Wong, Shirly Siew-Ling and Abu Mansor, Shazali and Puah, Chin-Hong and Liew, Venus Khim-Sen (2012): Forecasting malaysian business cycle movement: empirical evidence from composite leading indicator.
Download (334Kb) | Preview
Early detection of a turning point in a business cycle is crucial, as information about the changing phases in business cycles enables policy makers, the business community, and investors to cope better with unexpected events brought about by economic and business situations. The Malaysian economy is fortunate to own a publicly accessible composite of leading indicator (CLI) that is presumed capable of tracing the business cycle movement and thus contributes to the creation of an early signaling tool for short-term economic forecasting. Certainly, the usefulness of this CLI in monitoring the contemporary economic and business condition in Malaysia will be empirically appealing to the nation. Even though the present study can display the ability of the Malaysian CLI to trace the business cycle and offers advanced detection of business cycle turning points, the evidence of diminishing lead times foreseen by the CLI significantly weaken the fundamental function of a leading index as an early tool to signal economic vulnerability.
|Item Type:||MPRA Paper|
|Original Title:||Forecasting malaysian business cycle movement: empirical evidence from composite leading indicator|
|Keywords:||Business Cycle; Composite Leading Indicator; Early Signaling Tool|
|Subjects:||E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E32 - Business Fluctuations; Cycles
E - Macroeconomics and Monetary Economics > E1 - General Aggregative Models > E17 - Forecasting and Simulation: Models and Applications
|Depositing User:||Chin-Hong Puah|
|Date Deposited:||13. Feb 2012 20:47|
|Last Modified:||12. Feb 2013 15:26|
Ahmad, N. (2003). Malaysia Economic Indicators: Leading, Coincident and Lagging Indicators. Paper presented at the Workshop on Composite Leading Indicators and Business Tendency Survey, Bangkok.
Bascos-Deveza, T. (2006). Early Warning System on the Macroeconomy Identification of Business Cycles in the Philippines. Bangko Sentral Review, January, 7-16.
Bry, G. and Boschan, C. (1971). Cyclical Analysis of Time Series, Selected Procedures and Computer Programs (Technical Paper 20). Massachusetts Avenue, Cambridge: National Bureau of Economic Research, Columbia University Press.
Burns, A.F. and Mitchell, W.C. (1946). Measuring Business Cycles. In NBER (Ed.), Studies in Business Cycle. New York: Colombia University Press.
Cotrie, G., Craigwell, R.C. and Maurin, A. (2009). Estimating Indexes of Coincident and Leading Indicators for Barbados. Applied Econometrics and International Development, 9(2), 1-33.
Department of Statistics Malaysia. Malaysia Economic Indicators: Leading, Coincident and Lagging Indexes, various issues. Kuala Lumpur: Department of Statistics Malaysia.
Dickey, D. and Fuller, W. (1979). Distribution of the Estimators for Autoregressive Times Series with a Unit Root. Journal of the American Statistical Association, 74, 427-431.
Dickey, D. and Fuller, W. (1981). Likelihood Ratio Statistic for Autoregressive Times Series with a Unit Root. Econometrica, 49, 1057-1072.
European Central Bank (ECB) (2001). The Information Content of Composite Indicators of the Euro Area Business Cycle. In ECB (Ed.), Monthly Bulletin, November 2001 (pp. 39-50). Germany: ECB.
Engle, R.F. and Granger, C.W.J. (1987). Cointegration and Error Correction Representation, Estimation and Testing. Econometrica, 55, 251-276.
Everhart, S.S. and Duval-Hernandez, R. (2000). Leading Indicator Project: Lithuania. Policy Research Dissemination Center, Policy Research Working Paper Series 2365.
Everhart, S.S. and Duval-Hernandez, R. (2001). Short-Term Macro Monitoring: Leading Indicator Construction-Mexico. Georgia State University, Andrew Young School of Policy Studies, Working Paper 01-8.
Gandolfo, G. (1981). Qualitative Analysis and Econometric Estimation of Continuous Time Dynamic Models. Amsterdam: North-Holland Publishing Company.
Gonzalo, J. and Pitarakis, J-Y. (2002). Estimation and Model Selection Based Inference in Single and Multiple Threshold Models. Journal of Econometrics, 110(2), 319-352.
Hodrick, R.J. and Prescott, E.C. (1980). Postwar U.S. Business Cycles: An Empirical Investigation. Carnegie Mellon University Discussion Paper, No. 451.
International Monetary Fund (IMF). International Financial Statistics, Various Issues. Washington, DC: IMF.
Johansen, S. and Juselius, K. (1990). The Maximum Likelihood Estimation and Inference on Cointegration-With Application to Demand for Money. Oxford Bulletin of Economics and Statistics, 52, 169-210.
Klucik, M. and Haluska, J. (2008). Construction of Composite Leading Indicator for the Slovak Economy. Scientific Annals of the “Alexandru Ioan Cuza” University of Iasi – Economic Sciences Section, 363-370.
Kozlowski, P.J. (1980). Forecasting With Leading Indicators: Regional Economic Sense or Nonsense. The Journal of Regional Analysis and Policy, 19(1), 3-24.
Kranendonk, H., Bonenkamp, J. and Verbuggen, J. (2005). A Leading Indicator for the Dutch Economy. Central Planning Bureau (CPU), Discussion Paper, No. 32.
Mitchell, W.C. and Burns, A.F. (1938). Statistical Indicators of Cyclical Revivals, New York, NBER.
Phillips, P.C.B and Perron, P. (1988). Testing for a Unit Root in Time Series Regression. Biometrika, 75, 335–346.
Polasek, W. (2010). Dating and Exploration of the Business Cycle in Iceland. The Rimini Centre for Economic Analysis, Working Paper 10-13.
Yap, M.M.C. (2009). Assessing Malaysia’s Business Cycle Indicators. Monash University Discussion Paper, 04/09.
Zalewski, K. (2009). Forecasting Turning Points with Composite Leading Indicators – The Case of Poland, Ekonomia Journal, 24, 61-93.
Zhang, W.D. and Zhuang, J.Z. (2002). Leading Indicators of Business Cycles in Malaysia and the Philippines. Asian Development Bank, Economics and Research Department, Working Paper Series, No 32.