24 citations · 28 across the 6 of their papers we have counts for
9 papers
On the Optimality of Mental Accounting
Jarrod Burgh, Emerson Melo, Matthew Shum
Mental accounting is usually explained by self-control, and two-stage budgeting by separable preferences. We propose a third explanation based on sellers' market power. A consumer…
Estimation of random coefficients logit demand models with interactive fixed effects
Hyungsik Roger Moon, Matthew Shum, Martin Weidner
We extend the Berry, Levinsohn and Pakes (BLP, 1995) random coefficients discrete-choice demand model, which underlies much recent empirical work in IO. We add interactive fixed ef…
Managing Congestion in Two-Sided Platforms: The Case of Online Rentals
Caterina Calsamiglia, Laura Doval, Alejandro Robinson-Cortés +1
Thick two-sided matching platforms, such as the room-rental market, face the challenge of showing relevant objects to users to reduce search costs. Many platforms use ranking algor…
Discovery of Bias and Strategic Behavior in Crowdsourced Performance Assessment
Yifei Huang, Matt Shum, Xi Wu +1
With the industry trend of shifting from a traditional hierarchical approach to flatter management structure, crowdsourced performance assessment gained mainstream popularity. One…
Discrete Choice and Rational Inattention: a General Equivalence Result
Mogens Fosgerau, Emerson Melo, Andre de Palma +1
This paper establishes a general equivalence between discrete choice and rational inattention models. Matejka and McKay (2015, AER) showed that when information costs are modelled…
Inference on Estimators defined by Mathematical Programming
Yu-Wei Hsieh, Xiaoxia Shi, Matthew Shum
We propose an inference procedure for estimators defined by mathematical programming problems, focusing on the important special cases of linear programming (LP) and quadratic prog…
Semiparametric Estimation of Dynamic Discrete-Choice Models
Nicholas Buchholz, Haiqing Xu, Matthew Shum
We consider the estimation of dynamic discrete choice models in a semiparametric setting, in which the per-period utility functions are known up to a finite number of parameters, b…
Estimating Semi-parametric Panel Multinomial Choice Models using Cyclic Monotonicity
Xiaoxia Shi, Matthew Shum, Wei Song
This paper proposes a new semi-parametric identification and estimation approach to multinomial choice models in a panel data setting with individual fixed effects. Our approach is…
Random Projection Estimation of Discrete-Choice Models with Large Choice Sets
Khai X. Chiong, Matthew Shum
We introduce sparse random projection, an important dimension-reduction tool from machine learning, for the estimation of discrete-choice models with high-dimensional choice sets.…