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New Public Transportation Infrastructure and Tax Delinquency in Shrinking Cities: The Case of Detroit
Abstract
Fiscal stress is a common condition in shrinking cities such as Detroit. Among the contributing factors, property tax delinquency is a significant consideration due to the unwillingness or inability to pay property taxes. The literature shows that improvement in the quality of public goods and services can increase tax compliance and strengthen the social contract between taxpayers and the local government. Nonetheless, this relationship is unclear in the context of low-income shrinking cities. This article estimates the effects of new publicly provided transportation infrastructure on property tax compliance in Detroit, Michigan. Specifically, we use the announcement of the Qline in Detroit. We compute the effects of the Qline announcement on tax delinquency behavior using a Spatial Difference-in-Difference approach. The results indicate that the announcement of the Qline had an economically and statistically significant impact on tax delinquency for properties within one mile of the nearest Qline station.
In this paper, I review and assess what we have learned about what motivates individuals to pay – or to not pay – their legally due tax liabilities. I focus on three specific questions. First, what does theory say about what motivates tax compliance? Second, what does the evidence show? Third, how can government use these insights to improve compliance? I conclude with some suggestions – and some predictions – for future research.
This paper estimates the willingness-to-pay for anticipated journey-time savings introduced by the Crossrail intervention in the London Borough of Ealing. Given Crossrail remains under construction, we estimate how the anticipated benefit of Crossrail's announcement enters the house price determination process. Anticipated journey-time savings should enter the home-buyer's pricing equation because these benefits are speculatively internalised even before the service becomes operational. Using a experimental method that accounts for the possibility of a spatial autoregressive process in housing values, we test the hypotheses that the announcement of a new commuter rail service generated a location premium, and that house price appreciation reflected proximity to Crossrail terminals. Our evidence suggests home-buyers significantly valued proximity to planned Crossrail terminals following the post-announcement period.
We examine the fiscal consequences of sustained population loss in American cities. We find the starkest difference between growing and declining cities in their levels of social and economic distress: Declining cities have higher rates of poverty and crime. Our evidence also suggests that shrinking cities have less fiscal capacity than growing cities, although this relationship is complicated by an apparent nonlinearity: Shrinking and rapidly growing cities both have less fiscal capacity than high-demand cities that grow slowly. Lastly, both high distress and low fiscal capacity appear to predict further population loss. Together, our evidence suggests that population loss may both increase social problems and decrease the resources available to solve them, and that declining cities may enter vicious cycles that perpetuate further decline.
In this paper, we suggest that individuals’ tax compliance behaviours are affected by the behaviour of their “neighbours”, or those about whom they may have information, whom they may know, or with whom they may interact on a regular basis. Individuals are more likely to file and to report their taxes when they believe that other individuals are also filing and reporting their taxes; conversely, when individuals believe that others are cheating on their taxes, they may well become cheaters themselves. We use experimental methods to test the role of such information about peer effects on compliance behaviour. In one treatment setting, we inform individuals about the frequency that their neighbours submit a tax return. In a second treatment setting, we inform them about the number of their neighbours who are audited, together with the penalties that they pay. In both cases, we examine the impact of information on filing behaviour and also on subsequent reporting behaviour. We find that providing information on whether one's neighbours are filing returns and/or reporting income has a statistically significant and economically large impact on individual filing and reporting decisions. However, this “neighbour” information does not always improve compliance, depending on the exact content of the information. This article is protected by copyright. All rights reserved
Why do people pay taxes when they have an opportunity, even an incentive, to evade? The experimental results in this paper suggest that tax compliance occurs because some individuals overweight the low probability of audit, although such overweighting is not universal. The results also indicate that compliance does not occur simply because individuals believe that evasion is wrong, since subject behavior is unchanged by the use of either neutral or loaded terms. Finally, there is evidence that individuals pay taxes because they value the public goods that their taxes finance. In short, individuals exhibit much diversity in their behavior.
The purpose of this article is to evaluate the degree to which the demolition of low-quality structures affects property tax compliance in Detroit. During the real estate crisis, the rate of property tax delinquency in the city exceeded 50%. The demolition of dilapidated structures could lead to improvements in tax compliance in two ways. The first is through an amenity effect: removal of blighted structures improves the neighborhood and thus may increase the likelihood that neighbors pay their property taxes. The second is via the existence of a peer effect in property tax compliance decisions. We use a 6-year panel database to examine the degree to which demolitions affect nearby residential property tax delinquency. Even though we are unable to disentangle the amenity and peer effects, our analysis shows that when a dilapidated property is demolished, tax delinquency within the neighborhood is reduced, providing evidence that demolitions improve tax compliance.
Neighborhood decline is a critical issue in shrinking cities. Components of sustainable urbanism such as mixed land uses have risen as possible urban planning-based approaches to help mitigate urban and neighborhood decline. This research identifies examines if mixed land uses can help mitigate urban decline by using the tax delinquent status of single family houses as a proxy for decline in Dayton, Ohio, USA. Logistic regression models are utilized to estimate the probability of tax delinquency. The results suggest that the proximity to mixed land uses is associated with increasing or decreasing the probability of tax delinquent for single family lots. The number of commercial and industrial lots in a neighborhood also has effects on the probability of a lot becoming tax delinquent, but the specific types of commercial and industrial lots dictate the direction of effects. The existence of commercial apartment lots, retail lots, and industrial food and drink plant lots were shown to help decrease the probability of tax delinquent lots. Also, decreasing the amount of property tax applied to parcels can help to limit distress in neighborhoods. This research contributes to the ongoing efforts to stymie the amount of residential abandonment in depopulating and declining cities.
We develop a class of difference-in-differences regression models for the case of multiple transportation interventions that may occur sequentially over time and may generate causal spillover effects within a spatial system. We show how these models can be estimated using tools from spatial econometrics, and further extend the models to a system of seemingly unrelated outcomes such that there may be spatial correlation in the error terms. These models facilitate estimation of direct, indirect, and total average causal effects, as well as individual and cumulative effects of transportation interventions that partially overlap in space. Such estimates can assist policymakers in assessing potentially reinforcing effects originating from multiple transportation interventions located in close proximity. We develop an empirical example of our models to evaluate spatiotemporal socioeconomic impacts of the original and expanded light rail system in Denver, CO.
We test the hypothesis of transit-induced gentrification for the Regional Transportation District light rail system in Denver, CO. We use a quasi-experimental spatial econometric approach, the spatial difference-in-differences model, to measure the causal relationship between urban rail investments and gentrification, which allows us to capture the average direct and indirect (spatial spillover) effects of urban rail on several socioeconomic measures of gentrification. We further account for unobserved heterogeneity and spatial dependence via the use of a panel data estimator with spatial error components. Our analysis shows that the installation of a light rail station significantly increases household income and housing values in neighborhoods up to one mile from the station.
Urban sprawl and inner city decline are two common and interconnected outcomes of contemporary metropolitan development. More than 25% of large cities in the world are considered shrinking cities. Detroit is one of the most notorious examples of severe decline in North America. We examined the residential housing vacancy severity in the City of Detroit in comparison with the seventeen other cities in metropolitan Detroit. We developed a systematic and quantitative framework to investigate city shrinking from the perspectives of both causes and dynamics. The framework consists of three consequent regressions: the regional model to analyze the causes and dynamics of urban shrinking, the city models to reveal regional disparity and to identify primary inequality factors, and the regional logistic categorical model to examine the effect of primary social-spatial inequality factors on urban shrinking. Through these analyses, we found that the odds of becoming vacant were 9.01 times higher in census tracts with the highest concentration of less educated population, 7.16 times higher where a good portion of housing structures didn't have a full kitchen, 7.06 times higher in tracts with the most concentrated Black population, 5.47 times higher where a good portion of housing were multi-unit structures, and 4.76 times higher in tracts with the poorest population. We concluded that urban shrinking was often accompanied with urban sprawl; regional inequality was manifested in multiple scales and socio-spatial inequality became increasingly alarming; the causes and dynamics of urban shrinking were inevitably intertwined; and racial segregation and persistent poverty were the primary cause of long-lasting urban shrinking in Metropolitan Detroit.
We conduct an analysis of the costs and benefits of public investment in demolishing dilapidated residential housing in Detroit. While we estimate a positive net impact of demolitions on nearby property values, we also calculate a low marginal impact on local property tax collections. Under existing housing market conditions in Detroit, demolition costs exceed the present value of additional property tax revenues resulting from demolitions over 50 years. Using efficiency as the criteria for justifying spending public funds on demolition, average property values would have to increase by a factor of five to justify the demolition program.
We examine the influence of property tax delinquency on the sale price of nearby homes from 2002 to 2013 using more than 46,000 residential property sales in a representative midwestern central city—Milwaukee, Wisconsin. After controlling for a number of property and neighborhood characteristics including nearby foreclosures, we find property tax delinquency has a significant influence on nearby home sales. The relationship is negative; one additional tax delinquent property within 250 m of a home sale is associated with a discounted sale price of 0.79% or approximately $1,085 on average. In addition, the influence of tax delinquent properties on home sale prices diminishes with distance, suggesting blight is the source of the discount. Based on these findings, the negative influence of tax delinquency is likely to be exacerbated in central cities where housing density is greater and delinquency is higher and more persistent than the surrounding suburbs, which has the potential to lead to fiscal distress as property taxes are the primary revenue source for cities. As such, we suggest a two-tiered approach for cities to mitigate the negative consequences of tax delinquency: a combination of policies to eliminate delinquency and also to help homeowners become financially stable.
This article questions the strict parallelism of demographic and economic development in characterising urban shrinkage in Germany. As the cases of several Ruhr cities and East German cities prove, urban economic growth can be achieved thanks to the substantial presence of modern industries and business services, and despite declines in population size. Serious shrinkages of Halle, Cottbus and Schwerin are primarily due to failures in the post-industrial transformation process. Recent policy measures strongly oriented towards slowing the downsizing process of population (via e.g. urban regeneration strategies) do not appear to be sufficient for achieving urban resurgence in these cities. More active industrial policy measures are required there to create a competitive high-tech manufacturing sector, to stimulate innovation activities and to boost its growth interdependence with modern local services and R&D infrastructure.
Sugarcane production represents around 10% of the agricultural area and 1% of GDP in Brazil, and has grown substantially in recent years. The traditional harvest method involves burning the field to facilitate access to the canes, resulting in well-documented negative effects on health. The existing studies do not consider the effects on health in the surrounding areas. This article presents a new variety of a spatial diff-in-diff model to control for the effects of sugarcane production in neighboring non-producing regions. This method is an addition to the Spatial Econometrics literature, as it includes spatial effects on treated and untreated regions, so that the effects on both producing and surrounding non-producing regions can be properly estimated. The results indicate that the effects on the producing regions are 78% larger than if the effects on the surrounding areas were ignored. Moreover, the effects on the surrounding areas, typically ignored in other studies, are relevant, and almost as large as the effects on the producing areas.
We consider treatment effect estimation via a difference-in-difference approach for spatial data with local spatial interaction such that the potential outcome of observed units depends on their own treatment as well as on the treatment status of proximate neighbors. We show that under standard assumptions (common trend and ignorability) a straightforward spatially explicit version of the benchmark difference-in-differences regression is capable of identifying both direct and indirect treatment effects. We demonstrate the finite sample performance of our spatial estimator via Monte Carlo simulations.
In this empirical analysis, we estimate the impacts of property-tax delinquency, vacancy, and foreclosures on the value of neighboring homes. We demonstrate that these externalities differ in high- and low-poverty submarkets. Numerous studies have estimated the externality of foreclosures. These papers theorize that the foreclosure impact works partially through creating vacant and neglected homes. To our knowledge, this is only the second attempt to estimate the impact of vacancy itself and the first to use tax-delinquency as a measure of property neglect. We link vacancy observations from Postal Service data with property-tax delinquency and sales data from Cuyahoga County, Ohio. We find that an additional property within 500 ft that is vacant or delinquent reduces a home’s selling price by 1 to 2%. In low-poverty submarkets, the negative impact of a home that is both vacant and delinquent is −4.6%. Low-poverty submarkets penalize a sale near a tax-current recent foreclosure by 4 to 8%. In high-poverty submarkets, we observe positive correlations of sale prices with vacant foreclosures. This may reflect lenders selectively foreclosing only on relatively well-maintained properties.
This study assesses the impact of proximity to light rail transit stations on residential property values in Buffalo, New York, where light rail has been in service for 20 years, but population is declining and ridership is decreasing. Hedonic models are constructed of assessed value for residential properties within half a mile of 14 light rail stations and independent variables are included that describe property characteristics, neighbourhood characteristics and locational amenities. The model suggests that, for homes located in the study area, every foot closer to a light rail station increases average property values by 0.99 (using network distance). Consequently, a home located within one-quarter of a mile radius of a light rail station can earn a premium of $1300-3000, or 2-5 per cent of the city's median home value. Model results further suggest that three independent variables-the number of bathrooms, size of the parcel and location on the East side or West side of Buffalo-are more influential than rail proximity in predicting property values. Individual regression models for each of the light rail system's 14 stations suggest that effects are not felt evenly throughout the system. Proximity effects are positive in high-income station areas and negative in low-income station areas. An analysis of the actual walking distance to stations (along the street network) versus the perceived proximity to stations (measured by straight-line distance) reveals that the results are statistically more significant in the network distance than the straight-line distance model, but the effects are greater in the straight-line distance model, which suggests that apparent proximity to rail stations is an added locational advantage compared with physical walking distance to the station.
A flood of landlord-abandoned property fell to city ownership in New York; in response, the city developed programs transferring ownership to tenants, community groups, and screened landlords. A study of tenants in buildings sold through those programs revealed different patterns of response among the more successful cooperatives, co-ops still in crisis, and rental buildings; there were some similarities as well. Gender, race, and age affected tenant response. We conducted 87 intensive interviews, primarily with black Harlem residents, used additional data from 131 survey respondents, and then developed a Community-Household Model based on resource sharing among households, combined with community and government supports. We discuss the implications of the model for planning practice.
Economic decline has led to a new wave of population decline throughout the US, meaning more and more cities are shrinking. Growing interest in using smart decline principles to respond to shrinkage has been met with controversy in cities such as Detroit and Cleveland. This paper advances a foundational theory of smart decline that takes as its starting point discussions of ethics, equity, and social justice in the planning and political theory literature, but is well grounded in observations of successful smart decline practice.
Vacant and abandoned property is increasingly recognized as a significant barrier to the revitalization of central cities. This study sheds some light on the nature of the property abandonment problem and on current city efforts to address it. It is based upon the findings of a survey of the 200 most populous central cities in the United States, conducted during the summer and fall of 1997, and on follow-up interviews with a portion of the survey population, conducted during the summer of 1998. The findings of the survey and interviews indicate that vacant and abandoned property is perceived as a significant problem by elected and appointed officials in the nation's largest central cities. This type of property affects many aspects of community life, including housing and neighborhood vitality, crime prevention efforts, and commercial district vitality. Single- and multi-family housing, retail properties and vacant land are the most problematic types of vacant and abandoned property for most cities. Cities use a variety of techniques to address this problem, including aggressive code enforcement, tax foreclosure, eminent domain, and cosmetic improvements. One-third of the cities surveyed use a variety of other innovative tools to combat the vacant and abandoned property problem. Nevertheless, current efforts to combat the problem suffer from a number of shortcomings that are described in the article.
The tax that a taxpayer wishes to evade is determined on the basis of his perception of the fairness of his fiscal treatment, with respect to both governmental supply of public goods and the perceived behaviour of other taxpayers. The coercive powers of the State and the taxpayer's attitude toward risk determine the extent to which this desired level is undertaken in practice. This approach is able to produce implications for the relationship between public expenditure, tax rates and tax evasion which are more consistent with empirical evidence than the results of the conventional portfolio choice approach.
This paper discusses the bias that results from using nonrandomly selected samples to estimate behavioral relationships as an ordinary specification error or "omitted variables" bias. A simple consistent two stage estimator is considered that enables analysts to utilize simple regression methods to estimate behavioral functions by least squares methods. The asymptotic distribution of the estimator is derived.
Landlord abandonment of rental housing has affected many American cities since the 1960's. Because of data limitations, there have been few empirical analyses of the determinants of housing abandonment. In this paper, we use a rich database that contains information on individual residential properties in New York City to estimate a reduced form model of owner abandonment. We model an owner's decision to abandon his or her property as being similar to an investor's decision to exercise a put option on a financial instrument. When required to pay delinquent taxes, a wealth-maximizing landlord has an incentive to cede ownership of his or her residential property when the value of all outstanding liens exceeds the property's market value. Estimates from the model are used to examine whether empirical evidence supports this option model of abandonment.
Global Context. Shrinking Cities
- P Oswalt
- T Rieniets