Data and code for: How to Avoid Black Markets for Appointments With Online Booking Systems

Principal Investigator(s):  View help for Principal Investigator(s) Rustamdjan Hakimov, University of Lausanne and WZB Berlin Social Science Center; C-Philipp Heller, Nera Consulting; Dorothea Kübler, WZB Berlin Social Science Center and Technical University BErlin; Morimitsu Kurino, Keio University (Japan)

Version:  View help for Version V1

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README.pdf application/pdf 33.6 KB 06/16/2021 04:36:AM
do fromraw replication final.do text/x-stata-syntax 7.1 KB 03/09/2021 10:51:PM
raw_data_full_sample.dta application/x-stata 523.4 KB 03/04/2021 11:13:PM

Project Citation: 

Hakimov, Rustamdjan, Heller, C-Philipp, Kübler, Dorothea , and Kurino, Morimitsu. Data and code for: How to Avoid Black Markets for Appointments With Online Booking Systems. Nashville, TN: American Economic Association [publisher], 2021. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2021-06-23. https://doi.org/10.3886/E130921V1

Project Description

Summary:  View help for Summary
Abstract
Allocating appointment slots is presented as a new application for market design. Online booking systems are commonly used by public authorities to allocate appointments for visa interviews, driver's licenses, passport renewals, etc. We document that black markets for appointments have developed in many parts of the world. Scalpers book the appointments that are offered for free and sell the slots to appointment seekers. We model the existing first-come-first-served booking system and propose an alternative batch system. The batch system collects applications for slots over a certain time period and then randomly allocates slots to applicants. The theory predicts and lab experiments confirm that scalpers profitably book and sell slots under the current system with sufficiently high demand, but that they are not active in the proposed batch system. We discuss practical issues for the implementation of the batch system and its applicability to other markets with scalping.

Scope of Project

JEL Classification:  View help for JEL Classification
      C92 Design of Experiments: Laboratory, Group Behavior
      D47 Market Design
Data Type(s):  View help for Data Type(s) experimental data


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V1 [2021-06-23]

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