scholarly journals Does Off-Farm Work Improve Farm Income? Empirical Evidence from Tolon District in Northern Ghana

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Benjamin Tetteh Anang ◽  
Kwame Nkrumah-Ennin ◽  
Joshua Anamsigiya Nyaaba
Keyword(s):  
Propensity Score ◽  
Propensity Score Matching ◽  
Empirical Evidence ◽  
Farm Size ◽  
Northern Ghana ◽  
Farm Income ◽  
Income Diversification ◽  
Farm Work ◽  
On Farm ◽  
The Impact

Participation of farm households in off-farm work has gained prominence in recent times as an income diversification strategy. The effect of off-farm work on farm income is however unclear. This paper therefore sought to provide empirical evidence of the income effect of off-farm activity participation using a cross section of maize farmers in Tolon District of Ghana as a case study. In order to account for sample selection bias, the Heckman selection model was used to estimate the factors influencing participation in off-farm work and the determinants of farm income. Furthermore, the study employed propensity score matching to evaluate the impact of off-farm work on farm income. The results indicate that participation in off-farm work is influenced by sex, age, and years of formal education of the respondent, farm size, and number of dependents while farm income is influenced by age of the respondent, farm size, and access to credit. In addition, the result of the propensity score matching revealed that participants in off-farm work increased their farm income by at least GH¢ 1702 as a result of income diversification. The rural economy therefore provides off-farm and on-farm linkages that enhance farmers’ income from agriculture. The creation of employment opportunities outside the farm will therefore complement on-farm work and enhance income from farming.

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.

scholarly journals The Effects of Non-Farm Enterprises on Farm Households’ Income and Consumption Expenditure in Rural India

2019 ◽  
Vol 19 (1) ◽  
pp. 195
Author(s):  
. Zeeshan ◽  
Geetilaxmi Mohapatra ◽  
Arun Kumar Giri
Keyword(s):  
Propensity Score ◽  
Farm Households ◽  
Rural India ◽  
Farm Income ◽  
Consumption Expenditure ◽  
Income Diversification ◽  
Probit Models ◽  
Structural Differences ◽  
Nationally Representative ◽  
On Farm

Nationally representative data of farm households from India Human Development Surveys (IHDS) conducted in 2004-05 and 2011-12 are explored. This article analyzes the effects of income diversification in non-farm enterprises on farm households’ income and consumption expenditure in rural India. Panel probit models were built to examine the determinants of income diversification while propensity score matching was used to account selection bias resulting from unobserved factors and controls for structural differences between diversified and undiversified farm households. The results suggest that by engaging in non-farm enterprises, rural farm households make positive gains in farm income and consumption expenditure.

Geographical Indications and their Impact on Territorial Development: Empirical Evidence for Brazilian Municipalities

2021 ◽  
Vol 39 (8) ◽  
Author(s):  
Mirna de Lima Medeiros ◽  
Augusta Pelinski Raiher ◽  
João Luiz Passador
Keyword(s):  
Propensity Score ◽  
Propensity Score Matching ◽  
Empirical Evidence ◽  
Public Policies ◽  
Geographical Indications ◽  
Territorial Development ◽  
Matching Method ◽  
Development Intervention ◽  
The Impact

The promotion of Geographical indications (GIs) as a development intervention has gained growing support. However, despite discussions related to the development resulting from GIs, studies quantifying the impact of public policies for geographical indications are still scarce. In an attempt to fill in this gap, this paper evaluated the effect of geographical indications (GIs) in the process of territorial development of Brazilian municipalities, focusing on the coffee and wine GIs. Therefore, we employed the Propensity Score Matching method. Our results demonstrated a positive mean effect for most of the variables selected, evidencing the importance of the GIs for territorial development.

Impact of Improved Agricultural Technology Use on Household Income in Eastern Ethiopia: Empirical Evidence from a Propensity Score Matching Estimation

2021 ◽  
pp. 232102492110076
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

This article investigates the impact of improved agricultural technology use on farm household income in eastern Ethiopia. Primary data for the study were 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 procedure to establish the causal relationship between adoption of improved crop and livestock technologies and changes in farm income. Results from the econometric analysis show that households using improved agricultural technologies had, on average, 23,031.28 Birr1 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. Therefore, 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 multistakeholder innovation platforms.

scholarly journals Effect of off-farm work on agricultural productivity: empirical evidence from northern Ghana

2019 ◽  
Vol 11 (1) ◽  
pp. 49-58 ◽  
Author(s):  
B.T. Anang
Keyword(s):  
Empirical Evidence ◽  
Positive Impact ◽  
Agricultural Productivity ◽  
Northern Ghana ◽  
Farm Household ◽  
Switching Regression ◽  
Income Diversification ◽  
Farm Work ◽  
Rice Productivity ◽  
Household Heads

Abstract. In recent years, there has been increasing recognition of the importance of income diversification to agrarian households in developing countries. Empirical evidence of the effect of farm household income diversification on agricultural productivity remains scanty and inconclusive. An important policy question concerns the effect that farmer participation in off-farm work has on agricultural productivity. This paper answers that question by examining the factors that explain the decision of farm household heads to work off-farm and how this impacts farm productivity using a sample of 300 rice producing households in northern Ghana. Endogenous switching regression model supported by a treatment effect model was used to empirically assess the effect of off-farm work on agricultural productivity. Results show that engagement in off-farm work has a robust and positive impact on rice productivity. Farmers’ choice to work outside the farm thus contributed significantly to rice productivity of smallholders, confirming the role of income diversification in contributing to agricultural productivity of agrarian households.

scholarly journals Does microcredit use helps farmers win battle against food insecurity: evidence from Jimma zone of Southwest Ethiopia

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Amanuel Berhanu ◽  
Abayineh Amare ◽  
Birki Gurmessa ◽  
Yadeta Bekele ◽  
Tamiru Chalchisa
Keyword(s):  
Food Security ◽  
Propensity Score ◽  
Propensity Score Matching ◽  
Smallholder Farmers ◽  
Labour Force ◽  
Household Food Security ◽  
Farm Income ◽  
Household Food ◽  
Jimma Zone ◽  
The Impact

Abstract Background Lack of access to credit precludes smallholder farmers from making investment that generates greater level of income, consumption and wealth. To reverse this limit, Oromia Credit and Saving Share Company has been providing microcredit for rural households for the last two decades in the study area. Yet, there is limited knowledge on the impact of this microcredit service on rural household food security in Jimma zone. Therefore, this research aims at generating location-specific data on the impact of microcredit utilization on household food security in the study area. A multistage sampling procedure was employed to select 360 sample households. Data were generated through household survey, focus group discussion and key informant interview. Both descriptive and econometric data analysis techniques (binary logit model and Propensity score matching) were used. Results The results reveal that educational level, family size; land size and non/off-farm income of the households influenced microcredit utilization positively, whereas livestock ownership and farm income negatively influenced it. The analysis of food security status indicate that large proportion of households are food secure. The Propensity score matching result expose that microcredit utilization has generated a positive and significant impact on household food security. Conclusions Efforts towards scaling out services of microcredit institutions should target improving financial literacy of the rural poor and their current financial need on the basis of other resources such as land and livestock they owned with the ultimate goal of ensuring household food security. It is also imperative to realize the labour force capacity of the households in the process of expanding credit service.

Profitability analysis of rice production: a microeconomic perspective from northern Ghana

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abraham Zakaria ◽  
Shaibu Baanni Azumah ◽  
Gilbert Dagunga ◽  
Mark Appiah-Twumasi
Keyword(s):  
Cost Benefit ◽  
Rice Production ◽  
Farm Size ◽  
Northern Ghana ◽  
Farm Income ◽  
Content Type ◽  
Rice Farmers ◽  
Profitability Analysis ◽  
Significant Difference ◽  
The Impact

PurposeThe purpose of this study is to estimate the profitability of rice production for irrigated and rain-fed farmers; determine the factors that influence farmers' decision to participate in irrigation and the impact of irrigation on rice farmers' profitability in northern Ghana.Design/methodology/approachUsing cross-sectional data collected from 543 rice farmers in northern Ghana, the study employed both non-parametric (cost benefit analysis) and parametric (endogenous switching regression) approaches to analyse the data.FindingsThe empirical results reveal a significant difference between the profits of irrigated (GHS 2442.30) and rain-fed farmers (GHS 576.20), as well as the cost-benefit ratios between irrigators (2.53) and rain-fed farmers (1.37). Also, participation in irrigation was found to be influenced by relatively small farm size and off-farm income; while profitability was influenced by membership in a farmer-based organization, access to agricultural extension services and perception of decreasing rainfall intensity. Irrigation also had a positive significant net impact on profitability of rice production.Research limitations/implicationsThe results provide justification for development partners and the government of Ghana through the “one-village-one-dam” policy, to invest in irrigation in northern Ghana in order to improve household welfare as well as build resilience for sustainable production systems.Originality/valueThis study is the first of its kind to provide a robust analysis of the difference in profits of rain-fed and irrigated rice farmers while estimating the determinants of Ghanaian farmers' choice of either of the regimes within a bias-corrected framework.

scholarly journals Sustainable Soil Management Practices: Adoption and Its Impact on Farm Income in Ramechhap District, Nepal

2016 ◽  
Vol 3 (1) ◽  
pp. 33
Author(s):  
Rishi Ram Kattel ◽  
Suraj Acharya
Keyword(s):  
Nuclear Family ◽  
Household Head ◽  
Soil Management ◽  
Family Type ◽  
Farm Size ◽  
Farm Income ◽  
Tomato Production ◽  
Sustainable Soil Management ◽  
On Farm ◽  
The Impact

This study was carried out to assess the impact of sustainable soil management (SSM) practices in relation to technology adoption and farm income in Ramechhap district of Nepal in 2015. Total 120 sample households were taken (60 SSM practices adopters and 60 non-adopters) using random sampling technique. Primary data were collected through face-to-face interview, focus group discussion, direct observation and key informant interview to gauge the impact using with-without SSM project intervention approach. Descriptive statistics along with independent t-test, chi square test, Probit and income function multi-regression models were used for data analysis. From the cost-benefit analysis, in tomato production, all the variables were found to be significantly different except cost of planting materials. The gross margin, gross income and B: C ratio were also found to be significantly different in tomato production by SSM practices adoption. In beans, potato and cauliflower production, most of the variables were found to be significantly different. The results revealed that, farm income was higher in adopters by significant margin whereas the income from services and remittance was higher in non-adopters than adopters. Probit model revealed that type of family and trainings received were found statistically and positively significant on SSM practices adoption whereas education of household head had negative impact. Income function multi-regression model showed that SSM adoption, male of the respondent, education of the household head and farm size have positively significant on farm income whereas nuclear family type was negatively determinate on farm income. Among the variables, SSM practices adoption was major determinate factor on farm income. If farmer adopted SSM practices, farm income would be about 198 percent higher than among non-adopters. SSM technology has identified an environmentally friendly and improved rural farmers’ income in a sustainable manner in Nepal.

scholarly journals Labour-use pattern on Swiss dairy farms

2013 ◽  
Vol 59 (No. 4) ◽  
pp. 149-159
Author(s):  
M. Lips ◽  
D. Schmid ◽  
P. Jan
Keyword(s):  
Spatial Data ◽  
Dairy Farms ◽  
Farm Size ◽  
Farm Income ◽  
Marginal Effect ◽  
Farm Work ◽  
Farm Family ◽  
Wage Labour ◽  
Use Pattern ◽  
On Farm

Abstract: Analysing the labour-use pattern on Swiss dairy farms, we apply a typology scheme with two criteria: on-farm wage labour and off-farm family labour. The resultant four farm types are analysed based on the data from the Swiss Farm Accountancy Data Network (FADN) as well as the spatial data on available jobs. Only 17% of dairy farms have neither on-farm wage labour nor off-farm family labour. 60 % have family members involved in off-farm activities. On average, 0.3 annual work units (AWU) are employed in off-farm activities, earning double the on-farm income per AWU. In line with the literature, we found that the likelihood of on-farm wage labour increases with the farm size and the degree of diversification. Involvement in off-farm activities is more likely if the farm manager is young and has a spouse with a non-agricultural education. Furthermore, private consumption per consumer unit has a positive marginal effect on the likelihood of off-farm work. Finally, no evidence was found of available jobs within a range of 10 kilometres acting as a proxy for the local labour demand for off-farm activities, leading us to the conclusion that involvement in off-farm work is an option for most of the analysed dairy farms.  

scholarly journals Determinants of Off-Farm Income among Smallholder Rice Farmers in Northern Ghana: Application of a Double-Hurdle Model

2019 ◽  
Vol 2019 ◽  
pp. 1-7 ◽  
Author(s):  
Benjamin Tetteh Anang ◽  
Richard W. N. Yeboah
Keyword(s):  
Rural Areas ◽  
Smallholder Farmers ◽  
Northern Ghana ◽  
Farm Income ◽  
Hurdle Model ◽  
Income Diversification ◽  
Farm Work ◽  
Double Hurdle Model ◽  
Rice Farmers ◽  
Double Hurdle

Income diversification by farm households has gained the attention of researchers and policy makers due to its commonness especially in developing countries. This study sought to empirically investigate the determinants of off-farm income among smallholder farmers in northern Ghana using a sample of 300 rice farmers. A double-hurdle model was used to determine the factors influencing participation in off-farm work as well as the predictors of actual amounts earned from working outside the farm. The results revealed that gender, farming experience, years of education, and access to credit are the factors determining participation in off-farm work while farming experience, years of education, and geographical location are the determinants of income from off-farm work. The paper concludes that measures to enhance rural income diversification will spur the rural economy and these measures should seek to address the problem of low level of formal education in rural areas.

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