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Efficiency analysis under uncertainty: a simulation study

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  • Sriram Shankar

Abstract

type="main" xml:id="ajar12055-abs-0001"> We model production technology in a state-contingent framework assuming that the firms maximise ex ante their preference function subject to stochastic technology constraint; in other words, firms are assumed to act rationally. We show that rational producers who face the same stochastic technology can make significantly different production choices. Further, we develop an econometric methodology to estimate the risk-neutral probabilities, efficiency scores and the parameters of stochastic technology when there are two states of nature and only one of which is observed. Finally, we simulate noiseless data based on our state-contingent specification of technology. Our state-contingent estimator recovers technology parameters and other economic quantities of interest without any error. But, when we apply conventional efficiency estimators to the simulated data, we obtain biased estimates of technical efficiency.

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  • Sriram Shankar, 2015. "Efficiency analysis under uncertainty: a simulation study," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 59(2), pages 171-188, April.
    • Handle: RePEc:bla:ajarec:v:59:y:2015:i:2:p:171-188
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    1. John Quiggin & Robert G. Chambers, 2006. "The state-contingent approach to production under uncertainty ," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 50(2), pages 153-169, June.
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    2. Zheng, Hongyun & Ma, Wanglin & Wang, Fang & Li, Gucheng, 2021. "Does internet use improve technical efficiency of banana production in China? Evidence from a selectivity-corrected analysis," Food Policy, Elsevier, vol. 102(C).

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