000024184 001__ 24184
000024184 005__ 20180122202707.0
000024184 037__ $$a1322-2016-103559
000024184 041__ $$aen
000024184 245__ $$aOptimizing Production under Uncertainty: Generalisation of the State-Contingent Approach and Comparison of Methods for Empirical Application
000024184 260__ $$c2004
000024184 269__ $$a2004
000024184 300__ $$a35
000024184 336__ $$aWorking or Discussion Paper
000024184 446__ $$aEnglish
000024184 490__ $$aUnit of Economics Working Paper 2004/2
000024184 520__ $$aIn a recent paper Rasmussen (Rasmussen 2003) derived criteria for optimal production under uncertainty based on the state-contingent approach developed by Chambers and Quiggin (2000). While the criteria in the 2003-paper were derived for the one variable input case, and for different types of input, the present paper generalises the results to the multi-variable input case. It is further shown that with the output-cubical technology as the basic model, any type of input may be analysed as a special case within the general model framework developed. The main part of the paper is devoted to the problems of empirical application of the State-contingent approach. To empirically apply the optimization criteria derived, one needs specific functional forms of both the state-contingent production functions and the utility function based on state-contingent income measures. The paper shortly reviews the empirical approach normally taken when using the well-known Expected Utility (EU) model and this approach is in turn compared to the more general approach potentially available in the state-contingent model. Comparisons show that the potential benefit of the state-contingent approach compared to the expected utility model is limited by the empirical opportunities. Thus, it is unrealistic to expect production functions to be estimated for all possible states of nature. State-contingent production functions therefore, have to be considered as stochastic production functions. In this case, it is not obvious whether the state-contingent approach is better than the expected utility model, and it is proposed that this is further investigated using Monte-Carlo simulation.
000024184 650__ $$aProduction Economics
000024184 650__ $$aRisk and Uncertainty
000024184 700__ $$aRasmussen, Svend
000024184 8564_ $$s427889$$uhttp://ageconsearch.umn.edu/record/24184/files/ew040002.pdf
000024184 887__ $$ahttp://purl.umn.edu/24184
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  Previous issue date: 2004
000024184 982__ $$gRoyal Veterinary and Agricultural University>Food and Resource Economic Institute>Unit of Economics Working papers
000024184 980__ $$a1322