Constructive Data Mining: Modeling Argentine Broad Money Demand

Abstract

This paper assesses the empirical merits of PcGets and Autometrics-two recent algorithms for computer-automated model selection-using them to improve upon Kamin and Ericsson's (1993) model of Argentine broad money demand. The selected model is an economically sensible and statistically satisfactory error correction model, in which cointegration between money, inflation, the interest rate, and exchange rate depreciation depends on the inclusion of a "ratchet" variable that captures irreversible effects of inflation. Short-run dynamics differ markedly from the long run. Algorithmically based model selection complements opportunities for the researcher to contribute value added in the empirical analysis.

Encompassing and Automatic Model Selection*

“…Moreover, the automatic modeller may be able to find multiple models that are more or less equally good, providing additional information. An example is provided by Ericsson and Kamin (2009), who compare the models that two automatic model selection softwares (PcGets and Autometrics) find with the one they developed manually earlier. In their case, the new final model is only a marginal improvement over the manually determined model; however, the automatic procedure adds robustness and a level of objectivity to their efforts.…”