Introduction | The linear panel model | Software approach | Data structure | Interface | Estimation interface | Testing interface | Computational approach to estimation | The (quasi--)demeaning framework | The object-oriented approach to general GLS computations | Inference in the panel model | Managing data and formulae | Data transformation | Formulas | Model estimation | Estimation of the basic models with plm | More advanced use of plm | Random effects estimators | Introducing time or two-ways effects | Unbalanced panels | Instrumental variable estimators | Variable coefficients model | Generalized method of moments estimator | General FGLS models | Tests | Tests of poolability | Tests for individual and time effects | Hausman test | Tests of serial correlation | Unobserved effects test | Locally robust tests for serial correlation or random effects | Conditional LM test for AR(1) or MA(1) errors under random effects | General serial correlation tests | Wooldridge's test for serial correlation in "short" FE panels | Wooldridge's first-difference-based test | Tests for cross-sectional dependence | CD and LM-type tests for global cross-sectional dependence | CD(p) test for local cross-sectional dependence | Panel unit root tests | Overview of functions for panel unit root testing | Preliminary results | Levin-Lin-Chu model | Im-Pesaran-Shin (IPS) test | Simes' approach: intersecting hypotheses | Robust covariance matrix estimation | plm versus nlme and lme4 | Fundamental differences between the two approaches | Some false friends | A common taxonomy | The Laird-Ware representation for mixed models | Pooling and Within | Random effects | Variable coefficients, "random" | Variable coefficients, "within" | General FGLS | Some useful "econometric" models in nlme | AR(1) pooling or random effects panel | An LR test for serial correlation and one for random effects | Conclusions | Acknowledgments | Bibliography

Data management | Wide format | Long format | Model description | Testing | Bibliography

Random utility model | The distribution of the error terms | IIA property | Interpretation | Marginal effects | Marginal rates of substitution | Consumer's surplus | Application | ModeCanada | NOx | Predictions and marginal effects | Bibliography

The heteroskedastic logit model | The nested logit model | Applications | ModeCanada | JapaneseFDI | Bibliography

Derivation of the model | The probabilities | Individual parameters | Panel data | Application | Train | $$CC^{\top}=\left(\begin{array}{ccc}c_{11}^2 & c_{11} c_{12} & c_{11}c_{13} \c_{11}c_{12} & c_{12}^2 + c_{22}^2 & c_{12}c_{23}+c_{22}c_{23} \c_{11}c_{13} & c_{12}c_{3} + c_{22}c_{23} & c_{13}^2 + c_{23}^2 c_{33}^2\end{array}\right) | RiskyTransport | Bibliography

Bibliography

The model | $$\mbox{V}\left(\epsilon^l\right)=\mbox{V}\left(M^l\epsilon\right) | M^l\mbox | Identification | Simulations | $$\left(\begin{array}{c}\epsilon^l_1 \ \epsilon^l_2 \ \epsilon^l_3 \ \vdots \ \epsilon^l_J\end{array}\right) | Applications | Bibliography

Paired combinatorial logit model | The rank-ordered logit model | Bibliography

Bibliography

Introduction | Modelling strategy | Model specification | Probability distribution of censored dependent variable | Likelihood function | Model evaluation and selection using goodness of fit measures | Model selection using Vuong tests | Prediction and marginal effects | Software rationale | Estimation | Tests | Bibliography

Basic use of plm | The twoways effect model | Unbalanced panels | Instrumental variable estimators | Nested error component model | Bibliography

The score (or Lagrange multiplier) test | $$\frac{\partial \ln L}{\partial \theta}(\theta) =\left(\begin{array}{c}\frac{\partial \ln L}{\partial \beta}\\frac{\partial \ln L}{\partial \sigma}\\frac{\partial \ln L}{\partial \lambda}\\end{array}\right) | $$\frac{\partial \ln L}{\partial \theta}(\hat{\theta}_i) | $$\frac{\partial \ln L}{\partial \theta}(\hat{\theta}_o) | The conditional moment test | References