Format:
1 Online-Ressource (403 Seiten)
Edition:
First edition 2017
ISBN:
9781785609855
Series Statement:
Advances in Econometrics volume 37
Content:
Advances in Econometrics 37 highlights key research in econometrics in a user friendly way for economists who are not econometricians
Content:
Front Cover -- Spatial Econometrics: Qualitative and Limited Dependent Variables -- Copyright Page -- Contents -- List of Contributors -- Part I: Introduction -- Progress in Spatial Modeling of Discrete and Continuous Dependent Variables -- Part II: Discrete Dependent Variables - Maximum Likelihood -- Fast Simulated Maximum Likelihood Estimation of the Spatial Probit Model Capable of Handling Large Samples -- 1. Introduction -- 2. Spatial Probit Models -- 3. GHK Mechanics -- 3.1. GHK Applied to the Variance-Covariance Matrix -- 3.2. Sparsity and the GHK
Content:
3.3. GHK Applied to the Precision Matrix -- 4. GHK Performance -- 5. Empirical Examples -- 5.1. A Development Application -- 5.2. A Mortgage Application -- 6. Implementation Issues and Opportunities -- 6.1. Implementation -- 6.2. Opportunities -- 6.3. Evaluation of Likelihood -- 7. Conclusion -- Notes -- Acknowledgments -- References -- Likelihood Evaluation of High-Dimensional Spatial Latent Gaussian Models with Non-Gaussian Response Variables -- 1. Introduction -- 2. Spatial-dependent Variable Models -- 2.1. Baseline Model -- 2.2. Spatial Probit Models -- 2.3. Spatial Count Data Models
Content:
2.4. Censored Data -- 3. Spatial EIS -- 3.1. EIS Principle -- 3.2. Sequential EIS -- 3.3. Sequential EIS for Spatial Models -- 3.3.1. The Integrating Factors χi(u(i+1) -- ai) -- 3.3.2. Kernel Representation of f(ui&smid -- u(i+1)) -- 3.3.3. Construction of the EIS Kernel ki(u(i) -- ai) -- 3.3.4. Spatial EIS Implementation -- 3.3.5. Pseudo-Code -- 3.3.6. Sparse EIS Operations -- 3.4. Spatial Probit Model -- 3.5. Spatial Poisson Model -- 3.6. Censored Data -- 4. Monte Carlo Study -- 4.1. Spatial Probit Models -- 4.2. Spatial Poisson Models -- 5. Empirical Applications
Content:
5.1. Spatial Probit for the 1996 US Presidential Election -- 5.2. Spatial Count Model for US Firms Location Choices -- 6. Conclusions -- Notes -- Acknowledgments -- References -- Part III: Discrete Dependent Variables - Bayesian -- The Impact of Storms on Firm Survival: A Bayesian Spatial Econometric Model for Firm Survival -- 1. Introduction -- 2. Data -- 3. Spatial Probit Model Specification -- 4. Bayesian Inference in the Spatial Probit Model Specification -- 5. Results -- 6. Conclusion -- Notes -- Acknowledgments -- References -- Appendix -- Bayesian Spatial Bivariate Panel Probit Estimation
Content:
1. Introduction -- 2. Econometric Model -- 3. Model Estimation -- 3.1. Bayesian Estimation Procedure -- 3.1.1. Likelihood -- 3.1.2. Priors -- 3.2. Conditional Distributions -- 3.2.1. Conditional Distribution of y1* and y2* -- 3.2.2. Conditional Distribution of β -- 3.2.3. Conditional Distribution of λ1 and λ2 -- 3.2.4. Conditional Distribution of τ -- 3.2.5. Conditional Distribution of α -- 3.2.6. Interpretation of Results -- 4. Extensions -- 4.1. A Richer Structural Latent-Variable Framework -- 4.1.1. Model -- 4.1.2. Joint Distribution of (y1*,y2*) and the Likelihood -- 4.1.3. Priors
Content:
4.1.4. Conditional Distribution of y1* and y2*
Note:
Description based upon print version of record
Additional Edition:
ISBN 9781785609862
Additional Edition:
Erscheint auch als Druck-Ausgabe Spatial econometrics: qualitative and limited dependent variables Bingley : Emerald, 2017 ISBN 9781785609862
Language:
English
Keywords:
Electronic books
URL:
Volltext
(lizenzpflichtig)
Author information:
Baltagi, Badi H. 1954-
