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Author Gao, Ya, active 2019, author

Title Introduction to panel data, multiple regression method, and principal components analysis using Stata : study on the determinants of executive compensation : a behavioral approach using evidence from Chinese listed firms / Ya Gao, Marc Cowling
Published London : SAGE Publications Ltd, 2019
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Sage Research Methods Cases    View Resource Record  

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Description 1 online resource : illustrations
Series SAGE Research Methods. Cases
SAGE Research Methods. Cases
Summary This case study illustrates a quantitative research study on accounting and finance using panel data from firm databases. Our research argues for the existence of a reference point effect on executive compensation determination, internally (the pay of other directors on board), externally (the industry peer executives’ average pay), and historically (the executive’s pay in the last period), in Chinese listed firms. We illustrate (1) the research process of variable design, including the design and understanding of dependent variables, independent variables, and control variables, as well as the relevant hypotheses development and multiple regression models using firm data and the panel data context; (2) the process of data collection using secondary data from financial database and the construction of a panel dataset; (3) the commands in Stata to run the ordinary least squares multiple regression; and (4) the principal components analysis capturing the systematic effect of the three reference points and perform the principal components analysis in Stata
Bibliography Includes bibliographical references and index
Notes Description based on XML content
SUBJECT Stata -- Case studies
Stata. fast (OCoLC)fst01375322
Subject Accounting -- Case studies
Executives -- Salaries, etc. -- China -- Case studies
Finance -- Case studies
Accounting.
Executives -- Salaries, etc.
Finance.
China.
Genre/Form Case studies.
Form Electronic book
Author Cowling, Marc, author
ISBN 1526495988
9781526495983