English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

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 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.

Constructive Data Mining: Modeling Argentine Broad Money Demand