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Activity Number:
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267
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Type:
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Contributed
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Date/Time:
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Tuesday, August 4, 2009 : 8:30 AM to 10:20 AM
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Sponsor:
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Business and Economic Statistics Section
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| Abstract - #304514 |
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Title:
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Computer-automated Constructive Data Mining: Modeling Argentine Broad Money Demand
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Author(s):
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Neil R. Ericsson*+ and Steven B. Kamin
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Companies:
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Federal Reserve Board and Federal Reserve Board
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Address:
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Stop 15, Washington, DC, 20551,
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Keywords:
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cointegration ; dollarization ; dynamic specification ; error correction ; model design ; model selection
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Abstract:
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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.
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