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Collins, William and Katherine Shester, 2013, “Slum clearance and urban renewal in the United States

by Gini Li TP_LiGini

Collins, William and Katherine Shester, 2013, “Slum clearance and urban renewal in the United States: American Economic Journal: Applied Economics 5(1): 239-273.

Title 1 of the Housing Act of 1949 and Consequences

After World War II, American cities witnessed a substantial increase in slum growth. In 1941, the Federal Housing Administration and economists Guy Greer and Alvin Hansen published plans for urban redevelopment and slum elimination with federal aid. These objectives were seen as federal responsibilities because of the high financial and legal barriers for private organizations to organize large-scale redevelopment projects. Title I of the Housing Act of 1949 allowed urban renewal through federal subsidies for locally planned redevelopment projects, code enforcement, and rehabilitation efforts. The U.S. Urban Renewal Program faced controversy in issues such as the use of eminent domain, impact on the urban poor, destruction of neighborhoods, and destruction of historic buildings.

In the past, economists have tried to explain the effects of urban renewal programs through spatial equilibrium models. Roback’s (1982) model describes spatial equilibrium in terms of intercity dynamics and freely mobile workers, capital, and goods. In this model, local amenities are valued by both workers and firms, and will raise the equilibrium property values. Hornbeck and Keniston (2011) use a model to describe how cities rebuilt after fires experience higher values for buildings because of local externalities, plot consolidation, private investment, and new public infrastructure. This can happen because large fires, like urban renewal programs, remove the option for property owners to keep old buildings. Lastly, Schall (1976) shows through an intracity model that raising local housing quality might be unsustainable with public renewal projects.

Collins and Shester attempt to empirically analyze the effects of urban renewal programs on economic outcomes at the city-level through exploiting cross-place variation in urban renewal activity. Through their model and the context of the Rosen-Roback framework for spatial equilibrium, they found that cities with urban renewal programs had higher property values, income, and population growth in 1980.


Urban Renewal Programs and Economic Outcomes: the model and method

            This study improves previous studies on the impact of urban renewal projects on city-level economic development with the following added features:

1. Reducing bias in ordinary least square estimates through a variable that legally constrains cities’ ability to participate in the program

2. Utilizing a new data set that ranges from 1950-1980 for all cities with more than 25,000 residents.

3. Examining whether the effect of urban renewal on city-level economic outcomes worked primarily through the displacement of residents with low levels of human capital or through channels of economic growth. It uses data from the federal census for population and housing and from the U.S. Department of Housing and Urban Development’s Urban Renewal Directory for information on renewal efforts.[1]

The model seeks to explain the relationship between intensity of urban renewal projects, as represented by “grants approved” (URij), where i represents the city and j represents the census division, and economic outcomes in 1980 (Yij80). Additionally, it controls for census-division indicators and city-specific qualities through the variable dj.[2] An instrumental-variable strategy addresses endogeniety of funding and measurement error of URij, the measure of urban renewal intensity. Preprogram control variables (X¢ij50) include the quality, ownership, use and age of housing stock in 1950; demographics, size, and median educational attainment of the population in 1950; and employment characteristics, poverty level, and family income of the population in 1950. One would expect a positive b1 if cities that were similar in 1950 (before the implementation of urban renewal programs) had varying economic outcomes in 1980 that were dependent on the intensity of these programs (URij).

(1)                                           Yij80= a + b1URij + X¢ij50b2 + dj + uij80


Enabling Legislation as the Instrumental Variable

The level of deterioration in some cities is unobservable through the control variables in the basic model. If these types of cities implemented a large volume of urban renewal programs, the economic outcome in 1980 (Yij80) could be worse when compared to other cities, skewing the relationship between intensity of urban renewal programs and economic outcomes. In this scenario, the ordinary least squares coefficient is biased and would understate the impact of URij. The opposite could occur in which cities with high rates of investment in the 1950s also pursued many other urban renewal projects. In this case, they might have witnessed great economic outcomes in 1980, but the impact of federal urban renewal funding on that economic outcome is unclear. The authors attempt to address this problem through finding exogenous variation in urban renewal funding that can be attributed to differences in timing of state-enacted legislation. Because legislation that enables local governments to exercise eminent domain to acquire property for development was approved locally, urban renewal programs were not actually implemented uniformly in any given time period.

(2)                                           URij= g + t1Lij + X¢ij50t2 + lj + eij

X¢ij50in this equation is similar to the one in the first; it is a set of city-level characteristics in 1950. lj is similar to dj and acts as a set of census level controls for 1950. Lij represents each city’s “years of potential participation” in the federal urban renewal program. This is calculated by subtracting the year in which local enabling legislation was passed from 1974, the end of the program. If missing legislation actually did restrict cities from receiving federal grants, then t1would be a positive value. Results of this regression show that an additional year of eligibility for participation results in 9.71 additional dollars of grants per capita. The authors argue that this result is independent of local characteristics because adding the other control variables doesn’t significantly affect the value of t1, and it remains statistically significant.

With the assumption that local enabling legislation impacts the value of “intensity of urban renewal” as defined by the amount of federal grants received for urban renewal, the authors test the correlation between city-level economic outcome and enabling legislation in reduced form regressions. To challenge this assumption, they test the correlation between city-level outcomes (Yij80) and enabling legislation data (Lij) in rural areas. If this correlation exists, Lij represents more than just enabling legislation and therefore can’t be used as a proxy for the intensity of urban renewal projects. The results show no evidence of a relationship between urban renewal enabling legislation and outcomes in rural counties. This supports the authors’ assertion that the instrumental variable does not reflect unobserved differences across states in economic trends.



In 1980, urban renewal programs led to higher median incomes (2.4% increase for $100 per capita difference in grants) and median property values (6.9% increase for $100 per capita difference in grants) at a five percent significance level. The impact on employment rate and percentage of families in poverty is more imprecise, but the effects seem favorable. This research does not account for the impact that private investment has made on economic outcomes or the impact federal grants have on the intensity of private investment.


Robustness Tests

Other Urban Renewal Programs

To control for the impact of other urban renewal programs on the economic outcomes in 1980, the authors controlled for the number of units per capita of new public housing built under the Housing Act of 1949, application status under Johnson’s “Model Cities” program, and city level spending per capita on poverty reduction since 1966.

Quality of Local Governments

Using Moody’s city bond ratings for 1950 as a proxy for the fiscal quality and management quality of local governments, the authors created categories of cities with relatively high ratings, relatively low ratings, and no ratings. The results do not provide evidence that government quality affects economic outcomes.

Cross-state Differences in Support for Cities

The authors collected data on state aid given to city level governments in 1952 from a Bureau of Census publication, which expressed aid relative to the urban population’s size. They also controlled for differences in political conservativism through the percentage of votes for Barry Goldwater in 1964. The results are also vague and insignificant.

Shifts in the U.S. Economy

If secular change to the U.S. economy was correlated to the timing of enabling legislation, then the results for the instrumental variable is invalid. The authors created a control variable for three-digit state level industrial composition in 1950 with national level industry growth rates between 1950 and 1980. The results show that the results aren’t driven by shifts in the U.S. economy.

Without the Largest City in Each State

Large cities are more likely to be politically influential and be able to carry out federal grant programs independent of the timing of enabling legislation. Without the largest cities, the results are still similar to the baseline results and are still statistically significant. The same is true when the smallest cities were dropped.

Changing the Data Used in the Instrumental Variable

Even with two other data sets (one constructed from the earliest date of enabling legislation approval and one constructed from the latest date of enabling legislation approval from discordant legislative recordings), the results are close to the base results.


Application of Model in Multiple Time Periods

(3)                               Yijt = qt + p1tLijt + X¢ij50p2t + sjt + vijt

The equation above regresses city level outcomes (Yjit) in the years 1960, 1970, and 1980 on years of eligibility for urban renewal as of year t (Lijt). sjt represents census-division-by-year fixed effects and X¢ij50represents the standard set of control variables for 1950. The coefficients in this regression are allowed to change every year, so p1t shows the responsiveness of economic outcomes to eligibility for urban renewal at a point in time t. Results show that there is a strong relationship between urban renewal eligibility and property value in 1970, but not in 1960. This suggests that it takes time for real estate prices to adjust. However, there is a strong correlation between urban renewal eligibility and income and employment in 1960 and beyond.


Channels of Influence

After establishing that the intensity of urban renewal programs affect city-level economic outcomes, the authors try to figure out through which channel this occurred. One theory is that it drove away people of low human capital and essentially displaced them outside of the city. Another is that urban renewal creates a continuous virtuous cycle of organic economic growth. These two theories are not mutually exclusive, and the authors use the regression model (2) to see if urban renewal affected displacement proxies and growth proxies. If displacement were the main channel through which economic outcomes increased, then adding a displacement variable to the regression would decrease the value of b1. Findings suggest that this impact is small and imprecise when racial and educational attributes were used. However, growth proxies such as property prices, wages, and population is often linked with higher productivity in the Rosen-Roback model. For the authors, this suggests that increases in economic outcomes happen through the growth channel rather than the displacement channel.

In terms of policy, this is an important finding because it shows that federal funding has had a significant and positive impact on economic outcomes in American cities. This bolsters support for further steps in administering countrywide federal funding to address urban problems. However, it would be beneficial to distinguish between the most successful and least successful cities in this study, and figure out what factors increase potency of federal funding. This would be helpful in crafting future policy measures and increasing the efficiency of grant funding.


Works Cited

Hornbeck, Richard and Keniston, Daniel. Creative Destruction From the Great Boston Fire of 1872: Barriers to Urban Growth Illuminated. (draft), 2012.


Roback, Jennifer. “Wages, rents, and the quality of life.” The Journal of Political Economy (1982): 1257-1278.



Schall, Lawrence D. “Urban renewal policy and economic efficiency.” The American Economic Review 66.4 (1976): 612-628.



[1] This includes federal grants approved and disbursed for urban renewal projects and programs up until 1974.

[2] This encompasses 1950 value of Yij, city-level characteristics at the time of the federal program’s implementation, and indicator variables for nine census divisions.

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