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Aggregation in Large Dynamic Panels

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  • Pesaran, M.H.
  • Chudik, A.

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 Faculty of Economics, University of Cambridge in its series Cambridge Working Papers in Economics with number 1118.

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Date of creation: 31 Jan 2011
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Handle: RePEc:cam:camdae:1118

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Web page: http://www.econ.cam.ac.uk/index.htm

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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  1. M. Hashem Pesaran & Alexander Chudik, 2011. "Aggregation in large dynamic panels," Globalization and Monetary Policy Institute Working Paper 101, Federal Reserve Bank of Dallas.
  2. Zaffaroni, Paolo, 2004. "Contemporaneous aggregation of linear dynamic models in large economies," Journal of Econometrics, Elsevier, vol. 120(1), pages 75-102, May.
  3. Imbs, Jean & Mumtaz, Haroon & Ravn, Morten O. & Rey, Hélène, 2003. "PPP Strikes Back: Aggregation and the Real Exchange Rate," CEPR Discussion Papers 3715, C.E.P.R. Discussion Papers.
  4. 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.
  5. Chudik, Alexander & Pesaran, Hashem, 2009. "Infinite-dimensional VARs and factor models," Working Paper Series 0998, European Central Bank.
  6. Altissimo, Filippo & Mojon, Benoit & Zaffaroni, Paolo, 2009. "Can aggregation explain the persistence of inflation?," Journal of Monetary Economics, Elsevier, vol. 56(2), pages 231-241, March.
  7. Chudik, Alexander & Pesaran, Hashem & Tosetti, Elisa, 2009. "Weak and strong cross section dependence and estimation of large panels," Working Paper Series 1100, European Central Bank.
  8. Cheng Hsiao & Yan Shen & Hiroshi Fujiki, 2002. "Aggregate vs Disaggregate Data Analysis - A Paradox in the Estimation of Money Demand Function of Japan Under the Low Interest Rate Policy," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 A4-1, International Conferences on Panel Data.
  9. 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.
  10. 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.
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  14. 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.
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  16. 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.
  17. Peter C. B. Phillips & Hyungsik R. Moon, 1999. "Linear Regression Limit Theory for Nonstationary Panel Data," Econometrica, Econometric Society, vol. 67(5), pages 1057-1112, September.
  18. Van Garderen, K. J. & Lee, K. & Pesaran M., 1998. "Cross-sectional Aggregation of Non-linear Models," Cambridge Working Papers in Economics 9803, Faculty of Economics, University of Cambridge.
  19. Trapani, Lorenzo & Urga, Giovanni, 2010. "Micro versus macro cointegration in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 155(1), pages 1-18, March.
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  21. Natalia Bailey & George Kapetanios & M. Hashem Pesaran, 2012. "Exponent of Cross-sectional Dependence: Estimation and Inference," CESifo Working Paper Series 3722, CESifo Group Munich.
  22. 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.
  23. M. Hashem Pesaran & Alexander Chudik, 2010. "Econometric Analysis of High Dimensional VARs Featuring a Dominant Unit," CESifo Working Paper Series 3055, CESifo Group Munich.
  24. Pesaran, M Hashem & Pierse, Richard G & Lee, Kevin C, 1994. "Choice between Disaggregate and Aggregate Specifications Estimated by Instrumental Variables Methods," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(1), pages 11-21, January.
  25. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, 07.
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  28. 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.
  29. Rose, David E., 1977. "Forecasting aggregates of independent Arima processes," Journal of Econometrics, Elsevier, vol. 5(3), pages 323-345, May.
  30. 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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  33. Jan Kmenta & James B. Ramsey, 1980. "Evaluation of Econometric Models," NBER Books, National Bureau of Economic Research, Inc, number kmen80-1, octubre-d.
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Citations

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Cited by:
  1. Bussière, Matthieu & Chudik, Alexander & Sestieri, Giulia, 2009. "Modelling global trade flows: results from a GVAR model," Working Paper Series 1087, European Central Bank.
  2. Alexander Chudik & Hashem Pesaran, 2014. "Theory and Practice of GVAR Modeling," Cambridge Working Papers in Economics 1408, Faculty of Economics, University of Cambridge.
  3. Pesaran, M. Hashem & Smith, Ron P., 2011. "Beyond the DSGE Straitjacket," IZA Discussion Papers 5661, Institute for the Study of Labor (IZA).
  4. Fabio Bacchini & Cristina Brandimarte & Piero Crivelli & Roberta De Santis & Marco Fioramanti & Alessandro Girardi & Roberto Golinelli & Cecilia Jona-Lasinio & Massimo Mancini & Carmine Pappalardo & D, 2013. "Building the core of the Istat system of models for forecasting the Italian economy: MeMo-It," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 15(1), pages 17-45.
  5. Pesaran, M. Hashem & Chudik, Alexander, 2014. "Aggregation in large dynamic panels," Journal of Econometrics, Elsevier, vol. 178(P2), pages 273-285.

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