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Large Panels with Common Factors and Spatial Correlations

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Author Info
Pesaran, M.H.
Tosetti, E.

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Abstract

This paper considers the statistical analysis of large panel data sets where even after conditioning on common observed e¤ects the cross section units might remain dependently distributed. This could arise when the cross section units are subject to unobserved common e¤ects and/or if there are spill over e¤ects due to spatial or other forms of local dependencies. The paper provides an overview of the literature on cross section dependence, introduces the concepts of time-speci.c weak and strong cross section dependence and shows that the commonly used spatial models are examples of weak cross section dependence. It is then established that the Common Correlated Effects (CCE) estimator of panel data model with a multifactor error structure, recently advanced by Pesaran (2006), continues to provide consistent estimates of the slope coefficient, even in the presence of spatial error processes. Small sample properties of the CCE estimator under various patterns of cross section dependence, including spatial forms, are investigated by Monte Carlo experiments. Results show that the CCE approach works well in the presence of weak and/or strong cross sectionally correlated errors. We also explore the role of certain characteristics of spatial processes in determining the performance of CCE estimators, such as the form and intensity of spatial dependence, and the sparseness of the spatial weight matrix.

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Paper provided by Faculty of Economics, University of Cambridge in its series Cambridge Working Papers in Economics with number 0743.

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Length: 24
Date of creation: Aug 2007
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Handle: RePEc:cam:camdae:0743

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Related research
Keywords: Panels; Common Correlated Effects; Strong and Weak Cross Section Dependence.;

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Find related papers by JEL classification:
C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - General
C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data

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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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  10. Moon, H.R.Hyungsik Roger & Perron, Benoit, 2004. "Testing for a unit root in panels with dynamic factors," Journal of Econometrics, Elsevier, vol. 122(1), pages 81-126, September. [Downloadable!] (restricted)
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  11. Coakley, Jerry & Fuertes, Ana-Maria & Smith, Ron, 2006. "Unobserved heterogeneity in panel time series models," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2361-2380, May. [Downloadable!] (restricted)
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  12. Anselin, Luc, 2002. "Under the hood : Issues in the specification and interpretation of spatial regression models," Agricultural Economics, Blackwell, vol. 27(3), pages 247-267, November. [Downloadable!] (restricted)
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Alexander Chudik & M. Hashem Pesaran, 2009. "Infinite-dimensional VARs and factor models," Working Paper Series 998, European Central Bank. [Downloadable!]
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  2. Mario Cerrato & Christian de Peretti & Rolf Larsson & Nick Sarantis, 2009. "A Nonlinear Panel Unit Root Test under Cross Section Dependence," Working Papers 2009_28, Department of Economics, University of Glasgow. [Downloadable!]
    Other versions:
  3. Pesaran, M.H. & Zaffaroni, P., 2008. "Optimal Asset Allocation with Factor Models for Large Portfolios," Cambridge Working Papers in Economics 0813, Faculty of Economics, University of Cambridge. [Downloadable!]
    Other versions:
  4. Holly, S. & Petrella, I., 2008. "Factor demand linkages and the business cycle: Interpreting aggregate fluctuations as sectoral fluctuations," Cambridge Working Papers in Economics 0827, Faculty of Economics, University of Cambridge. [Downloadable!]
    Other versions:
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