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Aggregation in Large Dynamic Panels

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Author Info

  • Pesaran, M. Hashem

    () (University of Cambridge)

  • Chudik, Alexander

    () (University of Cambridge)

Abstract

This paper considers the problem of aggregation in the case of large linear dynamic panels, where each micro unit is potentially related to all other micro units, and where micro innovations are allowed to be cross sectionally dependent. Following Pesaran (2003), an optimal aggregate function is derived, and the limiting behavior of the aggregation error is investigated as N (the number of cross section units) increases. Certain distributional features of micro parameters are also identified from the aggregate function. The paper then establishes Granger's (1980) conjecture regarding the long memory properties of aggregate variables from 'a very large scale dynamic, econometric model', and considers the time profiles of the effects of macro and micro shocks on the aggregate and disaggregate variables. Some of these findings are illustrated in Monte Carlo experiments, where we also study the estimation of the aggregate effects of micro and macro shocks. The paper concludes with an empirical application to consumer price inflation in Germany, France and Italy, and re-examines the extent to which ‘observed’ inflation persistence at the aggregate level is due to aggregation and/or common unobserved factors. Our findings suggest that dynamic heterogeneity as well as persistent common factors are needed for explaining the observed persistence of the aggregate inflation.

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Bibliographic Info

Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 5478.

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Length: 56 pages
Date of creation: Feb 2011
Date of revision:
Handle: RePEc:iza:izadps:dp5478

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Related research

Keywords: aggregation; large dynamic panels; long memory; weak and strong cross section dependence; VAR models; impulse responses; factor models; inflation persistence;

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References

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  1. Granger, C. W. J., 1987. "Implications of Aggregation with Common Factors," Econometric Theory, Cambridge University Press, vol. 3(02), pages 208-222, April.
  2. Stoker, Thomas M, 1984. "Completeness, Distribution Restrictions, and the Form of Aggregate Functions," Econometrica, Econometric Society, vol. 52(4), pages 887-907, July.
  3. Pesaran, M. Hashem & Chudik, Alexander, 2011. "Aggregation in Large Dynamic Panels," IZA Discussion Papers 5478, Institute for the Study of Labor (IZA).
  4. M. H. Pesaran & R. G. Pierse & M. S. Kumar, 1988. "Econometric Analysis of Aggregation in the Context of Linear Prediction Models," UCLA Economics Working Papers 485, UCLA Department of Economics.
  5. Lutkepohl, Helmut, 1984. "Linear transformations of vector ARMA processes," Journal of Econometrics, Elsevier, vol. 26(3), pages 283-293, December.
  6. Hashem Pesaran, M., 2003. "Aggregation of linear dynamic models: an application to life-cycle consumption models under habit formation," Economic Modelling, Elsevier, vol. 20(2), pages 383-415, March.
  7. Jean Imbs & Haroon Mumtaz & Morton O. Ravn & Helene Rey, 2002. "PPP Strikes Back: Aggregation and the Real Exchange Rate," NBER Working Papers 9372, National Bureau of Economic Research, Inc.
  8. Zaffaroni, Paolo, 2004. "Contemporaneous aggregation of linear dynamic models in large economies," Journal of Econometrics, Elsevier, vol. 120(1), pages 75-102, May.
  9. Peter C.B. Phillips & Hyungsik R. Moon, 1999. "Linear Regression Limit Theory for Nonstationary Panel Data," Cowles Foundation Discussion Papers 1222, Cowles Foundation for Research in Economics, Yale University.
  10. Pesaran, M.H. & Chudik, A., 2010. "Econometric Analysis of High Dimensional VARs Featuring a Dominant Unit," Cambridge Working Papers in Economics 1024, Faculty of Economics, University of Cambridge.
  11. Stoker, Thomas M, 1993. "Empirical Approaches to the Problem of Aggregation Over Individuals," Journal of Economic Literature, American Economic Association, vol. 31(4), pages 1827-74, December.
  12. Granger, C.W.J. & Siklos, P.L., 1993. "Systematic Sampling, Temporal Aggregation, Seasonal Adjustment, and Cointegration: Theory and Evidence," Working Papers 93001, Wilfrid Laurier University, Department of Economics.
  13. Lewbel, Arthur, 1994. "Aggregation and Simple Dynamics," American Economic Review, American Economic Association, vol. 84(4), pages 905-18, September.
  14. Pesaran, M.H. & Smith, R., 1992. "Estimating Long-Run Relationships From Dynamic Heterogeneous Panels," Cambridge Working Papers in Economics 9215, Faculty of Economics, University of Cambridge.
  15. Lorenzo Trapani & Giovanni Urga, 2007. "Micro versus Macro Cointegration in Heterogeneous Panels," Working Papers 0711, Department of Economics and Technology Management, University of Bergamo.
  16. Alexander Chudik & M. Hashem Pesaran & Elisa Tosetti, 2009. "Weak and Strong Cross Section Dependence and Estimation of Large Panels," Working Paper Series 1100, European Central Bank.
  17. Granger, C. W. J., 1980. "Long memory relationships and the aggregation of dynamic models," Journal of Econometrics, Elsevier, vol. 14(2), pages 227-238, October.
  18. van Garderen, Kees Jan & Lee, Kevin & Pesaran, M. Hashem, 2000. "Cross-sectional aggregation of non-linear models," Journal of Econometrics, Elsevier, vol. 95(2), pages 285-331, April.
  19. Yan Shen & Cheng Hsiao & Hiroshi Fujiki, 2005. "Aggregate vs. disaggregate data analysis-a paradox in the estimation of a money demand function of Japan under the low interest rate policy," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(5), pages 579-601.
  20. Forni, Mario & Lippi, Marco, 1997. "Aggregation and the Microfoundations of Dynamic Macroeconomics," OUP Catalogue, Oxford University Press, number 9780198288008, July.
  21. Clive Granger & Tae-Hwy Lee, 1999. "The effect of aggregation on nonlinearity," Econometric Reviews, Taylor and Francis Journals, vol. 18(3), pages 259-269.
  22. Geweke, John, 1985. "Macroeconometric Modeling and the Theory of the Representative Agent," American Economic Review, American Economic Association, vol. 75(2), pages 206-10, May.
  23. Jan Kmenta & James B. Ramsey, 1980. "Evaluation of Econometric Models," NBER Books, National Bureau of Economic Research, Inc, number kmen80-1, October.
  24. Giacomini, Raffaella & Granger, Clive W.J., 2001. "Aggregationn of Space-Time Processes," University of California at San Diego, Economics Working Paper Series qt77f76455, Department of Economics, UC San Diego.
  25. Rose, David E., 1977. "Forecasting aggregates of independent Arima processes," Journal of Econometrics, Elsevier, vol. 5(3), pages 323-345, May.
  26. Granger, C. W. J., 1993. "Implications of seeing economic variables through an aggregation window," Ricerche Economiche, Elsevier, vol. 47(3), pages 269-279, September.
  27. Stoker, Thomas M, 1986. "Simple Tests of Distributional Effects on Macroeconomic Equations," Journal of Political Economy, University of Chicago Press, vol. 94(4), pages 763-95, August.
  28. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
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Citations

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Cited by:
  1. Matthieu Bussière & Alexander Chudik & Giulia Sestieri, 2012. "Modelling global trade flows: results from a GVAR model," Globalization and Monetary Policy Institute Working Paper 119, Federal Reserve Bank of Dallas.
  2. Pesaran, M. Hashem & Chudik, Alexander, 2011. "Aggregation in Large Dynamic Panels," IZA Discussion Papers 5478, Institute for the Study of Labor (IZA).
  3. Pesaran, M. Hashem & Smith, Ron P., 2011. "Beyond the DSGE Straitjacket," IZA Discussion Papers 5661, Institute for the Study of Labor (IZA).

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