Working Paper: CEPR ID: DP154
Authors: Michael Wickens; Trevor S. Breusch
Abstract: This paper discusses the best way to formulate and estimate a dynamic econometric model when interest focuses mainly upon its long-run properties. Using results derived for the more general context of transformed regression models, it is shown how point estimates and the standard errors of long-run multipliers and long-run structural coefficients can be obtained using standard estimation methods. It is argued that such formulations are preferable to other specifications such as the error correction model. If the explanatory variables that enter the long-run solution are trend-stationary then it is found that no harm is done to the asymptotic properties of the long-run coefficients by omitting short-run dynamics entirely, though this is not recommended in practice. The results of this paper are related to the concept of co-integration and to the work of Engle and Granger. Finally, a new methodology for the construction of dynamic models is proposed.
Keywords: dynamic specification; long-run models; nonstationary time series; cointegration theory
JEL Codes: 211
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| dynamic model specifications (C32) | long-run properties (D51) |
| omitting short-run dynamics (C22) | long-run parameters (C51) |
| trend-stationary variables (C22) | long-run behavior (D22) |
| reformulated dynamic models (C32) | estimation accuracy (C13) |
| certain reformulations (C60) | advantages over traditional error correction models (C52) |