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Do Differences in Technical Efficiency Explain the Adoption Rate of Hyv Rice? Evidence from Bangladesh

K. M. Zahidul Islam
Corresponding author
Department of Economics and Management, Faculty of Agriculture and Forestry. P.O. Box 27, FIN-00014 University of Helsinki, Finland

John Sumelius
Department of Economics and Management, Faculty of Agriculture and Forestry, P.O. Box 27, FIN-00014 University of Helsinki, Finland

Stefan Bäckma
Pellervo Economic Research, Eriksgatan 28 A, FI-00180 Helsingfors, Finland

Abstract/ Executive Summary:

This paper estimates the technical efficiency of traditional variety (TV) and high yielding-variety (HYV) rice producers in Bangladesh as well as explores the determinants of HYV rice adoption in a survey data from 360 farmers for the 2008/09 growing seasons. Estimates by stochastic frontier analysis indicated that in spite of its much yield potential, HYV rice production was associated with lower technical efficiency and had a greater variability in yield. Results indicated that technical efficiency of HYV and TV rice were related to age, experience, off-farm income, extension visits, and access to microfinance. A Tobit analysis revealed that the adoption of HYV rice was significantly and positively influenced by farmers’ age and experience, level of technical efficiency, irrigation coverage, off-farm incomes, access to microfinance, perception of yield and membership of village-local groups.

Keywords: Traditional variety, High-yielding-variety, Stochastic Frontier Analysis, Adoption, Tobit Analysis

Location: In Bangladesh

Start Date: 00-00-2008

End Date: 00-00-2009

Program Area: Variety and Species

Commodity: Rice

Objectives:

The first objective is to find out whether there are significant differences in technical efficiency of production between traditional local varieties and HYV rice. The second aim is to identify the factors that contribute towards the adoption of HYV rice.

Methodology:

Stochastic production frontier: Farrell’s (1957) seminal paper on efficiency measurement led to the development of several methodologies and approaches to efficiency and productivity analysis. Stochastic frontier analysis (SFA) and Data envelopment analysis (DEA) are the two pioneering contributions in this field. Aigner et al. (1977), and Meeusen and Van Den Broeck (1977) independently proposed the stochastic frontier production function with a composed error term including a stochastic error component and one-sided error component representing technical inefficiency of production. DEA was approached by Charnes et al.(1978). The advantages and disadvantages of each have been discussed by Coelli and Perelman (1999). The popular approach to measure the technical efficiency is frontier production function (Tzouvelekas et al., 2001; Wadud and White, 2000; Sharma et al., 1999; Battese and Coelli, 1995). The factors influencing technical efficiency have been analyzed in several studies by a second-stage regression after the estimation of efficiency scores. This approach contains serious problems regarding the assumptions made for the non-negative random variable, ui. Moreover, the second stage specification conflicts with the assumption that uis are independent and identically distributed. However, a number of authors (Kumbhakar et al., 1991; Battese and Coelli, 1995) modified and extended the stochastic production frontier model by suggesting a simultaneous estimation of the production frontier and inefficiency effects. They argued for a single stage approach by which the functional relationship between inefficiency effects and the firm-specific factors are directly incorporated into the Maximum Likelihood Estimation (MLE). Following Battese and Coelli (1995), the following stochastic frontier production function and inefficiency effects model can be estimated simultaneously in a single stage by using the computer program, FRONTIER 4.1, developed by Coelli (1996). Quantifying factors affecting adoption of HYV rice: Rogers (1962) defined adoption as ‘the mental process an individual passes through from first hearing about an innovation to final adoption’. Final adoption at the farm level is defined as the use of new technology in the long-run equilibrium, and assumes that the farm has full information about the new technology and it’s potential. However, if the innovation is modified periodically, the equilibrium level may not be reached. The literature also distinguishes between ‘rates of adoption’ and the ‘intensity of adoption’. The former determines the proportion of farmers who adopt a given technology regardless of the level of use, and the latter determines the level of use of that technology such as the proportion of land planted under HYVs or the quantity of fertiliser used. The adoption process starts with farmers experimenting with new varieties, which may lead them to select that new variety if its performance is viewed by the farmer as superior over those of traditional varieties (Shiyani et al., 2002). Data used for the estimation: Data were collected from 12 villages in north-west and north-central regions of Bangladesh by a survey conducted in June-August 2009. For microfinance borrowers, data were collected with the help of the client lists of Microfinance Institutions (MFIs). Personal interviews were conducted for both groups of borrowers and non-borrowers of microfinance. We interviewed 180 agricultural microfinance borrowers and also 180 non-borrowers as the control group. To avoid an ‘endogenous confounding problem’, we interviewed non-borrowers from those villages that had no microfinance program coverage. Description of the Data and Variables: Output was defined as the market value of rice production under Aus/Aman/Boro rice during the survey period. It was measured in Bangladesh Taka2. Rice output prices were gathered from individual farms. Land represented the total amount of land (own cultivated land, sharecropping land, and rented/leased land) used for producing each rice crop and was measured in hectares. Labour comprised family (imputed as hired labour) and non-family hired labour for pre and post-planting operations and harvesting excluding threshing and was measured in labour-days for each crop. Fertilizers include all sorts of organic and inorganic fertilizers used by the farm households for each rice crop.

Source of Information: AGRICULTURAL ECOOMICS REVIEW, 2012, Vol 13, o 1

Article Link (Online Journal):

Funding Source:

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Achievement/Findings:

This paper used stochastic frontier production functions to analyze the technical efficiency of TVs and HYV rice farmers in relation to their adoption of HYV rice growing in Bangladesh. It used detailed survey data obtained from 360 rice farms of 12 villages in 2008/2009 growing seasons. The mean technical efficiency of Aus and Aman rice crops were 86% and 92% respectively whereas for Boro (HYV) rice the technical efficiency was 89% which suggested substantial gains in output with given technology and resource endowments. It is evident that the farmers are tightly distributed at the upper end of the technical efficiency distribution for both TV and HYV rice. However, HYV rice producers had greater variability in per hectare yields and technical efficiency distribution. The empirical results revealed that inefficiency exists in the TVs and HYV rice production systems. Factors such as education, experience, extension visits and access to microfinance negatively influenced technical inefficiency, whereas age, family size, off-farm income and regional dummy showed a positive relation with technical inefficiency. The study also assessed and identified factors that influence the adoption of HYV Boro rice using the Tobit model. The factors which influenced the adoption of HYV rice included farmers’ age and education, technical efficiency, irrigation coverage, off-farm income, access to microfinance, perception of yield, membership of village-level organizations and cost of production per hectare. The significant positive impact of technical efficiency on the adoption rate of HYV rice shows that farmers with higher technical efficiency were able to transform their production systems to more efficient methods by adopting new technologies, changing production functions, intensively seeking improved farming practices from extension officers, research staff and other accessible private farm advisers. From a policy perspective, more concerted efforts directed at increasing the technical efficiency of HYV rice farms are likely to increase the adoption rate of HYV rice in Bangladesh. The results of the inefficiency model and factors that influence the adoption of HYV rice indicate that some common factors such as age, education, experience, access to microfinance, off-farm income, and region have significant impacts on technical inefficiency and on the decision to adopt HYV Boro rice. An insight into the above factors has clear implications as to how the technical inefficiency of both the TVs and HYV rice may be reduced and the adoption rate of HYV Boro rice may also be improved at a faster rate. Thus policies leading to raising the educational level of the farmer, increasing their technical efficiency, ensuring greater access to microfinance, crop-specific regional focusing and strengthening the extension services through more intensive on-farm demonstrations could be beneficial to increasing technical efficiency and adoption of HYV rice in Bangladesh.

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