Analysis of Panel Data

From the contents:
1. Introduction: 1.1 Advantages of panel data; 1.2 Issues involved in utilizing panel data; 1.3 Outline of the monograph; 2. Analysis of covariance: 2.1 Introduction; 2.2 Analysis of covariance; 2.3 An example; 3. Simple regression with variable intercepts: 3.1 Introduction; 3.2 Fixed-effects models: least-squares dummy-variable approach; 3.3 Random-effects models: estimation of variance-components models; 3.4 Fixed effects or random effects; 3.5 Tests for misspecification; 3.6 Models with specific variables and both individual- and time-specific effects; 3.7 Heteroscedasticity; 3.8 Models with serially correlated errors; 3.9 Models with arbitrary error structure "Chamberlain"-approach; 4. Dynamic mode ls with variable intercepts: 4.1 Introduction; 4.2 The covariance estimator; 4.3 Random-effects models; 4.4 An example - demand for natural gas; 4.5 Fixed effects models; 4.6 Estimation of dynamic models with arbitrary correlations in the residuals; 4.7 Fixed effects vector autoregressive models; 5. Simultaneous-equations models: 5.1 Introduction; 5.2 Joint generalized-least squares estimation technique; 5.3 Estimation of structural equations; 5.4 Triangular system; 6. Variable-coefficient models: 6.1 Introduction; 6.2 Coefficients that vary over cross-sectional units; 6.3 Coefficients that vary over time and cross-sectional units; 6.4 Coefficients that evolve over time; 6.5 Coefficients that are functions of other exogenous variables; 6.6 A mixed fixed and random coefficients model; 6.7 Dynamic random coefficients models; 6.8 An example - liquidity constraints and firm investment expenditure; 7. Discrete data: 7.1 Introduction; 7.2 Some discrete-response models; 7.3 The parametric approach to static models with heterogeneity; 7.4 The semiparametric
approach to static models; 7.5 Dynamic models; 8. Truncated and censored data: 8.1 Introduction; 8.2 Nonrandomly missing data; 8.3 Tobit models with random individual effects; 8.4 Fixed effects