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

2019 ◽  
Vol 11 (11) ◽  
pp. 3221 ◽  
Author(s):  
Liqiong Lin ◽  
Weizhuo Wang ◽  
Christopher Gan ◽  
Quang T. T. Nguyen
Keyword(s):  
Rural China ◽  
Switching Regression ◽  
Probit Regression ◽  
Credit Constraint ◽  
Fujian Province ◽  
Switching Model ◽  
Rural Farmers ◽  
Endogenous Switching ◽  
Analyse Data ◽  
Land Size

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.

scholarly journals Rural Credit Constraint and Informal Rural Credit Accessibility in China

2019 ◽  
Vol 11 (7) ◽  
pp. 1935 ◽  
Author(s):  
Liqiong Lin ◽  
Weizhuo Wang ◽  
Christopher Gan ◽  
David A. Cohen ◽  
Quang T.T Nguyen
Keyword(s):  
Regression Model ◽  
Rural China ◽  
Rural Households ◽  
Switching Regression ◽  
Probit Regression ◽  
Credit Constraint ◽  
Endogenous Switching Regression ◽  
Rural Credit ◽  
Endogenous Switching ◽  
The Impact

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.

scholarly journals Credit Constraint and Rural Household Welfare in the Mezam Division of the North-West Region of Cameroon

2021 ◽  
Vol 13 (11) ◽  
pp. 5964
Author(s):  
Louis Atamja ◽  
Sungjoon Yoo
Keyword(s):  
Regression Model ◽  
Rural Household ◽  
Household Welfare ◽  
Switching Regression ◽  
Probit Regression ◽  
Credit Constraint ◽  
Endogenous Switching Regression ◽  
North West ◽  
The North ◽  
West Region

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.

scholarly journals Does agricultural cooperative membership help reduce the overuse of chemical fertilizers and pesticides? Evidence from rural China

2021 ◽  
Author(s):  
Tongshan Liu ◽  
Gang Wu
Keyword(s):  
Rural China ◽  
Institutional Arrangement ◽  
Agricultural Cooperatives ◽  
Switching Regression ◽  
Family Farms ◽  
Chemical Fertilizers ◽  
Agricultural Cooperative ◽  
Endogenous Switching ◽  
The Family ◽  
Esr Model

Abstract The overuse of chemical fertilizers and pesticides (CFPs) has negatively impacted the environment and human health. It is an urgent issue that should be addressed. In this study, we investigate whether agricultural cooperatives can serve as an institutional arrangement that helps reduce the consumption of CFPs, using the data of 2012 family farms from the Ministry of Agriculture and Rural Affairs of China. Various approaches, including instrumental variable based two-stage residual inclusion approach (2SRI), endogenous switching probit (ESP) model, and endogenous switching regression (ESR) model, are utilized to help address the endogeneity issues of the cooperative membership variable. The results show that agricultural cooperative membership significantly increases the probability of reducing fertilizers and pesticides of the family farms and improves net return per yuan CFPs. Our findings highlight the importance of promoting the development of agricultural cooperatives to support green agricultural production in China.

scholarly journals An Exponential Endogenous Switching Regression with Correlated Random Coefficients

Econometrics ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 1
Author(s):  
Myoung-Jin Keay
Keyword(s):  
Structural Equation ◽  
Structural Model ◽  
Random Coefficients ◽  
Switching Regression ◽  
Treatment Variable ◽  
Health Insurance Data ◽  
Switching Model ◽  
Large Samples ◽  
Endogenous Switching ◽  
Insurance Data

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.

Capital and credit constraints in the engagement of youth in Ghanaian agriculture

2019 ◽  
Vol 80 (1) ◽  
pp. 22-37 ◽  
Author(s):  
Martinson Ankrah Twumasi ◽  
Yuansheng Jiang ◽  
Monica Owusu Acheampong
Keyword(s):  
Positive Impact ◽  
Credit Constraints ◽  
Rural Youth ◽  
Unique Contribution ◽  
Switching Regression ◽  
Credit Constraint ◽  
Data Set ◽  
Content Type ◽  
Application Procedure ◽  
The Impact

Purpose The purpose of this paper is to determine the factors influencing rural youth farmers’ credit constraints status and the effect of credit constraint on the intensity of participation of these farmers in Ghana. Design/methodology/approach The econometric estimation is based on cross-sectional data collected in 2018 from the Brong Ahafo region in Ghana. The sample data set consists of 450 rural youth farmers. The collected data were analyzed through different econometric techniques, using the endogenous switching regression model (ERSM). Findings The direct elicitation approach employed in this study revealed that out of the 450 farmers, 211 (47 percent) of the respondents were credit constrained compared to 239 (53 percent) of their counterparts who were unconstrained. The ERSM indicated that youth farmers education, age, savings, parents occupation reduced the probability of the rural youth farmer to be credit constrained but cumbersome loan application procedure and loan disbursement time positively affect credit constraint. Moreover, farmers that are credit constrained have lower intensity of participation in agriculture activities than a random farmer from the sample. This suggests that access to credit has a positive impact on the intensity of participation in agriculture activities. Research limitations/implications In this study, only rural youth farmers in a particular region were considered. However, there are youths all over the nation. Therefore, future researchers could consider other youth’s farmers elsewhere in the country. Originality/value Although existing studies have examined rural youth farmers’ participation in agriculture and credit constraint separately, the unique contribution of this paper is the analysis of credit constraint of rural youth farmers as well as the impact of credit constraint on the intensity of participation in agriculture activities.

Pushed out or pulled in? Participation in non-farm activities in rural China

2017 ◽  
Vol 9 (1) ◽  
pp. 111-129 ◽  
Author(s):  
Yuanxiang Liu
Keyword(s):  
Rural China ◽  
Rural Households ◽  
Household Survey ◽  
Switching Regression ◽  
Content Type ◽  
Income Gap ◽  
Income Differential ◽  
Farm Production ◽  
Commercial Farming ◽  
The Impact

Purpose The purpose of this paper is to identify the determinants of China’s rural households’ non-farm participation. The authors pay special attention to the effect of potential income differential on this participation. Design/methodology/approach The data used in this study come from a household survey conducted in Hubei Province. The authors estimate participation equation and income equation, respectively, then introduce potential income differential simulated in participation equation to examine its effect on non-farm participation. Findings Potential income differential serves as the major pull factor that favors non-farm participation. Education, proximity to a city and specialized commercial farming are crucial in helping rural households to participate in non-farm production; while the land shortage or the labor surplus act as the push factor in non-farm participation. Better quality of land reduces the household’s propensity to participate in non-farm activities. Moreover, the income gap between households that participate in non-farm activities and pure farmers is mainly determined by the differences in household characteristics. Originality/value The authors use the method of “switching regression and structural probit” to examine the impact of potential income differential on non-farm participation, and simulate the response of the participation probability to the change of potential income differential. The authors also analyze the sources of income gap between non-farm and farm households using Oaxaca decomposition.

Distance Traveled in Times of Pandemic: An Endogenous Switching Regression Approach

2021 ◽  
pp. 135481662110594
Author(s):  
David Boto-García ◽  
Veronica Leoni
Keyword(s):  
Potential Change ◽  
Behavioral Adaptation ◽  
Selection Effects ◽  
Switching Regression ◽  
Population Composition ◽  
Endogenous Switching Regression ◽  
Endogenous Switching ◽  
Regression Approach

This paper studies the change in the distance traveled by domestic tourists considering the pre- and post-pandemic outbreak summer periods of 2019 and 2020. Using representative monthly microdata involving more than 31,000 trips conducted by Spanish residents, we examine the heterogeneity in behavioral adaptation to COVID-19 based on sociodemographic and trip-related characteristics. To account for selection effects and the potential change in the population composition of travelers between the two periods, we estimate an endogenous switching regression that conducts separate regressions for the pre- and post-pandemic periods in a unified econometric framework. Our results point to heterogeneous shifts in the distance traveled by domestic travelers after COVID-19 outbreak per sociodemographic group, with notable differences by travel purpose and lower relevance of traditional determinants like income.

An Endogenous Switching Model to Poverty Dynamic Assessment in Tunisia

2019 ◽  
pp. 303-312
Author(s):  
Amal Jmaii
Keyword(s):  
Panel Data ◽  
Panel Data Analysis ◽  
Dynamic Assessment ◽  
Panel Data Model ◽  
Initial Condition ◽  
Switching Model ◽  
Endogenous Switching ◽  
Poverty Status ◽  
Poverty Dynamic ◽  
Over Time

This paper focus on the determinants of poverty dynamics in Tunisia by performing a two-stage endogenous model using a Bayesian algorithm to avoid missing data. Based on this approach author show that panel data analysis can be performed through potential variables such presented by the work of Donald B. Rubin. This contribution is rather empirical; researcher propose a method based on the concept of causal inference that enable to execute a panel data model using independent surveys. As the author assert the dependence between poverty status over time, they choose to use an endogenous switching model take into consideration the form of endogeneity caused by initial condition.

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