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Estimating Goldfeld’s Conventional Money Demand Function Using Ridge Regression

Estimating Goldfeld’s Conventional Money Demand Function Using Ridge Regression
Maman Setiawan, MT
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The purpose of this study was to examine the effectiveness of applying ridge regression procedures over OLS in Goldfeld’s conventional money demand function. Ridge regression has been known and developed as an alternative prediction method to ordinary least squares regression (OLS) in cases where there is a high degree of multicollinearity among the independent variables. This study used Indonesia Financial Data and used quarterly data for sample period 1995:1 – 2006:3. The results showed that ridge regression yielded predictive equations that improved on those equations derived from applying ordinary least square regression. The bias estimation as expected in the ridge estimation did not appear in this study when it was benchmarked to OLS Regression.

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