Factors determining allocation of land for improved wheat variety by smallholder farmers of northern Ethiopia
31 Mar 2015-Journal of development and agricultural economics (Academic Journals)-Vol. 7, Iss: 3, pp 105-112
TL;DR: In this article, the Tobit model was used to analyze factors influencing adoption of improved wheat technology econometrically, and a total of thirteen explanatory variables were included in the model including education level of household head, family size, tropical livestock unit, distance from main road and nearest market, access to credit service, extension contact and perception of household towards cost of the technology.
Abstract: This study was conducted in Northern Ethiopia, Adwa district. The main objective of the study was to examine factors influencing allocation of land for improved wheat variety by smallholder farmers of the study area. Descriptive, inferential and econometric methods were used to analyze data. Results of descriptive and inferential analyses showed that; adopters had high family size in adult-equivalent, high number of tropical livestock unit, large land size, high frequency of extension contact, access to credit service, they were followed formal schooling, and they were nearest to main road and market as compared to non-adopters. Tobit model was used to analyze factors influencing adoption of improved wheat technology econometrically. A total of thirteen explanatory variables were included in the model. From the tested variables only eight variables (education level of household head, family size, tropical livestock unit, distance from main road and nearest market, access to credit service, extension contact and perception of household towards cost of the technology) were found to be the significant factors affecting adoption of improved wheat variety. Implication of results of this study is that any development intervention through improved wheat technologies should consider the aforementioned socioeconomic characteristics and determinants of adoption for success.
Key words: Adoption of Improved wheat variety, Adwa, smallholder farmers, Topit model.
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TL;DR: In this paper, farm household survey data collected in rural districts of central and northern Malawi were used to investigate factors that influenced smallholders to replace groundnut varieties with modern ones, finding that the production of groundnuts for food and income increased the probability of replacing both conventional and modern varieties.
Abstract: Farm household survey data collected in rural districts of central and northern Malawi were used to investigate factors that influenced smallholders to replace groundnut varieties. The results of the study showed that smallholders have not entirely replaced conventional varieties with modern ones. For the group of smallholders that replaced conventional with the modern varieties, few reverted to the former. Further results of a bivariate probit regression model indicated that the production of groundnuts for food and income increased the probability of replacing both conventional and modern varieties. Farmers’ perception of the relevance of agricultural extension services to groundnut production and land allocated to the cultivation of groundnuts increased the likelihood to replace conventional varieties. Conversely, poor rural road infrastructure decreased the probability of replacing the same. In other results, experience in groundnut production, education level of the farmer, membership of farmer organisations, and inadequate access to quality seed increased the likelihood of replacing modern varieties. The study's findings suggest that promoting an integrated seed system of groundnut varieties is critical for the adoption and conservation of improved and conventional varieties and could contribute to the food and income security of farm households.
3 citations
Cites background from "Factors determining allocation of l..."
...…2021Transactions of the Royal Society of South Africa Huffman, 2014; Abebe et al., 2013; Alene et al., 2000; DansoAbbeam et al., 2017; Diiro et al., 2015; Gebresilassie and Bekele, 2015; Supaporn et al., 2013; Takam-Fongang et al., 2019; Uduji and Okolo-Obasi, 2018; Chandio and Yuansheng, 2018)....
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29 May 2020
TL;DR: In this article, the authors applied logit regression to examine determinants of adoption of improved wheat varieties in the Liban jewi district of West Showa zone Oromia region Ethiopia.
Abstract: Ethiopia is the second largest wheat producer in sub-Saharan Africa, after South Africa. In Ethiopia, wheat ranks fourth in total cultivated area and production. This study applied logit regression to examine determinants of adoption of improved wheat varieties in the Liban jewi district of West Showa zone Oromia region Ethiopia. The objective of the study is to analyze determinants that affect adoption of improved wheat varieties which exert significant influence on the adoption behavior of sample respondents in the study area. A total of 154 sample respondents drawn from 6 PAs of the district included in the survey. The model result shows that the adoption of improved wheat varieties by respondents in the study area was positively and significantly affected by farm size, livestock ownership, extension contact and access to credit, whereas, age of respondents, distance from market and distance from farmers training center had negatively and significantly influenced adoption of improved wheat varieties in the study area. The result underscores the need for research and extension programs to be sensitive to the needs of farmers when developing and disseminating technologies that are relevant to their agro-ecologies.
2 citations
Cites result from "Factors determining allocation of l..."
...This finding is confirms the findings of the studies [10, 19, 18, 23], who found positive effects of farm size on adoption of the new technology....
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TL;DR: In this paper , the authors used a cross-sectional survey data obtained from a sizable number of individual rice farmers and applied multinomial logit and multivariate Tobit models for the estimation.
2 citations
TL;DR: In this paper, a study aimed to estimate the resource use efficiency and identify the factors affecting land allocation for wheat production in Bangladesh, and the results revealed that farmers had experienced decreasing return to scale in wheat production.
Abstract: The present study aimed to estimate the resource use efficiency and identify the factors affecting land allocation for wheat production in Bangladesh. Primary data were randomly collected from 183 wheat producers from three Upzillas of Natore district. The results revealed that farmers had experienced decreasing return to scale in wheat production. Farm area, seed cost and labor cost were the main factors that positively, and irrigation negatively affected wheat production. The sampled farmers failed to show their efficiency in using the resources in wheat cultivation. There was further opportunity to increase wheat production using more seed, chemical fertilizers, manure and pesticides. However, there was no further scope to increase wheat production by using irrigation, land preparation and labor inputs. The study also revealed that farmers age, education, wheat farming experience, location and family size significantly affected the probability of land allocation in wheat production. Soil type in the study areas played a vital role in the decision process of wheat cultivation. It could be concluded that proper utilization of inputs can increase wheat in Bangladesh. The Agriculturists 2017; 15(1) 28-39
2 citations
Cites background from "Factors determining allocation of l..."
...Gebresilassie and Bekele (2014) examined factors influencing allocation of land for improved wheat variety by small holder farmers in the Northern Ethiopia....
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...Numerous research have been conducted on the adopting factors of agricultural crop production in African and Asian countries (Adesina and Baidu-Forson, 1995; Bakh and Islam, 2005; Baidu, 1999; Batz et al., 1999; Forson, 1999; Gebresilassie and Bekele, 2014; Grisley and Mwesigwa, 1994; Hasan and Islam, 2010; Mussei et al., 2001; Poison and Spencer, 1991; Strauss et al., 1991; Ransom et al., 2003; Wilson et al., 2001; Wubeneh, 2001)....
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...…crop production in African and Asian countries (Adesina and Baidu-Forson, 1995; Bakh and Islam, 2005; Baidu, 1999; Batz et al., 1999; Forson, 1999; Gebresilassie and Bekele, 2014; Grisley and Mwesigwa, 1994; Hasan and Islam, 2010; Mussei et al., 2001; Poison and Spencer, 1991; Strauss et al.,…...
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Journal Article•
TL;DR: In this article, the authors identify determinants of adoption and intensity of adoption of improved soya bean varieties, and show that the high importance of institutional and government support in the areas of education, training, infrastructural development (especially roads).
Abstract: Achieving national food security and diversifying export earnings from agricultural products is one of the major challenges currently facing developing countries like Ethiopia. Pulse crops in general and soya bean in particular play great role in improving households’ food security, increasing income for smallholder farmers. Despite the high production potential and the economic importance of the crop, adoption and dissemination of improved soya bean varieties is constrained by various factors. Therefore, this study aimed at identifying determinants of adoption and intensity of adoption of improved soya bean varieties. The study was based on cross sectional data collected from 146 randomly selected soya bean producing farmers. Descriptive and econometric analyses were used to analyze data. The result showed that sex of household, education level, training, distance to nearest market, participation on off-farm activities and TLU affected the probability of adoption while education, farm experience, training, distance to nearest market and TLU affected the intensity adoption of improved soya bean varieties significantly. This study suggests that the high importance of institutional and government support in the areas of education, training, infrastructural development (especially roads). Therefore, policy and development interventions should give emphasis to the improvement of such institutional support system and decrease gender disparities in access to such institutions so as to achieve the adoption practice which increases production and productivity of small scale farmers. Keywords: Adoption, intensity of adoption, soya bean, double hurdle DOI : 10.7176/JNSR/9-20-06 Publication date :October 31 st 2019
2 citations
References
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01 Jan 2008
TL;DR: Agriculture is a vital development tool for achieving the Millennium Development Goal that calls for halving by 2015 the share of people suffering from extreme poverty and hunger as mentioned in this paper, which is the overall message of this year's World Development Report (WDR), the 30th in the series.
Abstract: Agriculture is a vital development tool for achieving the Millennium Development Goal that calls for halving by 2015 the share of people suffering from extreme poverty and hunger. That is the overall message of this year's World Development Report (WDR), the 30th in the series. Three out of every four poor people in developing countries live in rural areas, and most of them depend directly or indirectly on agriculture for their livelihoods. This report provides guidance to governments and the international community on designing and implementing agriculture for development agendas that can make a difference in the lives of hundreds of millions of rural poor. The report highlights two major regional challenges. In much of Sub-Saharan Africa, agriculture is a strong option for spurring growth, overcoming poverty, and enhancing food security. Agricultural productivity growth is vital for stimulating growth in other parts of the economy. But accelerated growth requires a sharp productivity increase in smallholder farming combined with more effective support to the millions coping as subsistence farmers, many of them in remote areas. Recent improved performance holds promise, and this report identifies many emerging successes that can be scaled up. In Asia, overcoming widespread poverty requires confronting widening rural-urban income disparities. Asia's fast-growing economies remain home to over 600 million rural people living in extreme poverty, and despite massive rural-urban migration, rural poverty will remain dominant for several more decades. For this reason, the WDR focuses on ways to generate rural jobs by diversifying into labor intensive, high value agriculture linked to a dynamic rural, non-farm sector. In all regions, with rising land and water scarcity and the added pressures of a globalizing world, the future of agriculture is intrinsically tied to better stewardship of natural resources. With the right incentives and investments, agriculture's environmental footprint can be lightened and environmental services harnessed to protect watersheds and biodiversity.
3,822 citations
Book•
01 Jan 1988
TL;DR: In this article, the authors discuss diagnostic checking, model selection, and specification testing for Econometrics, including Diagnostic Checking, Model Selection, and Specification Testing, as well as a discussion of nonlinear regression, models of expectations, and nonnormality errors in Variables.
Abstract: Foreword Preface to the Second Edition Preface to the Third Edition Obituary INTRODUCTION AND THE LINEAR REGRESSION MODEL What is Econometrics? Statistical Background and Matrix Algebra Simple Regression *Multiple Regression VIOLATION OF THE ASSUMPTIONS OF THE BASIC MODEL *Heteroskedasticity *Autocorrelation Multicollinearity *Dummy Variables and Truncated Variables Simultaneous Equations Models Nonlinear Regression, Models of Expectations, and Nonnormality Errors in Variables SPECIAL TOPICS Diagnostic Checking, Model Selection, and Specification Testing *Introduction to Time--Series Analysis Vector Autoregressions, Unit Roots, and Cointegration *Panel Data Analysis *Large--Sample Theory *Small--Sample Inference: Resampling Methods Appendix A: *Data Sets Appendix B:* Data Sets on the Web Appendix C:* Computer Programs Index
3,694 citations
Book•
06 Dec 2013
TL;DR: In this article, a simple regression model with time series data and OLS asymptotics is presented. But the model is not suitable for the analysis of large datasets and it does not have the ability to handle large numbers of variables.
Abstract: 1. The Nature of Econometrics and Economic Data 2. The Simple Regression Model 3. Multiple Regression Analysis: Estimation 4. Multiple Regression Analysis: Inference 5. Multiple Regression Analysis: OLS Asymptotics 6. Multiple Regression Analysis: Further Issues 7. Multiple Regression Analysis with Qualitative Information: Binary (or Dummy) Variables 8. Heteroskedasticity 9. More on Specification and Data Issues 10. Basic Regression Analysis with Time Series Data 11. Further Issues in Using OLS with Time Series Data 12. Serial Correlation and Heteroskedasticity 13. Pooling Cross Sections Across Time: Simple Panel Data Methods 14. Advanced Panel Data Methods 15. Instrumental Variables Estimation and Two Stage Least Squares 16. Simultaneous Equations Models 17. Limited Dependant Variable Models and Sample Selection Corrections 18. Advanced Time Series Topics 19. Carrying Out an Empirical Project
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Posted Content•
TL;DR: In this paper, the authors examined the driving forces behind farmers' decisions to adopt agricultural technologies and the causal impact of adoption on farmers' integration into output market using data obtained from a random cross-section sample of 700 farmers in Ethiopia.
Abstract: This article examines the driving forces behind farmers’ decisions to adopt agricultural technologies and the causal impact of adoption on farmers’ integration into output market using data obtained from a random cross-section sample of 700 farmers in Ethiopia. We estimate a Double-Hurdle model to analyze the determinants of the intensity of technology adoption conditional on overcoming seed access constraints. We estimate the impact of technology adoption on farmers’ integration into output market by utilizing treatment effect model, regression based on propensity score as well as matching techniques to account for heterogeneity in the adoption decision, and for unobservable characteristics of farmers and their farm. Results show that knowledge of existing varieties, perception about the attributes of improved varieties, household wealth (livestock and land) and availability of active labor force are major determinants for adoption of improved technologies. Our results suggest that the adoption of improved agricultural technologies has a significant positive impact on farmers’ integration into output market and the findings are consistent across the three models suggesting the robustness of the results. This confirms the potential direct role of technology adoption on market participation among rural households, as higher productivity from improved technology translates into higher output market integration.
175 citations
"Factors determining allocation of l..." refers background or result in this paper
...The study by Solomon et al. (2011) was consistent with this result; distance from nearest market affects adoption of improved agricultural technology negatively and significantly....
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...And also according to the study by Isaiah et al. (2007), Solomon et al. (2011), Ayinde et al. (2010), Odoemenem and Obinne (2010) and Matata et al. (2010) frequency of contact with extension agent affect positively and significantly adoption decision of farmers for improved agricultural technology....
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...The study by Solomon et al. (2011) confirms this result....
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TL;DR: In this paper, the authors identify the major factors influencing the level of adoption of improved cereal crop production technologies in Nigeria and identify the difficulties inherent in using a practice; the consistency or how adaptable the practice is in the context of existing practices in which the farmers are already familiar with; and the expectations of the farmers using the practice.
Abstract: This paper identifies the major factors influencing the level of adoption of improved cereal crop production technologies in Nigeria. Intensity of extension contact, amount and use of credit, cooperative membership, all of which are institutional in nature, were found to be most important factors influencing the adoption of improved cereal crop production technologies. Data were collected from six Local Government Areas of Benue State through interview conducted among a total of 370 small-scale cereal crop farmers. The data were analyzed using descriptive and multiple regression statistics. Adoption of improved technology packages may, in part, be related to the way farmers receive the technologies introduced to them. The important factors in such a perception are the difficulties inherent in using a practice; the consistency or how adaptable the practice is in the context of the existing practices in which the farmers are already familiar with; and the expectations of the farmers using the practice.
104 citations
"Factors determining allocation of l..." refers background or result in this paper
...And also according to the study by Isaiah et al. (2007), Solomon et al. (2011), Ayinde et al. (2010), Odoemenem and Obinne (2010) and Matata et al. (2010) frequency of contact with extension agent affect positively and significantly adoption decision of farmers for improved agricultural technology....
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...Also studies by Isaiah et al. (2007), Motuma et al. (2010) and Odoemenem and Obinne (2010) confirmed similar results....
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