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Aggregation in Large Dynamic Panels

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  • Hashem M. Pesaran
  • Alexander Chudik

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 CESifo Group Munich in its series CESifo Working Paper Series with number 3346.

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Date of creation: 2011
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Handle: RePEc:ces:ceswps:_3346

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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. Stoker, Thomas M, 1984. "Completeness, Distribution Restrictions, and the Form of Aggregate Functions," Econometrica, Econometric Society, Econometric Society, vol. 52(4), pages 887-907, July.
  2. Bailey, Natalia & Kapetanios, George & Pesaran, M. Hashem, 2012. "Exponent of Cross-sectional Dependence: Estimation and Inference," IZA Discussion Papers 6318, Institute for the Study of Labor (IZA).
  3. Alexander Chudik & M. Hashem Pesaran, 2013. "Econometric Analysis of High Dimensional VARs Featuring a Dominant Unit," Econometric Reviews, Taylor & Francis Journals, Taylor & Francis Journals, vol. 32(5-6), pages 592-649, August.
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  6. Alexander Chudik & M. Hashem Pesaran & Elisa Tosetti, 2009. "Weak and Strong Cross Section Dependence and Estimation of Large Panels," CESifo Working Paper Series 2689, CESifo Group Munich.
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  11. Trapani, Lorenzo & Urga, Giovanni, 2010. "Micro versus macro cointegration in heterogeneous panels," Journal of Econometrics, Elsevier, Elsevier, vol. 155(1), pages 1-18, March.
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Citations

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Cited by:
  1. Pesaran, M. H. & Smith, R. P., 2011. "Beyond the DSGE straightjacket," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge 1138, Faculty of Economics, University of Cambridge.
  2. Pesaran, M.H. & Chudik, A., 2011. "Aggregation in Large Dynamic Panels," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge 1118, Faculty of Economics, University of Cambridge.
  3. Alexander Chudik & Hashem Pesaran, 2014. "Theory and Practice of GVAR Modeling," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge 1408, Faculty of Economics, University of Cambridge.
  4. Matthieu Bussière & Alexander Chudik & Giulia Sestieri, 2012. "Modelling global trade flows: results from a GVAR model," Globalization and Monetary Policy Institute Working Paper, Federal Reserve Bank of Dallas 119, Federal Reserve Bank of Dallas.
  5. 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), ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 15(1), pages 17-45.

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