In this paper, I analyze a dynamic model of a firm’s joint decisions to export and innovate, allowing both decisions to affect the firm’s production in accordance with selfselection and learning-by-exporting theories of firm-level export and production dynamics. I calibrate the model using Chilean manufacturing plant data from 2005 to 2007 and find that self-selection and learning-by-exporting ...

Randomization adds beneficial flexibility to the construction of optimal simple plans in dynamic environments. A decision-maker, restricted to the use of simple plans, may find a stochastic plan that strictly outperforms all deterministic ones. This is true even in noninteractive deterministic environments where the decision-maker’s choices have no influence on his signals nor on the future evo...

Advances in computer software and in agent-based computational finance allow the use of numerical methods in order to optimize different type of functions. In this paper we propose a numerical method in order to find the level of leverage that maximizes the geometric mean of a series of historical daily returns. One of the advantages of the use of numerical methods is that it requires less assu...

The objective of this work is to try to define and calculate the optimal growth path, in the presence of exogenous technical change, without resorting to the discounted-sum criterion. The solution suggested is to consider an optimality criterion expressing an Allais-anonymous intergenerational consensus. The partial characterization of consensual optimality was made possible thanks to the decom...

The method of endogenous gridpoints (ENDG) significantly speeds up the solution to dynamic stochastic optimization problems with continuous state and control variables by avoiding repeated computations of expected outcomes while searching for optimal policy functions. I provide an interpolation technique for non-rectilinear grids that allows ENDG to be used in n-dimensional problems in an intui...

In this paper, we consider expected value, variance and worst–case optimization of nonlinear models. We present algorithms for computing optimal expected values, and variance, based on iterative Taylor expansions. We establish convergence and consider the relative merits of policies based on expected value optimization and worst-case robustness. The latter is a minimax strategy and ensures opti...

We examine the effect of competition on investment decisions in an industry in which each firm has a completely irreversible investment opportunity and the product market has positive externalities for a small market size and negative externalities for a large market size. In the latter case, which corresponds to the traditional competitive industries, firms invest sequentially as market profit...

This paper studies price dynamics in a setting in which a monopolist sells a new experience good over time to many buyers, and the seller can neither price discriminate among the buyers nor commit to a price rule. Buyers learn from their own experiences about the effectiveness of the product. Individual learning generates ex post heterogeneity, which affects the buyers’ purchasing decisions, th...

a r t i c l e i n f o JEL classification: C61 D92 Keywords: Price induced technical progress Disembodied technical progress Comparative dynamics Optimal control Testable implications A theory of a wealth maximizing, capital accumulating, price taking firm facing adjustment costs and operating in the presence of disembodied and price-induced technical progress is developed. The testable implicat...

We model dynamic consumer choice in a stochastic optimal control framework and show conditions under which observable market share data possess the Markov property. Using 30 years of annual aggregate milk consumption data differentiated by fat content, maximum entropy is used to estimate nonstationary transition probabilities showing how consumer tastes and preferences have changed over time. T...