Finite Sample Properties of Parameterized Expectations Algorithm Solutions; Is the Length So Determinant?

Authors

  • A. Jesús Sánchez Fuentes Complutense Institute of International Studies (ICEI-UCM) & GEN-UVigo.

DOI:

https://doi.org/10.9781/ijimai.2022.02.007

Keywords:

Nonlinear Models, Numerical Solution Methods, Optimal Growth, Parameterized Expectations Algorithm

Abstract

The solution of the Parameterized Expectations Algorithm (PEA) is well defined based on asymptotic properties. In practice, it depends on the specific replication of the exogenous shock(s) used for the resolution process. Typically, this problem is reduced when a sufficiently long replication is considered. In this paper, we suggest an alternative approach which consists of using several, shorter replications. A centrality measure (the median) is used then to discriminate among the different solutions using two different criteria, which differ in the information used. On the one hand, the distance to the vector composed by median values of PEA coefficients is minimized. On the other hand, distances to the median impulse response is minimized. Finally, we explore the impact of considering alternative approaches in an empirical illustration.

Downloads

Download data is not yet available.

Downloads

Published

2022-03-01
Metrics
Views/Downloads
  • Abstract
    4
  • PDF
    1

How to Cite

Sánchez Fuentes, A. J. (2022). Finite Sample Properties of Parameterized Expectations Algorithm Solutions; Is the Length So Determinant?. International Journal of Interactive Multimedia and Artificial Intelligence, 7(3), 26–34. https://doi.org/10.9781/ijimai.2022.02.007