This paper shows how to solve dynamic agency models by extending recursive Lagrangean techniques à laMarcet and Marimon (2011) to problems with hidden actions. The method has many advantages with respect to the promised utilities approach (Abreu et al., 1990): it is a significant improvement in...

We propose a nonlinear infinite moving average as an alternative to the standard state space policy function for solving nonlinear DSGE models. Perturbation of the nonlinear moving average policy function provides a direct mapping from a history of innovations to endogenous variables, decomposes...

We prove that the undetermined Taylor series coefficients of local approximations to the policy function of arbitrary order in a wide class of discrete time dynamic stochastic general equilibrium (DSGE) models are solvable by standard DSGE perturbation methods under regularity and saddle point...

Klein (2000) advocates the use of the Schur decomposition of a matrix pencil to solve linear rational expectations models. Meanwhile his algorithm has become a center piece in several computer codes that provide approximate solutions to (non-linear) dynamic stochastic general equilibrium models....

I demonstrate how the discrete model of optimum income taxation can be used to derive the structure of optimal income tax rates. I compare simulations of the discrete and continuous models of optimum income taxation under identical circumstances, based on U.S. wage data. The two models produce...

In this paper we present a nonparametric approach to solving a simple one-sector stochastic growth model. A distinct advantage of our approach is that it does not require placing restrictions on the generally unknown conditional expectations functions. Our method is shown to be accurate and...

Our aim is to provide insights into some basic facts of US government debt management by introducing simple financial frictions in a Ramsey model of fiscal policy. We find that the share of short bonds in total U.S. debt is large, persistent, and highly correlated with total debt. A well known...

This paper uses an economic agent-based model of land use in a growing community on the urban fringe to explore the importance of key economic variables on the spatial patterns of development over time. Understanding dispersed patterns of urban development is important for designing policies for...

We analyse some practical aspects of implementing adaptive learning in the context of forward-looking linear models. In particular, we focus on how to set initial conditions for three popular algorithms, namely recursive least squares, stochastic gradient and constant gain learning. We propose...

This chapter discusses computational methods for approximating portfolio and asset pricing problems. Formulation of these problems is usually specified along with components, preferences, payoffs, etc., that are analytic functions. This implies that the solutions to these problems acquire this...