Working Paper: CEPR ID: DP5266
Authors: Andreas Beyer; Roger E. A. Farmer; Jérôme Henry; Massimiliano Marcellino
Abstract: New-Keynesian models are characterized by the presence of expectations as explanatory variables. To use these models for policy evaluation, the econometrician must estimate the parameters of expectation terms. Standard estimation methods have several drawbacks, including possible lack of identification of the parameters, misspecification of the model due to omitted variables or parameter instability, and the common use of inefficient estimation methods. Several authors have raised concerns over the validity of commonly used instruments to achieve identification. In this paper we analyse the practical relevance of these problems and we propose remedies to weak identification based on recent developments in factor analysis for information extraction from large data sets. Using these techniques, we evaluate the robustness of recent findings on the importance of forward looking components in the equations of the New-Keynesian model.
Keywords: Determinacy of Equilibrium; Factor Analysis; Forward-looking Output Equation; New Keynesian Phillips Curve; Rational Expectations; Taylor Rule
JEL Codes: E5; E52; E58
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Omitted variables (C29) | Biased parameter estimates (C51) |
| Parameter instability (C62) | Biased parameter estimates (C51) |
| Correlation of instruments with error terms (C10) | Biased parameter estimates (C51) |
| Single-equation GMM estimation (C20) | Biased parameter estimates (C51) |
| Fully specified structural model (C20) | Robust findings on forward-looking components (G41) |
| Factors extracted from large datasets (C55) | Improved identification of forward-looking components (G17) |
| Inclusion of additional identifying information (Y90) | Mitigation of specification bias (C83) |