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Developing countries: agricultural and food problems --- Bangladesh

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This paper examines the agricultural productivity-farm size relationship in the context of Bangladesh. Features of Bangladesh's agriculture help overcome several limitations in testing the inverse farm size-productivity relationship in other developing country settings. A stochastic production frontier model is applied using data from three rounds of a household panel survey to estimate simultaneously the production frontier and the technical inefficiency functions. The "correlated random effects" approach is used to control for unobserved heterogeneous household effects. Methodologically, the results suggest that the stochastic production frontier models that ignore the inefficiency function are likely mis-specified, and may result in misleading conclusions on the farm size-productivity relationship. Empirically, the findings confirm that the farm size and productivity relationship is negative, but with the inverse relationship diminishing over time. Total factor productivity growth, driven by technical change, is found to have been robust across the sample. Across farm size groups, the relatively larger farmers experienced faster technical change, which helped them to catch up and narrow the productivity gap with the smaller farmers.

Agriculture --- Finance and Financial Sector Development --- Food Security --- Labor Markets --- Productivity --- Rural Development --- Rural Labor Markets --- Social Protections and Labor --- Stochastic Frontier --- Technical Change

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April 1999 - The sensitivity of empirical results to potential data errors and model misspecification can yield misleading policy implications and investment signals. A widely disseminated study of the impact of the training and visit (T&V) system of management for extension services in Kenya is a striking example of how innocuous data errors and alternative specifications lead to strikingly different results. Gautam and Anderson revisit the widely disseminated results of a study (Bindlish and Evenson 1993, 1997) of the impact of the training and visit (T&V) system of management for public extension services in Kenya. T&V was introduced in Kenya by the World Bank and has since been supported through two successive projects. The impact of the projects continues to be the subject of much debate. Gautam and Anderson's paper suggests the need for greater vigilance in empirical analysis, especially about the quality of data used to support Bank policy and the need to validate potentially influential findings. Using household data from 1990, Bindlish and Evenson found the returns from extension to be very high. But Gautam and Anderson find that the returns estimated by Bindlish and Evenson suffer from data errors, and limitations imposed by cross-sectional data. After correcting for several data processing and measurement errors, the authors show the results to be less robust than reported by Bindlish and Evenson and highly sensitive to regional effects. When region-specific effects are included, a positive return to extension cannot be established, using Bindlish and Evenson's data set and cross-sectional model specifications. After testing the robustness of results using a number of tests, Gautam and Anderson could not definitively establish the factors underlying strong regional effects, largely because of the limitations imposed by the cross-sectional framework. Household panel data methods would have allowed greater control for regional effects and would have yielded better insight into the impact of extension. The impact on agricultural productivity in Kenya expected from T&V extension services is not discernible from the available data, and the impact may vary across districts. The hypothesis that T&V had no impact in Kenya between 1982 and 1990 cannot be rejected. The sample data fail to support a positive rate of return on the investment in T&V. This paper-a product of the Sector and Thematic Evaluation Division, Operations Evaluation Department-is part of a larger exploration by the department of the effects of the investment in agricultural extension in Kenya. The authors may be contacted at mgautam@worldbank.org or janderson@worldbank.org.

Agencies --- Agricultural --- Agricultural Extension --- Agricultural Production --- Agriculture --- Banks and Banking Reform --- Crops --- Crops and Crop Management Systems --- E-Business --- Econometrics --- Economic Theory and Research --- Education --- Extension --- Extension Services --- Family --- Farmers --- Farms --- Information --- Investment --- Labor Policies --- Land --- Livestock --- Macroeconomics and Economic Growth --- Management --- Private Sector Development --- Research --- Rural Development --- Rural Development Knowledge and Information Systems --- Science and Technology Development --- Science Education --- Scientific Research and Science Parks --- Social Protections and Labor --- Statistical and Mathematical Sciences --- Training

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Social costs. Social benefits --- Developing countries: agricultural and food problems --- Agricultural techniques --- World Bank --- Kenya --- Agricultural extension work - Kenya --- Agricultural extension work