1. Constructive Data Mining: Modeling Argentine Broad Money Demand
- Author:
- Neil R. Ericsson and Steven B. Kamin
- Publication Date:
- 09-2008
- Content Type:
- Working Paper
- Institution:
- Board of Governors of the Federal Reserve System
- Abstract:
- his 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 correc- tion model, in which cointegration between money, inflation, the interest rate, and exchange rate depreciation depends on the inclusion of a “ratchet” variable that cap- tures 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.
- Topic:
- Economics, Markets, Finance, and Inflation
- Political Geography:
- Argentina and South America