Working Paper: CEPR ID: DP10197
Authors: Michael R. Wickens
Abstract: This lecture is about how best to evaluate economic theories in macroeconomics and finance, and the lessons that can be learned from the past use and misuse of evidence. It is argued that all macro/finance models are `false' so should not be judged solely on the realism of their assumptions. The role of theory is to explain the data, They should therefore be judged by their ability to do this. Data mining will often improve the statistical properties of a model but it does not improve economic understanding. These propositions are illustrated with examples from the last fifty years of macro and financial econometrics
Keywords: Asset price modelling; DSGE modelling; Theory and evidence in economics; Time series modelling
JEL Codes: B1; C1; E1; G1
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| quality of economic models (E17) | ability to explain data (C29) |
| improved statistical performance (C52) | economic insight (D46) |
| theoretical assumptions (C12) | empirical criticisms (B41) |