Constructive Data Mining: Modeling Argentine Broad Money Demand

FRB International Finance Discussion Paper No. 943

36 Pages Posted: 1 Nov 2008

See all articles by Neil R. Ericsson

Neil R. Ericsson

Board of Governors of the Federal Reserve System

Steven B. Kamin

Board of Governors of the Federal Reserve System

Date Written: September 4, 2008

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: Argentina, autometrics, broad money, dynamic specification, cointegration, conditional models, currency substitution, dollarization, error correction, exogeneity, hyperinflation, irreversibility, model design, model selection, money demand, PcGets, ratchet effect

JEL Classification: C52, E41

Suggested Citation

Ericsson, Neil R. and Kamin, Steven B., Constructive Data Mining: Modeling Argentine Broad Money Demand (September 4, 2008). FRB International Finance Discussion Paper No. 943, Available at SSRN: https://ssrn.com/abstract=1292412 or http://dx.doi.org/10.2139/ssrn.1292412

Neil R. Ericsson (Contact Author)

Board of Governors of the Federal Reserve System ( email )

20th Street and Constitution Avenue NW
Washington, DC 20551
United States
202-452-3709 (Phone)
202-736-5638 (Fax)

Steven B. Kamin

Board of Governors of the Federal Reserve System ( email )

20th St. and Constitution Ave.
Washington, DC 20551
United States
202-452-3339 (Phone)
202-736-5638 (Fax)

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