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Title:	Forecasting money demand in Malaysia with the inclusion of financial innovation
Authors:	Aliha Payam Mohammad (P72806)
Supervisor:	Tamat Sarmidi, Assoc. Prof. Dr.
Keywords:	Financial engineering Financial crises Finance Universiti Kebangsaan Malaysia -- Dissertations Dissertations, Academic -- Malaysia
Issue Date:	2019
Description:	Shifting from paper-based transactions to electronic-based transactions paves the way to achieve higher economic growth and improve the competitiveness of the economy through its effect on money demand. The introducing of new payment technologies and other financial innovations have changed traditional money demand function. Ignoring the financial innovations may lead to serious statistical issues which in turn makes monetary policy ineffective and inefficient. Cointegration failure can also be attributed to excluding financial innovation in money demand specification. Malaysia has been successful in accelerating the transition to electronic payments and encouraging the public to use electronic payment methods. Fast adoption of electronic payments justifies the need to study in-depth the impact of these new payment technologies and innovations on the Malaysian money demand. Forecasting money demand as a policy instrument, is considered essential for decision making of the central bank. Monetary authorities need the forecast of money demand to achieve their targets through formulating and implementing more appropriate rules and regulation and sustain long run economic growth. The main objectives of this study is comparing forecasting accuracy of different estimation methods based on in-sample performance and generating out-of sample forecast for 5 years ahead based on the best fitted model and second, investigating the effect of financial innovation on money demand in Malaysia based on the selected model (with the best forecasting performance. The methods of analyses are first, cointegrating and univariate models and second, ARCH-type models using monthly data from 2010 to 2018 for Malaysia. Main findings can be classified as follow: first, multivariate models generate more accurate forecast compared to univariate models and DOLS provides the most accurate forecast among all of the estimation methods. second, the forecasting performance of univariate models are fairly good for short time horizon and ETS proves to be superior to ARIMA; third, the forecast from the best fitted ARCH-type model (EGARCH) is very accurate second only to DOLS. Fourth, in all methods except one, static forecasts are superior to dynamic forecasts; fifth, according to DOLS estimation results, charge cards and debit cards have significant and negative impact on money demand though the magnitude of these effects are very small. Overall, structural based models (multivariate) generate more accurate forecast compared to non-structural based models (univariate models) as the former rely on a structural relationship between money demand and other independent variables which give the model more explanatory power for the purpose of forecasting. Including financial innovation in money demand specification helps deriving a stable money demand which is essential for current policy target (interest rate targeting) in Malaysia and leads to enhanced forecasting power of the selected model. Under such stable money demand, Bank Negara Malaysia may consider revisiting its former policy (monetary policy).,Ph.D
Pages:	248
Call Number:	HG176.7A444 2019 tesis
Publisher:	UKM, Bangi
Appears in Collections:	Faculty of Economy and Management / Fakulti Ekonomi dan Pengurusan

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