Estimation of Chinese agricultural production efficiencies with panel data
AbstractFast and steady economic growth in China during the 1990s attracted much international attention. Given the scarcity of resources, it is important for economic growth to depend on production efficiency improvement to achieve sustainability. As China is the world's second largest foreign capital recipient, foreign capital plays an important role in investment. If economic growth is fuelled by investment, an exodus or a shortage of foreign capital will render growth unsustainable. However, if growth is propelled by improvements in production efficiency, it is more likely to be sustained and to withstand reduction in production input. This paper estimates production efficiency in the agricultural sector in China with a panel data set comprising 30 provinces for the 7-year period, 1991–1997. A panel data model based on the Cobb–Douglas production function is used to represent the production frontier and to compute technical efficiency at the provincial level. Individual effects are tested to determine if pooled estimation is preferred to unpooled (panel) estimation. The test confirms significant differences between the provinces, and hence warrants panel data estimation. Both fixed and random effects models are estimated, with provincial technical inefficiency specified as province-specific intercept terms for the former, and regression disturbances for the latter. Although the random effects model is rejected in favour of the fixed effects model, the latter did not produce estimates with correct signs, and is rejected on economic grounds. Using the random effects model, production efficiency has increased for most provinces, but the gap between the affluent coastal region and the hinterland in the west has increased.
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Bibliographic InfoArticle provided by Elsevier in its journal Mathematics and Computers in Simulation (MATCOM).
Volume (Year): 68 (2005)
Issue (Month): 5 ()
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Web page: http://www.journals.elsevier.com/mathematics-and-computers-in-simulation/
Panel data; Production frontier; Time varying; Random effects; Fixed effects;
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