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Lois W. Sayrs - Pooled time series analysis

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Researchers have often been troubled with relevant data available from both temporal observations at regular intervals (time series) and from observations at single points of time (cross-sections). Pooled Time Series Analysis combines time series and cross-sectional data to provide the researcher with an efficient method of analysis and improved estimates of the population being studied. In addition, with more relevant data available this analysis technique allows the sample size to be increased, which ultimately yields a more effective study.

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title Pooled Time Series Analysis Sage University Papers Series - photo 1

title:Pooled Time Series Analysis Sage University Papers Series. Quantitative Applications in the Social Sciences ; No. 07-070
author:Sayrs, Lois W.
publisher:Sage Publications, Inc.
isbn10 | asin:0803931603
print isbn13:9780803931602
ebook isbn13:9780585217062
language:English
subjectTime-series analysis.
publication date:1989
lcc:QA280.S29 1989eb
ddc:519.5/5
subject:Time-series analysis.
Page a
Pooled Time Series Analysis
Page b
SAGE UNIVERSITY PAPERS
Series: Quantitative Applications in the Social Sciences
Series Editor: Michael S. Lewis-Beck, University of Iowa
Editorial Consultants
Richard A. Berk, Sociology, University of California, Los Angeles
William D. Berry, Political Science, Florida State University
Kenneth A. Bollen, Sociology, University of North Carolina, Chapel Hill
Linda B. Bourque, Public Health, University of California, Los Angeles
Jacques A. Hagenaars, Social Sciences, Tilburg University
Sally Jackson, Communications, University of Arizona
Richard M. Jaeger, Education, University of North Carolina, Greensboro
Gary King, Department of Government, Harvard University
Roger E. Kirk, Psychology, Baylor University
Helena Chmura Kraemer, Psychiatry and Behavioral Sciences, Stanford
University
Peter Marsden, Sociology, Harvard University
Helmut Norpoth, Political Science, SUNY, Stony Brook
Frank L. Schmidt, Management and Organization, University of Iowa
Herbert Weisberg, Political Science, The Ohio State University
Publisher
Sara Miller McCune, Sage Publications, Inc.
INSTRUCTIONS TO POTENTIAL CONTRIBUTORS
For guidelines on submission of a monograph proposal to this series, please write
Michael S. Lewis-Beck, Editor
Sage QASS Series
Department of Political Science
University of Iowa
Iowa City, IA 52242
Page 1
Series/Number 07-070
Pooled Time Series Analysis
Lois W. Sayrs
University of Iowa
Picture 2
SAGE PUBLICATIONS
The International Professional Publishers
Newbury Park London New Delhi
Page 2
Copyright 1989 by Sage Publications, Inc.
Printed in the United States of America
All rights reserved. No part of this book may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, or by any information storage and retrieval system, without permission in writing from the publisher.
For information address:
Picture 3
SAGE Publications, Inc.
2455 Teller Road
Newbury Park, California 91320
E-mail: order@sagepub.com
SAGE Publications Ltd.
6 Bonhill Street
London EC2A 4PU
United Kingdom
SAGE Publications India Pvt. Ltd.
M-32 Market
Greater Kailash I
New Delhi 110 048 India
International Standard Book Number 0-8039-3160-3
Library of Congress Catalog Card No. L.C. 89-061129
99 00 01 02 12 11 10 09 08
When citing a professional paper, please use the proper form. Remember to cite the correct Sage University Paper series title and include the paper number. One of the two following formats can be adapted (depending on the style manual used):
(1) IVEERSEN, GUDMUND R. and NORPOTH, HELMUT (1976) "Analysis of Variance." Sage University Paper series on Quantitative Applications in the Social Sciences, 07-001. Beverly Hills and London: Sage Publications.
OR
(2) Iversen, Gudmund R. and Norpoth, Helmut. 1976. Analysis of Variance. Sage University Paper series on Quantitative Applications in the Social Sciences, series no. 07-001. Beverly Hills and London: Sage Publications.
Page 3
Contents
Series Editor's Introduction
5
1. Introduction
7
2. Theoretical Derivation of the Pooled Time Series Model
8
Picture 4
Pooling in Application
8
Picture 5
The Pooled Linear Regression Model
10
Picture 6
Four Models of Pooling
14
Picture 7
Preliminary Diagnostics and Residual Analysis
16
3. The Constant Coefficients Model
19
Picture 8
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