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Local Externalities

Paper Session

Saturday, Jan. 7, 2017 1:00 PM – 3:00 PM

Sheraton Grand Chicago, Ontario
Hosted By: American Real Estate and Urban Economics Association
  • Chair: Janet Kohlhase, University of Houston

The Effect of Legalizing Retail Marijuana on Housing Values: Evidence From Colorado

Cheng Cheng
,
University of Mississippi
Walt Mayer
,
University of Mississippi
Yanling Mayer
,
FNC, Inc.

Abstract

Does legalizing retail marijuana generate more benefits than costs? This paper addresses this question by measuring the benefits and costs that are capitalized into housing values. We exploit the time-series and cross-sectional variations in the adoption of Colorado’s municipality retail marijuana laws (RMLs) and examine the effect on housing values with a difference-in-differences strategy. Our estimates show that the legalization leads to an average 6 percent increase in housing values, indicating that the capitalized benefits outweigh the costs. In addition, we find suggestive evidence that this relatively large housing value appreciation is likely due to RMLs inducing strong housing demand while having no discernible effect on housing supply. Finally, we show that the effect of RMLs is heterogeneous across locations and property types.

Bankruptcies After the Removal of Neighborhood Slot Machines

Barry Scholnick
,
University of Alberta
Vyacheslav Mikhed
,
Federal Reserve Bank of Philadelphia
Hyungsuk Byun
,
University of Alberta

Abstract

Ackerlof and Shiller (2015), and many others, argue that slot machines are manipulative and deceptive. We examine whether the removal of slots from a specific bar or restaurant impacts bankruptcy filings in the immediate vicinity. Our identification strategy compares consumers that are fractions of a kilometer from the closed slot location, compared to consumers slightly further away. We find that the removal of slots from a bar or restaurant significantly reduces the number of neighboring bankruptcies. These effects are dependent on the dollar amount of gambling removed from each location, as well as the distance from the location.

House Prices and Individual Perceptions of Terrorism in the Wake of September 11th

Adam Nowak
,
West Virginia University
Juan Sayago-Gomez
,
West Virginia University

Abstract

Ahmed and Hammarstedt (2008) document that landlords are less likely to call back a rental applicant if the applicant’s sends a strong signal that he or she is a Muslim. This paper is interested in asking if homeowners were less willing to live next to individuals with ethnically Arab names in the wake of the September 11th attacks. Identifying ethnically Arab names is done using a machine learning approach. In a novel methodology, Olympic rosters for 221 countries are used in order to create an algorithm that can be used to associate a name with a country or region. With this algorithm, we use Seattle, Washington assessor data and identify homeowners with ethnically Arab names. After performing this identification strategy we estimate a repeat sales model to estimate the effect of having a neighbor ethnically associated to an Arab name close to the dwelling and the effect after the September 11th attacks. Our estimates show a decrease in the price of the dwelling of roughly four to six percent.
Discussant(s)
David Brasington
,
University of Cincinnati
Han Li
,
Southwestern University of Finance and Economics
Vikram Maheshri
,
University of Houston
JEL Classifications
  • R2 - Household Analysis