Random Coefficient Panel Data Models

By Cheng Hsiao, M. Pesaran. Social Science Research Network, 2004

133 citations recorded by the source corpus.

This paper provides a review of linear panel data models with slope heterogeneity, introduces various types of random coefficients models and suggest a common framework for dealing with them. It considers the fundamental issues of statistical inference of a random coefficients formulation using both the sampling and Bayesian approaches. The paper also provides a review of heterogeneous dynamic panels, testing for homogeneity under weak exogeneity, simultaneous equation random coefficient models, and the more recent developments in the area of cross-sectional dependence in panel data models.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/25c7d4999ac37ea2710eea85dc816cb2428298c1

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Citations in the corpus

Testing Slope Homogeneity in Large Panels (2005, unknown): “See Pesaran, Smith and Im (1996) and Hsiao and Pesaran (2004) .”
Identifying distributional characteristics in random coefficients panel data models (2009, background): “(46) Then matrix Ωi is identified from the within-group covariance restrictions (36) alone.”
The Impact of Foreign Interest Rates on the Economy: The Role of the Exchange Rate Regime (2006, background): “Recent tests developed by Pesaran (2004)”
Unobserved heterogeneity in panel time series models (2006, background): “Such random coe¢ cient models (RCM) are discussed by Hsiao (2003) and Hsiao and Pesaran (2004).”
Spatial Panel Econometrics (2008, unknown): “…the data are sufficiently rich (and, typically, in large T contexts), the correlation is determined by the model residuals (for further details, see Driscoll and Kraay, 1998, Coakley et al., 2002, Coakley et al., 2005, Hsiao and Pesaran, 2004, Pesaran, 2005 and Kapetanios and Pesaran, 2005).”
Do all countries follow the same growth process? (2009, background): “Hsiao and Pesaran (2004) discuss the problem in the context of randomcoefficient panel data models but they do not examine finite-mixture models.”
The Feldstein-Horioka Puzzle: a Panel SmoothTransition Regression Approach (2007, unknown): “For instance, it is possible to consider a heterogeneous panel model by assuming that the FH parameters βit are randomly distributed (for a presentation of random coefficients models, see Hsiao and Pesaran, 2004).”
Evolution of Forecast Disagreement in a Bayesian Learning Model (2008, background): “However, as pointed out by Hsiao and Pesaran (2008), this general formulation is not estimable, since the number of parameters to be estimated exceeds the number of observations.”
Using mixtures in econometric models: a brief review and some new results (2016, background): “This rules out discrete regressors and regressors with bounded support, although Gautier and Kitamura (2013) also discuss a possible extension to limited-support covariates.”