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STOCHASTIC DYNAMIC PROGRAMMING IN SPACE: AN APPLICATION TO BRITISH COLUMBIA FORESTRY

We construct an intertemporal model of rent-maximizing behaviour on the part of a single seller of timber under multi-dimensional risk as well as geographical heterogeneity. Subsequently, we use recursive methods (in particular, the method of dynamic programming) to characterize the optimal policy function, the rent-maximizing timber-harvesting proflle. One noteworthy feature of our empirical application is the unique and detailed information we have organized in the form of a dynamic geographical information system to account for site-speciflc cost heterogeneity in harvesting and transportation as well as uneven-aged stand dynamics in timber growth and yield across space and time in the presence of stochastic lumber prices and timber volumes. Our model is a powerful tool with which to conduct policy analysis.