scholarly journals The Analysis of Groundwater Quality and the Impact of Remedial Measures Adopted by the Wheat Growers: Using Endogenous Switching Regression Model Approach

2021 ◽  
Vol 3 (3) ◽  
pp. 144-151
Author(s):  
Mahreen Alam ◽  
Muhammad Ashfaq ◽  
Sarfraz Hassan ◽  
Asghar Ali
Keyword(s):  
Regression Model ◽  
Groundwater Quality ◽  
Farmyard Manure ◽  
Remedial Measures ◽  
Switching Regression ◽  
Economic Activities ◽  
Endogenous Switching Regression ◽  
Endogenous Switching ◽  
Experience Education ◽  
The Impact

Groundwater pollution is a serious problem, posing severe problems on many economic activities. The study's main objectives were to access the groundwater quality in the study area and analyze the role of farmers in improving the groundwater quality. Total 108 groundwater samples were collected from different locations along the 11-L distributary located in District Sahiwal, Punjab-Pakistan. Samples were tested to analyze the quality of groundwater for agriculture and livestock.  The parameters included pH, Ec, and TDS, were tested. Results showed that 14 samples were found to be fit, 23 were marginally fit and 71 were declared unfit for agricultural consumption. The results of CCME water quality index were also in favour of lab reports.  Most wheat-growing farmers were using gypsum as a remedial measure to minimize the side effects of poor groundwater quality. Few farmers were using farmyard manure to improve groundwater quality. There are many factors that influence the adoption of remedial measures to compensate for the poor groundwater. Farmers were facing a few limitations that compelled them to avoid incurring any further costs in order to improve groundwater quality. The financial constraint was the main issue. The endogenous switching regression model was used for data analysis. The findings revealed that family workers, experience, education, and soil quality positively impact remedial measures adoption. The study recommended that proper groundwater quality monitoring is required on a regular basis. Farmers should be educated regarding the proper use of gypsum. The sewerage system was absent in many villages of the study area. To avoid the further leaching of hazardous materials into groundwater, it is critical to construct an effective waste management system.

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.

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

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