2002 World Congress of Environmental and Resource Economists

In this paper we develop a positive calibrated approach to stochastic dynamic programming. Risk aversion and intertemporal substitution preferences of the decision-maker are calibrated by a procedure that minimizes the mean squared error from data on past decisions. We apply this framework to managing stochastic water supplies from Oroville Reservoir, located in Northern California. The calibrated positive SDP closely reproduces the historical storage and releases from the dam and show sensitivity of optimal decisions to a decision-maker’s risk aversion and intertemporal preferences. In comparison with a risk neutral simulation, the calibrated model had average prediction errors that were half of those from the risk neutral model.



	Paper Title:	Calibrated Stochastic Dynamic Models For Resource Management
	Presenting Author:	Richard E Howitt (University of California, Davis)
	Coauthor 1:	Arnaud Reynaud
	Coauthor 2:	Siwa Msangi
	Coauthor 3:	Keith Knapp
	Abstract:	In this paper we develop a positive calibrated approach to stochastic dynamic programming. Risk aversion and intertemporal substitution preferences of the decision-maker are calibrated by a procedure that minimizes the mean squared error from data on past decisions. We apply this framework to managing stochastic water supplies from Oroville Reservoir, located in Northern California. The calibrated positive SDP closely reproduces the historical storage and releases from the dam and show sensitivity of optimal decisions to a decision-maker’s risk aversion and intertemporal preferences. In comparison with a risk neutral simulation, the calibrated model had average prediction errors that were half of those from the risk neutral model.
	Link to paper:	Not available

	Session / Day / Time	2D / Monday / 10:15 - 11:45 am

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