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Regional inflation dynamics using space-time models

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  • H. Marques
  • G. Pino
  • JD. Tena

    ()

Abstract

This paper provides empirical evidence of the role of spatial factors on the determination of inflation dynamics for a representative set of tradable commodities in Chile. We present a simple model that explains inflation divergence across regions in a monetary union with similar preferences as a consequence of the geographical allocation of producers in the different regions. Our results indicate that spatial allocation together with transport costs are important determinants of regional inflation while macroeconomic common factors do not play an important role in this process. Existing literature had obtained the opposite result for Europe and the reasons for that difference warrant further investigation. Moreover, we find that geographical distance seems to be a more appropriate measure of neighbourhood than the adjacency of regions.

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Bibliographic Info

Paper provided by Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia in its series Working Paper CRENoS with number 200915.

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Date of creation: 2009
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Handle: RePEc:cns:cnscwp:200915

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Keywords: regional inflation dynamics; space-time models; chile;

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  1. Juan de Dios Tena & Antoni Espasa & Gabriel Pino, 2010. "Forecasting Spanish Inflation Using the Maximum Disaggregation Level by Sectors and Geographical Areas," International Regional Science Review, , vol. 33(2), pages 181-204, April.
  2. Obstfeld, Maurice & Rogoff, Kenneth, 1995. "Exchange Rate Dynamics Redux," CEPR Discussion Papers 1131, C.E.P.R. Discussion Papers.
  3. Altissimo, Filippo & Benigno, Pierpaolo & Rodriguez Palenzuela, Diego, 2005. "Long-Run Determinants of Inflation Differentials in a Monetary Union," CEPR Discussion Papers 5149, C.E.P.R. Discussion Papers.
  4. Culver, Sarah E & Papell, David H, 1997. "Is There a Unit Root in the Inflation Rate? Evidence from Sequential Break and Panel Data Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(4), pages 435-44, July-Aug..
  5. Raffaella Giacomini & Clive W.J. Granger, 2002. "Aggregation of Space-Time Processes," Boston College Working Papers in Economics 582, Boston College Department of Economics.
  6. 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.
  7. Beck, Günter W. & Hubrich, Kirstin & Marcellino, Massimiliano, 2006. "Regional inflation dynamics within and across euro area countries and a comparison with the US," CFS Working Paper Series 2007/01, Center for Financial Studies (CFS).
  8. Parsley, David C & Wei, Shang-Jin, 1996. "Convergence to the Law of One Price without Trade Barriers or Currency Fluctuations," The Quarterly Journal of Economics, MIT Press, vol. 111(4), pages 1211-36, November.
  9. Schumacher, Christian & Breitung, Jörg, 2008. "Real-time forecasting of German GDP based on a large factor model with monthly and quarterly data," International Journal of Forecasting, Elsevier, vol. 24(3), pages 386-398.
  10. Stephen G. Cecchetti & Nelson C. Mark & Robert J. Sonora, 2002. "Price Index Convergence Among United States Cities," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 43(4), pages 1081-1099, November.
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