This chapter describes feedforward neural networks as approximators and relates them to statistical discriminant functions, and explains the ways in which neural nets of varying complexity can represent equilibria in two repeated games and one dynamic economic model. Because linear strategies...

This paper describes the recent advances for rapidly and accurately solving matrix Riccati and Sylvester equations and applies them to devise efficient computational methods for solving and estimating dynamic linear economies. The chapter explores the most promising solution methods available...

Robust control theory is a tool for assessing decision rules when a decision maker distrusts either the specification of transition laws or the distribution of hidden state variables or both. Specification doubts inspire the decision maker to want a decision rule to work well for a ∅ of models...

In Lucas and Stokey's (1983) economy, tax rates inherit the serial correlation structure of government expenditures, belying Barro's (1979) result that taxes should be a random walk for any stochastic process of government expenditures. To recover a version of Barro's 'random walk' tax-smoothing...

In an economy studied by Lucas and Stokey, tax rates inherit the serial correlation structure of government expenditures, belying Barro's earlier result that taxes should be a random walk for any stochastic process of government expenditures. To recover a version of Barro's random walk...

This paper studies an optimal fiscal policy problem of Lucas and Stokey (1983) but in a situation in which the representative agent's distrust of the probability model for government expenditures puts model uncertainty premia into history-contingent prices. This situation gives rise to a motive...

An optimal tax and government borrowing plan in a setting with tax distortions (Barro,1979) locally pin down the marginal cost of servicing government debt, called marginal p. An option to default determines the government's debt capacity and its optimal state-contingent risk management policies...

For a Markov decision problem in which unknown transition probabilities serve as hidden state variables, we study the quality of two approximations to the decision rule of a Bayesian who each period updates his subjective distribu- tion over the transition probabilities by Bayes’ law. The...