The Impact of the Opportunity Zone Program on Residential Real Estate

被引:0
作者
Bekkerman, Ron [1 ]
Cohen, Maxime C. [2 ]
Liu, Xiaoyan [3 ]
Maiden, John [1 ]
Mitrofanov, Dmitry [4 ]
机构
[1] Cherre Inc, New York, NY 10018 USA
[2] McGill Univ, Desautels Fac Management, Montreal, PQ H3A 1G5, Canada
[3] Santa Clara Univ, Leavey Sch Business, Santa Clara, CA 95053 USA
[4] Boston Coll, Carroll Sch Management, Chestnut Hill, MA 02467 USA
关键词
opportunity zones; real estate; public policy; natural experiment; fairness-aware optimization; OPTIMIZATION;
D O I
10.1287/msom.2024.0746
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Problem definition: : Opportunity zones (OZs) are designated census tracts in which real estate investments can gain tax benefits. Introduced by the U.S. Tax Cuts and Jobs Act of 2017, the goal of the OZ program is to foster economic development in distressed neighborhoods. In this paper, we investigate and optimize the OZ selection process and examine the impact of OZs by exploiting two data sets: a proprietary real estate data set that includes 36.1 million residential transactions spanning all 50 U.S. states and censustract demographics data between 2010 and 2019. Methodology/results: : We show that census tracts with higher poverty and unemployment rates were more likely to be selected. Counterintuitively, however, tracts with a higher average real estate price were also more likely to be selected. We then apply difference-in-differences, synthetic control, and matching techniques to rigorously assess the impact of the OZ program on two key real estate metrics: price and transaction volume. We find that the OZ program increased real estate prices by 4.03%-6.13% but do not observe a significant effect on the transaction volume. We also find that investors primarily targeted the high-end real estate market, namely, exhibiting a cherry-picking behavior. To better fulfill its intended societal and economic goals, we propose an optimization framework with fairness considerations for OZ assignment decisions. We show that the OZs assigned from our fairness-aware optimization formulation can better serve distressed communities and mitigate investors' cherry-picking behavior. Managerial implications: : Our paper underscores the importance of incorporating fairness in OZ designation to achieve a desirable real estate market reaction. Our largescale empirical analysis provides a comprehensive assessment of the current government OZ assignment, and our fairness-aware optimization framework provides concrete recommendations for policy makers.
引用
收藏
页码:2142 / 2159
页数:19
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