Format:
1 online resource (350 pages)
Edition:
1st ed.
ISBN:
9780521631693
,
9780511155888
Content:
This important collection brings together leading econometricians to discuss advances in the areas of the econometrics of panel data, limited dependent variable models and limited dependent variable models with panel data. The collection is in honour of G. S. Maddala, whose contributions in this area were particularly influential
Note:
Cover -- Half-title -- Title -- Copyright -- Contents -- Contributors -- Foreword -- Introduction -- References -- 1 A note on left censoring -- 1 Introduction -- 2 A single state model -- 3 Why divide by P -- 4 A simple example -- Ignoring selectivity -- Maximizing conditional LF -- Maximizing full LF -- 5 Observe only spells continuing at 0 -- 6 Method which does not require starting-time distribution -- 7 Semiparametric estimation of h(x) and Theta -- 8 Separate estimation of h(x) -- 9 Two-states model -- Observe both states -- Observe one state -- Method which does not require starting-time distribution -- References -- 2 Autoregressive models with sample selectivity for panel data -- 1 Introduction -- 2 The model -- 3 Estimation and hypothesis testing -- 3.1 Estimating the reduced form -- 3.2 Asymptotic least squares estimation -- 3.3 Estimates based on orthogonal deviations -- 3.4 Testing the overidentifying restrictions -- 3.5 Consistent OLS estimation using predicted differences -- 4 An application to female labor supply and wages -- 5 Concluding remarks -- Appendix A Descriptive statistics and additional parameter estimates -- Appendix B Type I Tobit with symmetric trimming -- Appendix C Models with exogenous variables -- References -- 3 Mixture of normals probit models -- 1 Introduction -- 2 Bayesian inference for probit models -- 2.1 Conventional probit model -- 2.2 Mixture of normals probit model -- 2.3 A posterior simulator -- 2.4 Comparison of models -- 3 Some results with artificial data -- 4 An example: labor force participation of women -- 5 Conclusion -- References -- 4 Estimation of dynamic limited-dependent rational expectations models -- 1 Introduction -- 2 Serial correlation and dynamics in LDV models under RE -- 2.1 One-limit and two-limit LDRE models -- 2.2 Likelihood functions
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2.3 Serial correlation and inconsistent estimation -- 3 RE solution and simulation -- 4 Likelihood simulation and recursion -- 5 Renewal and variance reduction -- 6 Monte Carlo experiments and results -- 7 Conclusions -- Appendix: Existence and uniqueness of SRE solution -- References -- 5 A Monte Carlo study of EC estimation in panel data models with limited dependent variables and heterogeneity -- 1 Introduction -- 2 The EC-EM and large T approximation setup -- 3 The Monte Carlo probits experimental design -- 4 Monte Carlo results -- 4.1 Design I: Unpoolable slopes -- 4.1 Design II: Poolable slopes -- 5 Concluding remarks -- References -- 6 Properties of alternative estimators of dynamic panel models: an empirical analysis of cross-country data for the study... -- 1 Introduction -- 2 Recent empirical investigations of convergence and the rate of convergence -- 3 Alternative methods for estimation -- 3.1 Inconsistency of the pooled-sample OLS estimates of the dynamic error components model -- 3.2 Inconsistency of the OLS estimators of the dummy variable, or fixed-effects, model -- 3.3 Generalized least squares and feasible GLS -- 3.4 Bounds for the coefficient of the lagged dependent variable -- 3.5 Maximum likelihood conditional on the initial value of the lagged dependent variable -- 3.6 Unconditional likelihood and unconditional maximum likelihood -- 4 Empirical evidence on the comparative performance of different panel data methods -- 5 Conclusions -- References -- 7 Modified generalized instrumental variables estimation of panel data models with strictly exogenous instrumental variables -- 1 Introduction -- 2 Setup -- 2.1 The model and instrumental variables estimation -- 2.2 Redundancy in instrumental variables -- 3 Properties of MGIV -- 3.1 MGIV and GIV -- 3.2 Redundancy results -- 4 Application to models with time-invariant effects
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3.2 Bias corrections applied directly to the estimator of the long-run coefficients -- 3.3 Bootstrap bias-corrected estimator -- 4 Small sample performance of bias-reduction methods -- 4.1 Monte Carlo results for a single time series regression -- 4.2 Monte Carlo results for panels -- 5 Concluding remarks -- References -- Curriculum vitae of G.S. Maddala -- Current position -- Educational background -- Previous appointments -- Other research appointments -- Scholarly honors and awards -- National Science Foundation research grants -- Offices in professional associations -- Publications -- Production functions and productivity -- Distributed lag models -- Panel data -- Simultaneous equations models -- Qualitative variables models -- Limited dependent variable models -- Self-selection models -- Disequilibrium models -- Time series models -- Bootstrap models -- Errors in variables -- Income distribution -- Pseudo data -- Survey data -- Others -- Books -- Edited journal volumes -- Books forthcoming -- Other -- Doctoral dissertations -- Index
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4.1 Fixed-effects models -- 4.2 Random-effects models -- 4.3 Hausman and Taylor-type models -- 5 Application to models with time-varying effects -- 6 Monte Carlo experiments -- 7 Conclusions -- Appendix -- References -- 8 Expectations of expansions for estimators in a dynamic panel data model: some results for weakly exogenous regressors -- 1 Introduction -- 2 The stochastic structure of the model -- 3 The bias of the LSDV estimator -- 4 The location of particular IV estimators -- 5 Conclusions -- Appendix -- References -- 9 Re-examining the rational expectations hypothesis using panel data on multi-period forecasts -- 1 Introduction -- 2 The econometric framework -- 3 Forecast errors and their covariances -- 4 Data and estimates of the error components -- 5 Preliminary versus revised data -- 6 GMM tests for bias -- 7 Martingale test for efficiency -- 8 Conclusion -- References -- 10 Prediction from the regression model with one-way error components -- 1 Introduction -- 2 Asymptotic mean squared error (AMSE) of prediction -- 2.1 The ordinary predictor with estimated parameters -- 2.2 The truncated predictor -- 2.3 The misspecified OLS predictor -- 2.4 The fixed effects predictor -- 3 Monte Carlo results -- 4 Conclusion -- References -- 11 Bayes estimation of short-run coefficients in dynamic panel data models -- 1 Introduction -- 2 Model -- 3 Classical approach -- 4 Bayesian approach -- 5 Asymptotics -- 6 The design of the Monte Carlo study -- 7 Monte Carlo results -- 8 An empirical application: the q investment model re-examined -- 9 Conclusion -- References -- 12 Bias reduction in estimating long-run relationships from dynamic heterogeneous panels -- 1 Introduction -- 2 Dynamic models of heterogeneous panels -- 3 Bias-reduction techniques for estimation of the long-run coefficients -- 3.1 The "naive" bias-corrected estimator (NBC)
Additional Edition:
Print version Hsiao, Cheng Analysis of Panels and Limited Dependent Variable Models Cambridge : Cambridge University Press,c1999 ISBN 9780521631693
Language:
English
Keywords:
Electronic books
URL:
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