MODELING OF INDONESIA CONSUMER PRICE INDEX USING MULTI INPUT INTERVENTION MODEL
Abstract
There are some events which are expected effecting CPI»s fluctuation, i.e. financial crisis 1997/ 1998, fuel price risings, base year changing»s, independence of Timor-Timur (October 1999), and Tsunami disaster in Aceh (December 2004). During re-search period, there were eight fuel price risings and four base year changing’s. The objective of this research is to obtain multi input intervention model which can describe magnitude and duration of each event effected to CPI. Most of intervention re-searches that have been done are only contain of an intervention with single input, ei-ther step or pulse function. Multi input intervention was used in Indonesia CPI case because there are some events which are expected effecting CPI. Based on the result, those events were affecting CPI. Additionally, other events, such as Ied on January 1999, events on April 2002, July 2003, December 2005, and September 2008, were affecting CPI too. In general, those events gave positive effect to CPI, except events on April 2002 and July 2003 which gave negative effects.
JEL Classification: C22, C43, E31, I38
Keywords: CPI, Multi Input Intervention, and Fuel Price Rising.
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References
Bhatacharyya, M.N., and Layton, A.P. “Effectiveness of Seat Belt Legislation on the Queenslan Road Toll - An Australian case study in intervention analysis”, Journal of American Statistics Association, 1979, 74, p. 596-603.
Brockwell, P.J., and Davis, R.A., (1996), Introduction to Time Series and Forecasting, Spinger-Verlag, New York.
Bowerman, B.L. and O’Connell, R.T., (1993), Forecasting and Time Series: An Applied Approach, 3rd edition, Duxbury Press, California.
Dholakia, Kruti. “What Has Affected The Unemployment Rates in The USA: Preliminary Analysis of The Last 12 Years-Elections and 9/11”, Midwestern Business and Economic Review, 2003, 32, p. 34-43.
Hamilton, J.D., (1994), Time Series Analysis, Princeton University Press, New Jersey.
Kendall, S.M. and Ord, J.K., (1990), Time Series, 3rd edition, Edward Arnold, London.
Leonard, M., (2001), “Promotional Analysis and Forecasting for Demand Planning: A Practical Time Series Approach”, SAS institute Inc, USA.
Parwitasari, D., “Modeling Transportation CPI in Surabaya which Contains of Structural Change”, Unpublished Bachelor Final Project, Department of Statistics, Institut Teknologi Sepuluh Nopember. 2006,
Rupingi, A. Slamet, “Intervention Analysis and Generalized Autoregressive Conditional Heteroskedasticity (GARCH): Indonesia CPI Case Study”, Unpublished Bachelor Final Project,nDepartment of Statistics, Institut Teknologi Sepuluh Nopember, 2001.
Rosa, B. Citra, “The effect of Fuel Price in Each Commodity and Services of Indonesia CPI 1998-2005”, http://youngstatistician.com/?pilih=skripsi&nip=se10604, (2006).
Suhartono, “Theory and Application of Pulse Function Intervention”, Jurnal MatStat, 2007, 7(2), p. 191-214.
Tsay, R.S, (2002), Analysis of Financial Time Series, John Wiley & Sons, Inc., New Jersey.
Valadkhani, A. and Layton, A.P., “Quantifying the Effect of the GST on Inflation in Australia’s Capital Cities: An Intervention Analysis”, Australian Economic Review, 2004, 37(2), p. 125-138.
Wei, W.W.S, (1990), Time Series Univariate and Multivariate Methods, Addison Wesley Publishing Company Inc., Canada.
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