Panel Data Models with Time-varying Latent Group Structures

Panel Data Models with Time-varying Latent Group Structures
Author :
Publisher :
Total Pages : 0
Release :
ISBN-10 : OCLC:1391984501
ISBN-13 :
Rating : 4/5 ( Downloads)

Book Synopsis Panel Data Models with Time-varying Latent Group Structures by : Yiren Wang

Download or read book Panel Data Models with Time-varying Latent Group Structures written by Yiren Wang and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Panel Data Models with Time-varying Latent Group Structures Related Books

Panel Data Models with Time-varying Latent Group Structures
Language: en
Pages: 0
Authors: Yiren Wang
Categories:
Type: BOOK - Published: 2023 - Publisher:

GET EBOOK

Large-dimensional Panel Data Econometrics: Testing, Estimation And Structural Changes
Language: en
Pages: 167
Authors: Feng Qu
Categories: Business & Economics
Type: BOOK - Published: 2020-08-24 - Publisher: World Scientific

GET EBOOK

This book aims to fill the gap between panel data econometrics textbooks, and the latest development on 'big data', especially large-dimensional panel data econ
Panel Data Econometrics
Language: en
Pages: 432
Authors: Mike Tsionas
Categories: Business & Economics
Type: BOOK - Published: 2019-06-19 - Publisher: Academic Press

GET EBOOK

Panel Data Econometrics: Theory introduces econometric modelling. Written by experts from diverse disciplines, the volume uses longitudinal datasets to illumina
Longitudinal and Panel Data
Language: en
Pages: 492
Authors: Edward W. Frees
Categories: Business & Economics
Type: BOOK - Published: 2004-08-16 - Publisher: Cambridge University Press

GET EBOOK

An introduction to foundations and applications for quantitatively oriented graduate social-science students and individual researchers.
Latent Curve Models
Language: en
Pages: 312
Authors: Kenneth A. Bollen
Categories: Mathematics
Type: BOOK - Published: 2005-12-23 - Publisher: John Wiley & Sons

GET EBOOK

An effective technique for data analysis in the social sciences The recent explosion in longitudinal data in the social sciences highlights the need for this ti