The adoption and impact of E-commerce in rural China: Application of an endogenous switching regression model

2021 ◽  
Vol 83 ◽  
pp. 106-116
Author(s):  
Min Liu ◽  
Shi Min ◽  
Wanglin Ma ◽  
Tianjun Liu
Keyword(s):  
Regression Model ◽  
Rural China ◽  
Switching Regression ◽  
Endogenous Switching Regression ◽  
Endogenous Switching

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.

Cotton Yield and Climate Change Adaptation in Pakistan: Application of Multinomial Endogenous Switching Regression Model

2021 ◽  
Vol 7 (3) ◽  
Author(s):  
Muhammad Masood Anwar ◽  
Aisha Siddiqua ◽  
Aftab Anwar ◽  
Jamshaid Ur Rehman
Keyword(s):  
Climate Change ◽  
Regression Model ◽  
Management Practices ◽  
Household Survey ◽  
Switching Regression ◽  
Cotton Yield ◽  
Sources Of Information ◽  
Cotton Production ◽  
Endogenous Switching Regression ◽  
Endogenous Switching

Purpose:Cotton is the backbone of Pakistan economy, as country is the 4th largest producer of cotton in the world. Despite this importance there is steep decline in cotton production over time due to climate change. The need to evaluate the potential of adaptation in improving cotton yield has necessitated this study. Design/Methodology/Approach:This study is based on the farm household survey of four cotton producing districts, two from each Punjab and Sindh that were purposively selected from heat stress regions of Pakistan. Data were analyzed through multinomial endogenous switching regression model and treatment effect framework. Findings:Farm management practices were evaluated for their significance in reducing adverse impacts of climatic extremes on cotton yield. Adaptation in the combination of first three strategies observed to be the most successful strategies in increasing yield. Implications/Originality/Value:For effective adaptation access to credit and extension, education, farming experience, and sources of information revealed to be important predictors

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

2019 ◽  
Vol 6 (1) ◽  
pp. 20-33
Author(s):  
David Tanoh Aduhene ◽  
Sylvester Boadu ◽  
Ernest Obeng
Keyword(s):  
Regression Model ◽  
Financial Institutions ◽  
Primary Data ◽  
Easy Access ◽  
Switching Regression ◽  
Endogenous Switching Regression ◽  
Access To Credit ◽  
Agriculture Sector ◽  
Endogenous Switching ◽  
The Impact

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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