INVESTIGATING THE EFFECT OF FINANCIAL INNOVATIONS ON THE DEMAND FOR MONEY IN AUSTRALIA USING DOLS AND FMOLS AND COMPARING THEIR PREDICTIVE POWERS

Payam MOHAMMAD ALIHA

Ph.D candidate, Universiti Kebangsaan Malaysia (UKM), Malaysia

payammaliha@gmail.com

Tamat SARMIDI

Associate Professor Dr. at Faculty of Economics and Management, Universiti Kebangsaan Malaysia (UKM), Malaysia

tamat@ukm.edu.my

Fathin FAIZAH SAID

Dr. at Faculty of Economics and Management, Universiti Kebangsaan Malaysia (UKM), Malaysia

fatin@ukm.edu.my

Abstract

In this paper we apply two different estimation methods, namely DOLS and FMOLS to estimate real demand for money in Australia with the inclusion of financial innovations. We use a conventional money demand function that was enriched with a proxy for financial innovations. This sum of the number of cheques, credit cards, charge cards, ATM and direct entry payment was included in the regression model to proxy the effect of financial innovations on the money demand. The results indicate that the estimated coefficient of TPI using DOLS is not significant yet it is highly significant using FMOLS and it bears positive sign so that 1 percent increase in TPI leads to the increase of money demand by 0.24 percent. Also, using “Root Mean Squared Error” as the benchmark for predictive power, we conclude that FMOLS is superior to DOLD when it comes to forecasting.

Keywords: financial innovations, money demand, dynamic OLS, fully modified OLS, forecast

JEL classification: E41, E42, E52
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INVESTIGATING THE EFFECT OF FINANCIAL INNOVATIONS ON THE DEMAND FOR MONEY IN AUSTRALIA USING DOLS AND FMOLS AND COMPARING THEIR PREDICTIVE POWERS

Payam MOHAMMAD ALIHA

Ph.D candidate, Universiti Kebangsaan Malaysia (UKM), Malaysia

payammaliha@gmail.com

Tamat SARMIDI

Associate Professor Dr. at Faculty of Economics and Management, Universiti Kebangsaan Malaysia (UKM), Malaysia

tamat@ukm.edu.my

Fathin FAIZAH SAID

Dr. at Faculty of Economics and Management, Universiti Kebangsaan Malaysia (UKM), Malaysia

fatin@ukm.edu.my

Abstract

In this paper we apply two different estimation methods, namely DOLS and FMOLS to estimate real demand for money in Australia with the inclusion of financial innovations. We use a conventional money demand function that was enriched with a proxy for financial innovations. This sum of the number of cheques, credit cards, charge cards, ATM and direct entry payment was included in the regression model to proxy the effect of financial innovations on the money demand. The results indicate that the estimated coefficient of TPI using DOLS is not significant yet it is highly significant using FMOLS and it bears positive sign so that 1 percent increase in TPI leads to the increase of money demand by 0.24 percent. Also, using “Root Mean Squared Error” as the benchmark for predictive power, we conclude that FMOLS is superior to DOLD when it comes to forecasting.

Keywords: financial innovations, money demand, dynamic OLS, fully modified OLS, forecast

JEL classification: E41, E42, E52

read more