under varying degrees of TCRFs. Despite the highlighted advantages of SLM adoption, female farmers are less likely to adopt SLM practices because they do not have access to productive resources. Hence, the study proposes the need of gender targeted extension services, accompanied by some seed capital for SLM adoption. Besides, there is need to sensitize farmers on the complementarities between inorganic fertilizer and SLM practices. Lastly, future studies should assess the effect of sustained SLM adoption or dis-adoption and input intensification on farm productivity.

Climate change adaptation and its impacts on farm income and downside risk exposure

Multiple previous reports have established that climate change disproportionately impacts smallholder farmers in developing countries. This study investigates the impact of climate change adaptation, defined by farmers’ decisions to adopt the improved practices to mitigate or reduce the effects of climate change, on crop revenue and revenue risk exposure. We employ the control function approach in an endogenous switching regression framework to account for selection bias. Using the household survey data from Nepal, we find that climate change adaptation positively affects crop revenue and revenue risk reduction. Specifically, climate change adaptation leads to a 21.6% increase in farm revenue and a 6.4% reduction in downside risk exposure, which are robust to several specifications. Counterfactual analysis shows the considerable heterogeneities in the outcomes among adapters and non-adapters. In particular, adapting farm households realize substantial and distinguishable gains in revenues and declines in risk levels relative to their non-adapting peer households. Our findings imply that adapting to climate change can be an effective management practice to mitigate the risks associated with climate change and increase resilience. • We explore the impact of climate change adaptation on crop revenue and revenue risk exposure in Nepal. • The study employs the control function approach in an endogenous switching regression framework to account for selection bias. • Climate change adaptation positively affects crop revenue and revenue risk reduction. • Adapting farm households realize substantial and distinguishable gains in revenues and declines in risk levels relative to their non-adapting peer households. • Adapting to climate change can be an effective management practice to mitigate the risks associated with climate change and increase resilience.

Impact assessment of adopting improved rice variety on farm household welfare in Ethiopia

This article presents the evaluation of the impact of the adoption of improved rice varieties on yield, commercialization, multidimensional poverty, and subjective poverty using data collected from 594 rice producing smallholder farmers in Ethiopia. We adopted an endogenous switching regression model complemented with a propensity score matching methodology to test robustness and reduced selection bias restricting from both observed and unobserved characteristics. The analysis results are consistent across models, indicating that adoption of improved rice varieties has a robust and positive impact on rice yield, and commercialization. Controlling the variations in household characteristics, the average effect of improved rice varieties adoption on productivity was 0.564 t/ha. Similarly, the econometric result showed that improved rice variety adoption decreased multidimensional poverty and subjective poverty by 1.7% and 12.4%, respectively. The government should work with development partners and NGOs to ease the accessibility and expansion of improved rice varieties in rice producing areas of the country. Therefore, policymakers and development organizations should consider improved rice variety adoption as the main strategy to increase productivity, commercialization, and reduce poverty of the rice farm households. • The study evaluates the impact of improved rice varieties on smallholder farmers' welfare. • The study employed an endogenous switching regression model to analyze data collected from the major rice-producing area of Ethiopia. • Factors influencing the adoption of improved rice varieties identified. • Improved rice variety adoption leads to significant yield and commercialization gains. • Improved rice variety adoption have significant multidimensional poverty and subjective poverty-reducing impacts.

Climate-Smart Agriculture, Non-Farm Employment and Welfare: Exploring Impacts and Options for Scaling Up

Climate-smart agriculture (CSA) has been receiving increasing attention in recent policy dialogues for its potential to improve agricultural transformation, risk management, and welfare. This study seeks to provide evidence on the welfare impacts of CSA adoption and its complementarity with non-farm employment using household-level data from Ethiopia combined with novel historical weather data. The study uses a multinomial endogenous switching regression model to deal with selection bias and farmer heterogeneity. The results show that households adopting CSA enjoy higher welfare benefits than non-adopter households. Households experience a higher welfare impact (lower monetary and multidimensional poverty rate) when CSA and non-farm employment are adopted simultaneously. However, there is less evidence regarding the complementarity between CSA and non-farm employment when considering per capita consumption expenditure. The study findings will have important policy implications for climate change adaptation, resilience, and poverty reduction in low-income countries.

Welfare implications of participating in agri‐value chains among vegetable farmers in Northern Ghana

AbstractThis study investigates the welfare implications of agri‐value chain participation utilizing data collected from 423 smallholder vegetable farmers in northern Ghana. The endogenous switching regression (ESR) model estimates the determinants of agri‐value chain participation and their associated impacts on farmers' welfare, measured by household income and consumption expenditure. The ESR model accounts for selectivity bias associated with observed and unobserved factors. We find that agri‐value chain participation improves vegetable farmers' welfare. Participation significantly increases household income and consumption expenditure by about 22% and 40%, respectively. Our results also reveal that agri‐value chain participation is significantly determined by education, household size, mobile phone ownership, irrigation, farm size, farmer group membership, and extension visits. Variables such as education, access to irrigation, farm size, access to credit, farmer group membership, and extension are the significant determinants of farmers' welfare [EconLit Citations: D24, Q12, Q18].

Testing the Effects of Water-Saving Technologies Adapted to Drought: Empirical Evidence from the Huang-Huai-Hai Region in China

The aggravation of extreme weather events has dramatically increased the risk of severe water shortages and seriously threatened agricultural production. The Huang-Huai-Hai region, an important agricultural production region in China, is subject to a severe water shortage and is often hit by drought. As a result, water-saving technologies (WSTs) have been implemented. It remains unclear how effectively these WSTs can reduce crop yield loss, crop yield variation, and the loss of net crop income caused by water scarcity. Therefore, this paper aimed to analyze the role of WSTs in response to drought by establishing a multi-objective expected utility function based on 988 farmers across the Huang-Huai-Hai region. Econometric analysis employing an endogenous switching regression model showed that using WSTs can significantly reduce crop yield loss and net income loss caused by drought. Adopting household-based WSTs or community-based water-saving technology generates even greater positive effects on crop yield and farmers’ net income. Therefore, the government should promote farmers’ adoption of more advanced WSTs by increasing subsidies and strengthening policy support.

Ecological Sustainability and Households’ Wellbeing: Linking Households’ Non-Traditional Fuel Choices with Reduced Depression in Rural China

A sustainable and pleasant environment is deemed to offer various positive externalities such as scenic, visual and behavioral archetypes and patterns exhibiting in various forms. Such a scenario can significantly relieve households from many psychological and personal complications such as depression. Depression has aroused great concerns in recent years due to its personal and social burdens and unforeseeable damage. Many studies have explored the effects of air pollution caused by traditional fuel consumption on depression. However, limited evidence is available on how household non-traditional fuel choices affect depression. Based on a nationally representative dataset collected from China Family Panel Studies (CFPS) in 2012, this paper employs an endogenous switching regression (ESR) model and an endogenous switching probit (ESP) model to address the endogenous issue and to estimate the treatment effects of non-traditional fuel choices on depression in rural China. The empirical results show that non-traditional fuel users have significantly lower Epidemiologic Studies Depression Scale (CES-D) scores, indicating non-traditional fuel users face a lower risk of depression. Compared to solid fuels, employing non-traditional fuels will lead to a 3.659 reduction in depression score or decrease the probability of depression by 8.2%. In addition, the results of the mechanism analysis show that household non-traditional fuel choices affect depression by reducing the probability of physical discomfort and chronic disease. This study provides new insight into understanding the impact of air pollution in the house on depression and how to avoid the risk of depression in rural China effectively.

Private debt renegotiation, corporate policies, and performance: empirical evidence from Europe

ABSTRACT We investigate the effects of private debt renegotiation on a firm’s performance and financial and investment policies. We employ endogenous switching regressions using a large cross-country sample of loans issued and amended over a long-term in Europe. We find that bank loan renegotiation has an economically significant and causal impact on financial policy and performance. Renegotiation offers firm added degrees of freedom and unlocks its economic potential, implying significant effects of the firm’s tangibility, growth, opportunities, and cash on financial policy and performance. Bank loan renegotiation also shows a certification and signalling effect, which can increase the effect of amendments to the credit agreement on a firm’s financial policy.

Climate change adaptation and production risks among paddy farmers in Sri Lanka

Production risks are unavoidable in paddy production due to unprecedented climate changes in many developing countries. This study intends to identify the production risks and farmers’ decisions to adapt the climate change in paddy production. A survey was conducted, gathering cross-sectional data from 1410 farmers cultivating paddy in rural Sri Lanka. This research analyses farmers' adaptation decisions against climate change using climate-smart practices, socio-economic parameters, and household characteristics. It estimates the impact of experiencing drought and flood among adapting and non-adapting farming communities. The study uses an endogenous switching regression model to avoid endogeneity and selection bias: the study measures productivity, volatility, downside risk exposure and kurtosis between the adapters and non-adaptors. The results revealed that adaptors are sensitive to drought and flood, influencing the four production outcomes. However, the adaptors significantly reduced their volatility and risk exposure, while the non-adapters were susceptible to environmental stress experiences. Adaptation is highly influenced by climate-related variables and socio-economic and credit-related variables in the empirical analysis. The role of the extension services, access to credit, total credit, and income are prominent in the adaptation of paddy production.

Does the Agricultural Productive Service Embedded Affect Farmers’ Family Economic Welfare Enhancement? An Empirical Analysis in Black Soil Region in China

The modernization of agriculture in China has begun to take shape, but some groups of farmers still have relatively weak access to welfare and live in poverty, which is closely related to national food security and sustainable agricultural development. Based on survey data from northeastern China, this study analyzes the logical framework of “Agricultural Productive Services (APS) Embedded—Farmers’ Family Economic Welfare Enhancement” by the endogenous switching regression model. The main findings are as follows. First, the purchase of APS brings a significant positive impact on farmers’ family economic welfare improvement, mainly through the income effect and the substitution effect. Second, with the income effect, there are significant differences in the strength of the “pulling power” of different forms of APS for farmers’ family economic welfare. Compared with farmers who purchase APS for the entire production chain, farmers who purchase only some of the services are more likely to increase their welfare in the later stages. Third, with the substitution effect, the re-employment behavior of the rural surplus laborers who are “squeezed out” under the embedding of APS is promoted, which makes farmers’ income channels, income types, and income opportunities diversify, and their welfare will be more obviously strengthened after purchasing services. In order to enhance farmers’ welfare more efficiently and meet their needs for a better life, this study suggests a combination of farmer information archiving and labor market information transparency to reduce service risks, expand employment channels, and enhance the effectiveness of the linkage between farmers and service providers.

Impact assessment of Striga resistant maize varieties and fertilizer use in Ghana: A panel analysis

AbstractThis study analyzes the impact of a component of climate‐smart agriculture (CSA) technology—Striga‐resistant maize (SRM) varieties and mineral fertilizer—on maize yield and food security using two rounds of panel data in Ghana. The study employs a multinomial endogenous switching regression model and finds that joint adoption of SRM varieties and mineral fertilizer increased maize yield by 872 kg/ha, food consumption scores by 17, and consumption per adult equivalent unit by 38 kg/ha. The positive impact of maize yield is high among adopters of multiple CSA technologies. The result is robust to an alternative endogeneity‐correcting model and the implications of the findings are discussed.

Can rural livelihood programs enhance capabilities and reduce vulnerability to poverty? Evidence from a tribal region of eastern India

Quantitative evidence on the impact of social protection such as livelihood programs (LPs) on reducing vulnerability to poverty (VtP) is scant. Therefore, this paper aims to estimate VtP and the ability of LPs to reduce it. The analysis is based on the primary data collected in 2018–19 from 479 households in a tribal region of eastern India. First, household VtP was estimated using the feasible generalized least squares (FGLS) method. Households were categorized into four groups based on their current and predicted future poverty status: chronic poor, transient poor, escaped poverty, and non-poor. Second, factors influencing this movement of households from current to future poverty states were determined using multinomial logistic regression. Third, the impact of the LP on VtP was investigated using the endogenous switching regression (ESR) approach. The FGLS estimates show that 34.7% of households are vulnerable to future poverty, which exceeds the actual poverty rate of 28.6%. The major factors responsible for exacerbating chronic poverty and causing transient poverty are chronic illness, climate shocks, and the sale of assets. The ESR results indicate that a household’s VtP is reduced by 3% for those that participate in LPs. Although the LP evaluated in this study has an average positive impact in reducing vulnerability, there is wide heterogeneity among the beneficiaries as the geographically disadvantaged communities lag behind the others. Therefore, the study suggests strengthening such LPs with a particular focus on disadvantaged and vulnerable communities.

Cameroon’s adaptation to climate change and sorghum productivity

Cameroon’s semi-arid zone (northern and far northern regions) is an important part of the local ecosystem that is vulnerable to climate change. This vulnerability raises concerns about rural households’ well-being. Adapting to this vulnerability could mitigate some of the negative effects, agricultural shocks, and catastrophic risks associated with agricultural ecosystem destruction. Thus, the goal of this paper is to assess the impact of climate change adaptation strategies on rural households’ sorghum productivity in Cameroon’s semi-arid zone. On 721 households’ secondary data, we used the endogenous switching regression model and the matching method. The results show that adopting adaptation strategies increases sorghum productivity in adapted households by approximately 21,99% more than in non-adapted households. In the absence of coping strategies, these households will lose 11,22% of their sorghum productivity. The importance of these findings adds to the debate about the need to implement climate change adaptation programmes and policies that address the concerns of all households.

How has the new round of farmland certification in China affected farmers’ economic welfare?

It is vital to evaluate the effects of China’s farmland certification programme on farmers’ economic welfare and clarify the impact mechanism. This paper uses the China Labour Dynamics Survey (2014, 2016),1 building endogenous switching regression and endogenous switching probit models to test the impact of the farmland certification programme on farmers’ net agricultural income and poverty status after correcting for endogeneity. A robustness analysis is conducted applying instrumental variable and propensity score matching methods. The results indicate that the farmland certification programme can significantly increase farmer households’ economic welfare, including an 83.10% improvement in agricultural net income and a 3.17% reduction in poverty. Farmland certification also prompts farmers to allocate more resources to agriculture and reduces poverty by increasing farmers’ agricultural income. This study presents a constructive evaluation of the performance of China’s farmland certification policy, providing a strong theoretical and empirical foundation and a useful policy reference for consolidating the achievements of poverty alleviation and effectively linking rural revitalisation.

The impact of free farmland transfer on the adoption of conservation tillage technology -- empirical evidence from rural China

At present, there are a large number of free farmland transfer without monetary or physical rents in rural China. It is relatively worthwhile to verify whether the transferees who transfer in farmland for free, the actual operators of farmland, would adopt the conservation tillage technology (CTT), which is crucial in protecting farmland quality and improving agricultural production efficiency. Based on the data of 527 plots surveyed by China Land Economic Survey (CLES) in Jiangsu Province in 2020, this paper employs Negative Binomial Regression (NBR), Poisson Regression with Endogenous Treatment Effects (ETPR) and Endogenous Switching Regression (ESR). Results show that: (1) Compared with the transferees who transfer into farmland with compensation, the free transfer is not conducive to the transferees' adoption of CTTs such as straw mechanical returning, soil testing and formulated fertilization. Specifically, the total number of technology adoptions by transferees who transfer in farmland without compensation is decreased by 39.54%. The result is still robust after replacing the dependent variable. (2) Further heterogeneity analysis results of different types of technologies show that the number of labor-saving CTTs such as straw mechanical returning adopted by the transferees of free transfer decreases by 11.55%, and the number of labor-intensive tillage technologies such as soil testing and formulated fertilization decreases by 83.20%. Thus, free transfer has a stronger inhibitory effect on the transferees’ adoption of labor-intensive CTTs. Therefore, for the most developing countries including China, the governments should continue to improve the farmland factor market oriented by price mechanism and implement targeted conservation tillage technology according to the different degree of transfer marketization in different places.

Assessing the trade and welfare effects of certification schemes: The case of GlobalGAP in Ghana's mango sector

The study analyzes the trade and welfare effects of GlobalGAP certification using primary data collected from 224 mango farmers in Southern Ghana. The multivariate probit model and an endogenous switching regression (ESR) model were used to estimate the effects of certification on the choice of marketing channels, quantity sold and income, respectively. The results show that certified farmers are less likely to supply to local traders and more likely to sell to industrial processors and the export market. The study found that certification increased quantity sold to high-value markets by 12% for certified farmers. GlobalGAP certification also has the potential to increase income by 20% more for farmers who opt to be certified. It is, therefore recommended that government and development partners shouldcontribute to the development of the technical and financial capacities of farmers in order to enhance farmers’ participation in certification schemes.

Strengthen or weaken? Research on the influence of internet use on agricultural green production efficiency

With the rise of “Internet + Agriculture”, existing related research has focused on the impact of Internet use on agricultural productivity. However, few studies have considered the impact on agricultural green production efficiency. This paper employed the SBM model to calculate the agricultural green production efficiency using the observation data of 459 farmers in Shaanxi, Shanxi, and Henan provinces. Further, the influencing factors, their nonlinear impact, and even the effect of using the internet on agricultural green production efficiency were analyzed. The results show that corn’s average agricultural green production efficiency is 0.44, with the main peak distributed in a low-level range. The impact of the Internet use on agricultural green production efficiency is positively moderated by rural infrastructure, household assets, and educational attainment. Age and arable land area significantly impact agricultural green production efficiency. The endogenous switching regression model (ESR) shows that the agricultural green production efficiency of farmers who do not use the internet will increase by 41.45% if they use the internet. Internet use has a “U-shaped” impact on agricultural green production efficiency, and the threshold value of the farmers’ expenditure to income ratio is 0.0886. The policy aimed at improving agricultural green production efficiency and popularizing Internet use should, therefore, focus on strengthening the emphasis on increasing agricultural green production, increasing investment in rural human capital, providing green production subsidies and green production skills training, improving infrastructure construction in rural areas, integrating and enriching agricultural-related information on the Internet.