Endogenous Switching Regression Model Research Articles

Impact of India’s farm science centers (Krishi Vigyan Kendras) on farm households’ economic welfare: An evidence from a national farmers’ survey

This study examines the impact of access to India’s farm science centers (Krishi Vigyan Kendras, or KVKs) on agricultural households’ welfare using household data from the nationally representative Situation Assessment Survey of Agricultural Households conducted by India’s National Sample Survey Office in 2013. Employing different matching techniques and endogenous switching regression models, it was observed that the KVKs have a positive and statistically significant impact on agricultural households’ economic welfare, although, that impact is heterogeneous. Further, the investments made in expansion of India’s network of KVKs have been quite remunerative, as the benefit- to-cost ratio of expenditure on KVKs ranges from 8–12. Moreover, present findings suggest that expanding rural formal credit markets and promoting literacy can maximize the potential impact of KVKs on agricultural households’ economic welfare.

Impact of Climate Change Adaptation Strategies on Food Security of Farm Households in Rural Dire Dawa Administration, Ethiopia

Background: The impact of climate change on smallholder farmers in underdeveloped countries—specifically, Ethiopia is widely recognized. Farm households employ a range of geographically and temporally varying adaptation strategies to cope with the adverse consequences of climate change. Therefore, it is critical to examine the few empirical studies that examine how rural Ethiopian farm households confronting drought have responded to climate change to ensure food security. Primary data were collected from 385 randomly selected farm households using a semi-structured survey form. Data analysis was performed using endogenous switching regression models and descriptive statistics. Result: Results show that the majority of the sample households (76.7%) adopted climate change adaptation strategies (livelihood diversification, soil and water conservation, and chemical fertilizers separately or in combination) while the remaining 23.3% are non-adopters. Climate change knowledge is validated as an instrumental variable. Model results revealed that adopter farmers would have significantly lower (11.6%) daily calorie intake if they had not adopted them, and non-adopter farmers would have gained significantly higher (12.8%) daily calorie intake if they had adopted them. Sex, marital status, land fragmentation, education, family size, farm size, credit access, extension contacts, and livestock ownership are significantly associated with the likelihood of adoption. Results also show systematic differences where the sex of the head variable is inversely related to the food security of adopters and vice versa for non-adopters. Conclusion: The majority of farm households in the study area know the implications of climate change (73.5%) and suffer from food insecurity (59%). Farmers' knowledge about climate change and variability varies, affecting social, economic, biophysical, and institutional issues. This was shown using descriptive statistics and OLM data. Farm households led by young, male farmers who are married, frequently interact with extension agents, have access to loans and information about climate change, and have non-fragmented plots possess greater knowledge about climate change than other households. Adaptation interventions should consider the above factors and heterogeneities to increase adoption and improve the food security of farm households in the study area.

Socio‑Economic Drivers of Food Security Among Rural Households: Evidence From Smallholder Rice Farmers in Ebonyi State, Nigeria

Nigeria has been facing a food crisis problem, with most of the poor population having limited access to adequate quantity and quality food. Food security reflects the stability of food supply, availability of, and access to food, and affects the amount of food consumed with implications on the population’s health. Thus, this study examined the socio-economic drivers of food security among smallholder rice farmers in Ebonyi State, Nigeria. Primary data was collected under the Feed the Future Innovation Lab for Fish (Integrated rice-fish farming system) funded by USAID through a three-stage sampling technique. Foster–Greer–Thorbecke (FGT) and the Endogenous Switching Regression model were applied in the data analysis. The mean per capita household food expenditure is estimated at N 1,026.43; the food security measure shows that 46.67% of the households experience the incidence of food insecurity, 24.6% point is the food insecurity depth, and 17.2 % point is the severity of food insecurity. The ESR model shows that the drivers of food security are access to credit, marital status, farming experience, primary occupation, education, and farm size. The study proposed implementing more programmes that focus on poverty alleviation, which should be gender inclusive with credit support.

Multiple large shareholders, earnings management, and operating risk: Empirical evidence from China

This study uses the annual financial data of Chinese A-share listed firms from 2010 to 2020 to investigate the relationship between multiple large shareholders (MLS) and earnings management (EM). After analyzing the samples using the Ordinary Least Squares (OLS) model and endogenous switching regression (ESR) model, the empirical results show that the presence of MLS can increase corporate EM activities and the MLS have a significantly positive effect on EM in both the treatment and control groups. In addition, this conclusion still holds after conducting multiple robustness tests. The cross-section analysis shows that the external audit supervision quality, institutional shareholders, and the uncertainty of the external economic environment have significant impacts on the baseline model results. Lastly, mediation effect analysis shows that the presence of MLS increases the corporate operating risk through EM activities. The conclusions of this paper are critical for policymakers to supervise China’s capital market, improve the level of corporate governance of China’s listed firms, and further promote reform of ownership structure.

Sustainable practices in cocoa production. The role of certification schemes and farmer cooperatives

In Côte d'Ivoire and Ghana, many small-scale cocoa producers cultivate cocoa in unshaded or low-shaded plots, leading to challenges such as reduced biodiversity, soil fertility depletion, and increased soil erosion. To assess the adoption of sustainable agricultural practices in the cocoa sector, we develop a scale that incorporates dimensions of agroforestry, soil conservation, pest and disease management and farm sanitation. Using data from >1700 cocoa producers, we examine farmer participation in cooperatives and three main certification schemes (incl. Fairtrade, Rainforest Alliance and Organic) to understand their roles in promoting sustainable practices. We apply a multinomial endogenous switching regression model to control for potential selection bias and estimate the impact of participating in certification schemes, farmer cooperatives or both. In Côte d'Ivoire, econometric results show that joint participation in both a certification scheme and a farmer cooperative is associated with a significantly higher sustainability score. In Ghana, certification scheme membership shows the highest effect.

Being a happy farmer: Technology adoption and subjective well-being

This paper empirically investigates the impact of technology adoption on farmers’ subjective well-being, as measured by happiness and life satisfaction. A theoretical framework is constructed to link farmers’ subjective well-being to technology adoption, with a particular emphasis on mechanization services in agricultural production. By fitting a nationally representative panel dataset – China Family Panel Studies – into an endogenous switching regression model that addresses potential selection bias, we find that technology adoption leads to a 0.194 standard deviation increase in happiness and a 0.065 standard deviation increase in life satisfaction. Further analysis reveals that the effect is more pronounced for individuals engaged in off-farm employment and varies across farm sizes. To underpin the causal effect, we test three plausible mechanisms – absolute income, relative income, and leisure – which are well-documented in the literature for their correlations with happiness and life satisfaction. Our empirical analysis indicates that the adoption of agricultural mechanization services indeed increases the absolute income of farmers and allows them to allocate more time to leisure activities.

Does Ecological Planting–Breeding Mix Pattern Improve Farmers’ Subjective Well-Being? Evidence from the Middle and Lower Reaches of the Yangtze River

The Chinese government is making vigorous efforts to control agricultural pollution. The promotion of an ecological planting–breeding mix pattern is one of them. Farmers’ mode of production will affect their subjective well-being. Thus, this paper aims to analyze the impact of adopting the ecological planting–breeding mix pattern on farmers’ subjective well-being based on 895 pieces of survey data from the provinces of Hubei, Hunan, and Jiangxi in the middle and lower reaches of the Yangtze River. Using the endogenous switching regression model, we find that the adoption of the ecological planting–breeding mix pattern has a significant positive effect on farmers’ subjective well-being. Based on this counterfactual hypothesis, if the farmers who actually adopted the ecological planting–breeding mix pattern did not adopt it, their subjective well-being would decrease from 4.006 to 3.669. Further examination indicates that self-worth identification, income increase, and neighborhood communication could be potential mechanisms. Additionally, the effect of the ecological planting–breeding mix pattern on subjective well-being is stronger in the group with low financial support. The technical support provided by the government does not have a significant regulatory effect on the adoption of the ecological planting–breeding mix pattern on subjective well-being. Our results suggest that farmers’ ecological production behavior can affect their subjective well-being. This may be relevant to many developing countries today that are attempting to adopt ecological agriculture patterns.

Adoption Analysis of BADC Produced <i>Boro</i> Rice Seed and Its Impact on Farm Household Food Security in Bangladesh

The purpose of this study is to look into the factors that influence adoption of BADC produce <i>Boro</i> rice seed and its impact on farm household food security in Bangladesh. The endogenous switching regression model (ESRM) and the propensity score matching (PSM) method were employed to identify the factors that influence adoption of BADC <i>Boro</i> rice seed and assessed its adoption impact on farm household food security. The analysis revealed that age, farm size, rice area, farm income, extension service, livestock ownership and government assistance had significant influence on adoption of BADC <i>Boro</i> rice seed. The estimated results show that education, farm size, earning members, farm income had positive and significant influence in attaining food security status of both adopters and non-adopters farm household. The estimated coefficient of correlation between the adoption equation and the food security equation of adopters was positive and significant. The study confirms that BADC produce <i>Boro</i> rice seed adoption had positive and significant impact on farm household food security of Bangladesh. The study recommended that BADC should implement appropriate policies to increase <i>Boro</i> rice seed production and enhance its adoption level through extension service so that food security situation improve in Bangladesh.

Assessing the inhibitory effect and intervention mechanism of food traceability system on reducing hog farmers’ overuse of animal antibiotics in China

The use of animal antibiotics is a double-edged sword. It can be used for disease treatment, health protection, and growth promoters. It also creates antibiotic residues and resistance, poses risks, and damages food safety, ecosystems, and public health. Under the pressure of disease risk and expected losses, farmers' overuse of animal antibiotics exacerbates this dual objective incompatibility. In this study, we employ the endogenous switching regression (ESR) model and the mediating effect method to empirically analyze the inhibitory effect and intervention mechanism of the food traceability system (FTS) on reducing farmers’ overuse of antibiotics by using the survey data of hog farmers from China. This paper measures the “dose” unit of antibiotics farmers use regarding cost and the active ingredients of antibiotics per kilogram of treated infected hogs. The study finds evidence that the FTS exerts a significant inhibitory effect on the overuse of antibiotics by farmers. The counterfactual hypothesis unveils that non-participation in the FTS by the involved farmers will increase the cost of antibiotics overuse by 0.080 yuan/kg, while if the farmers currently not participating are to engage with the FTS, the price will decrease by 0.126 yuan/kg. This effect persists across control variables controlled in turn and the unit doses of active ingredients of tetracycline, sulfonamides, β-lactam, chloramphenicol, and macrolide antibiotics. Moreover, our results reveal thatthe inhibitory effects of the FTS on over-the-counter and broad-spectrum antibiotics are more significant than on prescription and narrow-spectrum antibiotics. The results show that the inhibition effect of the FTS on the overuse of antibiotics by free-range, professional, and large-scale farmers exhibits an approximately inverse-U curvilinear relationship. Besides, the intervention mechanism of the FTS on the overuse of antibiotics by farmers mainly consists of social reputation maintenance, liability traceability for antibiotic residues, and biosafety enhancement, and the proportion of their mediating effects in the total impact are 24.22%, 21.84%, and 10.87%, respectively. Our empirical study has yielded several implications, such as strengthening the FTS construction, improving farmers’ antibiotic use skills, promoting standardized breeding levels, and increasing the market premium for food products that adhere to antibiotic residue standards. These outcomes not only contribute to the improvement of livestock production safety but also reduce the problem of antibiotic overuse.

Impact of urban productive safety net programme on poverty reduction and food security: Evidence from major cities of Eastern Ethiopia (Dire Dawa, Harar and Jigjiga)

AbstractDifferent social protection programs are designed in low‐income countries to eradicate poverty and improve the food security of poor people. Currently, the Urban Productive Safety Net Program (UPSNP) is designed to support those who are living in poverty and face food insecurity with predictable and reliable support through food, cash, or vouchers. However, limited empirical evidence has been presented about the significant impact of the program on the well‐being of households who participated in the program and the factors that affect the households' decision to participate in the program. Hence, this study aims to evaluate the impact of participation in UPSNP on well‐being using household survey data gathered from three main cities of Ethiopia: Dire Dawa, Harar, and Jigjiga in 2022. This study employed both propensity score matching (PSM) and endogenous switching regression (ESR) models to assess the impact of the UPSNP. The result shows that the probability of a household's participation decision is determined by the age of the household head, number of children, savings, house ownership, employment status of the household head, and shock. Furthermore, we found a consistently positive impact across models, indicating that participation in UPSNP reduces poverty and increases food security of households.

Self-generation and outage losses: A firm-level analysis for emerging and developing Asian countries

Access to reliable and affordable electricity is critical to economic development in emerging and developing Asia. However, many firms in these regions face challenges in obtaining consistent and affordable electricity from the grid, leading them to invest in self-generation technologies. This paper examines the strategic decision of firms to self-generate electricity and the economic losses incurred during power outages. Using survey data from the World Bank Enterprise Survey (WBES) of 5639 manufacturing firms in seven Asian countries, we identify factors driving the decision to self-generate and assess the impact of self-generation on mitigating economic losses during power outages. An endogenous switching regression model is employed to account for self-selection bias. The results show that firms experiencing more outages and higher electricity costs are more likely to invest in self-generation. Larger, older, and exporting firms also show a higher propensity to self-generate. In addition, the results indicate that firms that invested in self-generation would have experienced, on average, outage losses that were 88 percent higher than their actual losses if they had not invested. Conversely, firms without self-generation could have reduced their actual outage losses by on average 5 percent by implementing self-generation strategies. Overall, our results indicate that self-generating firms in Asian emerging and developing countries are particularly vulnerable to losses from power outages and underscore the importance of self-generation as a strategic choice for these firms.

Participation in village savings and lending associations and rice profitability in Tanzania: Application of propensity score matching and endogenous switching regression

We assess the contribution of participation in bundled service-bundled VSLAs on rice productivity and profit among smallholder rice farmers in Mvomero District, Tanzania. The study propensity score matching (PSM) and endogenous switching regression (ESR) models, and found that participation in VSLA has a positive and significant contribution to rice productivity and profit for smallholder rice farmers. Participation in VSLAs increases farmers' ability to regenerate income for investing in improving productivity and profitability and enhancing rice sector development. VSLAs prove as a tool for building financial capital through savings and easy access to credit in rural areas. This study improves on existing research and offers new insights into the effects of VSLA as one of the financial inclusion tools on the economic activities of agricultural households in Tanzania.

Does Digital Agricultural Technology Extension Service Enhance Sustainable Food Production? Evidence from Maize Farmers in China

This research aims to investigate the average and heterogeneous impacts of digital agricultural technology extension service use on eco-efficiency among 1302 maize-producing farmers from a major maize-producing area in Northeast China in 2022. The slack-based measure model with undesirable outputs is applied to calculate the eco-efficiency of maize production. To obtain an unbiased estimation of the average effect, the self-selection problem generated by observable and unobservable factors is solved by the endogenous switching regression model. Quantile regression is utilized to analyze the heterogeneous effect. Notably, the mediated effects model is utilized to examine the potential mechanism between them. Our findings indicate that digital agricultural technology extension service use can increase maize production’s eco-efficiency. Digital agricultural technology extension service users would have reduced the eco-efficiency of the service by 0.148 (21.11%) if they had not used it. Digital agricultural technology extension service nonusers would have improved the eco-efficiency of the service by 0.214 (35.20%) if they had used it. The robustness check reconfirms the results. Moreover, digital agricultural technology extension service use is more helpful for maize farmers who have lower eco-efficiency than those who have higher eco-efficiency. Digital agricultural technology extension service use can improve the eco-efficiency of maize production through the application of organic fertilizers, green pesticides, and biodegradable agricultural films. There are policy implications of these findings: there is an argument for using the publicity of the digital agricultural technology extension service to encourage farmers to use sustainable inputs; additionally, it might be worthwhile to implement a categorized promotion strategy based on the different real-world situations.

Impact of access to cash remittances on cocoa yield in Southwestern Nigeria

Access to cash remittances has a positive impact on the food security of people living in developing countries. However, little is known about the impact of access to cash remittances concerning cocoa yield. Therefore, the study investigates the impact of access to cash remittances on cocoa yield. A multistage sampling technique was used to select 300 cocoa farming households for the study. The data were analysed using the exponential double hurdle model (Churdle) estimation process, inverse probability weighted regression adjustment (IPWRA), and endogenous switching regression model (ESRM). According to the ATU estimate, the average farmer would produce a yield of 0.824 times more when he/she has access to cash remittances. The conditional treatment effect (ATT), which assesses the impact of access to cash remittances on cocoa yield, was correspondingly approximately 0.828 and statistically significant at 1 %. As a result, the typical farmer who has access to cash remittances would produce a yield that is 0.828 times more than it would be if he/she did not have access to cash remittances. The study found that access to cash remittances has a positive impact on cocoa yield among farmers in rural Nigeria after adjusting for both observable and unobserved factors.

Farmers’ adoption of multiple climate-smart agricultural technologies in Ghana: determinants and impacts on maize yields and net farm income

This study investigates the factors affecting maize farmers’ decisions to adopt climate-smart agricultural (CSA) technologies and estimates the impacts of CSA technology adoption on maize yields and net farm income. Unlike most previous studies that analyze a single technology, we consider different combinations of three CSA technologies (zero tillage, row planting, and drought-resistant seed). A multinomial endogenous switching regression model addresses selection bias issues arising from observed and unobserved factors and analyses data collected from 3197 smallholder farmers in three Ghana regions (Brong-Ahafo, Northern, and Ashanti). The findings show that smallholder farmers’ decisions to adopt multiple CSA technologies are influenced by farmer-based organization membership, education, resource constraints such as lack of land, access to markets, and production shocks such as perceived pest and disease stress and drought. We also find that adopting all three CSA technologies together has the largest impact on maize yields, while adopting row planting and zero tillage as a combination has the largest impact on net farm income. Governments should collaborate with farmer-based groups and extension officers to improve farmers’ awareness and understanding of the benefits associated with CSA technologies and help them adopt multiple technologies that generate higher benefits.

Machinery Adoption and Its Effect on Maize Productivity among Smallholder Farmers in Western Kenya: Evidence from the Chisel Harrow Tillage Practice

A major component of contemporary agriculture is machinery. Nonetheless, in Kenya and other African nations, the rate of adoption of agricultural machinery remains quite low. Understanding the fundamental causes and their impacts on agricultural output is crucial. Using data collected from a household survey of 1,499 farmers in Western Kenya, this study employed the endogenous switching regression model to examine the use of chisel harrows and their effects on maize production. Results show that the adoption of the chisel harrow was positively impacted by factors such as farm size, credit accessibility, gender, extension contact, and education attainment, while factors such as age and market proximity had a negative impact. The yield per hectare was higher for adopters than for non-adopters. According to the counterfactual analysis results, those who utilized chisel harrow tools were able to achieve a higher yield (1512 kg/ha) than they would have if they had not used the equipment (1099 kg/ha). The average maize yield per hectare increased by 413 kg and 217 kg for adopters and non-adopters, respectively, when chisel harrows were used. It is concluded that while training and field demonstrations may also be held to increase farmers’ understanding of the benefits of the chisel harrow, encouraging farmers to adopt the tool has the potential to improve low production in the surveyed regions.

Impacts of internet access and use on grain productivity: evidence from Central China

The impacts of Internet use on farming productivity in China have been extensively examined. However, existing studies focus on non-grain crops and often do not distinguish between Internet access and Internet use. This study investigates the effects of both Internet access and Internet use for farming purposes on farmers’ technical efficiency (TE) using data collected from 855 grain-farmers in Central China. The TE is evaluated following a stochastic frontier analysis approach. Endogenous switching regression models are used to address the potential endogeneity issue associated with Internet access or use. Our empirical results show that the use of the Internet for obtaining farming-related information is crucial for improving farmers’ TE. Having access to the Internet itself does not necessarily improve TE. This is also true when considering the effects through the two channels of technology adoption and risk management. Furthermore, using the Internet for non-farming purposes could impede the improvement of TE. Heterogeneity analysis indicates that the Internet can help to reduce the discrepancy of TE among grain farmers.

Transaction costs, crop-livestock integration participation, and income effects in China

The crop-livestock integration model is the main path for the sustainable development of agriculture and animal husbandry in China, and farmers' participation behavior is critical to the formation of this model. So this paper based on a field survey data of 615 farmers in 10 pilot counties of Crop-Livestock Integration (CLI) in the dairy industry in the east, middle, and west of Inner Mongolia, the relationship among transaction costs, farmers' decision-making of participating in the CLI model, and income effects was analyzed using the Endogenous Switching Regression (ESR) model in this paper. The results show that under the current market environment, the proportion of farmers participating in the CLI model is 37.56% of the farmer surveyed. The high costs of information searching, negotiation, and execution are the critical factors to inhibit farmers from participating in the CLI model. The results of the counterfactual test of the ESR model show that the effect of the CLI model on the income of participated farmers is not noticeable, while the effect is more significant on the income of non-participating farmers. Moreover, there is no obvious heterogeneity in the effects of the farmer level and “farmers-to-farm” level CLI models on farmers' income. Based on these conclusions, this paper proposes that the government should actively promote the establishment of the information-sharing platform and training mechanism about the CLI model, reduce farmers' costs in information searching and negotiation, optimize the incentive policy of the CLI model, incorporate the farmers planting forage into the subsidy scope of the CLI model, improve the economic benefits of farmers participating in the CLI model, and stimulate the enthusiasm of farmers participating in the CLI model, so as to effectively promote the realization of the CLI model in the animal husbandry industry.

Enhancing Financial Stability in Ghana's Universal Banking Sector: A Governance Perspective and Practical Insights

Purpose: This study investigates the impact of corporate governance structures on financial distress within the universal banking sector in Ghana.
 Methodology: The research systematically gathers data from 19 banks spanning 10-year period. Financial distress indicators were extracted from financial statements, while corporate governance measures were obtained from annual reports. The data was analysed through regression analysis and counterfactual analysis through an endogenous switching regression model.
 Findings: Key findings reveal that profitability, liquidity, and effective risk management are critical factors influencing financial distress in both strong and weak governance environments. The results also showed that improving the strength of Corporate Governance has a positive influence on Altman Z Scores, contributing to a potential reduction in financial distress.
 Unique contributor to theory, policy and practice: The study provides valuable insights for policymakers, regulators, and banking institutions in Ghana, emphasizing the need to prioritize and strengthen governance practices for a resilient banking sector. Limitations include data unavailability, reliance on unbalanced panel data, and a narrow focus on board characteristics.

The Impact of Livelihood Diversification As a Climate Change Adaptation Strategy on the Food Security Status of Pastoral Households in Southeastern and Southern Ethiopia

The objective of this study was to investigate the determinants of food security and quantify the impact of livelihood diversification as an adaptation strategy on the level of food security of pastoral households in Arero district in Borena zone and Rayitu district in Bale zone in Ethiopia. A multistage sampling technique was used, selecting 396 households from Arero and Rayitu districts. The study used a multidimensional food security index to measure the food security status of pastoralist households. The descriptive result showed that 60.6 percent, 20.2 percent, and 19.2 percent of the pastoralist households had medium, high and low food security, respectively. The result of ordered logistic regression showed that the age of household head, herd size (TLU) and frequency of extension contacts significantly increased the food security status of pastoralist households. However, male household head, age of household head, household size (adult equivalent) and distance to market significantly decrease the food security status of pastoral households in Arero district. On the other hand, the result of the multinomial endogenous switching regression model showed that the uptake of non-farm activities as well as crop production and non-farm activities together have a positive and significant impact on the level of food security of the pastoralist households. Therefore, the results of the study suggest that working on participatory strategies to promote livelihood diversification among pastoralist communities is very important to improve the food security of pastoralist households.