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Aggregation in Large Dynamic Panels

Aggregation in large dynamic panels
Authors: Pesaran, M. Hashem; Chudik, Alexander;

Aggregation in Large Dynamic Panels

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.

Country
United Kingdom
Keywords

VAR-Modell, weak and strong cross section dependence, impulse responses, Frankreich, Italien, Large Dynamic Panels, Lebenshaltungsindex, Aggregation, VAR Models, VAR models, Statistical methods; economic indices and measures, Deutschland, Applications of statistics to economics, large dynamic panels, E31, Long Memory, inflation persistence, ddc:330, Hysteresis, aggregation, long memory, Factor analysis and principal components; correspondence analysis, Inflation Persistence, Weak and Strong Cross Section Dependence, Faktorenanalyse, Time series, auto-correlation, regression, etc. in statistics (GARCH), factor models, aggregation, large dynamic panels, long memory, weak and strong cross section dependence, VAR models, impulse responses, factor models, inflation persistence, Inflationsrate, Factor Models, Panel, C43, Theorie, Schätzung, jel: jel:C43, jel: jel:E31

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
39
Top 10%
Top 10%
Top 10%
Green
bronze