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Modeling Ordered Choices

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  • Greene,William H.
  • Hensher,David A.

Abstract

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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Bibliographic Info

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This book is provided by Cambridge University Press in its series Cambridge Books with number 9780521142373 and published in 2010.

Order: http://www.cambridge.org/uk/catalogue/catalogue.asp?isbn=9780521142373
Handle: RePEc:cup:cbooks:9780521142373

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Web page: http://www.cambridge.org

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Cited by:
  1. "Belderbos, Rene & Ikeuchi, Kenta & Fukao, Kyoji & Kim, Young Gak & Kwon, Hyeog Ug, 2013. "Plant Productivity Dynamics and Private and Public R&D Spillovers: Technological, Geographic and Relational Proximity," CEI Working Paper Series 2013-05, Center for Economic Institutions, Institute of Economic Research, Hitotsubashi University.
  2. William H Greene & Mark N Harris & Preety Srivastava & Xueyan Zhao, 2013. "Econometric Modelling of Social Bads," Bankwest Curtin Economics Centre Working Paper series WP1305, Bankwest Curtin Economics Centre (BCEC), Curtin Business School.
  3. William H. Greene & Mark N. Harris & Bruce Hollingsworth, 2014. "Inflated Responses in Measures of Self-Assessed Health," Working Papers 14-12, New York University, Leonard N. Stern School of Business, Department of Economics.
  4. Stefan Boes, 2013. "Nonparametric analysis of treatment effects in ordered response models," Empirical Economics, Springer, vol. 44(1), pages 81-109, February.
  5. Udo Schneider & Christian Pfarr & Brit Schneider & Volker Ulrich, 2012. "I feel good! Gender differences and reporting heterogeneity in self-assessed health," The European Journal of Health Economics, Springer, vol. 13(3), pages 251-265, June.
  6. Migliardo, Carlo, 2012. "Heterogeneity in price setting behavior, spatial disparities and sectoral diversity: Evidence from a panel of Italian firms," Economic Modelling, Elsevier, vol. 29(4), pages 1106-1118.
  7. Timothy A. Weterings & Mark N. Harris & Bruce Hollingsworth, 2012. "Extending Unobserved Heterogeneity - A Strategy for Accounting for Respondent Perceptions in the Absence of Suitable Data," Monash Econometrics and Business Statistics Working Papers 12/12, Monash University, Department of Econometrics and Business Statistics.
  8. David ARISTEI & Manuela Gallo, 2012. "The Drivers of Household Over-Indebtedness and Delinquency on Mortgage Loans: Evidence from Italian Microdata," Quaderni del Dipartimento di Economia, Finanza e Statistica 105/2012, Università di Perugia, Dipartimento Economia, Finanza e Statistica.
  9. Greene, William H. & Gillman, Max & Harris, Mark N. & Spencer, Christopher, 2013. "The Tempered Ordered Probit (TOP) Model with an Application to Monetary Policy," CEI Working Paper Series 2013-04, Center for Economic Institutions, Institute of Economic Research, Hitotsubashi University.

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