• Media type: E-Book
  • Title: Counterfactual Evaluation in Semiparametric Multinomial Choice Models
  • Contributor: Chiong, Khai [Author]; Hsieh, Yu-Wei [Other]; Shum, Matthew [Other]
  • Published: [S.l.]: SSRN, [2017]
  • Published in: USC-INET Research Paper ; No. 17-20
  • Extent: 1 Online-Ressource (19 p)
  • Language: English
  • DOI: 10.2139/ssrn.3006737
  • Identifier:
  • Origination:
  • Footnote: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments May 30, 2017 erstellt
  • Description: We propose using cyclic monotonicity, a convex-analytic property of the random utility choice model, to derive bounds on counterfactual choice probabilities in semiparametric multinomial choice models. These bounds are useful for typical counterfactual exercises in aggregate discrete-choice demand models. In our semiparametric approach, we do not specify the parametric distribution for the utility shocks, thus accommodating a wide variety of substitution patterns among alternatives. Computation of the counterfactual bounds is a tractable linear programming problem. We illustrate our approach in a series of Monte Carlo simulations and an empirical application using scanner data
  • Access State: Open Access