Firms adjust to differences in market size and demand uncertainty by changing the frequency and size of their export shipments. In our inventory model, transportation costs and optimal shipment frequency are determined on the basis of demand as well as inventory and per shipments costs. Using a...

We identify total factor productivity (TFP) news shocks using standard VAR methodology and document a new stylized fact: in response to news about future increases in TFP, inventories rise and comove positively with other major macroeconomic aggregates. We show that the standard theoretical...

The paper shows that taking inventory control out of the hands of competitive or exclusive retailers and assigning it to a manufacturer increases the value of a supply chain especially for goods whose demand is highly volatile. This is because doing so solves incentive distortions that arise...

The Dasgupta-Heal-Solow-Stiglitz model of capital accumulation and resource depletion poses the following sustainability problem: is it feasible to sustain indefinitely a level of consumption that is bounded away from zero? We provide a complete technological characterization of the...

We develop a simple model of managing a system subject to pollution damage under risk of an abrupt and random jump in the damage coefficient. The model allows the full dynamic characterization of the optimal emission policies under uncertainty. The results, that imply prudent behavior due to...

We show that the standard Value Function Iteration (VFI) algorithm has difficulties approximating models with jump discontinuities in policy functions. We find that VFI fails to accurately identify the location and size of jump discontinuities while other methods - such as the Endogenous Grid...

We analyze optimal compensation schedules for the directors of two plants belonging to the same owner and producing the same good but serving geographically differentiated markets. Since the outcome of each director depends on his own effort and on a random variable representing market...

We propose a new method for solving high-dimensional dynamic programming problems and recursive competitive equilibria with a large (but finite) number of heterogeneous agents using deep learning. The "curse of dimensionality" is avoided due to four complementary techniques: (1) exploiting...