scholarly journals Assessing the Impact of Climate Resilient Technologies in Minimizing Drought Impacts on Farm Incomes in Drylands

2021 ◽  
Vol 14 (1) ◽  
pp. 382
Author(s):  
Josily Samuel ◽  
Chitiprolu Anantha Rama Rao ◽  
Bellapukonda Murali Krishna Raju ◽  
Anugu Amarender Reddy ◽  
Pushpanjali ◽  
...  
Keyword(s):  
Household Income ◽  
Farm Size ◽  
Farm Income ◽  
Farm Household ◽  
Cropping Pattern ◽  
Factors Influencing ◽  
Control Village ◽  
On Farm ◽  
The Impact ◽  
Livestock Rearing

Abstract: Asia is the region most vulnerable to climate change and India is ranked as one of the most climate vulnerable countries in the world, frequently affected by natural disasters. In this study, we investigated the impact of drought on crop productivity, farmer’s employment and income. The difference-in-difference model (DID) and stepwise multiple linear regression (MLR) were employed to quantify the impact of adopting climate resilient technologies (CRTs) on farm household income during a drought. The factors influencing farm incomes were analyzed using MLR. The study used survey data collected from the drought prone district of Telangana, India. Sixty farmers each from a village adopted under the National Innovations in Climate Resilient Agriculture (NICRA) program and a control village were interviewed. Primary data on the socio-economic characteristic of farmers, cropping pattern, income composition, productivity of major crops, employment and climate resilient interventions adopted by farmers were collected using a well-structured schedule. The results reveal that income crop cultivation was the major contributor to household income (60%) followed by livestock rearing. Farmers reported that droughts decreased the income from crops by 54 per cent and income from livestock rearing by 40 per cent. The farmers belonging to the climate resilient village had 35 per cent higher incomes compared to those in the control village and it was estimated to be Rs. 31,877/farm household/year during droughts using the DID estimate. Farm size, livestock possession, adoption of CRTs and investment in agriculture were the determining factors influencing farm income. Thus, farmers especially in drought prone regions need to be encouraged and supported to adopt cost effective, location specific climate resilient technologies.

scholarly journals Farm household income inequality in Slovenia

2020 ◽  
Vol 17 (4) ◽  
pp. e0112 ◽  
Author(s):  
Štefan Bojnec ◽  
Imre Fertő
Keyword(s):  
Income Inequality ◽  
Agricultural Policy ◽  
Common Agricultural Policy ◽  
Household Income ◽  
Farm Income ◽  
Farm Household ◽  
Data Set ◽  
Market Income ◽  
On Farm ◽  
The Impact

Aim of study: To investigate the structure and evolution of farm household income and examine the contribution of different sources of farm household income, particularly the impact of Common Agricultural Policy reform on farm household income inequality in Slovenia.Area of study: Slovenia, one of the European Union member states.Material and methods: A panel data set was compiled using Slovenian Farm Accountancy Data Network data at farm level for the period 2007-2013. Total farm household income was disaggregated into two different components: 1) income components, which can contain market income and off-farm income, and 2) subsidy components, which can contain subsidies from Pillars 1 and 2. Pillar 2 support included subsidies related to agri-environmental measures, less favoured areas and other rural development measures. The income distribution and decomposition were examined using the Gini decomposition method to determine the contribution of each income source and the policy shift from market to government support on farm household income and overall inequality.Main results: A shift in Common Agricultural Policy and related measures determined the structure and evolution of farm household incomes. Off-farm income had a lesser and rather stable impact on farm household income inequality, while the major change involved an increase in the importance of subsidies from Pillar 2 which is consistent with a policy of targeting farms in less favoured areas. Subsidies from Pillar 1 reduced, while market income increased farm household income inequality.Research highlights: Subsidies in farm incomes increased. They could reduce farm household income inequality.

The Impact of Rural Taxation Reform on Farm Household Income

2009 ◽  
Vol 42 (4) ◽  
pp. 75-90 ◽  
Author(s):  
Cuiping Xu ◽  
Qinghua Shi ◽  
H. Holly Wang
Keyword(s):  
Household Income ◽  
Farm Household ◽  
Taxation Reform ◽  
On Farm ◽  
The Impact

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 Factors influencing the adoption of improved vegetable production practices among women farmers in Aguata-Agricultural Zone, Anambra State, Nigeria

Agrosearch ◽  
2021 ◽  
Vol 20 (2) ◽  
pp. 67-81
Author(s):  
L.E. Odoemlam ◽  
F.C. Nzeakor
Keyword(s):  
New Technologies ◽  
Women Farmers ◽  
Farm Size ◽  
Farm Income ◽  
Vegetable Production ◽  
Probit Regression ◽  
Factors Influencing ◽  
Production Practices ◽  
Adoption Level ◽  
On Farm

The study examined the level and determinants of adoption of improved vegetable production practices in the study area. A three-stage sampling procedure was used in the selection of 160 respondents. A structured questionnaire was used for data collection. Data collected were analysed using descriptive statistics and Probit regression model. Results on adoption level of the selected improved vegetable production practices indicated that improved seeds had a grand mean of 𝑥̅ = 3.17, field preparation (𝑥̅ = 3.19), planting distance (𝑥̅ = 2.99), water management (𝑥̅ = 3.43), fertilizer/organic manure application (𝑥̅ = 3.55), pesticides (𝑥̅ = 2.57), harvesting ( 𝑥̅= 5.00) and storage procedure (𝑥̅ = 4.89) based on 5-point Likert scale adoption level. On factors influencing adoption of improved vegetable production practices, the result revealed that farm size (1.00188***), credit access (4.704902**), on-farm demonstration (2.900749**) and farm labour (1.295902***) had a positive and significant influence on improved vegetable production practices by the respondents. The result further indicated that the age (0.3135258***) and the off-farm income (0.0870768) of the farmers had a negative influence on the adoption of improved vegetable production practices. Based on these findings, the study revealed that the women farmers could have full adoption of the improved production practices if the factors are adequately addressed. The study therefore recommends that before the introduction of a new technology, the ADPs should ensure that maximum audience analysis is carried out to address some of the factors influencing adoption. Besides, introduction of new technologies to farmers should go hand-in-hand with on-farm demonstration since it is by that they would develop confidence and allay their fears associated with improved practices.

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 DISTRIBUSI PENDAPATAN RUMAH TANGGA PETANI DI KABUPATEN KARANGANYAR

Agro Ekonomi ◽  
2016 ◽  
Vol 8 (1) ◽  
pp. 27
Author(s):  
Umi Barokah ◽  
Dwidjono Hadi Darwanto ◽  
Supriyanto Supriyanto
Keyword(s):  
Income Distribution ◽  
Household Income ◽  
Industrial Area ◽  
Farm Income ◽  
Cluster Sampling ◽  
Farm Household ◽  
Small Farmers ◽  
Income Household ◽  
Multi Stage ◽  
On Farm

The purpose of this research is to study the contribution of off-farm to income household and the effect of off-farm to income distribution between farm household. The location is choosen purposively based on the number of people as farmers, numbers and kind of industries and acessibility to reach economic centre. This research used multi stage sampling, the first was by cluster sampling, where all farm household from two village in Ngringo (kecamatan Jaten) and Tunggulrejo (kecamatan Jumantono) interviewed. And second stratified sampling based on farm size.The result showed that off-farm income (56,26 %) is greater than farm income (43,74 %). Off-farm income of small farmers (71,42 %) is greater than large farmers (45,18 %). Off-farm employment increased household income and the inequality of income tend to reduce. But off-farm employment is mainly for large farmers and close to the industrial area. In contrast, off-farm income increase inequality for small farmers in area far from industrial area

scholarly journals Technology Adoption and Off-Farm Household Income: The Case of Herbicide-Tolerant Soybeans

2005 ◽  
Vol 37 (3) ◽  
pp. 549-563 ◽  
Author(s):  
Jorge Fernandez-Cornejo ◽  
Chad Hendricks ◽  
Ashok Mishra
Keyword(s):  
Technology Adoption ◽  
Household Income ◽  
Nationwide Survey ◽  
Farm Household ◽  
Agricultural Technologies ◽  
Farm Work ◽  
Total Household Income ◽  
Herbicide Tolerant ◽  
On Farm ◽  
The Impact

We model the interaction of off-farm work and adoption of agricultural technologies and the impact of adopting these technologies on farm household income from on farm and off-farm sources after controlling for such interaction, and estimate the model for the case of adoption of herbicide-tolerant (HT) soybeans using a nationwide survey of soybean farms for 2000. We find that adoption of HT soybeans is positively and significantly related to off-farm household income for U.S. soybean farmers, after controlling for other factors. In addition, while on-farm household income is not significantly related to adoption, total household income increases significantly with adoption.

scholarly journals PENDAPATAN DAN TINGKAT KESEJAHTERAAN RUMAH TANGGA NELAYAN TRADISIONAL DI KECAMATAN TELUK PANDAN KABUPATEN PESAWARAN

2020 ◽  
Vol 8 (2) ◽  
pp. 272
Author(s):  
Marina Ulva ◽  
Fembriarti Erry Prasmatiwi ◽  
Eka Kasymir
Keyword(s):  
Household Income ◽  
Sampling Method ◽  
Binary Logistic Regression ◽  
Simple Random Sampling ◽  
Survey Method ◽  
Farm Household ◽  
Welfare Level ◽  
Factors Influencing ◽  
Central Agency ◽  
On Farm

This research is to analyze income obtained by traditional fishermen from fish catching, their householdincome, the level of welfare, and factors influencing the welfare level of traditional fishermen households inTeluk Pandan District. This study was conducted in Sukajaya Lempasing Village, Teluk Pandan District,Pesawaran Regency with a survey method. Respondents were 48 traditional fishermen who used netfish andwere selected using simple random sampling method. Household income consists of on farm, off-farm, andnon-farm. Household welfare level is analyzed by Central Agency on Statistics 2014 and the Sajogyo 1997criteria. The factors influencing welfare are determined using binary logistic regression. The resultsshowed that the income obtained by fishermen from fish catches in the western season was Rp6,570,375, inthe eastem season was Rp25,452,214, and in the normal season was Rp15,229,771. The contribution of fishcatches income (on farm) was 91.01 percent, the contribution of bussines income in the agricultural sectoroutside the fish catches (off farm) was 5.55 percent, and the contribution of business outside the agriculturalsector (non-farm) was 3.60 percent. As many as 68.77percent of the traditional fishermen households areclassified as unprosperous yet and 31.25 percent are prosperous based on Central agency on Statistics 2014criteria. The factors influencing the welfare of traditional fishermen households were the level of educationand income.Key words: income, traditional fishermen, welfare.

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 Impact of introducing low lift pump on improving income of farm households in some areas of Bhola district in Bangladesh

2012 ◽  
Vol 9 (2) ◽  
pp. 233-240
Author(s):  
MK Majumder ◽  
MS Rahman
Keyword(s):  
Household Head ◽  
Sampling Technique ◽  
Farm Households ◽  
Primary Data ◽  
Farm Income ◽  
Cropping Pattern ◽  
Cropping Patterns ◽  
On Farm ◽  
The Impact ◽  
Average Educational Level

This study focuses the impact of low lift pump (LLP) on farm income and cropping patterns followed by the selected farmers in Bhola district. A random sampling technique was used for the study. Primary data were collected from 60 LLP users from January to March, 2010 through two set of pre-tested questionnaires. Descriptive statistics and profit function were used in the study. Most of the farmers are well experience in farming. The average age of the household head is 47 for owner, 45 for tenant, 44 for owner cum tenant and 41 for LLP owners. The average educational level is 6 for owner, 4 for cash tenant, 5 for owner cum tenant and 5 for LLP Owners. Household size is the largest for cash tenant which is 5.36. Mug – Fallow - B.Aman was the main cropping patterns before using LLP and it was 39.22%. On the other hand, Boro – Fallow -T.Aman was the main cropping pattern after introducing LLP and it was 53.22% in the study area. The income increased in all categories of farmers due to the introduction of LLP. Cash tenant earned more and owner cultivators earned less among the farmer’s categories.   DOI: http://dx.doi.org/10.3329/jbau.v9i2.11035   J. Bangladesh Agril. Univ. 9(2): 233–240, 2011

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