The econometrics of multi-dimensional panels: theory and applications

Contributor(s):

Matyas, Laszlo [Editors]

Material type: Text

TextSeries: Advanced Studies in Theoretical and Applied Econometrics; Vol. 54Publication details: Cham Springer 2024Edition: 2ndDescription: xxi, 551 pISBN:

9783031498510

Subject(s):

Econometrics

DDC classification:

330.015195 MAT

Summary: This book presents the econometric foundations and applications of multi-dimensional panels, including modern methods of big data analysis. In light of the big data revolution and the emergence of higher dimensional panel data sets, it provides new results to synthesize existing knowledge on the field. 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. This second extended and revised edition provides an update of all existent chapters to reflect on new developments in the area as well as several new chapters on topics such as machine learning, nonparametric models,networks, and multi-dimensional panels in health economics. The book serves as a standard reference work, a textbook for graduate students in economics, and a source of background material for professionals conducting empirical studies. (https://link.springer.com/book/10.1007/978-3-031-49849-7)

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Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	Public Policy & General Management	330.015195 MAT (Browse shelf(Opens below))	1	Available		008981

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Previous	330.015195 KAC Essential econometric techniques: a guide to concepts and applications	330.015195 KIV Applied statistics and econometrics: basic topics and tools with gretl and R	330.015195 MAD Introduction to econometrics:	330.015195 MAT The econometrics of multi-dimensional panels: theory and applications	330.015195 MIG Principles of econometrics: theory and applications	330.015195 PED Econometrics for dummies	330.015195 POR Introduction to mathematics for economics with R	Next

Table of contents:
Front Matter
Pages i-xxi
Download chapter PDF
Fixed Effects Models
László Balázsi, László Mátyás, Tom Wansbeek
Pages 1-37
When and How Much Do Fixed Effects Matter?
Felix Chan, László Mátyás, Ágoston Reguly
Pages 39-60
Random Effects Models
László Balázsi, Badi H. Baltagi, László Mátyás, Daria Pus
Pages 61-98
Estimation of Sparse Variance-Covariance Matrix
Felix Chan, Ramzi Chariag
Pages 99-131
Models with Endogenous Regressors
László Balázsi, Maurice J. G. Bun, Felix Chan, Mark N. Harris
Pages 133-169
Dynamic Models and Reciprocity
Maurice J. G. Bun, Felix Chan, Mark N. Harris, Wei Ern (Ben) Yeo
Pages 171-195
Random Coefficients Models
Monika Avila Marquez, Jaya Krishnakumar, László Balázsi
Pages 197-237
Nonparametric Models with Random Effects
Yiguo Sun, Wei Lin, Qi Li
Pages 239-284
Nonparametric Models with Fixed Effects
Daniel J. Henderson, Alexandra Soberon
Pages 285-323
Multi-dimensional Panels in Quantile Regression Models
Antonio F. Galvao, Gabriel V. Montes-Rojas
Pages 325-351
Multi-Dimensional Models for Spatial Panels
Julie Le Gallo, Alain Pirotte
Pages 353-379
The Econometrics of Gravity Models in International Trade
Badi H. Baltagi, Peter H. Egger, Katharina Erhardt
Pages 381-412
Modelling Housing Using Multi-dimensional Panel Data
Badi H. Baltagi, Georges Bresson
Pages 413-453
Modelling Migration
Raul Ramos
Pages 455-478
Multi-dimensional Panels in Health Economics with an Application on Antibiotic Consumption
Anikó Bíró, Péter Elek, Nóra Kungl
Pages 479-509
Can Machine Learning Beat Gravity in Flow Prediction?
György Ruzicska, Ramzi Chariag, Olivér Kiss, Miklós Koren
Pages 511-545
Back Matter
Pages 547-551

[https://link.springer.com/book/10.1007/978-3-031-49849-7]

This book presents the econometric foundations and applications of multi-dimensional panels, including modern methods of big data analysis. In light of the big data revolution and the emergence of higher dimensional panel data sets, it provides new results to synthesize existing knowledge on the field. 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.

This second extended and revised edition provides an update of all existent chapters to reflect on new developments in the area as well as several new chapters on topics such as machine learning, nonparametric models,networks, and multi-dimensional panels in health economics. The book serves as a standard reference work, a textbook for graduate students in economics, and a source of background material for professionals conducting empirical studies.

(https://link.springer.com/book/10.1007/978-3-031-49849-7)

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