Coalition for the Homeless Joined by Win, The Legal Aid Society, and Homeless Services United in Calling for IBO to Retract Deeply Flawed Manhattan Home Value Report
The Coalition for the Homeless released today the following statement and analysis of the IBO’s new report on the impact of homeless shelters on property values in Manhattan.
Giselle Routhier, Policy Director, said:
“Stoking NIMBYism with a fatally flawed report that casts shelters as a blight rather than a public good (and indeed a legal requirement) only serves to further stigmatize and discriminate against the victims of our city’s affordable housing crisis. The cost of homelessness to our city is immense by both an economic and moral accounting. The city’s shelter system saves tens of thousands of men, women, and children from being cast to our streets, and is the reason we don’t have the massive tent cities we see in other localities. Because of the flawed conclusions of this report, it will serve to advance harmful stereotypes and elicit discrimination against people of color, people with disabilities, and families with children in violation of the Fair Housing Act. We call on the IBO to immediately retract this report and acknowledge its errors.”
The IBO’s report fails in the following areas:
Flawed basic methodology (p. 2): The IBO identifies two more robust methods of analyzing the data, which they do not use because they did not have the data, or the appropriate sample size. Instead, they use a third-tier methodology that uses only a limited number of controls that could alternatively explain the outcomes, omitting such things as age and quality of the unit.
Basic errors of causation (p. 6): The report makes a huge leap from correlation based on flawed methodology to definite causation. This is a mistake one is taught to avoid in every Statistics 101 class.
Potential gross additive errors (p. 5-6): The estimates that property values will decrease by 24.5% or 23.8% for being within 500 feet of a shelter and being within 1,000 feet of more than one shelter are calculated by adding the two metrics. However, the author does not provide sufficient justification for adding these two estimates together, likely because they are not mutually exclusive. This methodological flaw yields a strikingly large and probably erroneous number that was listed as the first takeaway in press reports.
Misunderstanding basic facts about shelters and leaving out shelters from the analysis (p. 2-3): The IBO mischaracterizes types of shelters. Their definition of congregate v. non-congregate is not correct. They include in their definition of congregate facilities family shelters with shared sleeping quarters and bathrooms, which do not exist, and commercial hotels, which have individual rooms and are therefore not congregate. Their primary aim in making this distinction is to arbitrarily remove “non-congregate” facilities from the analysis, which they describe as any facility which is only partly used as a shelter, including hotels and cluster sites.
Their own data contradict their conclusion (p. 4): Before adding their limited controls, they actually report in the descriptive statistics: “For shelters serving families with children, the median price of residences located within 500 feet is roughly the same as the median for similar residences located 500 feet to 1,000 feet away; the median price of the properties located 500 feet to 1,000 feet from family shelters is roughly $15,000 (1.1 percent) less than the median for properties located closer to the facilities.”
They leave out other data that contradict their conclusion (p. 6): The IBO tested many variables and landed on the one that gave them results that confirmed a preconceived notion. For example, “IBO tested a binary variable that indicated whether the sale occurred on the same block as a shelter, but the estimated coefficients, some positive and some negative, were statistically insignificant. The estimated coefficient on the shelter capacity variable was statistically significant but virtually zero, indicating only a trivial effect on sales prices.”