scholarly journals Evaluating the Impact of Large-Scale Agricultural Investments on Household Food Security Using an Endogenous Switching Regression Model

Land ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 323
Author(s):  
Wegayehu Fitawek ◽  
Sheryl Hendriks
Keyword(s):  
Food Security ◽  
Regression Model ◽  
Selection Bias ◽  
Large Scale ◽  
Household Food Security ◽  
Switching Regression ◽  
Endogenous Switching Regression ◽  
Household Food ◽  
Endogenous Switching ◽  
Agricultural Investments

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.

scholarly journals Does smallholder farmers’ awareness of Sustainable Development Goal 2 improve household food security in the Northern Region of Ghana?

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Franklin Nantui Mabe ◽  
Eliasu Mumuni ◽  
Nashiru Sulemana
Keyword(s):  
Sustainable Development ◽  
Food Security ◽  
Smallholder Farmers ◽  
Northern Region ◽  
Household Food Security ◽  
Switching Regression ◽  
Sustainable Development Goal ◽  
Endogenous Switching Regression ◽  
Development Goal ◽  
Household Food

Abstract Background Sustainable Development Goal 2 aims at ending hunger, achieving food security, improving nutrition and promoting sustainable agriculture. Whilst some smallholder farmers are aware of this goal, others are not. The question that arises is whether or not awareness translates into food security. Therefore, this study assessed whether or not smallholder farmers’ awareness of Sustainable Development Goal 2 improves household food security in the Northern Region of Ghana. Methods The study used cross-sectional primary data collected from two districts and two municipalities in the region. An endogenous switching regression treatment effects model with ordered outcome was used to estimate the effects of smallholder farmers’ awareness of Sustainable Development Goal 2 on household food insecurity level. Results The age of household head, distance of households to the regional capital, membership of farmer-based organizations, access to e-extension, education, and ownership of radio are the key drivers of farmers’ awareness of Sustainable Development Goal 2. The results from the endogenous switching regression treatment effects model with ordered outcome showed that households who are aware of the second goal are more food secure than their counterparts. Conclusions It is therefore prudent for stakeholders promoting and championing Sustainable Development Goals to educate farmers on goal 2 as their awareness of the goal is critical to achieving food security.

The effect of large-scale agricultural investments on household food security in Madagascar

Food Security ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1349-1365
Author(s):  
Wegayehu Fitawek ◽  
Sheryl Hendriks ◽  
Aurélien Reys ◽  
Filippo Fossi
Keyword(s):  
Food Security ◽  
Large Scale ◽  
Household Food Security ◽  
Household Food ◽  
Agricultural Investments

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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