scholarly journals Off-farm Income, Credit Constraints, and Farm Investment

2020 ◽  
Vol 52 (4) ◽  
pp. 642-663
Author(s):  
Nigel Key
Keyword(s):  
Household Income ◽  
Credit Constraints ◽  
Limited Resource ◽  
Capital Expenditures ◽  
Farm Income ◽  
Farm Labor ◽  
Federal Programs ◽  
Net Worth ◽  
Access To Credit ◽  
Farm Investment

AbstractMany farmers face borrowing limits that depend on their household income and net worth. Given such credit constraints, an increase in off-farm income should allow farmers to borrow more, thus influencing production decisions and productivity. To test this hypothesis, the education level of the farm operator’s spouse is used to identify exogenous variation in off-farm income. Findings indicate that higher off-farm income leads to more borrowing, capital expenditures, capital input intensity, farm labor use, output, farm income, and productivity. Results suggest that Federal programs that promote access to credit for limited-resource farmers may increase farm investment and productivity.

scholarly journals Farm Household Income and On- and Off-Farm Diversification

2005 ◽  
Vol 37 (1) ◽  
pp. 37-48 ◽  
Author(s):  
Kevin T. McNamara ◽  
Christoph Weiss
Keyword(s):  
Household Income ◽  
Census Data ◽  
Farm Income ◽  
Federal State ◽  
Farm Labor ◽  
Farm Household ◽  
Labor Allocation ◽  
Farm Diversification ◽  
Upper Austria ◽  
On Farm

The paper analyzes the relationship between off-farm labor allocation and on-farm enterprise diversification as farm household income stabilization strategies with census data from the federal state of Upper Austria, Austria. The results suggest that both on-farm diversification and off-farm labor allocation are related to farm and household characteristics. Larger farms tend to be more diversified. Younger farmers are more likely to work off-farm. Larger farm households tend to allocate more labor to off-farm income activities.

scholarly journals The Impact of Internet Use on Income: The Case of Rural Ghana

2020 ◽  
Vol 12 (8) ◽  
pp. 3255 ◽  
Author(s):  
Anthony Siaw ◽  
Yuansheng Jiang ◽  
Martinson Ankrah Twumasi ◽  
Wonder Agbenyo
Keyword(s):  
Household Income ◽  
Internet Use ◽  
Farm Households ◽  
Farm Income ◽  
Switching Regression ◽  
Information Communication ◽  
Education Access ◽  
Access To Credit ◽  
Employment Education ◽  
The Impact

This study analyzed the effects of internet use on farm income and household income using survey data from 478 rural farmers from two regions in Ghana. An endogenous switching regression (ESR) model and probit models were employed to achieve the aims of the study. The results revealed that internet use was influenced by off-farm employment, education, access to credit, non-fixed asset (NFA), age, and perception variables. We found that internet use increased farm income and household income by 20.1% and 15.47%, respectively. Regarding heterogeneous impacts, the estimates showed that internet use reduced farm income by 18.12% for farm households that participated in off-farm activities but increased farm income by 14.66% for households that had access to NFA. The estimates also indicated that internet use increased household income by 31.77% for farm households that engaged in off-farm employment and by 15.33% for those that had access to NFA. Furthermore, internet use increased the household income for households that did not engage in off-farm activities by 24.85%. The findings of this study will contribute significantly to the existing literature on information communication technology (ICT) in developing countries by providing a new reference for improving rural development and solving the problem of poverty.

scholarly journals Farm Income Variability and the Supply of Off-Farm Labor by Limited-Resource Farmers

2004 ◽  
Vol 36 (2) ◽  
pp. 467-479 ◽  
Author(s):  
Oscar Vergara ◽  
Keith H. Coble ◽  
George F. Patrick ◽  
Thomas O. Knight ◽  
Alan E. Baquet
Keyword(s):  
Labor Supply ◽  
Limited Resource ◽  
Farm Income ◽  
Farm Labor ◽  
Farm Work ◽  
Income Transfers ◽  
Experience Education ◽  
The Government ◽  
Income Variability ◽  
On Farm

We study the relationship between the off-farm labor decision and the limited-resource farmers' and spouses' off-farm wages, experience, education, and sources of income. We found that farmers' and spouses' off-farm experience and wages are significant factors in explaining the off-farm labor supply decision. Contrary to expectations, farm income variability is not significant in the farmers' and spouses' decision to seek off-farm work. The off-farm labor supply of farmers and their spouses is negatively correlated with income transfers from the government. It was also found that the spouse is a residual supplier of on-farm and off-farm labor.

scholarly journals Adoption of improved agricultural technology and its impact on household income: a propensity score matching estimation in eastern Ethiopia

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Muluken G. Wordofa ◽  
Jemal Y. Hassen ◽  
Getachew S. Endris ◽  
Chanyalew S. Aweke ◽  
Dereje K. Moges ◽  
...  
Keyword(s):  
Propensity Score ◽  
Propensity Score Matching ◽  
Technology Use ◽  
Household Income ◽  
Agricultural Technology ◽  
Primary Data ◽  
Farm Income ◽  
Agricultural Technologies ◽  
Eastern Ethiopia ◽  
The Impact

Abstract Background Adoption of improved agricultural technologies remains to be a promising strategy to achieve food security and poverty reduction in many developing countries. However, there are limited rigorous impact evaluations on the contributions of such technologies on household welfare. This paper investigates the impact of improved agricultural technology use on farm household income in eastern Ethiopia. Methods Primary data for the study was obtained from a random sample of 248 rural households, 119 of which are improved technology users and the rest are non-users. The research employed the Propensity Score Matching (PSM) procedure to establish the causal relationship between adoption of improved crop and livestock technologies and changes in farm income. Results Results from the econometric analysis show that households using improved agricultural technologies had, on average, 23,031.28 Birr (Birr is the official currency of Ethiopia. The exchange rate according to the National Bank of Ethiopia (NBE) was 1 USD = 27.6017 Birr on 04 October 2018.) higher annual farm income compared to those households not using such technologies. Our findings highlight the importance of promoting multiple and complementary agricultural technologies among rural smallholders. Conclusions We suggest that rural technology generation, dissemination and adoption interventions be strengthened. Moreover, the linkage among research, extension, universities and farmers needs to be enhanced through facilitating a multistakeholders innovation platforms.

How access to non‐farm income affects farm investment in rural India?

2021 ◽  
Author(s):  
Zeeshan ◽  
Mohd Arshad Khan ◽  
Md Riyazuddin Khan ◽  
Neena Pandey ◽  
Isha Kaushik ◽  
...  
Keyword(s):  
Rural India ◽  
Farm Income ◽  
Farm Investment

scholarly journals The Impact of Cooperative Membership on Fish Farm Households’ Income: The Case of Ghana

2021 ◽  
Vol 13 (3) ◽  
pp. 1059
Author(s):  
Martinson Ankrah Twumasi ◽  
Yuansheng Jiang ◽  
Bismark Addai ◽  
Zhao Ding ◽  
Abbas Ali Chandio ◽  
...  
Keyword(s):  
Peer Influence ◽  
Household Income ◽  
Sample Selection ◽  
Institutional Arrangement ◽  
Fish Farm ◽  
Farm Income ◽  
Switching Regression ◽  
Farm Work ◽  
Household Heads ◽  
The Impact

The emergence of agricultural cooperatives is extensively viewed as a necessary institutional arrangement that can help farmers in developing countries overcome the constraints that impede them from improving sustainable agricultural production and acquiring new marketing opportunities. Therefore, this study examines the determinants of cooperative membership and its impact on fish farm household income, using data collected from two regions in Ghana. An endogenous switching regression (ESR) model is utilized to address the potential sample selection bias issue. The results show that household heads’ decisions to join cooperatives are affected by their access to credit, off-farm work, education level, and peer influence. Cooperative membership can increase both household and farm income by 28.54% and 34.75%, respectively. Moreover, we show that different groups of households’ cooperative impacts on farm and household income are heterogeneous. Our findings highlight the importance of cooperative patronization and provide implications that can improve households’ welfare.

scholarly journals ANALISIS PENDAPATAN DAN TINGKAT KESEJAHTERAAN RUMAH TANGGA MASYARAKAT SEKITAR TAMAN NASIONAL BUKIT BARISAN SELATAN KABUPATEN PESISIR BARAT

2021 ◽  
Vol 9 (3) ◽  
pp. 418
Author(s):  
M. Reza Fachrezy ◽  
Zainal Abidin ◽  
Adia Nugraha
Keyword(s):  
Household Income ◽  
National Park ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Farm Income ◽  
Labor Costs ◽  
The Third ◽  
Average Household Income ◽  
Average Education ◽  
On Farm

This study aims to determine the socio-economic characteristics of farmers, analyze the income structure, the factors that affect the income of farmers, and the level of household welfare of farmers who live around Bukit Barisan Selatan National Park, Pesisir Barat District. This research is a survey research involving 99 respondents who were randomly selected. Respondents were spread across four subdistricts, namely Bengkunat Belimbing, Ngambur, Pesisir Selatan, and Karya Penggawa Districts. The study was conducted from July to August 2018. The first objective was analyzed qualitatively, the second objective was analyzed using household income analysis, the third objective used multiple linear regression analysis, and the fourth objective was using Sajogyo's criteria (1997). The study suggested that the socio-economic characteristics of the farmers around TNBBS were spread from 15 to 64 years of age with an average age of 43.74 years. The average education level was elementary school, the number of majority of family sizes was from 4 to 6 people (67.68%), and the average land was 1.41 ha. The average household income of farmers is IDR 36,946,883.94 per year, which consists of on-farm income 63.68%, off-farm income 11.00%, and non-farm income 25.33%.. Factors that affect farmers' income are fertilizer costs and labor costs. The welfare of farmers around TNBBS is in quite prosperous category.Key words: characteristics, household income, welfare

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