Stephan D. Whitaker

Big Data versus a survey

Economists are shifting attention and resources from work on survey data to work on “big data.” This analysis is an empirical exploration of the trade-offs this transition requires. Parallel models are estimated using the Federal Reserve Bank of New York Consumer Credit Panel/Equifax and the Survey of Consumer Finances. After adjustments to account for different variable definitions and sampled populations, it is possible to arrive at similar models of total household debt. However, the estimates are sensitive to the adjustments. Little similarity is observed in parallel models of nonmortgage debt. While surveys intentionally collect theoretically related variables, it may be necessary to merge external data into commercial big data. In this example, some education and income measures are successfully integrated with the big data, but other external aggregates fail to adequately substitute for survey responses. Big data offers sample sizes, frequencies, and details that surveys cannot match. However, this example illustrates why caution is appropriate when attempting to substitute big data for a carefully executed survey.

Land Bank 2.0: An Empirical Evaluation

Cuyahoga County created a land bank in 2009 explicitly intended to acquire low-value properties, mitigate blighted housing, help stabilize neighborhoods, and slow the decline of property values. This paper evaluates the effectiveness of the land bank by estimating spatially-corrected hedonic price models using sales near the land bank homes. Homes that sold within 500 feet of a property that would be acquired by the land bank in the next six months show a 3 to 5 percent discount versus observationally similar homes. Homes that sold within 500 feet of a land bank owned home sold at prices approximately 5 percent higher than similar homes. A land bank demolition appears to have a positive externality, which adds 9 percent to the value of a nearby home sale. These results are consistent through a wide variety of specifications, but they are not measured precisely enough to be statistically significant.

LAND BANK 2.0: AN EMPIRICAL EVALUATION: LAND BANK 2.0

In 2009, Cuyahoga County, Ohio (Cleveland and 58 suburbs), established a land bank to acquire low�?value properties, mitigate blighted housing, and slow the decline of property values. This empirical study evaluates the effectiveness of the land bank by estimating spatially corrected hedonic price models using sales near the land�?bank homes. The land bank reduces the negative externalities of the properties it acquires. Its largest impact is the preservation of equity in unsold homes. We also estimate the recovered value for homes sold during the study period and the property tax revenue that may have been forgone, absent the land bank.

Prioritization in Private-Activity-Bond Volume Cap Allocation

This paper proposes and tests a structural model reflecting the process of authorizing private-activity municipal bond issuance. Private-activity municipal bonds offer tax-exempt financing for programs including industrial development, utilities, low-income housing, and student loans. The Federal tax code sets annual caps on the total tax-exempt issuance within each state, so authorization becomes a scarce resource distributed via a political process. Interviews with program administrators in several states suggested the authorization process involves prioritizing categories of use, authorizing bonds for high-priority uses first, and then authorizing bonds for lower-priority uses until the cap is exhausted. A model representing this process suggests variables to include in reduced-form estimations and an alternative interpretation of the coefficients. The fit of the model can be improved by adding measures of political influence and imposing a structure that reflects the political prioritization process. In general, industrial development and utilities appear to be the highest priority uses of private-activity municipal bonds. Mortgage revenue bonds are the residual category most frequently.

Predictive Modeling of Surveyed Property Conditions and Vacancy

Using the results of a comprehensive in-person survey of properties in Cleveland, Ohio, we fit predictive models of vacancy and property conditions. We draw predictor variables from administrative data that is available in most jurisdictions such as deed recordings, tax assessors property characteristics, and foreclosure filings. Using logistic regression and machine learning methods we are able to make reasonably accurate out-of-sample predictions. Our findings indicate that housing professionals could use administrative data and predictive models to identify distressed properties between surveys or among non-surveyed properties in an area subject to a random sample survey.

Can Local Ordinances Prevent Neighborhood Destabilization

Abstract This article assesses the ability of local housing ordinances to prevent neighborhood destabilization, specifically that arising as a consequence of the most recent housing crisis. We evaluate the degree to which vacancy registrations and point-of-sale inspection requirements influenced housing market outcomes during the housing crisis. With comprehensive real property data from Cuyahoga County, Ohio, we measure outcomes that characterize housing market distress including foreclosures, sales below the tax-assessed value, bulk sales, flipping, and property tax delinquency. We evaluate outcomes across properties in regulated and unregulated municipalities using matching procedures on linked data containing property, neighborhood, loan, and transaction characteristics. We find evidence that vacancy registrations substantially reduce foreclosures. In contrast, we find little evidence that point-of-sale inspections reduce undesirable transactions. Rather, properties in cities with inspection requirements displayed higher levels of foreclosure and tax delinquency relative to the control group during the study period.

Premium Municipal Bonds and Issuer Fiscal Distress

Economic theory suggests that bond issuers of lower credit quality or higher opacity should be more likely to issue bonds with premium coupons (higher coupon rates relative to yields at issuance). Using a comprehensive data set of municipal bonds issued between 1992 and 2012 by more than 21,000 issuers, we show that this has not been the case until the early 2000s. We examine what changed in this market to bring it into greater alignment with economic principles. We argue that the Government Accounting Standards Board’s Statement 34 that required the use of accrual accounting rules in government financial reports deserves the credit.

Adjusting the Volume: Private‐Activity Municipal Bonds and the Variation in the Volume Cap

States allocate authority, under a federally‐imposed volume cap, to issue tax‐exempt bonds for financing private activities including industrial development, utilities, and low‐income housing. The generosity of the cap varies widely between states. This paper analyzes the relationships between the caps, political characteristics of the states, and the authorizations to competing constituencies. In per capita terms, each additional dollar of volume cap is associated with an additional

Can Local Housing Ordinances Prevent Neighborhood Destabilization

0.49 to

Household Debt and Local Public Finances

0.66 of borrowing per year. Mortgage revenue bonds and student loan bonds are the most responsive to variation in the cap. There is some evidence of political influence on the allocation process.