Participation in farmer organizations and adoption of farming technologies among rice farmers in Ghana

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kwabena Nyarko Addai ◽  
Omphile Temoso ◽  
John N. Ng'ombe
Keyword(s):  
Selection Bias ◽  
Crop Productivity ◽  
Farm Size ◽  
Northern Ghana ◽  
Farm Income ◽  
Content Type ◽  
Rice Farmers ◽  
Farmer Organizations ◽  
Agricultural Innovations ◽  
Farmer Organization

PurposeThe authors examine the factors influencing membership in farmer organizations (FO) and their effects on the decision to adopt farm technologies by rice farmers in Ghana.Design/methodology/approachThis study uses a farm survey of 900 households from Northern Ghana and a recursive bivariate probit (RBP) model that accounts for selection bias and endogeneity.FindingsThe results indicate that the household head’s decision to adopt machinery and row planting increases by 38.4 and 25.3%, respectively, upon joining a farmer organization. Membership in farmer organization is positively influenced by off-farm income, asset value, farmer organization location and farmer location in Upper West region but negatively by males, age and total livestock units owned. Machinery adoption is positively influenced by membership in farmer organizations and respondent being male but negatively influenced by the years of schooling, farm size, farm distance and location of a farmer in Ghana's Upper East and West regions. Similarly, row planting adoption is positively influenced by membership in farmers' organization but adversely by farm size, farm distance and a farmer's location in Upper East region of Ghana.Research limitations/implicationsIt can be concluded that membership in farmers' organizations significantly impacts farm household head’s decision to adopt machinery and row planting in rice production, which potentially enhance crop productivity.Practical implicationsThese results show the importance of agricultural stakeholders in encouraging the formation and strengthening of farmer organizations to support the adoption of modern farming technologies.Originality/valueDeveloping literature has demonstrated that farmer organizations promote the adoption of agricultural innovations. However, most of these studies have concentrated on conventional agricultural innovations and have used methods that fail to account for potential selection bias. This paper fills this important gap.

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.

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.

scholarly journals Musculoskeletal disorders among rice farmers in Phimai District, Nakhon Ratchasima Province, Thailand

2019 ◽  
Vol 33 (6) ◽  
pp. 494-503
Author(s):  
Ekarat Sombatsawat ◽  
Titaporn Luangwilai ◽  
Parichat Ong-artborirak ◽  
Wattasit Siriwong
Keyword(s):  
Musculoskeletal Disorders ◽  
Work Experience ◽  
Rank Correlation ◽  
Agricultural Practices ◽  
Farm Size ◽  
Body Region ◽  
Cross Sectional ◽  
Content Type ◽  
Rice Farmers ◽  
Body Regions

Purpose The purpose of this paper is to explore the prevalence of musculoskeletal disorders (MSDs) and determine factors influencing MSDs among rice farmers. Design/methodology/approach A cross-sectional study was carried out among 156 rice farmers from 14 villages in Tarnlalord sub-district, Phimai district, Nakhon Ratchasima province, Thailand, from February 2017 to March 2017. Face-to-face interviews, including demographics, work characteristics and musculoskeletal pain, were conducted using a modified standardized Nordic questionnaire. Findings The results revealed that both 78 males and 78 females participated in the study to which the average of age and body mass index (BMI) was 45.5±11.4 years and 24.9±4.0 kg/m2, respectively. All rice farmers reported MSDs in at least one body region during the six months preceding the interview. The highest prevalence of MSDs showed 86.5 percent in the lower back area, followed by 85.9 percent in the neck, and 80.7 percent in the shoulders. The analysis of binary logistic regression and Spearman’s rank correlation showed that factors such as gender, age, BMI, work experience and farm size influence MSDs’ occurrence, and pain severity in one or more body regions (p < 0.05). Originality/value Musculoskeletal injuries are a significant health problem in rice farmers. The study indicated that appropriate agricultural practices such as working posture, equipment size selection and carrying loads should be recommended to prevent MSDs. Thus, the occupational health and safety services in agricultural workers are needed.

scholarly journals DETERMINANTS OF AGRICULTURAL LOAN DECISION MAKING PROCESS FOR RICE (ORYZA SATIVA) FARMERS IN ABUJA, NIGERIA. APPLICATIONS OF HECKMAN TWO-STAGE MODEL AND FACTOR ANALYSIS

2021 ◽  
Vol 59 (1) ◽  
Author(s):  
Olugbenga Omotayo Alabi ◽  
Ayoola Olugbenga Oladele ◽  
Mohammed Bello Usman
Keyword(s):  
Rice Production ◽  
Farm Size ◽  
Farm Income ◽  
Decision Making Process ◽  
Stage Model ◽  
Gross Margin ◽  
Two Stage ◽  
Rice Farmers ◽  
Factors Influencing ◽  
Socio Economic Factors

This study focuses on determinants of the agricultural loan decision-making process of rice (Oryza sativa) farmers in Abuja, Nigeria, using the Heckman two-stage model and factor analysis. This study was designed specifically to achieve the following objectives: determine the socio-economic profiles or characteristics of rice farmers, analyze the costs and returns of rice production, evaluate factors influencing rice farmers’ decision to obtain an agricultural loan, evaluate socio-economic factors influencing the amount of the agricultural loan, and determine the constraints or problems facing rice farmers. A multi-stage sampling design was employed. A total sample of one hundred (100) rice farmers was included, and primary data were utilized. Data were obtained through the use of a well-structured and well-designed questionnaire. Statistical and econometric tools used in analyzing data included descriptive statistics, gross margin analysis, financial analysis, the Heckman two-stage model, and principal component analysis. The results show that 63% of rice farmers were between the age of 31–50 years. The mean age was 41.90 years. About 65% of rice farmers were male, and 54% of them were married. Also, 93% of rice farmers had formal education and were literate. The household sizes were large, with an average of six persons per household. An average of 71,550 nairas was the loan amount granted to rice farmers by financial institutions. The average farm size amounted to 1.49 hectares. Factors influencing the decision of rice farmers to obtain agricultural loan included age (P < 0.01), marital status (P < 0.05), household size (P < 0.10), educational level (P < 0.05), farm size (P < 0.05), farm and non-farm income (P < 0.10), farm experience (P < 0.05), collateral property (P < 0.05), extension services (P < 0.10), and awareness of loan or credit facilities (P < 0.05). Rice production was profitable with a net farm income of 744,300 nairas. The gross margin ratio of 0.95 means that 95 kobos covered profits, taxes, expenses, interest, and depreciation for every naira invested in rice production activities. Socio-economic factors statistically and significantly influencing the amount of agricultural loan obtained by rice farmers included (P < 0.05) sex (P < 0.01), household size (P < 0.05) and educational level (P < 0.01). The constraints facing rice farmers in obtaining the agricultural loan and production activities included lack of collateral property, lack of fertilizer input, poor-quality feeder roads, lack of credit facilities, inadequate labor input, and complicated and costly administrative procedures to obtain a loan. It is recommended that agricultural loans be made available to rice farmers in sufficient amounts and at low-interest rates. Also, farm inputs, fertilizer inputs, improved seeds, and chemicals should be made available to rice farmers

Farm and lender structural change: implications for federal credit

2017 ◽  
Vol 77 (1) ◽  
pp. 78-94 ◽  
Author(s):  
Charles B. Dodson ◽  
Bruce L. Ahrendsen
Keyword(s):  
Land Tenure ◽  
Commodity Price ◽  
Farm Size ◽  
Farm Income ◽  
Service Agency ◽  
Credit System ◽  
Content Type ◽  
Farm Credit ◽  
Size Groups ◽  
Guaranteed Loans

Purpose The purpose of this paper is to examine changes in the structures of US farms and lenders and identify prospective implications for federal credit. Design/methodology/approach Data from US farm operations for 1996-2014 were adjusted to 2014 values using commodity price indices. Farm size groups were constructed by value of farm production to analyze changes in farm numbers, production, assets, debt, leverage, liquidity, profitability, land tenure, commodity type, contract production, organization type, and use of Farm Service Agency (FSA) direct and guaranteed loans by farm size. Bank, Farm Credit System (FCS), and FSA data from 1996 to 2015 were adjusted to 2014 values. Lender size groups were constructed to analyze changes in bank and association numbers, farm loans, and use of FSA guaranteed loans by lender size. Findings The greatest consolidation has been by farms with over $2 million in production. More farm debt is held by large, complex organizations, frequently with multiple operators, more variable income, and greater reliance on production contracts and operating and nonreal estate credit. Large farms have greater leverage, are more profitable, and have a larger share of household income from the farm. Banks and FCS institutions are fewer and larger, yet smaller institutions use FSA guarantees to a greater extent. Larger farms tend to be more reliant on both direct and guaranteed FSA loans and are likely to become more dependent on FSA credit. Originality/value Changing farm and lender structure together with softening farm income may require FSA farm loan program changes to meet any increase in loan demand. Policy alternatives are provided to meet changing demand for farm credit.

The ripple effect of credit accessibility on the technical efficiency of maize farmers in Ghana

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anthony Siaw ◽  
Yuansheng Jiang ◽  
Martinson Ankrah Twumasi ◽  
Wonder Agbenyo ◽  
Gideon Ntim-Amo ◽  
...  
Keyword(s):  
Technical Efficiency ◽  
Farm Size ◽  
Farm Income ◽  
Agricultural Credit ◽  
Maize Production ◽  
Content Type ◽  
Frontier Analysis ◽  
Access To Credit ◽  
Variable Approach ◽  
The Impact

PurposeThe purpose of this study is to examine the impact of access to credit on technical efficiency (TE) of maize farmers in a developing country, Ghana.Design/methodology/approachThe study employed an instrumental variable approach and the stochastic frontier analysis (SFA) method for the estimation of the results.FindingsThe study found that farmers who have access to agricultural credit stand the chance of increasing TE by a margin of 8%, which also influences the maize production than those who did not have access to credit. The average TE score of the farmers was 74%. The study also found out that factors like membership, gender, farmers' access to credit, age and social network determine farmers' possibility of accessing agricultural credit. The study finds out that returns to size are increasing among the maize farmers and that significant improvement in efficiency can be realized by increasing the level of input used in production. Also, factors such as farm size, labor, seeds and fertilizer are the essential determinants of maize production output. Also, gender, extension, age, off-farm income, access to credit and membership were significant factors influencing technical inefficiency (TI).Originality/valueThe paper contributes to the existing literature on agricultural credit on rural agricultural development. The problem of endogeneity associated with access to credit, which has been considered by other researchers, is dealt with this study. This paper also provides information to government policymakers, practitioners and all other stakeholders in the maize sub-sectors and also will benefit small farmers outside the study area.

Rice farm income diversification in Ghana and implications on household consumption expenditure

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Bismark Amfo ◽  
James Osei Mensah ◽  
Ernest Baba Ali ◽  
Gilbert Dagunga ◽  
Seth Etuah ◽  
...  
Keyword(s):  
Value Chain ◽  
Production Systems ◽  
Rice Production ◽  
Primary Data ◽  
Farm Income ◽  
Crop Diversification ◽  
Consumption Expenditure ◽  
Income Diversification ◽  
Content Type ◽  
Rice Farmers

PurposeThis study investigates implications of crop and income diversifications on consumption expenditure (welfare) of rice-producing households in Ghana. It further compares diversification by three rice production systems: two-season rain-fed, two-season irrigated and one-season rain-fed rice production.Design/methodology/approachPrimary data were sourced from 225 rice farmers. Margalef index and three-stage least-squares were employed.FindingsMajority of rice-farming households in Ghana diversify livelihoods. The extent of livelihood diversification differs among two-season rain-fed, two-season irrigated and one-season rain-fed rice-producing households. Credit, distance to district capitals, production purpose and number of farming seasons influence crop and income diversifications, and consumption expenditure of rice-producing households. While crop diversification reduces consumption expenditure, income diversification increases it. Crop and income diversifications positively influence each other. Consumption expenditure reduces crop diversification but increases income diversification.Practical implicationsPolicy should be directed towards the promotion of more livelihood activities to boost rice farmers' welfare. There should be awareness creation and training programmes to enable rice farmers realize different economic activities within and outside the agricultural value chain.Originality/valueCrop and income diversifications were measured as continuous response variables, unlike previous studies that used a binary response variable. The authors established a synergy among crop and income diversifications, and consumption expenditure (welfare). The authors further compared crop and income diversifications by three rice production systems: two-season rain-fed, two-season irrigated and one-season rain-fed rice production systems.

Agricultural credit rationing in Ghana: what do formal lenders look for?

2014 ◽  
Vol 74 (3) ◽  
pp. 364-378 ◽  
Author(s):  
Dadson Awunyo-Vitor ◽  
Ramatu Mahama Al-Hassan ◽  
Daniel Bruce Sarpong ◽  
Irene Egyir
Keyword(s):  
Financial Institutions ◽  
Agricultural Sector ◽  
Credit Rationing ◽  
Farm Size ◽  
Farm Income ◽  
Two Stage ◽  
Agricultural Credit ◽  
Content Type ◽  
Access To Credit ◽  
Improve Access

Purpose – The purpose of this paper is to investigate the determinants of agricultural credit rationing by formal lenders in Ghana. Design/methodology/approach – This study employed descriptive statistics, analysis of variance (ANOVA) and Heckman's two-stage regression model to identify types of rationing faced by farmers and investigate factors that influence agricultural credit rationing by formal financial institutions. Data used in this study are gathered through a survey of 595 farmers in seven districts within Brong Ahafo Region of Ghana. Findings – The result reveals that farmers face three types of rationing. Evidence from the Heckman two-stage models shows that engagement in off farm income generating activities, increase in farm size, positive balances on accounts and commercial orientation of the farmers has the potential to reduce rationing of credit applicants by formal lenders. Practical implications – The results provide information on the factors that need to be considered as important in an attempt to reduce agricultural credit rationing by formal lenders. Originality/value – The value of this study is that farmers would use the results of this study to improve access to required amount of agricultural credit from formal financial institutions. The information would also benefit stakeholders in the agricultural sector, particularly youth in agriculture program organized by Ministry of Food and Agriculture in Ghana as how to improve access to credit and reduce rationing of program participants by formal financial institutions.

Non-performance of financial contracts in agricultural lending

2016 ◽  
Vol 76 (3) ◽  
pp. 362-377 ◽  
Author(s):  
Basri Savitha ◽  
Naveen Kumar K.
Keyword(s):  
Default Risk ◽  
Secondary Data ◽  
Binary Logistic Regression ◽  
Farm Size ◽  
Farm Income ◽  
Multinomial Regression ◽  
Agricultural Credit ◽  
Family Responsibilities ◽  
Content Type ◽  
Loan Defaults

Purpose Evaluating a portfolio of agricultural loans has become an important issue in recent years primarily due to a large number of loan defaults. The purpose of this paper is to investigate the factors influencing credit repayment behavior of farmers in Karnataka. Design/methodology/approach The study is based on secondary data of 590 farmers collected from a private bank in the state of Karnataka, India. Binary logistic regression and multinomial regression analysis was carried out to estimate the probability of non-payment of a loan. Findings The results of the regression confirm a significant relationship between non-repayment of agricultural credit and characteristics of borrowers such as the age, years of banking relationship, yield of the crop, distance to bank branch, size and tenure of the loan, farm size and leverage and efficiency ratio. Practical implications The factors predicted by the model do certainly help in improving the decision-making process in agricultural lending. A rigorous assessment of family responsibilities, farm size, credit-to-asset ratio, interest burden on the farmers and farm income is suggested to reduce the probability of doubtful assets. Originality/value The studies that predict default risk in agricultural loan are limited in India. This is one of the few studies that estimate the determinants of substandard and doubtful categories of credit in a private sector bank.

scholarly journals Economic implication of contract farming on small-scale rice farmers in Kwara State, Nigeria

Agrosearch ◽  
2020 ◽  
Vol 19 (2) ◽  
pp. 26-40
Author(s):  
S.O. Akanbi ◽  
W.I. Alarape ◽  
O.S. Olatunji
Keyword(s):  
Technical Efficiency ◽  
Positive Impact ◽  
Stochastic Frontier ◽  
Farm Size ◽  
Farm Income ◽  
Small Scale ◽  
Economic Implication ◽  
Contract Farming ◽  
Productivity Level ◽  
Rice Farmers

This study examines the implication of contract farming on Olam Out-growers farming scheme in Kwara State, Nigeria. The objectives of the study are to determine the costs and returns to production of rice, assess the productivity level of rice, evaluate the technical efficiency of rice farm and identify the determinants of the technical inefficiency of the rice farms in contract farming. In this study, the average net farm income of the rice farmers under the scheme was N191,862.56 and the land productivity level was 2,006.04kg/ha. The technical efficiency of the rice farm was estimated using Cobb-Douglas Stochastic Frontier Production function which shows that likelihood coefficients for quality of seeds, hired labour and farm size were statistically significant at 1% level. Likewise, the determinants of technical efficiency among the farmers were household size and farming experience. The results further show that the contract farming scheme has a positive impact on the lives of rice farmers. Therefore, there is a need for partnership with private contract farming outfits in order to improve the current level of access to inputs by rice farmers. Keywords: Contract farming, Out-growers rice farmers, Technical efficiency, Farm income

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