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Details about Thomas Otter

Homepage:https://www.marketing.uni-frankfurt.de/en/professoren/otter/prof-dr-thomas-otter.html
Workplace:Fachbereich Wirtschaftswissenschaft (Faculty of Economics and Business Administration), Goethe Universität Frankfurt am Main (Goethe University Frankfurt), (more information at EDIRC)

Access statistics for papers by Thomas Otter.

Last updated 2025-03-17. Update your information in the RePEc Author Service.

Short-id: pot65


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Working Papers

2024

  1. Do financial advisors have different beliefs than lay people?
    IMFS Working Paper Series, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS) Downloads

2022

  1. Measuring Income and Wealth Effects on Private-Label Demand with Matched Administrative Data
    CEPR Discussion Papers, C.E.P.R. Discussion Papers Downloads
    See also Journal Article Measuring Income and Wealth Effects on Private-Label Demand with Matched Administrative Data, Marketing Science, INFORMS (2022) Downloads (2022)

Journal Articles

2025

  1. Discrete choice in marketing through the lens of rational inattention
    Quantitative Marketing and Economics (QME), 2025, 23, (1), 45-104 Downloads

2022

  1. Better Information From Survey Data: Filtering Out State Dependence Using Eye-Tracking Data
    Psychometrika, 2022, 87, (2), 620-665 Downloads
  2. Measuring Income and Wealth Effects on Private-Label Demand with Matched Administrative Data
    Marketing Science, 2022, 41, (3), 637-656 Downloads
    See also Working Paper Measuring Income and Wealth Effects on Private-Label Demand with Matched Administrative Data, CEPR Discussion Papers (2022) Downloads (2022)

2020

  1. How to generalize from a hierarchical model?
    Quantitative Marketing and Economics (QME), 2020, 18, (4), 343-380 Downloads View citations (7)

2018

  1. Advancing Non-compensatory Choice Models in Marketing
    Customer Needs and Solutions, 2018, 5, (1), 82-92 Downloads View citations (4)

2014

  1. Bayesian estimation of the random coefficients logit from aggregate count data
    Quantitative Marketing and Economics (QME), 2014, 12, (1), 43-84 Downloads View citations (3)

2013

  1. Successive Sample Selection and Its Relevance for Management Decisions
    Marketing Science, 2013, 32, (1), 170-185 Downloads View citations (7)
  2. The Dimensionality of Customer Satisfaction Survey Responses and Implications for Driver Analysis
    Marketing Science, 2013, 32, (4), 533-553 Downloads View citations (11)

2011

  1. Testing Models of Strategic Behavior Characterized by Conditional Likelihoods
    Marketing Science, 2011, 30, (4), 686-701 Downloads View citations (6)

2008

  1. Choice Models in Marketing: Economic Assumptions, Challenges and Trends
    Foundations and Trends(R) in Marketing, 2008, 2, (2), 97-184 Downloads View citations (20)
  2. Sequential sampling models of choice: Some recent advances
    Marketing Letters, 2008, 19, (3), 255-267 Downloads View citations (13)
  3. The Dependent Poisson Race Model and Modeling Dependence in Conjoint Choice Experiments
    Psychometrika, 2008, 73, (2), 261-288 Downloads View citations (9)

2007

  1. Heterogeneity distributions of willingness-to-pay in choice models
    Quantitative Marketing and Economics (QME), 2007, 5, (3), 313-331 Downloads View citations (92)
  2. Investigating Endogeneity Bias in Marketing
    Marketing Science, 2007, 26, (5), 642-650 Downloads View citations (15)

2006

  1. Contemporary Bayesian Econometrics and Statistics. John Geweke
    Journal of the American Statistical Association, 2006, 101, 1313-1314 Downloads View citations (1)

2005

  1. Adjusting Choice Models to Better Predict Market Behavior
    Marketing Letters, 2005, 16, (3), 197-208 Downloads View citations (15)

2004

  1. Bayesian Analysis of the Heterogeneity Model
    Journal of Business & Economic Statistics, 2004, 22, (1), 2-15 View citations (23)

Chapters

2022

  1. Bayesian Models
    Springer

2012

  1. Implications of Linear Versus Dummy Coding for Pooling of Information in Hierarchical Models
    Springer
 
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