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Regional Indexes of Activity: Combining the Old with the New


  • Edda Claus

    (Melbourne Institute of Applied Economic and Social Research, The University of Melbourne)

  • Chew Lian Chua

    (Melbourne Institute of Applied Economic and Social Research, The University of Melbourne)

  • G. C. Lim

    () (Melbourne Institute of Applied Economic and Social Research, The University of Melbourne)


This paper proposes a framework to construct indexes of activity which links two strands of the index literature – the traditional business cycle analysis and the latent variable approach. To illustrate the method, we apply the framework to Australian regional data, namely to two resource-rich and two service-based states. The results reveal differences in the evolution and drivers of economic activity across the four states. We also demonstrate the value of the Index in a broader context by using a structural vector autoregression (SVAR) approach to analyse the effects of shocks from the US and from China. This Index-SVAR approach facilitates a richer analysis because the unique feature of the index method proposed here allows impulse responses to be traced back to the components.

Suggested Citation

  • Edda Claus & Chew Lian Chua & G. C. Lim, 2011. "Regional Indexes of Activity: Combining the Old with the New," Melbourne Institute Working Paper Series wp2011n15, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
  • Handle: RePEc:iae:iaewps:wp2011n15

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    References listed on IDEAS

    1. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2005. "The Generalized Dynamic Factor Model: One-Sided Estimation and Forecasting," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 830-840, September.
    2. Vasishtha, Garima & Maier, Philipp, 2013. "The impact of the global business cycle on small open economies: A FAVAR approach for Canada," The North American Journal of Economics and Finance, Elsevier, vol. 24(C), pages 191-207.
    3. Issler, Joao Victor & Vahid, Farshid, 2006. "The missing link: using the NBER recession indicator to construct coincident and leading indices of economic activity," Journal of Econometrics, Elsevier, vol. 132(1), pages 281-303, May.
    4. Aruoba, S. BoraÄŸan & Diebold, Francis X. & Scotti, Chiara, 2009. "Real-Time Measurement of Business Conditions," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 417-427.
    5. Edda Claus, 2011. "Seven Leading Indexes of New Zealand Employment," The Economic Record, The Economic Society of Australia, vol. 87(276), pages 76-89, March.
    6. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    7. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-162, April.
    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. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, July.
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    More about this item


    Regional economic activity; coincident indicators; dynamic latent factor model;

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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