Journal articles: 'Endogenous Switching Regression Model (ESRM)'

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Aduhene, David Tanoh, Sylvester Boadu, and Ernest Obeng. "An Empirical Assessment of the Impact of Access to Credit on Farm Output: A Case Study of Sefwi-Wiawso Municipality Ghana." Journal of Social Economics Research 6, no. 1 (2019): 20–33. http://dx.doi.org/10.18488/journal.35.2019.61.20.33.

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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.

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Jabbar, Awais, Wei Liu, Ye Wang, Jian Zhang, Qun Wu, and Jianchao Peng. "Adoption and Impact of Integrated Soil Fertility Management Technology on Food Production." Agronomy 12, no. 10 (2022): 2261. http://dx.doi.org/10.3390/agronomy12102261.

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Amid recent climate difficulties, integrated soil fertility management (ISFM) strategies are vital in restoring soil fertility, enhancing yield, and achieving the farmer community’s well-being. This study examines ISFM’s adoption and impact on wheat yields in Punjab, Pakistan, by employing an endogenous switching regression model (ESRM). The selection equation highlights the multiple factors such as age, gender, education, extension access, credit access, and social influence as essential predictors of ISFM adoption. Treatment effects showed that the average wheat yield is higher for adopters. The findings suggest refining the current institutional system will enhance adoption and food security by improving agricultural production.

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Oduniyi, Oluwaseun Samuel, and Sibongile Sylvia Tekana. "The Impact of Sustainable Land Management Practices on Household Welfare and Determinants among Smallholder Maize Farmers in South Africa." Land 10, no. 5 (2021): 508. http://dx.doi.org/10.3390/land10050508.

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This study investigated the impact of Sustainable Land Management Practices (SLMP) on the smallholder maize farmer’s welfare in the Gert Sibande District in the Mpumalanga Province of South Africa. Farmers’ welfare is paramount to agricultural development and rural vitalisation, especially in sub-Saharan Africa. The aim of the study is to identify the factors that influence the adoption of SLMP and to assess its impact on the net farm income. A multivariate-probit (MVP) model was used to analyse the determinants of SLMP adopted and an efficient endogenous switching regression model (ESRM) was used to estimate the impact of SLMP on the net farm income of the smallholder maize farmers. The MVP results show that household socio-economic characteristics and institutional factors statistically influenced the choice of SLMP. Subsequently, the pair-wise correlation matrix of the MVP model revealed complementarities among all SLMP implemented by the farmers. Similarly, the ESRM treatment effect indicated that the average net farm income of farmers who adopted SLMP were significantly higher than that of the group who did not. Consequently, the study recommended support policies on farmers’ demography, farm-based characteristics, and institutional factors to improve the welfare of the farmers and promote rural vitalisation.

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Yao, AGBENO. "Impact of Access to Agricultural Credit on the Productivity of Togolese Farmers." International Journal of Agricultural Sciences and Technology 1, no. 4 (2021): 13–23. https://doi.org/10.51483/IJAGST.1.4.2021.13-23.

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The objective of this paper is to measure the impact of access to agricultural credit on the productivity of farmers in Togo. The results show that there is a difference between farmers who have access to credit and those who do not. Also, farmers with access to credit have higher productivity than those without. Thus, access to credit is an essential factor in increasing agricultural productivity. Togolese decision-makers must, in the development of their agricultural policy, place greater emphasis on mechanisms to promote access to agricultural credit.

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Xie, Chongxin, Yun Gao, Yu Zhong, and Zhijun Zhao. "Impact of Digital Agro-Technology Services on Technical Efficiency and Income of Small-Scale Farmers: Empirical Study from Mango Production in China." Agriculture 14, no. 12 (2024): 2143. http://dx.doi.org/10.3390/agriculture14122143.

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With the market-driven approach to agricultural technical services and the application of digital technology, digital agro-technical services have gradually emerged as a novel service model. However, there is a lack of empirical research on the effectiveness of this service in the academic literature. To address this research gap, this study measured the impact of this service on the technical efficiency and income levels of mango farmers, using data collected from 131 mango farmers in Hainan Province, China, from 2022 to 2024. This study employed the endogenous switching regression model (ESRM) and the inverse probability-weighted regression adjustment model (IPWRA) to analyze the data, addressing endogeneity through the instrumental variable method by replacing core explanatory variables and conducting sub-regional regression for robustness testing. The main research conclusions are as follows: Under the counterfactual assumption of ESRM, farmers who adopt this service would have experienced a decrease in technical efficiency by 0.025 (a decline of 3.6%) if they had not adopted the service. Conversely, farmers who did not adopt it would have seen an increase in technical efficiency by 0.047 (an increase of 7.3%) if they had chosen to do so. Additionally, under the post-treatment income effect estimation using IPWRA, compared to farmers who did not receive the service, those who did so saw an income increase of 15.6%. The analysis results from methods such as K-nearest neighbors matching also confirm this conclusion. Therefore, it is evident that digital agro-technology services play a significant role in improving the technical efficiency and income levels of small-scale farmers.

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Ojo, T. O., L. J. S. Baiyegunhi, and A. O. Salami. "Impact of Credit Demand on the Productivity of Rice Farmers in South West Nigeria." Journal of Economics and Behavioral Studies 11, no. 1(J) (2019): 166–80. http://dx.doi.org/10.22610/jebs.v11i1(j).2757.

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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 farmersâ€™ 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 farmersâ€™ 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 farmersâ€™ 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 farmersâ€™ productivity and their householdsâ€™ incomes.

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Ifeoma, Anwasia Anthonia, Anselm Anibueze Enete, and Ezeibe Adaku Bridget. "Determinant and Impact of Renewable Energy Utilization on Farm Productivity in South-South Nigeria." Journal of Agriculture and Crops, no. 91 (December 28, 2022): 105–13. http://dx.doi.org/10.32861/jac.91.105.113.

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Nigeria is endowed with abundant renewable and non-renewable energy resources but despite this abundance, the country is currently facing inadequate supply and widening demand for energy. In this study, we examine how farmers’ use of renewable energy is related to their productivity in Nigeria. Since not all farmers are using renewable energy in the study area, it is important to separate them into 2 groups, “Users” and “Non-users” in order to estimate the productivity level of each group. Primary data was analyzed using an endogenous switching regression model (ESRM) with a sample size of 313 farm households. The result of the study indicates that renewable energy use increased agricultural productivity by 39%. The study also reveals that of the farmers surveyed, 75% are willing to use renewable energy. These results provide knowledge to stakeholders on the need to protect agricultural land and increase agricultural production and productivity through continuous use of renewable energy.

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Omodara, Olabisi, Oluwaseun Adetunji, and Oluwemimo Oluwasola. "The nexus between agricultural loan access and farm income of small-scale cassava processors in Oyo state, Nigeria: An endogenous switching regression approach." Journal of Agricultural Sciences, Belgrade 67, no. 1 (2022): 83–104. http://dx.doi.org/10.2298/jas2201083o.

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An agricultural loan is an essential tool for transforming commercial agriculture into a profitable venture. In view of this, this study investigated determinants of access to agricultural loans and the profitability of small-scale cassava processing. It also tested whether access to agricultural loans affected the net farm income of cassava processors in Oyo State using budgetary analysis, endogenous switching regression model (ESRM) and augmented inverse probability weighted regression adjustment (AIPWRA) as a robustness check. A multistage random sampling procedure was employed to gather information from 120 cassava processors. The results revealed that female processors dominated cassava processing, and processors had a mean age of 41.1?7.5 years. Only 23% of the respondents had agricultural loan access, which was primarily sourced informally. Budgetary analysis showed that processors earned an average net farm income of N10,449.87 (US$29.03) in a production cycle. Endogenous switching regression analysis revealed that married and educated cassava processors that were socially inclusive and that had a large processing unit and earned meagre off-farm income were more likely to access agricultural loans. Furthermore, education (?=0.019, p<0.1), number of family members working (?=0.241, p<0.01), processors? experience (?=0.028, p<0.05) and enterprise size (?=0.001, p<0.01) influenced the net farm income of processors that had access to agricultural loans. The treatment effect from the AIPWRA result revealed that ATT and POM for cassava processing were 4.5% and 37%, respectively. Business risks, small enterprise size and high interest rate were the major constraints to agricultural loan access. From the foregoing, a need for a technical support system among cassava processors is inevitable. More so, cassava processors should be encouraged to join trade associations, and young processors should be given priority in credit initiatives for cassava processing.

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Shabangu, T., M. S. C. Ngidi, T. O. Ojo, and S. C. Babu. "Impact of Recapitalisation and Development Programme on Performance of Land Reform Beneficiary Farmers in KwaZulu-Natal, South Africa." Journal of Agricultural Science 13, no. 5 (2021): 91. http://dx.doi.org/10.5539/jas.v13n5p91.

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Providing appropriate post-settlement support to farmers is crucial for sustainable development of smallholder agriculture in South Africa. In unravelling this, the South Africa&rsquo;s Recapitalization and Development Programme (RADP) was initiated. Hence, this study analysed the impact of RADP on performance of land reform beneficiary farmers in KwaZulu-Natal, South Africa. A multistage sampling procedure was used to select (n = 264) respondents for the study. Accounting for endogeneity issues in RADP assessments and its impact on the performance of land reform farmers, an endogenous switching regression model (ESRM) was employed. In the same vein, a doubly-robust inverse probability weighted regression adjustment was used as credible remedy for potentially biased estimates of ATT and POM of endogenous treatment model. The main findings revealed that tax compliance, secondary organization, legal entity, farm potential income at acquisition, farmers receiving third party assistance and strategic partnership were statistically significant in influencing the participation of farmers in RADP. Mentorship remains an extremely challenging element in post-settlement. However, through the strategic partnership of RADP farmers had likelihood to improve the farm and increase farm income. The results of the suggest that the RADP can contribute to a deep process of change and empowerment of farmers. In the same vein, strategic partnership of RADP is likely to improve the farmers&rsquo; performance. Therefore, there is a need to strongly improve mentorship and strategic partnership programme to encourage participation of land reform farmers in the support programmes.

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Lin, Haihua, Qingfeng Bao, Muhammad Umer Arshad, and Haiying Lin. "Assessing Income Heterogeneity from Farmer Participation in Sustainable Management of Forest Health Initiatives." Sustainability 17, no. 7 (2025): 2894. https://doi.org/10.3390/su17072894.

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Farmers’ participation in sustainable forest management plays a significant role in increasing their income and contributing to the comprehensive advancing of the rural revitalization strategy. This study focuses on farmers living near existing national forest health bases in Inner Mongolia. Using the endogenous switching regression model (ESRM), we empirically examine the income effects of farmers’ participation in sustainable forest management through employment and land leasing. The robustness of the model estimation is tested through various methods, including replacing the dependent variable. Furthermore, heterogeneity analysis is conducted using quantile regression. The results show the following: (1) Participation in sustainable forest management through employment (p < 0.001) and land leasing (p < 0.001) significantly increases annual household income by 4.28% and 1.44%, respectively. The income effect for farmers participating through employment is 2.84% higher than for those participating through land leasing. (2) For farmers who did not participate in sustainable forest management, the counterfactual scenario indicates a reduction in annual household income by 5.87% and 2.55%, respectively, highlighting a greater potential income improvement for non-participating farmers if they were to engage in sustainable forest management. (3) Heterogeneity analysis reveals that the income effects of the two participation forms vary across income levels. Employment participation in forest health bases has a more significant impact on low-income (QR_10) farmers, while land leasing participation has a greater impact on high-income (QR_90) farmers.

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Xiao, Xinlan, Youping Yu, Qiang He, et al. "Does Regular Physical Activity Improve Personal Income? Empirical Evidence from China." Nutrients 14, no. 17 (2022): 3522. http://dx.doi.org/10.3390/nu14173522.

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A lack of adequate exercise threatens human health, weakening human capital accumulation. The relationship between exercise and income has become the focus of attention in health economics. In terms of reducing body weight and improving physical fitness, diet and physical exercise are intertwined and become effective ways to shape a healthy state. Based on individual-level survey data from China, this study quantified the economic returns of habitual exercise behavior by using an endogenous switching regression model (ESRM) to eliminate selection bias. The study shows that (1) participants in the group with regular exercise behavior increased their income by 3.79% compared with those not exercising regularly; (2) for the group with no regular exercise behavior, regular exercise increased their income by 13.36% compared with those not exercising regularly. Additionally, empirical evidence shows that both drinking and smoking can significantly increase individual income, despite unhealthy habits. These results suggest that the habit of regular physical activity plays a vital role in increasing individual income and improving overall national health, and the effect of individual behavior on income is affected by national culture. The outcomes are empirical evidence for the Chinese government to promote Healthy China Action and support developing countries worldwide to enable habitual exercise, stimulating a policy of exercise behavior.

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Zhang, Mengling, Li Zhou, Yuhan Zhang, and Wangyue Zhou. "Economic and Environmental Effects of Farmers’ Green Production Behaviors: Evidence from Major Rice-Producing Areas in Jiangxi Province, China." Land 13, no. 10 (2024): 1668. http://dx.doi.org/10.3390/land13101668.

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This study examines the economic and environmental impacts of green production practices among farmers. It aims to contribute to sustainable agricultural development, mitigate agricultural non-point source (NPS) pollution, and align environmental protection with economic growth. This paper utilizes survey data from 1345 farm households in the main rice production areas of Jiangxi Province, China, using the example of reduced fertilizer application (RFA) among rice farmers. This study constructs a slack-based measure data envelopment analysis (DEA—SBM) model with undesirable outputs to measure environmental effects and applies an endogenous switching regression model (ESRM) to test the economic and environmental effects of farmers’ adoption of green production technologies. We found the following: (1) The RFA behavior of farmers has a significant positive impact on their net profit per hectare (NPH), helping farmers increase their income, with the increase ranging from 2.05% to 6.54%. (2) Farmers’ RFA behavior has a significant positive impact on agricultural green productivity (AGP), contributing to the improvement of the environment, ranging from 44.09% to 45.35%. (3) A heterogeneity analysis found inconsistencies in the income-enhancing and environmental-enhancing effects at different quantiles of NPH and AGP. Therefore, attention should be placed on improving the agricultural product quality supervision system under the market circulation mechanism, creating land scale conditions conducive to the promotion and application of fertilizer reduction technologies and promoting the implementation of externality internalization compensation systems.

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Mia, Md Shahin, Md Taj Uddin, Humayun Kabir, Md Abdul Monayem Miah, and Md Abdus Salam. "Adoption Analysis of BADC Produced Boro Rice Seed and Its Impact on Farm Household Food Security in Bangladesh." International Journal of Agricultural Economics 9, no. 2 (2024): 76–88. http://dx.doi.org/10.11648/j.ijae.20240902.14.

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The purpose of this study is to look into the factors that influence adoption of BADC produce &lt;i&gt;Boro&lt;/i&gt; 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 &lt;i&gt;Boro&lt;/i&gt; 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 &lt;i&gt;Boro&lt;/i&gt; 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 &lt;i&gt;Boro&lt;/i&gt; 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 &lt;i&gt;Boro&lt;/i&gt; rice seed production and enhance its adoption level through extension service so that food security situation improve in Bangladesh.

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Ngidi, Mjabuliseni Simon Cloapas, Sinethemba Sibusisiwe Zulu, Temitope Oluwaseun Ojo, and Simphiwe Innocentia Hlatshwayo. "Effect of Consumers’ Acceptance of Indigenous Leafy Vegetables and Their Contribution to Household Food Security." Sustainability 15, no. 6 (2023): 4755. http://dx.doi.org/10.3390/su15064755.

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In the past decades, indigenous leafy vegetables (ILVs) have played a significant role in household food security, especially in poor rural households. However, ILVs have been replaced by exotic cash crops in the contemporary world. This study was conducted to assess the consumption of indigenous leafy vegetables and their contribution to household food security of households in Limpopo and Mpumalanga provinces. The study used secondary data collected by the South African Vulnerability Assessment Committee in 2016. A total of 1520 respondents were selected using a multistage sampling method. The results from descriptive statistics revealed that most consumers did not produce ILVs but consumed them. Meanwhile, a small number of people produced ILVs yet did not consume them. The results from the Household Food Insecurity Access Scale (HFIAS) showed that a large proportion of the population experienced moderate food security while some of the individuals within the population experienced severe food insecurity. An endogenous switching regression model (ESRM) was employed to analyze the impact of the consumption of ILVs on household food security. The results revealed that only a few variables of the consumption of ILVs were significant and positive (household size, wealth index, and ‘if the disabled person receives grants’). As a result, the consumption of ILVs had a minimal impact on the household food security of the Limpopo and Mpumalanga provinces. The findings further revealed that age, gender, and education variables negatively influenced the consumption of ILVs. Thus, the recommended programs must be established to educate people about the importance of consuming ILVs. Agricultural extension services must equally promote the consumption of exotic cash crops and ILVs. Lastly, policies can contribute by increasing the diversity of ILVs left at retail outlets through diverse production.

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Hasebe, Takuya. "Endogenous switching regression model and treatment effects of count-data outcome." Stata Journal: Promoting communications on statistics and Stata 20, no. 3 (2020): 627–46. http://dx.doi.org/10.1177/1536867x20953573.

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In this article, I describe the escount command, which implements the estimation of an endogenous switching model with count-data outcomes, where a potential outcome differs across two alternate treatment statuses. escount allows for either a Poisson or a negative binomial regression model with lognormal latent heterogeneity. After estimating the parameters of the switching regression model, one can estimate various treatment effects with the command teescount. I also describe the command lncount, which fits the Poisson or negative binomial regression model with lognormal latent heterogeneity.

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Keay, Myoung-Jin. "An Exponential Endogenous Switching Regression with Correlated Random Coefficients." Econometrics 10, no. 1 (2021): 1. http://dx.doi.org/10.3390/econometrics10010001.

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This paper presents a method for estimating the average treatment effects (ATE) of an exponential endogenous switching model where the coefficients of covariates in the structural equation are random and correlated with the binary treatment variable. The estimating equations are derived under some mild identifying assumptions. We find that the ATE is identified, although each coefficient in the structural model may not be. Tests assessing the endogeneity of treatment and for model selection are provided. Monte Carlo simulations show that, in large samples, the proposed estimator has a smaller bias and a larger variance than the methods that do not take the random coefficients into account. This is applied to health insurance data of Oregon.

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Atamja, Louis, Sungjoon Yoo, and Dongjoo Lee. "Formal and informal finance and rural household welfare in Mezam division of the North-West Region of Cameroon: A comparative assessment." Journal of Contemporary Research in Business, Economics and Finance 7, no. 2 (2025): 1–15. https://doi.org/10.55214/jcrbef.v7i2.6558.

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The purpose of this study is to comparatively assess the impact of formal and informal finance on rural household welfare in the Mezam division of the Northwest region of Cameroon. A probit regression model was used to examine the determinants of households’ credit access, while a Propensity Score Matching and an Endogenous Switching Regression model were used to analyze the impact of formal and informal finance on household welfare. The results from the probit regression model indicate the importance of occupation, extension services, and household participants in accessing credit. On the other hand, a prediction from the propensity score matching and endogenous switching regression model confirms that access to either formal or informal finance has an impact on welfare, with informal finance having a positive and significant impact.

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Abildtrup, Jens, Serge Garcia, and Eric Kere. "Land use and drinking water supply: a spatial switching regression model with spatial endogenous switching." Revue d’Économie Régionale & Urbaine mai, no. 1 (2015): 321. http://dx.doi.org/10.3917/reru.151.0321.

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Manuela, Coromaldi, and Parisi Valentino. "Voluntary Environmental Information Disclosure and Firms' Profitability: Evidence from the Italian Manufacturing Sector." Empirical Economics Letters 22, no. 9 (2023): 1–9. https://doi.org/10.5281/zenodo.8411619.

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Abstract: This paper investigates the impact of voluntary environmental information disclosure on firm profitability. Based on data for the period 2015–2018, we implement a two-stage panel endogenous switching regression model to deal with endogeneity issues. Our findings document that voluntary environmental information disclosure enhances firms’ performance. Keywords: Environment, Information Disclosure, Firm’s Profitability, Panel Models, Endogenous Switching JEL Classification Number: Q56, D21, C23, C24

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Lin, Liqiong, Weizhuo Wang, Christopher Gan, and Quang T. T. Nguyen. "Credit Constraints on Farm Household Welfare in Rural China: Evidence from Fujian Province." Sustainability 11, no. 11 (2019): 3221. http://dx.doi.org/10.3390/su11113221.

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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.

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Si, Xiaofei, and Maishou Li. "Impact of the internet use on informal workers’ wages: Evidence from China." PLOS ONE 18, no. 5 (2023): e0285973. http://dx.doi.org/10.1371/journal.pone.0285973.

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Based on the data from the China Family Panel Studies (CFPS) in 2018, the relationship between internet use and informal workers’ wages and its internal mechanism were empirically discussed using the ordinary least squares and endogenous switching regression(ESR) model. The study found that internet use could significantly raise the level of wages of informal workers, and this conclusion still holds after the endogenous problem was solved through the endogenous switching regression model. Further research found that the influences of the internet use on informal workers’ wages was heterogeneous. In other words, internet use has a more obvious impact on the wages of informal workers aged 31 to 40, 41 to 50, and 51 to 60 with the educational level of university and above in cities and towns, while it has a significant negative impact on wages of informal workers aged 16 to 20.

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Atamja, Louis, and Sungjoon Yoo. "Credit Constraint and Rural Household Welfare in the Mezam Division of the North-West Region of Cameroon." Sustainability 13, no. 11 (2021): 5964. http://dx.doi.org/10.3390/su13115964.

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The purpose of this study is to examine the effect of the rural household’s head and household characteristics on credit accessibility. This study also seeks to investigate how credit constraint affects rural household welfare in the Mezam division of the North-West region of Cameroon. Using data from a household survey questionnaire, we found that 36.88% of the households were credit-constrained, while 63.13% were unconstrained. A probit regression model was used to examine the determinants of households’ credit access, while an endogenous switching regression model was used to analyze the impact of credit constraint on household welfare. The results from the probit regression model indicate the importance of the farmer’s or trader’s organization membership, occupation, and savings to the household’s likelihood of being credit-constrained. On the other hand, a prediction from the endogenous switching regression model confirms that households with access to credit have a better standard of welfare than a constrained household. From the results, it is necessary for the government to subsidize microfinance institutions, so that they can take on the risk of offering credit to rural households.

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Lin, Liqiong, Weizhuo Wang, Christopher Gan, David A. Cohen, and Quang T. T. Nguyen. "Rural Credit Constraint and Informal Rural Credit Accessibility in China." Sustainability 11, no. 7 (2019): 1935. http://dx.doi.org/10.3390/su11071935.

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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.

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Sichoongwe, Kiru, and JinxiaWang. "Effectiveness of Smallholder Farmers adaptation to climate extremes: Evidence from the Southern Province of Zambia." Agricultural Science 7, no. 1 (2023): 19–31. http://dx.doi.org/10.55173/agriscience.v7i1.111.

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Climate extreme is one of Zambia's most pressing issues impacting socio-economic development. This paper assessed the impact of adaptation to climate extremes, as well as the effectiveness of adaptation strategies to mitigate the negative impact on food production. A total of 270 smallholder farmers were sampled. Descriptive analysis, and, the endogenous switching regression model were applied. According to the study's findings, adaptors and non-adaptors have a number of different characteristics. Furthermore, based on the estimates of the endogenous switching regression model, radio ownership, seed quantity and farming experience, had a positive relationship with adaptation. Also, the results showed that adaptors are ‘better producers’ than the non-adaptors. In light of the findings, some policy recommendations were made. When drafting policies (a) it is necessary to draw on the expertise and experience of farmers and local institutions, (b) consider the assets of the farmers and (c) enhance farmers’ access to more affordable agricultural inputs.

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Sichoongwe, Kiru, and Jinxia Wang. "Effectiveness of smallholder farmers' adaptation to climate extremes: Evidence from the Southern Province of Zambia." Acta agriculturae Serbica 28, no. 55 (2023): 63–69. http://dx.doi.org/10.5937/aaser2355063s.

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Climate extreme is one of Zambia's most pressing issues impacting socioeconomic development. This paper assessed the impact of adaptation to climate extremes, as well as the effectiveness of adaptation strategies to mitigate the negative impact on food production. A total of 270 smallholder farmers were sampled. Descriptive analysis and the endogenous switching regression model were applied. According to the study's findings, adapted farms and non-adapted farms have a number of different characteristics. Furthermore, based on the estimates of the endogenous switching regression model, owning a radio, seed quantity and farming experience had a positive relationship with adaptation. Also, the results showed that adaptors are 'better producers' than non-adaptors. In light of the findings, some policy recommendations were made. When drafting policies, it is necessary to (a) draw on the expertise and experience of farmers and local institutions, (b) consider the assets of farmers and (c) enhance farmers' access to more affordable agricultural inputs.

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Fitawek, Wegayehu, and Sheryl Hendriks. "Evaluating the Impact of Large-Scale Agricultural Investments on Household Food Security Using an Endogenous Switching Regression Model." Land 10, no. 3 (2021): 323. http://dx.doi.org/10.3390/land10030323.

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This study set out to estimate the effects of large-scale agricultural investments (LSAIs) on household food security in one community each in Kenya, Madagascar and Mozambique. An endogenous switching regression model was adopted to control for a possible selection bias due to unobserved factors. It was found that households with members employed by large-scale agricultural investment companies were more likely larger households headed by younger migrant males holding smaller plots and fewer livestock than non-engaged households. The endogenous switching regression results confirmed the presence of both a positive and negative selection bias. In general, the results showed that households with a member employed by an LSAI enjoyed better household food security, higher dietary diversity, better food consumption scores and more adequate household food provisioning. Households without employed members could also enjoy these benefits should the LSAIs employ their members. However, the seasonal nature and low wages paid by LSAI may only support the purchase of food and not facilitate savings and investments to significantly improve food security.

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Ankrah Twumasi, Martinson, Abbas Ali Chandio, Ghulam Raza Sargani, Isaac Asare, and Huaquan Zhang. "Off-Farm Employment and Agricultural Credit Fungibility Nexus in Rural Ghana." Sustainability 14, no. 15 (2022): 9109. http://dx.doi.org/10.3390/su14159109.

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This study examined the impact of off-farm employment on rural household agriculture credit fungibility (CF) using survey data collected from four regions in Ghana; however, the study paid more attention to agriculture credit received from different sources. By employing the endogenous switching regression (ESR) model, we solved the endogenous issue of off-farm employment. The econometrics model result revealed that off-farm employment negatively influences the household’s probability of practicing agriculture CF. Our results discovered the importance of off-farm employment on agriculture CF and recommended policy implications capable of alleviating agriculture CF.

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Calzolari, Giorgio, Maria Gabriella Campolo, Antonino Di Pino, and Laura Magazzini. "Maximum likelihood estimation of an across-regime correlation parameter." Stata Journal: Promoting communications on statistics and Stata 21, no. 2 (2021): 430–61. http://dx.doi.org/10.1177/1536867x211025834.

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In this article, we describe the mlcar command, which implements a maximum likelihood method to simultaneously estimate the regression coefficients of a two-regime endogenous switching model and the coefficient measuring the correlation of outcomes between the two regimes. This coefficient, known as the “across-regime” correlation parameter, is generally unidentified in the traditional estimation procedures.

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Chen, Qianqian, Chao Zhang, Ruifa Hu, and Shengyang Sun. "Can Information from the Internet Improve Grain Technical Efficiency? New Evidence from Rice Production in China." Agriculture 12, no. 12 (2022): 2086. http://dx.doi.org/10.3390/agriculture12122086.

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The Internet has become an important channel through which farmers obtain technical information regarding agricultural production. While previous studies have examined the effect of information from the Internet on technical efficiency in cash-crop production, there is little knowledge about how information from the Internet affects technical efficiency in grain production. This study aims to provide new evidence for the effect of information from the Internet on technical efficiency in rice production using the random survey data of 1122 rice farmers from the Yangtze River Basin in China. A stochastic frontier production function is employed to estimate technical efficiency in rice production, and the endogenous switching regression model is utilized to address the potential self-selectivity bias. The results show that 13.6% of surveyed rice farmers obtain information regarding agricultural production from the Internet. After addressing the self-selectivity bias, information from the Internet is found to increase rice farmers’ technical efficiency by 6.657 percentage points using the endogenous switching regression model. Meanwhile, information from the Internet exerts greater positive effects on technical efficiency in rice production among farmers with larger farm size and less farming experience as well as those in the Guizhou and Hubei provinces.

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Choi, Pilsun, and Insik Min. "Estimating endogenous switching regression model with a flexible parametric distribution function: application to Korean housing demand." Applied Economics 41, no. 23 (2009): 3045–55. http://dx.doi.org/10.1080/00036840701335595.

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Akpalu, Wisdom, and Ametefee K. Normanyo. "Illegal fishing and catch potentials among small-scale fishers: application of an endogenous Switching regression model." Environment and Development Economics 19, no. 2 (2013): 156–72. http://dx.doi.org/10.1017/s1355770x13000478.

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AbstractCapture fish stocks are facing an increasing threat of extinction, partly due to the use of illegal fishing methods. In developing coastal countries – where fishing activities are the mainstay of the population along the coast – livelihoods are being directly threatened. Although a number of studies exist on fishing regulations and those who violate them, little has been done on the relationship between intrinsic catch potentials/fishing skills and illegal fishing behavior. Using data on violations of light attraction regulation among small-scale fishers in Ghana, our results show that the risk of punishment, the amount of fishing experience, the skipper's age, and religious norms all influence the decision to violate fishing regulations. Most importantly, we found that violators and non-violators have different fishing skills. Consequently, policies targeting illegal fishing must focus on equalizing efficiency and/or fishing skills among the fishermen as well as on traditional variables that influence violation decisions.

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Trent, Colene, and Walter J. Mayer. "Working the Night Shift: The Impact of Compensating Wages and Local Economic Conditions on Shift Choice." Economics Research International 2014 (October 9, 2014): 1–15. http://dx.doi.org/10.1155/2014/632506.

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The theory of compensating differentials asserts that night shift workers should receive compensating wage differentials due to undesirable work conditions. In weak local economies, workers may have difficulty finding jobs; thus, these workers might be more likely to accept night shift work and be less concerned with the size of the compensating differential for night shifts. Using CPS data from 2001, this paper employs maximum likelihood estimation of an endogenous switching regression model to analyze wages of day and night shift workers and shift choice. The findings indicate the presence of selection bias, thus emphasizing the importance of correcting for self-selection into night shifts. The average of the estimated wage differentials for night shift work is negative for the overall sample, with differentials varying by worker characteristics. The shift differential is found to be a statistically significant predictor of shift choice, indicating that shift premiums play an important role in motivating individuals to select night shift work. Using two measures of local economic conditions and a new method of analyzing interaction effects in the context of an endogenous switching regression model, this paper finds limited evidence that weak local economic conditions lessen the impact of compensating differentials on shift choice.

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Ullah, Ihsan, Nawab Khan, Yonghong Dai, and Amir Hamza. "Does Solar-Powered Irrigation System Usage Increase the Technical Efficiency of Crop Production? New Insights from Rural Areas." Energies 16, no. 18 (2023): 6641. http://dx.doi.org/10.3390/en16186641.

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Fossil fuel and electricity-powered irrigation techniques boost the water availability expense and increase greenhouse gas emissions. Especially in developing countries, solar-powered irrigation is becoming more popular as a response to the growing energy and environmental issues associated with agriculture systems. The existing study used data from 1080 wheat farmers in Balochistan, Pakistan, to investigate the impact of solar-powered irrigation system (SPIS) usage on the technical efficiency (TE) of wheat production. The TE of wheat production is estimated using a stochastic frontier production function, and the potential self-selectivity bias is addressed using an endogenous switching regression model. The findings indicated that 13.7% of the wheat cultivators assessed used SPISs to produce their crops. Using an endogenous switching regression model shows that SPIS usage increases the TE of wheat growers by 6.657%, after controlling for self-selection bias. While using SPISs, wheat farmers with large farms and farming familiarity had stronger positive effects on TE. The results highlight the need for more investigation and research into evidence-based good practice for SPIS solutions at the site level to ensure that the rollout of modern equipment not only drives the energy sector forward but also contributes significantly to our level playing field and sustainable environment.

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Liu, Min, Shi Min, Wanglin Ma, and Tianjun Liu. "The adoption and impact of E-commerce in rural China: Application of an endogenous switching regression model." Journal of Rural Studies 83 (April 2021): 106–16. http://dx.doi.org/10.1016/j.jrurstud.2021.02.021.

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Tang, Hui-Wen, and Chong-Chuo Chang. "Does corporate governance affect the relationship between earnings management and firm performance? An endogenous switching regression model." Review of Quantitative Finance and Accounting 45, no. 1 (2014): 33–58. http://dx.doi.org/10.1007/s11156-013-0427-z.

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Bocher, Temesgen Fitamo, Bamlaku Alamirew Alemu, and Zerihun Getachew Kelbore. "Does access to credit improve household welfare? Evidence from Ethiopia using endogenous regime switching regression." African Journal of Economic and Management Studies 8, no. 1 (2017): 51–65. http://dx.doi.org/10.1108/ajems-03-2017-145.

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Purpose The purpose of this paper is to investigate how credit access affects the welfare of households and sheds light on how household characteristics influence the decision to take credit and the efficiency in credit use. Design/methodology/approach This study uses data from the fourth round of the Ethiopian Rural Household Survey conducted in 2009, and examines factors that determine the decision to take credit and the effect of such decision on household welfare. The household welfare variable is measured by the food security indicator and total food expenditure. The study employs endogenous Regime Switching model to account for endogeneity in access to credit and self-selection bias in the decision to participate in credit. Findings The result from the kernel distribution shows households with access to credit have more consumption expenditure than those without access to credit. The ordinary least square regression shows that access to credit increases total consumption by 12 percent without considering self-selection bias. Participation in non-farm activity increases the demand for credit by 17 percent. Land holding, household size, and participation in saving associations increase the probability of getting credit by 5, 11, and 20 percent, respectively. Access to credit appears to have a positive impact on food security in both actual and counterfactual cases for the current credit receivers. Originality/value This study provides a thorough analysis of the impacts of access to credit on household welfare in Ethiopia. The study contributes to the debate on the link between access to credit and household welfare and provides valuable input for policy makers.

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Zhang, Liangying, and Yunhua Wu. "The Effect of Farmers’ Insurance-Adoption Behavior on Input for Beef-Cattle Disease Prevention: Endogenous Switching Regression Model." Agriculture 15, no. 6 (2025): 659. https://doi.org/10.3390/agriculture15060659.

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This study selects the Inner Mongolia Autonomous Region (IMAR), among the most crucial beef-cattle farming areas in China, to obtain data from the micro-surveys of 447 beef-cattle farmers. Utilizing an endogenous switching regression (ESR) model, this research empirically investigates the effect of farmers’ beef-cattle insurance enrollment behavior on their input of disease prevention. This study finds that farmers adopting beef-cattle insurance reduce beef-cattle disease-prevention input. Based on counterfactual assumptions, if insured farmers had not adopted insurance, their input in disease prevention would increase by 33.45%. Further research confirms that a decrease in the market purchase price of beef cattle enhances the negative effect of farmers’ insured behavior on input for beef-cattle disease prevention. The heterogeneity analysis leads to two more conclusions. One is that insured farmers have the largest reduction in shed-disinfection input, the smallest reduction in voluntary vaccination input, and an intermediate reduction in deworming input. The other is that the act of adopting insurance reduces disease-prevention input to a greater extent for farmers who are far from the core areas of beef-cattle farming or who have not experienced beef-cattle deaths.

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Turinawe, A., and JH Ainembabazi. "Does pluralistic agricultural advisory service delivery enhance sustainable land management? Evidence from southwestern Uganda." African Journal of Food, Agriculture, Nutrition and Development 24, no. 5 (2024): 26493–513. http://dx.doi.org/10.18697/ajfand.130.23350.

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Declining land productivity and increasing land and food scarcity, amidst high population growth have precipitated the need for intensification of crop production. Sustainable land management technologies (SLMTs) have been suggested as a way to support the intensification process. In Uganda, agricultural advisory services (AAS) geared towards improved adoption of the SLMTs are provided, and farmers can access AAS from diverse sources, with the possibility of accessing from single or multiple sources. This study attempts to identify and prioritize the drivers of farmers’ access to (single/multiple) sources of AAS and determine the impact of access to these sources of AAS on the adoption of SLMT, and crop productivity. The study uses cross-sectional data collected from 435 households in the southwestern highlands of Uganda, in Kisoro and Kabale districts. The multinomial endogenous switching regression model combined with an endogenous switching regression model was used to analyse the data. Results indicate that both single and multiple sources of AAS have a positive effect on adoption of SLMTs and crop productivity, with the latter having a positive effect on the adoption of more SLMTs, while it seems to reduce the adoption of some other SLMTs. Similarly, accessing AAS from multiple sources has a higher positive impact on crop productivity, when compared to no access, but a lower impact when compared to access to a single source of AAS. These results suggest that access to multiple sources of AAS has positive impacts, but there are possible inherent challenges in the way it is implemented; lack of synchronisation of the messages given to the farmers, and the top-down approaches used to disseminate knowledge on SLMTs by some of the AAS providers may confound the possibly higher benefits of access to multiple sources of AAS. This study points out the need for policy to consider the advantages of having a streamlined agricultural extension system, with coordinated efforts from all agricultural advisory service providers and stakeholders. Key words: Agriculture, advisory services, sustainable land management, switching regression, highlands, Uganda

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Oparinde, Lawrence Olusola. "Land Rights and Improvement Investments Among Crop Farmers in Southwest, Nigeria." Nigerian Journal of Technological Research 16, no. 1 (2021): 1–12. http://dx.doi.org/10.4314/njtr.v16i1.1.

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This study examined the effects of land rights on investment decisions of farmers and determinants of land rights as well as the impact of land rights on farm productivity in Southwest Nigeria. Multistage sampling process was used in the selection of 320 respondents for the study. Two-stage conditional maximum likelihood (2SCML) approach of multivariate probit regression model and Endogenous switching regression (ESR) model were used for the analysis of the collected data. The results of Average Treatment Effect on the Treated (ATT) estimates from ESR revealed that land rights increase farm productivity. This study further confirmed the importance of land rights in facilitating investment in soil-improving measures which subsequently leads to higher productivity. One of the policy implications emanating from this study suggests that having use and transfer rights as against use only rights goes a long way in enhancing investment in soil-improving or conservation measures. Keywords: Crop, Investment, Land, Multivariate Probit Regression Model, Rights, Two-stage Conditional Maximum Likelihood.

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Zhang, Xiaoheng, Guiquan Yan, Qipei Feng, Amar Razzaq, and Azhar Abbas. "Ecological Sustainability and Households’ Wellbeing: Linking Households’ Non-Traditional Fuel Choices with Reduced Depression in Rural China." International Journal of Environmental Research and Public Health 19, no. 23 (2022): 15639. http://dx.doi.org/10.3390/ijerph192315639.

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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.

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Pigini, Claudia, and Stefano Staffolani. "Teleworkers in Italy: who are they? Do they make more?" International Journal of Manpower 40, no. 2 (2019): 265–85. http://dx.doi.org/10.1108/ijm-07-2017-0154.

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Purpose The 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/approach The 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. Findings Results 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/value Accounting 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.

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Kihoro, David, Geofrey Kingori Gathungu, Rael Nkatha Mwirigi, and Vicky Nyambura Wairimu. "Effects of Adoption of Agricultural Technologies on Irish Potato Yield in Ol Kalou Sub-County Kenya: Application of Endogenous Switching Regression Model." Turkish Journal of Agriculture - Food Science and Technology 13, no. 1 (2025): 151–57. https://doi.org/10.24925/turjaf.v13i1.151-157.7028.

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Population growth has increased demand and diversified use of Irish potato which have increased its demand. The crop has become a major source of food and income for many households across the world. However, despite the high potential of about 30 tonnes per hectare (ha), smallholder farmers in Kenya realize low Irish potato yields ranging from 4-8 tonnes per ha due to limited uptake of agricultural technologies. The low yields calls for a profound understanding of the factors influencing the uptake agricultural technologies. The study analyzed the effects of the adoption of agricultural technologies on Irish potato yield in Ol Kalou Sub County. The study considered chemical fertilizer, certified seeds, fungicides, and farm machinery as the four main agricultural technologies that that affect yield. A descriptive cross-sectional research design was used to obtain data from a study population of 21,942 smallholder Irish potato farmers in Ol Kalou Sub County. A multiple-stage sampling technique was employed to generate a sample size of 385 respondents who provided primary data. Data collected was analyzed using endogenous switching regression model using STATA version 17. The study found that the average treatment effect on treated (ATT) was 10.21 bags per acre. In addition, the Endogenous switching regression model showed that the expected yield for the adopter increased by 51.83%. Out of the four technologies, the use of chemical fertilizers had the highest effect of 37% on yield. The study concluded that the adoption of agricultural technologies increases the yield of Irish potatoes. The study recommends that national and county governments should develop policy regulations such as training and extension services, market access, price support and public-private partnerships encouraging farmers to uptake agricultural technologies. The study also recommends that both levels of government should subsidize agricultural technologies, hence reducing the cost of adoption.

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Luh, Yir-Hueih, Yun-Cih Chang, and Shuay-Tsyr Ho. "Crop Switching and Farm Sustainability: Empirical Evidence from Multinomial Treatment-Effect Modeling." Sustainability 14, no. 3 (2022): 1422. http://dx.doi.org/10.3390/su14031422.

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Crop switching has been examined in the literature addressing the production effects of irrigation or as viable strategy in the adaptation to climate change, which is closely related to agricultural resilience. Attention to the identification of the direct linkage between crop switching and farm profitability, and, thus, farm sustainability, however, has been quite limited. This study attempts to provide a significant complement to the extant research by identifying the treatment effect of crop switching on the net returns of crop growers in Taiwan. A multinomial endogenous treatment effects model with the latent-factor structure is used to take self-selection into account. The result suggests that farm households’ economic resilience is closely related to their choice of crops, which constitute the major source of farm income. Specifically, among the six cash crop categories, fruit crops and other crops are found to be most remunerating and, thus, suggests possible improvements in farm households’ economic resilience through crop switching. A further analysis of the distributional implications of crop switching through quantile regression confirms the persistent and stronger effects of crop choice on net returns when moving from the bottom to the top quartiles along the net-return distribution. This result suggests a close association of crop choices with farm income inequality among the crop farm households in Taiwan, which in turn implies possible distributional effects of crop switching.

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Zhao, J., J. Zhang, and P. J. Barry. "Do formal credit constraints affect the rural household consumption in China?" Agricultural Economics (Zemědělská ekonomika) 60, No. 10 (2014): 458–68. http://dx.doi.org/10.17221/161/2013-agricecon.

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The article investigates the consequences of credit constraints on rural household consumption in China. Based on a unique rural finance and consumption survey, the authors first identify the credit constraint status of rural households from formal financial institutions. Then, they apply an endogenous switching regression model to compare the consumption responses to household production inputs for credit constrained and non-constrained households. The estimation results reveal that the credit constraint could result in the crowding out effect of the aggregate household consumption from its production inputs. Nonetheless, similar to the non-constrained households, the credit constraint households are capable of smoothing their necessary consumption. &nbsp;

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Kabayiza, A., G. Owuor, K. J. Langat, P. Mugenzi, and F. Niyitanga. "Does credit utilization lead to increasing farm outcome? a micro-perspective of tea production from Rwanda." Agro-Science 20, no. 2 (2021): 92–100. http://dx.doi.org/10.4314/as.v20i2.15.

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Credit is a crucial factor for tea growers to pay for physical farm inputs mainly input fertilizers, research and development of high yielding tea clones and labour in order to improve the production of green tea leaf and to meet factories’ demand for raw materials. However, mismanagement of accessed credits by farmers has been reported among the snags affecting the sector development. The study analyzed the determinants and impact of credit utilization on farm income among smallholder tea growers in Nyaruguru District, Rwanda. Crosssectional tea household level data were collected from 358 farmers randomly selected from tea cooperatives. The credit utilization and causal effect were estimated using the Endogenous Switching Regression model. Results showed a positive and significant relationship between credit utilization and tea farm income. Precisely, the causal effect of credit is a 7% increase in tea income for farmers who utilised credit for tea production, while its potential effect is up to a 55% decrease in tea income for those who divert credit for out-off tea production uses. Furthermore, training on good agricultural practices and credit management, cost of farm inputs, labour and access to group credit significantly influence utilization of credit for tea production. However, the size of credit (cash) and off-farm businesses significantly increase the diversion of credit and level of tea farm income. Tea farmers are encouraged to use tea credits for planned projects. Sensitizing farmers to procure farm input fertilizers in bulk through cooperatives should be vigorously pursued to discourage credit diversion. Key words: tea credits, tea farming households, farm income, endogenous switching regression

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Kimhi, Ayal. "Estimation of an endogenous switching regression model with discrete dependent variables: Monte-Carlo analysis and empirical application of three estimators." Empirical Economics 24, no. 2 (1999): 225–41. http://dx.doi.org/10.1007/s001810050053.

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Hu, Zhineng, Qiong Feng, Jing Ma, and Shuangyi Zheng. "Poverty Reduction Effect of New-Type Agricultural Cooperatives: An Empirical Analysis Using Propensity Score Matching and Endogenous Switching Regression Models." Mathematical Problems in Engineering 2021 (June 10, 2021): 1–12. http://dx.doi.org/10.1155/2021/9949802.

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Agricultural cooperatives have been found to effectively alleviate poverty in developing countries because of their specific socioeconomic functions that allow poor households to overcome marketing and production constraints. However, cooperative evaluations are inevitably influenced by other poverty alleviation measures and rarely consider the characteristics of specific ethnic groups. Using cross-sectional surveys in Southwest China and employing propensity score matching (PSM) and endogenous switching regression (ESR) models, this paper analyzed the participation of poor households in New-type Agricultural Cooperatives (NACs) in ethnic areas and assessed the income impacts of NAC membership by eliminating unobserved biases and group heterogeneity. This study detected heterogeneous policy perceptions and behavioral differences between the member and nonmember groups, and the PSM and ESR model results indicated that, overall, participation in the NACs had a positive effect on household income. The ESR model was found to be more plausible as it was able to reveal the significant income gaps under a counterfactual inference framework. Local policymakers need to focus on the policy perception and behavioral and earning capability differences between groups and increase the balanced policy implementation.

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Cao, Yangzhe, Brent Swallow, and Feng Qiu. "Identifying the effects of a land-use policy on willingness to pay for open space using an endogenous switching regression model." Land Use Policy 102 (March 2021): 105183. http://dx.doi.org/10.1016/j.landusepol.2020.105183.

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Kumar, Suresh, D. R. Singh, G. K. Jha, N. P. Singh, and Kingsly T. Immanuelraj. "Impact of natural resource management technologies on technical efficiency in sorghum cultivation: Application of meta-frontier and endogenous switching regression model." AGRICULTURAL ECONOMICS RESEARCH REVIEW 33, confspl (2020): 85–98. http://dx.doi.org/10.5958/0974-0279.2020.00020.8.

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Sarma, P. K., and M. M. Rahman. "Impact of Government Agricultural Input Subsidy Card on Rice Productivity in Rajbari District of Bangladesh: Application of Endogenous Switching Regression Model." Universal Journal of Agricultural Research 8, no. 5 (2020): 131–45. http://dx.doi.org/10.13189/ujar.2020.080501.

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Journal articles on the topic 'Endogenous Switching Regression Model (ESRM)'

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