[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-45709-en":3,"doc-seo-45709-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":13,"seo_description":14,"update_tm":28,"read_time":29},45709,4398048950312,"Violet","https://ap-avatar.wpscdn.com/avatar/400002538284de19e3c?_k=1778320343897328908",8,"Research & Report","Econometrics of Panel Data Methods and Applications","Econometrics of Panel Data: Methods and Applications presents panel data analysis for economics and the social sciences, emphasizing how temporal–spatial variation motivates matrix-based techniques while keeping matrix algebra from becoming a barrier. The text grows from lecture notes developed over years and targets beginners through advanced readers with chapters that progress from foundational topics to intermediate and modern methods. Special attention is given to identification, two-way random effects, random coefficients, measurement errors, unbalanced panels, and links to aggregation and micro-econometrics.","Econometrics of Panel Data  \nEconometrics of Panel Data  \nMethods and Applications  \nErik Biørn  \n1  \n3  \nGreat Clarendon Street, Oxford, ox2 6dp, United Kingdom  \nOxford University Press is a department of the University of Oxford. It furthers the University’s objective of excellence in research, scholarship, and education by publishing worldwide. Oxford is a registered trade mark of Oxford University Press in the UK and in certain other countries  \n© Erik Biørn 2017  \nThe findings, interpretations, and conclusions expressed in this work are entirely those of the authors and should not be attributed in any manner to the World Bank, its Board of Executive Directors, or the governments they represent.  \nThe moral rights of the author have been asserted First Edition published in 2017  \nImpression: 1  \nAll rights reserved. No part of this publication may be reproduced, stored ina retrieval system, or transmitted, in any form or by any means, without the prior permission in writing of Oxford University Press, or as expressly permitted by law, by licence, or under terms agreed with the appropriate reprographics rights organization. Enquiries concerning reproduction outside the scope of the above should be sent to the Rights Department, Oxford University Press, at the address above  \nYou must not circulate this work in any other form  \nand you must impose this same condition on any acquirer  \nPublished in the United States of America by Oxford University Press  \n198 Madison Avenue, New York, NY 10016, United States of America  \nBritish Library Cataloguing in Publication Data Data available  \nLibrary of Congress Control Number: 2016937737 ISBN 978–0–19–875344–5  \nPrinted in Great Britain by Clays Ltd, St Ives plc  \nLinks to third party websites are provided by Oxford in good faith and for information only. Oxford disclaims any responsibility for the materials contained in any third party website referenced in this work.  \n PREFACE  \nPanel data is a data type used with increasing frequency in empirical research in economics, social sciences, and medicine. Panel data analysis is a core field in modern econometrics and multivariate statistics, and studies based on such data occupy a growing part of the field in all the mentioned disciplines. A substantial literature on methods and applications has accumulated, also synthesized in survey articles and a number of textbooks. Why then write another book on panel data analysis? I hope that some of my motivation and part of the answer will be given in the following paragraphs.  \nThe text collected in this book has originated, and been expanded through several years, partly in parallel with courses I have given at the University of Oslo for master’s and doctoral students of economics. I have been interested in the field, both its models and methods and applications to social sciences, for more than forty years. The first drafts were lecture notes, later expanded and synthesized into course compendia, first in Norwegian, later in English. In compiling the text, I have had no ambition of giving an account of the history of panel data analysis and its various subfields, some of which have a longer history than others. Within some 350 pages it is impossible to give a complete coverage, and the choice of topics, and the depth of discussion of each of them, to some extent reflect my preferences. Some readers may miss topics like cross-section-time-series analysis in continuous time, duration analysis, and analysis of non-linear panel data models (outside the limited dependent variables field). Topics I give specific attention to, more than many comparable texts, I think, are coefficient identification of models mixing two-dimensional and individual-specific variables, regression models with two-way random effects, models and methods for handling random coefficients and measurement errors, unbalanced panel data, and panel data in relation to aggregation. Problems at the interface between unbalance a","cbCairrkZSpf1BPl","https://ap.wps.com/l/cbCairrkZSpf1BPl","pdf",3368145,2,1,417,"English","en",105,"# Preface\n## Purpose and scope of the book\n## Topic selection and coverage limits\n## Pedagogical approach and notation\n## Chapter-level structure and prerequisites","[{\"question\":\"What is the main purpose of Econometrics of Panel Data in the preface?\",\"answer\":\"To motivate and organize methods for panel data analysis across economics and other social fields, offering a structured progression from basic ideas to more advanced topics.\"},{\"question\":\"Which topics does the author note are not fully covered?\",\"answer\":\"The author points out gaps such as continuous-time cross-section-time-series analysis, duration analysis, and nonlinear panel data models beyond the limited dependent variables area.\"},{\"question\":\"How does the book help readers who struggle with matrix algebra?\",\"answer\":\"Most chapters begin with simple scalar or elementary vector examples and then gradually move to fuller matrix notation, including some repetition to reduce obstacles for first-time panel data 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