Modeling Ordered Choices: A Primer

Modeling Ordered Choices: A Primer pdf

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William Greene

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English

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383

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2087748 MB

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William Greene is Professor of Economics (emeritus) at theStern School of Business, New York University. His fields of interest are applied econometrics, panel data analysis, discrete choice modeling, production economics, health econometrics, transport economics and planning, and economics of the entertainment industry. He is also president of Econometric Software, Inc. He is the author of software LIMDEP and NLOGIT, textbooks Econometric Analysis (Ed.1 to 8), books on discrete choice modeling, Modeling Ordered Choices and Applied Choice Analysis, and over 100 articles in peer reviewed journals. He is the editor in chief of Foundations and Trends in Econometrics and of the Journal of Productivity Analysis. He has also consulted to industry, including American Society of Composers, Authors and Publishers (ASCAP), National Economic Research Associates (NERA), the U.S.EPA, Booz Allen, U.S. Postal Service and numerous others.

Book Description

Modeling Ordered Choices: A Primer pdf by William Greene

It is increasingly common for analysts to seek out the opinions of individuals and organizations using attitudinal scales such as degree of satisfaction or importance attached to an issue. Examples include levels of obesity, seriousness of a health condition, attitudes towards service levels, opinions on products, voting intentions, and the degree of clarity of contracts. Ordered choice models provide a relevant methodology for capturing the sources of influence that explain the choice made amongst a set of ordered alternatives. The methods have evolved to a level of sophistication that can allow for heterogeneity in the threshold parameters, in the explanatory variables (through random parameters), and in the decomposition of the residual variance. This book brings together contributions in ordered choice modeling from a number of disciplines, synthesizing developments over the last fifty years, and suggests useful extensions to account for the wide range of sources of influence on choice.

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