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Efficiency analysis under uncertainty: a simulation study
Author(s) -
Shankar Sriram
Publication year - 2015
Publication title -
australian journal of agricultural and resource economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.683
H-Index - 49
eISSN - 1467-8489
pISSN - 1364-985X
DOI - 10.1111/1467-8489.12055
Subject(s) - estimator , production (economics) , ex ante , constraint (computer aided design) , econometrics , function (biology) , computer science , preference , stochastic modelling , rational expectations , economics , mathematical optimization , mathematics , microeconomics , statistics , geometry , finance , evolutionary biology , biology , macroeconomics
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.