Modeling Ordered Choices: A Primer

Modeling Ordered Choices: A Primer PDF

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William Greene ist emeritierter Professor für Wirtschaftswissenschaften an der Stern School of Business der New York University. Seine Interessengebiete sind angewandte Ökonometrie, Paneldatenanalyse, Discrete-Choice-Modellierung, Produktionsökonomie, Gesundheitsökonometrie, Verkehrsökonomie und -planung sowie Ökonomie der Unterhaltungsindustrie. Er ist außerdem Präsident von Econometric Software, Inc. Er ist Autor der Software LIMDEP und NLOGIT, der Lehrbücher Econometric Analysis (Ed. 1 bis 8), der Bücher über Discrete-Choice-Modellierung, Modeling Ordered Choices und Applied Choice Analysis sowie von über 100 Artikeln in peer-reviewed Zeitschriften. Er ist Chefredakteur von Foundations and Trends in Econometrics und des Journal of Productivity Analysis. Er hat auch die Industrie beraten, darunter die American Society of Composers, Authors and Publishers (ASCAP), National Economic Research Associates (NERA), die U.S.EPA, Booz Allen, den U.S. Postal Service und zahlreiche andere.

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Modeling Ordered Choices: A Primer pdf von 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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