The Impact of Farmland Price Changes on Farm Size and Financial Structure

1986 ◽  
Vol 68 (4) ◽  
pp. 838-848 ◽  
Author(s):  
J. DeBoer‐Lowenberg ◽  
Michael Boehlje
Keyword(s):  
Financial Structure ◽  
Farm Size ◽  
Price Changes ◽  
On Farm ◽  
The Impact

scholarly journals Impact of Federal Fiscal-Monetary Policy on Farm Structure

1983 ◽  
Vol 15 (1) ◽  
pp. 61-68 ◽  
Author(s):  
Luther Tweeten
Keyword(s):  
Price Level ◽  
Aggregate Demand ◽  
Farm Size ◽  
Full Time ◽  
Capital Labor Ratio ◽  
Farm Structure ◽  
Investment Capital ◽  
Part Time ◽  
On Farm ◽  
The Impact

This paper examines the impact of federal fiscal-monetary (FM) policy on farm structure. FM policy is multifaceted but is confined here mainly to policies influencing aggregate demand. Inflation is defined as an increase in the general price level. Farm structure refers to farm size and numbers, tenure, legal organization, investment, capital-labor ratio, productivity, and status (part-time or full-time farming).

scholarly journals Impact of Formal Financial Market Participation on Farm Size and Expenditure on Variable Farm Inputs: The Case of Maize Farmers in Ghana

2014 ◽  
Vol 2014 ◽  
pp. 1-9
Author(s):  
Dadson Awunyo-Vitor ◽  
Ramatu M. Al-Hassan ◽  
Daniel B. Sarpong
Keyword(s):  
Financial Market ◽  
Farm Size ◽  
Market Participation ◽  
Financial Market Participation ◽  
Multistage Sampling ◽  
Improved Technology ◽  
On Farm ◽  
The Impact ◽  
Farm Inputs ◽  
Structured Questionnaire

The study examined maize farmers’ participation in the formal financial market and its impact on farm size and expenditure on variable farm inputs. A multistage sampling method was used in selecting 595 maize farmers from the seven districts in Ashanti and Brong Ahafo Regions of Ghana. A structured questionnaire and interview schedule were used to elicit information from the respondents. The impact of formal financial market participation on farm size and expenditure on variable inputs was estimated using Propensity Score Matching (PSM) method. The results of the study showed that formal financial market participation has the potential to significantly increase expenditure on variable inputs by farmers and consequently use of improved technology. Therefore, formal financial market participation should be encouraged through education and promotional activities.

scholarly journals The Impact of IFAD’s Involvement as an Inter-Governmental Organisation in the Livelihood of Moroccan Family-Farms

2021 ◽  
Vol 17 (1) ◽  
pp. 47-76
Author(s):  
Gwladys Nicimbikije ◽  
Elisabeth Dewi
Keyword(s):  
Geographical Location ◽  
Skills Training ◽  
Farm Size ◽  
Family Farms ◽  
Family Farming ◽  
Rural Transformation ◽  
Intergovernmental Organization ◽  
On Farm ◽  
The Impact

Family farming exists overall and each has its own unicity in term of managing the farm operations, farm size, productivity, socio-economic conditions, local knowledge and geographical location besides the externalities such as depletion of resources exacerbated by the climate change. Hence, the following question drove the authors: “to what extent of involvement are intergovernmental organization concerned with farmers’ livelihood in Morocco?” Therefore, this research purpose outlines the role of family farming and their characteristics; challenges of farming livelihood and productivity in Morocco; and IFAD’s support for inclusive rural transformation. The authors hold view that family farming with higher on-farm innovative inputs of processing activities can expect increased yield. The findings revealed that IFAD’s global governance endowed by modern corporation, -corporate governance for instance, - enables participation of rural beneficiaries in their projects thus increases their self-management onto (environmental) natural resources and sustainability. Skills, training, innovation and technologies allow them to diversify and intensify their agricultural holdings hence access to new markets and cope with the ecological risks though there is limitation with the innovation and services extension.

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 EFFECT OF LAND OWNERSHIP ON THE TECHNICAL EFFICIENCY OF CROP FARMERS

2021 ◽  
Vol 53 (4) ◽  
pp. 357-367
Author(s):  
Adedeji OGUNWUSI ◽  
Ivie OLAGHERE ◽  
Olubunmi OMOTESHO
Keyword(s):  
Technical Efficiency ◽  
Land Ownership ◽  
Average Treatment Effect ◽  
Farm Size ◽  
Stochastic Production Frontier ◽  
Access To Credit ◽  
Farm Efficiency ◽  
The Government ◽  
On Farm ◽  
The Impact

The essence of this study was to examine the land ownership pattern in Osun State, Nigeria, with a view to assessing its effect on the technical efficiency of the farms. Precisely, the farm efficiency level was estimated; factors that determine farm efficiency were identified, and the impact of land ownership on-farm efficiency was also assessed. A three-stage random sampling was used to select 144 respondents. Data collected using a pretested interview schedule was subjected to descriptive statistics, stochastic production frontier function, and average treatment effect. The results show that land ownership by absolute interest accounted for about 65% of the farmers. The mean technical efficiency level of the farms was 47%. Farm size and labour are necessary factors to be increased to have increased output. The non-access to credit and land ownership by absolute interest constituted to technical inefficiency of the farms. Similarly, ownership of farmland by absolute interest reduced efficiency by 24% among sampled farmers and 25.5% among owners of farmland. The study, therefore, suggested that farm size should be increased, and credit facilities are made available to farmers to facilitate the acquisition of necessary inputs to increase output given the existing technology. This can be by way of making accessible to food crop farmers, lands belonging to the government, which are currently not in use.

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 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.

Impact of agricultural credit on farm income under the Savanna and Transitional zones of Ghana

2019 ◽  
Vol 79 (1) ◽  
pp. 60-84 ◽  
Author(s):  
Abdul-Hanan Abdallah ◽  
Micheal Ayamga ◽  
Joseph A. Awuni
Keyword(s):  
Selection Bias ◽  
Farm Size ◽  
Farm Income ◽  
Data Set ◽  
Content Type ◽  
Credit Access ◽  
Access To Credit ◽  
Mean Differences ◽  
On Farm ◽  
The Impact

PurposeThe purpose of this paper is twofold: to determine the factors contributing to farm income in the Transitional and Savanna zones of Ghana and to ascertain variations between in the same and across the two locations; and to determine the impact of credit on farm income in each of the two zones and to ascertain the variation in impact of credit across the two locations.Design/methodology/approachIn order to address endogeneity and sample selection bias, the authors draw from the theory of impact evaluation in nonrandom experiment, employing the endogenous switching regression (ESR) while using the propensity score matching (PSM) to check for robustness of the results.FindingsThe results show significant mean differences between some characteristics of households that have access to credit and those that did not have access. Further, the results revealed farm size, labor; gender, age, literacy, wealth and group membership as the significant determinants of both credit access and income in the two zones. With the ESR, credit access increases households farm income by GH¢206.56/ha and GH¢39.74/ha in the Transitional and Savanna zones, respectively, but with the PSM, credit increases farm income by GH¢201.50 and GH¢45.69 and in the Transitional and Savanna, respectively.Research limitations/implicationsThe mean differences in characteristics of the households revealed the presence of selection bias in the distribution of household’s covariates in the two zones. The results further indicate the importance of productive resources, information and household characteristics in improved access to credit and farm income. Also, the results from both methods indicate that credit access leads to significant gains in farm income for households in both zones. However, differences exist in the results of PSM and that of the ESR results.Practical implicationsThe presence of selection bias in the samples suggests that the use of ESR and PSM techniques is appropriate. Further, the results suggesting that enhanced credit access and farm income could be attained through improved access to household resources and information. The results also suggest the need for establishing and expanding credit programs to cover more households in both zones. The differential impact of credit between the two methods employed in each zone revealed the weakness of each model. The low values from PSM could indicate the presence of selection bias resulting from unobservable factors whiles the high values from the ESR could stem from the restrictive assumption of the model. This reinforces the importance of combining mixed methods to check robustness of results and to explore the weakness of each method employed.Originality/valueThe novelty of this study lies in the use of a very extensive and unique data set to decompose the determinants of credit access and farm income and as well as the impacts of credit into zones.

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