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Large Panels with Common Factors and Spatial Correlations

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  • M. Hashem Pesaran
  • Elisa Tosetti

Abstract

This paper considers the statistical analysis of large panel data sets where even after condi-tioning on common observed effects the cross section units might remain dependently distrib-uted. This could arise when the cross section units are subject to unobserved common effects and/or if there are spill over effects due to spatial or other forms of local dependencies. The paper provides an overview of the literature on cross section dependence, introduces the con-cepts of time-specific 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.

Suggested Citation

  • M. Hashem Pesaran & Elisa Tosetti, 2007. "Large Panels with Common Factors and Spatial Correlations," CESifo Working Paper Series 2103, CESifo.
  • Handle: RePEc:ces:ceswps:_2103
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    More about this item

    Keywords

    panels; Common Correlated Effects; strong and weak cross section dependence;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • D13 - Microeconomics - - Household Behavior - - - Household Production and Intrahouse Allocation
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation
    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development

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