Constructive data mining: modeling Argentine broad money demand

Neil R. Ericsson () and Steven B. Kamin

No 943, International Finance Discussion Papers from Board of Governors of the Federal Reserve System (U.S.)

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.

Keywords: Money supply; Demand for money (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cba, nep-ecm, nep-mac and nep-mon
Date: 2008
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