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A Model to Estimate the Composite Index of Economic Activity in Romania – IEF-RO

Author

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  • Albu, Lucian Liviu

    () (Research Professor, Institute for Economic Forecasting)

Abstract

One of the most significant impediments for short-term forecasts is the frequency of publishing GDP. At present, national institutes of statistics are publishing officially registered GDP only quarterly. In our study, we tried to build a composite indicator based on usually monthly data and to use it in order to obtain short-term forecasts for economic activity at national level. This indicator could be useful taking into account that actually there is no synthetic indicator to describe the short-run dynamics of economic activity. Thus, such an estimating model we are proposing for the Romanian economy is coming from the last results in this field, especially from the OECD methodology. Moreover, to validate the main hypotheses of the estimating model for the composite indicator in the case of the Romanian economy we used the quarterly data and, as benchmark indicator was considered the quarterly published GDP. Using certain models based on composite indicators (leading indicators, coincidence indicators, and post-cycle indicators), beside other models to analyse high frequency time series and to obtain sort-term forecasts (such as principal component method, so-called virtual monthly GDP method or various interpolating methods), it can result in richer information for the business environment which in modern times founds itself in an accelerated process of change.

Suggested Citation

  • Albu, Lucian Liviu, 2008. "A Model to Estimate the Composite Index of Economic Activity in Romania – IEF-RO," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 5(2), pages 44-50, June.
  • Handle: RePEc:rjr:romjef:v:5:y:2008:i:2:p:44-50
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    References listed on IDEAS

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    1. Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.
    2. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, pages 111-130.
    3. Alberto Alesina & Dani Rodrik, 1994. "Distributive Politics and Economic Growth," The Quarterly Journal of Economics, Oxford University Press, vol. 109(2), pages 465-490.
    4. Stark, Tom & Croushore, Dean, 2002. "Forecasting with a real-time data set for macroeconomists," Journal of Macroeconomics, Elsevier, pages 507-531.
    5. Albu, Lucian-Liviu, 2006. "A dynamic model to estimate the long-run trends in potential GDP," MPRA Paper 3708, University Library of Munich, Germany.
    6. Phillips, Keith R., 2004. "A new monthly index of the Texas business cycle," Working Papers 0401, Federal Reserve Bank of Dallas.
    7. Scutaru, Cornelia & Stanica, Cristian Nicolae, 2005. "Output Gap And Shocks Dynamics. The Case Of Romania," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 2(4), pages 25-43.
    8. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters,in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409 National Bureau of Economic Research, Inc.
    9. Christophe Croux & Mario Forni & Lucrezia Reichlin, 2001. "A Measure Of Comovement For Economic Variables: Theory And Empirics," The Review of Economics and Statistics, MIT Press, vol. 83(2), pages 232-241, May.
    10. James H. Stock & Mark W. Watson, 1993. "A Procedure for Predicting Recessions with Leading Indicators: Econometric Issues and Recent Experience," NBER Chapters,in: Business Cycles, Indicators and Forecasting, pages 95-156 National Bureau of Economic Research, Inc.
    11. Stanica, Cristian, 2004. "Aplicatii privind exprimarea PIB-ului potential trimestrial," Working Papers of Macroeconomic Modelling Seminar 040203, Institute for Economic Forecasting.
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    Citations

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    Cited by:

    1. Albu, Lucian-Liviu & Ciuiu, Daniel, 2009. "A method to evaluate composite performance indices based on variance-covariance matrix," MPRA Paper 19979, University Library of Munich, Germany, revised Aug 2009.
    2. Savoiu, Gheorghe & Dinu, Vasile & Ciuca, Suzana, 2013. "Foreign Direct Investment based on Country Risk and other Macroconomic Factors. Econometric Models for Romanian Economy," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 39-61, March.
    3. Lucian-Liviu Albu & Vasile Dinu, 2009. "How Deep and How Long Could Be the Recession in Romania," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 11(Number Sp), pages 675-683, November.
    4. S. V. S. Dixit & Maxwell Opoku-Afari, 2012. "Tracking Short-Term Dynamics of Economic Activity in Low-Income Countries in the Absence of High-Frequency Gdp Data," IMF Working Papers 12/119, International Monetary Fund.
    5. Dan Nicolae & Valentin Pau & Mihaela Jaradat & Mugurel Ionut Andreica & Vasile Deac, 2010. "Mathematical Model for Forecasting and Estimating of Market Demand," Post-Print hal-00768770, HAL.

    More about this item

    Keywords

    business cycle indicators; coincident and leading indicators; composite index;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E20 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - General (includes Measurement and Data)
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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