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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.

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Paper provided by Melbourne Institute of Applied Economic and Social Research, The University of Melbourne in its series Melbourne Institute Working Paper Series with number wp2011n15.

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Length: 28 pages
Date of creation: Jun 2011
Date of revision:
Handle: RePEc:iae:iaewps:wp2011n15
Contact details of provider: Postal: Melbourne Institute of Applied Economic and Social Research, The University of Melbourne, Victoria 3010 Australia
Phone: +61 3 8344 2100
Fax: +61 3 8344 2111
Web page: http://www.melbourneinstitute.com/
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  1. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2005. "The generalised dynamic factor model: one sided estimation and forecasting," ULB Institutional Repository 2013/10129, ULB -- Universite Libre de Bruxelles.
  2. 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.
  3. Issler, João Victor & Vahid, Farshid, 2002. "The Missing Link: Using the NBER Recession Indicator to Construct Coincident and Leading Indices of Economic Activity," Economics Working Papers (Ensaios Economicos da EPGE) 445, FGV/EPGE Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil).
  4. Pesaran, M. H. & Shin, Y., 1997. "Generalised Impulse Response Analysis in Linear Multivariate Models," Cambridge Working Papers in Economics 9710, Faculty of Economics, University of Cambridge.
  5. Chiara Scotti & S.Boragan Aruoba & Francis X. Diebold & University of Maryland, 2006. "Real-Time Measurement of Business Conditions," Computing in Economics and Finance 2006 387, Society for Computational Economics.
  6. 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.
  7. 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, June.
  8. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-62, April.
  9. 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.
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