Econometric analysis of panel data
Provides students with a comprehensive assessment of the latest panel data techniques, especially for serial correlation, heteroskedasticity, simultaneous equations, dynamic models and incomplete panels. Includes extensive coverage of estimation, testing and prediction methods using panel data. The author uses two data sets to illustrate the techniques and cites several empirical studies so that readers can relate econometric methods with economic applications. Packed with exercises which proceed from single equation to simultaneous equation techniques.
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The Oneway Error Component Regression Model
The Twoway Error Component Regression Model
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2SLS 3GLS Amemiya ANOVA apply Arellano and Bond assumed assumption asymptotically distributed bias cohort compute considered consistent estimates covariance matrix cross-section denotes dependent variable derived dummies EC2SLS EC3SLS efficient equation error component model exogenous explanatory variables F-statistic F-test fact feasible GLS estimators fixed effects model Fuller and Battese given Hausman heteroskedastic homoskedastic households individual effects instrumental variable iterative least squares likelihood function LM statistic LM test Maddala measurement error method MINQUE MSE criterion Note null hypothesis observed obtained OLS residuals one-way error component orthogonal panel data panel data model parameters performed period poolability probit model problem random effects model regression coefficients regressors rejected remainder disturbances restrictions sample serial correlation set of instruments sums of squares Survey test statistic time-series transformation two-way error component typical element unbiased values variance components variance-covariance matrix vector verify yields zero