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Books on the topic 'Discrete choice'

Author: Grafiati

Published: 4 June 2021

Last updated: 11 March 2023

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1

Zwerina, Klaus. Discrete Choice Experiments in Marketing. Heidelberg: Physica-Verlag HD, 1997. http://dx.doi.org/10.1007/978-3-642-50013-8.

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2

Börsch-Supan, Axel, ed. Econometric Analysis of Discrete Choice. Berlin, Heidelberg: Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-45633-6.

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3

Páez, Antonio, and Geneviève Boisjoly. Discrete Choice Analysis with R. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-20719-8.

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4

Discrete choice methods with simulation. 2nd ed. New York: Cambridge University Press, 2009.

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5

Mariel, Petr, David Hoyos, Jürgen Meyerhoff, Mikolaj Czajkowski, Thijs Dekker, Klaus Glenk, Jette Bredahl Jacobsen, et al. Environmental Valuation with Discrete Choice Experiments. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-62669-3.

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6

Brocke, Michaela. Präferenzmessung durch die Discrete Choice-Analyse. Wiesbaden: Gabler, 2006. http://dx.doi.org/10.1007/978-3-8350-9046-0.

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7

Chorus, Caspar G. Random Regret-based Discrete Choice Modeling. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29151-7.

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8

Chesher, Andrew. Taste variation in discrete choice models. Bristol: University of Bristol, Department of Economics, 1995.

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9

Andre, De Palma, and Thisse Jacques Franc̜ois, eds. Discrete choice theory of product differentiation. Cambridge, Mass: MIT Press, 1992.

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10

Nechyba, Thomas J. Community choice and local public services: A discrete choice approach. Cambridge, MA: National Bureau of Economic Research, 1997.

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11

Hutchinson, Bruce G., Peter Nijkamp, and Michael Batty, eds. Optimization and Discrete Choice in Urban Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 1985. http://dx.doi.org/10.1007/978-3-642-51020-5.

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12

Chesher, Andrew. Discrete choice models without the IIA property. Bristol: University ofBristol, Department of Economics, 1992.

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13

Petrin, Amil. Omitted product attributes in discrete choice models. Cambridge, Mass: National Bureau of Economic Research, 2003.

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14

Brock, William A. Discrete choice with social interactions I: Theory. Cambridge, MA: National Bureau of Economic Research, 1995.

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15

Chorus, Caspar G. Random regret-based discrete choice modeling: A tutorial. Berlin: Springer, 2012.

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16

Adda, Jérôme. The dynamics of car sales: A discrete choice approach. Cambridge, MA: National Bureau of Economic Research, 2000.

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17

R, Lerman Steven, ed. Discrete choice analysis: Theory and application to travel demand. Cambridge, Mass: MIT Press, 1985.

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18

Ryan, Mandy, Karen Gerard, and Mabel Amaya-Amaya, eds. Using Discrete Choice Experiments to Value Health and Health Care. Dordrecht: Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-5753-3.

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19

Discrete choice modelling and air travel demand: Theory and applications. Farnham, Surrey: Ashgate, 2010.

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20

Murphy, Anthony. Artificial regression based mis-specification tests for discrete choice models. Dublin: University College Dublin, Department of Economics, 1994.

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21

Garrow, Laurie A. Discrete choice modelling and air travel demand: Theory and applications. Farnham, Surrey: Ashgate, 2009.

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22

Cooper, Russell. Euler-equation estimation for discrete choice models: A capital accumulation application. Cambridge, MA: National Bureau of Economic Research, 2010.

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23

Boehm, Thomas P. A discrete choice model of dividend reinvestment plans: Classification and prediction. Atlanta, Ga.]: Federal Reserve Bank of Atlanta, 2007.

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24

Ackerberg, Daniel A. Unobserved product differentiation in discrete choice models: Estimating elasticities and welfare effects. Cambridge, MA: National Bureau of Economic Research, 2002.

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25

Discrete choice experiments in marketing: Use of priors in efficient choice designs and their application to individual preference measurement. Heidelberg: Physica-Verlag, 1997.

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26

Johnston, Richard Stanley. An analysis of pricing strategies for a multiproduct monopolist in a discrete choice model. Kingston, RI: University of Rhode Island, Dept. of Resource Economics, 1994.

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27

Fang, Hanming. Estimating dynamic discrete choice models with hyperbolic discounting, with an application to mammography decisions. Cambridge, MA: National Bureau of Economic Research, 2010.

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28

Gandhi, Amit. Identification and estimation in discrete choice demand models when endogenous variables interact with the error. Cambridge, MA: National Bureau of Economic Research, 2011.

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29

Dubé, Jean-Pierre. Improving the numerical performance of blp static and dynamic discrete choice random coefficients demand estimation. Cambridge, MA: National Bureau of Economic Research, 2009.

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30

Tavakoli, Manouch. A new approach to estimating demand for broadcasting products: A dynamic logit model of discrete choice. Uxbridge: Centre for Research into Innovation, Culture & Technology, 1989.

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31

Börsch-Supan, Axel. Econometric analysis of discrete choice: With applications on demand for housing in the U.S. and West-Germany. Berlin: Springer-Verlag, 1987.

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32

Hahn, Christian. Conjoint- und Discrete Choice-Analyse als Verfahren zur Abbildung von Präferenzstrukturen und Produktauswahlentscheidungen: Ein theoretischer und computergestützter empirischer Vergleich. Münster: Lit, 1997.

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33

World Bank. How to conduct a discrete choice experiment for health workforce recruitment and retention in remote and rural areas: A user guide with case studies. Washington, DC: International Bank for Reconstruction and Development/World Bank, 2013.

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34

Bruce, Hutchinson, Nijkamp Peter, and Batty Michael, eds. Optimization and discrete choice in urban systems: Proceedings of the International Symposium on New Directions in Urban Systems Modelling, held at the University of Waterloo, Canada, July 1983. Berlin: Springer-Verlag, 1985.

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35

Andrew, Henley, and University of Kent at Canterbury., eds. Location choice and labour market perceptions: A discreet choice study. Canterbury: University of Kent at Canterbury, 1989.

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36

Novikov, Anatoliy, Tat'yana Solodkaya, Aleksandr Lazerson, and Viktor Polyak. Econometric modeling in the GRETL package. ru: INFRA-M Academic Publishing LLC., 2023. http://dx.doi.org/10.12737/1732940.

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Abstract:

The tutorial describes the capabilities of the GRETL statistical package for computer data analysis and econometric modeling based on spatial data and time series. Using concrete economic examples, GRETL considers classical and generalized models of linear and nonlinear regression, methods for detecting and eliminating multicollinearity, models with variable structure, autoregressive processes, methods for testing and eliminating autocorrelation, as well as discrete choice models and systems of simultaneous equations. For the convenience of users, the tutorial contains all the task data files used in the work in the format .GDTs are collected in an application in the cloud so that users have access to them. Meets the requirements of the federal state educational standards of higher education of the latest generation in the disciplines of "Econometrics" and "Econometric modeling". For students and teachers of economic universities in the field of Economics, as well as researchers who use econometric methods to model socio-economic phenomena and processes.

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37

Lahdenperä, Harri. Female labour supply in Finland: Econometric applications of discrete choise models to married women's labour supply decisions. Helsinki: Suomen Pankki, 1991.

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38

Glasgow, Garrett, and R. Michael Alvarez. Discrete Choice Methods. Edited by Janet M. Box-Steffensmeier, Henry E. Brady, and David Collier. Oxford University Press, 2009. http://dx.doi.org/10.1093/oxfordhb/9780199286546.003.0022.

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Abstract:

This article describes the statistical models commonly used to study discrete choices. It concentrates on the ‘basic’ discrete choice models, and the theoretical choice situations that lead to these models. Specifically the choice situation addressed include: the ordered choice situation and the unordered choice situation. In addition, the article discusses two extensions of the basic discrete choice models commonly seen in political science research — models allowing for heteroskedasticity in the choices made across political agents (such as the heteroskedastic probit), and models that estimate substitution patterns across choice alternatives (such as the multinomial probit and mixed logit). Suggestions for further reading are also given.

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39

Johnson, Lester W., and David A. Hensher. Applied Discrete-Choice Modelling. Taylor & Francis Group, 2018.

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40

Glasgow, Garrett. Interpreting Discrete Choice Models. Cambridge University Press, 2022.

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41

Hensher, David A., and Lester W. Johnson. Applied Discrete-Choice Modelling. Routledge, 2018. http://dx.doi.org/10.4324/9781351140768.

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42

Glasgow, Garrett. Interpreting Discrete Choice Models. Cambridge University Press, 2022.

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43

Applied Discrete-Choice Modelling. Taylor & Francis Group, 2018.

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44

Applied Discrete-Choice Modelling. Taylor & Francis Group, 2018.

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45

Johnson, Lester W., and David A. Hensher. Applied Discrete-Choice Modelling. Taylor & Francis Group, 2018.

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46

Johnson, Lester W., and David A. Hensher. Applied Discrete-Choice Modelling. Taylor & Francis Group, 2018.

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47

Train, Kenneth E. Discrete Choice Methods with Simulation. Cambridge University Press, 2010.

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48

Train, Kenneth E. Discrete Choice Methods with Simulation. Cambridge University Press, 2003.

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49

Boisjoly, Geneviève, and Antonio Páez. Discrete Choice Analysis with R. Springer International Publishing AG, 2023.

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50

Discrete Choice Methods with Simulation. Cambridge University Press, 2009.

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