جهت دسترسی به کاربرگه ی زیر، از این لینک استفاده کنید. http://dl.pgu.ac.ir/handle/Hannan/185590
Title: The econometrics of multi-dimensional panels :;Theory and Applications /;
Authors: M??ty??s, L??szl?, ; editor ;
Keywords: Big data ;;Data mining ;;Game theory ;;Statistics ;;Econometrics ;;330 ;;HB141 ;
Issue Date: 2017
Publisher: Springer,
place: Cham, SWITZERLAND :
Series/Report no.: 
Abstract: This book presents the econometric foundations and applications of multi-dimensional panels, including modern methods of big data analysis. The last two decades or so, the use of panel data has become a standard in many areas of economic analysis. The available models formulations became more complex, the estimation and hypothesis testing methods more sophisticated. The interaction between economics and econometrics resulted in a huge publication output, deepening and widening immensely our knowledge and understanding in both. The traditional panel data, by nature, are two-dimensional. Lately, however, as part of the big data revolution, there has been a rapid emergence of three, four and even higher dimensional panel data sets. These have started to be used to study the flow of goods, capital, and services, but also some other economic phenomena that can be better understood in higher dimensions. Oddly, applications rushed ahead of theory in this field. This book is aimed at filling this widening gap. The first theoretical part of the volume is providing the econometric foundations to deal with these new high-dimensional panel data sets. It not only synthesizes our current knowledge, but mostly, presents new research results. The second empirical part of the book provides insight into the most relevant applications in this area. These chapters are a mixture of surveys and new results, always focusing on the econometric problems and feasible solutions.-- ; Provided by publisher ;
Description: Available to OhioLINK libraries ;;Original ; 9783319607825 ; 3319607820 ; (OCoLC)987282763 ;
Table Of Contents: Foreword; Preface; Acknowledgments; Contents; List of Contributors; Chapter 1 Fixed Effects Models; 1.1 Introduction; 1.2 Models with Different Types of Heterogeneity; 1.3 Least Squares Estimation of the Models; 1.4 Incomplete Panels; 1.5 The Within Estimator; 1.5.1 The Equivalence of the LSDV and the Within Estimator; 1.5.2 Incomplete Panels and the Within Estimator; 1.5.2.1 No Self-flow Data; 1.5.2.2 General Incompleteness; 1.6 Heteroscedasticity and Cross-correlation; 1.6.1 The New Covariance Matrices and the GLS Estimator ;
1.6.2 Estimation of the Variance Components and the Cross Correlations1.7 Extensions to Higher Dimensions; 1.7.1 Different Forms of Heterogeneity; 1.7.2 Least Squares and the Within Estimators; 1.7.3 Incomplete Panels; 1.8 Varying Coefficients Models; References; Chapter 2 Random Effects Models; 2.1 Introduction; 2.2 Different Model Specifications; 2.2.1 Various Heterogeneity Formulations; 2.2.2 Spectral Decomposition of the Covariance Matrices; 2.3 FGLS Estimation; 2.4 Unbalanced Data; 2.4.1 Structure of the Covariance Matrices; 2.4.2 The Inverse of the Covariance Matrices ;
2.4.3 Estimation of the Variance Components2.5 Extensions; 2.5.1 4D and Beyond; 2.5.2 Mixed FE-RE Models; 2.6 Testing; 2.7 Conclusion; References; Appendix 1; Example for normalizing with 1: Model (2.14), T ????; Example for normalizing with ??N1N2/A: Model (2.2), N1,N2 ????; Appendix 2: Proof of formula (2.19); Appendix 3: Inverse of (2.34), and the estimation of the variance components; Chapter 3 Models with Endogenous Regressors; 3.1 Introduction; 3.2 The Hausman-Taylor-like Instrument Variable Estimator; 3.2.1 A Simple Approach; 3.2.2 Sources of Endogeneity; 3.2.3 The Hausman-Taylor Estimator ;
3.2.3.1 Extending the Hausman-Taylor Two-Stage Least Squares Estimator3.2.3.2 The More Efficient Hausman-Taylor Estimator; 3.2.4 Time Varying Individual Specific Effects; 3.2.5 Properties; 3.2.6 Using External Instruments; 3.3 The Non-linear Generalized Method of Moments Estimator; 3.4 Mixed Effects Models; 3.5 Exogeneity Tests; 3.5.1 Testing for Endogeneity; 3.5.2 Testing for Instrument Validity; 3.5.3 Testing in the Case of Fixed Effects; 3.5.3.1 Improper Model Specifications; 3.5.3.2 Conventional Endogeneity; 3.6 Further Considerations; 3.6.1 Incomplete Data ;
3.6.2 Notes on Higher-dimensional PanelsReferences; Appendix: Proofs; Proof of Proposition 1; Proof of Corollary 1; Chapter 4 Dynamic Models and Reciprocity; 4.1 Introduction; 4.2 Dynamics; 4.2.1 Estimation; 4.2.2 Monte Carlo Experiments; 4.3 Reciprocity; 4.3.1 Within Estimator; 4.3.2 GMM Estimation; 4.3.3 No Self-flow; 4.4 Combining Dynamics and Reciprocity; 4.4.1 Monte Carlo Experiments; 4.5 Extensions; 4.5.1 Generalized Reciprocity; 4.5.2 Higher Dimensions; References; Appendix; Proof of Proposition 1; Proof of Proposition 2; Chapter 5 Random Coefficients Models; 5.1 Introduction ;
URI: http://dl.pgu.ac.ir/handle/Hannan/185590
ISBN: 9783319607832 ;
3319607839 ;
Format: 1 online resource ;
Edition: 
Type Of Material: Latin Book
Appears in Collections:Economy

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