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Brookings-Wharton Papers on Urban Affairs 2006
Brookings Institution Press
Copyright © 2006
Brookings Institution Press
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Chapter One Editors' Summary
Brookings-Wharton Papers on Urban Affairs presents new research on urban economics to a broad audience of interested policy analysts and researchers. The papers and comments contained in this volume, the seventh in the series, were presented at a December 8-9, 2005, conference at the Brookings Institution. The papers treat a range of issues examined by contemporary urban economists, including the effects of population growth and changing income inequality on neighborhood segregation, the economic gains from creating express lanes and charging congestion prices on busy expressways, recent trends in the school achievement gap between white and black youngsters, the impact of neighborhood poverty on barriers to employment, the potential benefits of restructuring local property taxes, and the effects of land use restrictions and jurisdictional fragmentation on sprawl and the price of housing.
U.S. income inequality rose sharply after 1979, increasing the gap between America's rich and poor. Tara Watson examines some effects of this development on the income segregation of urban and suburban neighborhoods in "Metropolitan Growth, Inequality, and Neighborhood Segregation by Income." Watson begins by observing that neighborhood segregation is particularly malleable when the local housing stock is first built. It is more costly to change the physical characteristics and distribution of amenities after housing has already been constructed. Neighborhoods built when the local income distribution is comparatively equal may reflect this reality. Many neighborhoods in a metropolitan area may have a similar average level of amenities, and the distribution of physical amenities may be similar across a large proportion of neighborhoods. However, an unequal income distribution will give metropolitan residents unequal access to housing amenities. High-income residents can afford dwellings with better amenities, including neighborhood attractions such as safe streets, good schools, and well-maintained parks.
Depending on the connection between residents' incomes and their tastes for housing amenities, it is easy to imagine that higher income inequality will be associated with greater income segregation across neighborhoods. Increased inequality can boost residential segregation in both direct and indirect ways. As incomes grow more unequal, rich and poor households will be less willing or able to spend the same amount of money to live in the same neighborhood. As less-affluent households become more concentrated in selected neighborhoods, there may be feedback effects on neighborhood amenities, further reducing the attractiveness of neighborhoods from which well-to-do households have moved. Watson notes that housing markets can easily accommodate changing preferences induced by changes in the income distribution when the metropolitan population is climbing rapidly. Increased inequality translates into newly built neighborhoods in which there is greater sorting by households' income ranks. On the other hand, in metropolitan areas experiencing population decline, the increased demand for residential segregation may not be large enough to overcome the high cost of retrofitting old homes or building new ones. A big shock in inequality may be needed in stagnant or declining areas to cause a shift in residential segregation patterns.
Watson finds a U-shaped relationship between the rise of residential segregation in metropolitan areas and population growth. The greatest changes in income segregation have occurred in distressed areas with stagnant or declining populations and in areas with rapidly growing populations. There typically has been less change in residential segregation in areas with moderate rates of population growth. Watson also finds support for some of her predictions on the relationship between changing income inequality and residential segregation patterns. As expected, higher income inequality is associated with higher levels of residential segregation by income. Also as predicted, rising inequality has a larger effect on segregation in rapidly growing areas compared with areas with stagnant or declining populations. Large increases in segregation are accommodated with higher-than-expected housing construction in distressed areas, but unexpectedly high rates of new construction are not needed in areas with big population gains. Finally, income segregation tends to be persistent within a metropolitan area, and the persistence is more pronounced in cities with an older housing stock.
Few urban roads in the United States impose charges on the motorists who use them. Like many public goods that are provided without charge, urban roads tend to be overused, particularly during rush hour when a large number of drivers want access to a limited number of streets and highways. One by-product of overuse is traffic congestion, which greatly reduces motorists' average speed. Even though drivers do not pay tolls for using most streets and highways, they do suffer inconvenience as a result of longer commutes at peak driving times. Economists have long argued that the traffic congestion and its attendant welfare costs can be slashed by charging drivers for the privilege of using roads, especially during peak commuting hours. This suggestion is widely unpopular among voters as well as policymakers, who are responsible for managing the urban highway network. As an alternative, planners have set aside special limited-access highway lanes for vehicles containing two or more passengers. In some cases, motorists who are willing to pay a toll are also permitted to use these high-speed lanes.
In "Differentiated Road Pricing, Express Lanes, and Carpools: Exploiting Heterogeneous Preferences in Policy Design," Kenneth A. Small, Clifford Winston, and Jia Yan examine the potential welfare gains that can be achieved using sensible pricing of highway access. In order to assess the political acceptability of different kinds of pricing schemes, the analysts also determine the distribution of welfare gains and losses across different classes of motorists. The authors collected information from drivers who use a ten-mile stretch of California State Route 91 to form estimates of motorists' willingness to pay for faster and more reliable travel times to their rush-hour destinations. This busy Orange County highway has four free lanes and two express lanes in each direction. Drivers who use the express lanes need to establish a financial account and carry a special electronic instrument in order to pay the toll, which varies hourly over the day. At the time of the authors' survey, vehicles containing three or more passengers were able to use the express lanes at a substantial discount.
The authors collected information on motorists' actual driving choices (their revealed preference decisions) as well as their stated preferences under a variety of hypothetical pricing arrangements. Using this information in a sophisticated statistical analysis, the authors examined three interrelated decisions: the decision by motorists to obtain the electronic fare collection instrument, the decision to use the express lane for a particular trip, and the decision to carry two or more additional passengers in order to qualify for a trip discount. The authors assume that motorists' choices are affected by their socioeconomic status as well as the characteristics of the planned travel, including the trip's total distance, the toll, and expected travel time as well as the reliability of the expected travel time across the alternative travel options. After estimating the average preference parameters and the distribution of preferences in the sampled population, the authors use statistical simulation to compare motorists' choices and well-being under alternative highway pricing regimes.
Among the policy options that the authors examine are the standard high-occupancy vehicle (HOV) policy, which limits express lane use to vehicles containing three or more passengers, and a high-occupancy toll (HOT) policy, which permits toll-paying vehicles containing two or fewer riders to use the HOV lanes. The authors also evaluate the impacts of a policy that assesses the same express-lane toll on all vehicles, regardless of the number of passengers they carry. Finally, they consider policies where tolls are charged both for the use of the express lane and other lanes, but with a higher toll in the express lanes. They consider a variant of this last policy in which high-occupancy vehicles can travel at no charge in either set of lanes. In all cases, the authors use the results of their statistical analysis to select the tolls that maximize the social welfare of the sampled drivers.
Not surprisingly, the policy that imposes rush-hour tolls on drivers in both express lanes and other lanes is the regime that yields the highest social welfare. Traveling times improve markedly, both in the express lanes and in the more congested lanes, and the reliability of travel times improves. However, this policy also causes many individual drivers, especially those from lower-income groups, to suffer losses in consumer welfare. The congestion effects of busy highways are less costly to these drivers than the tolls they would have to pay if highway prices were set so as to maximize social welfare. If the two-toll policy were modified to allow free use of both sets of lanes by high-occupancy vehicles, the welfare gains would also be quite sizable. Again, however, many motorists would consider themselves worse off, because the improvements in travel time and reliability would not be large enough to offset the higher weekly cost of paying highway tolls. The authors' results show why HOV and HOT policies are more politically acceptable than the more efficient two-toll pricing policy. Even though the two-toll policy produces considerably bigger reductions in traffic congestion and commuting time, it causes many travelers to suffer high and very unequal losses in consumer welfare. Furthermore, the largest losses are suffered by drivers in the lowest income groups, because they assign the lowest valuation to their own time and to improvements in travel-time reliability.
The authors investigate a compromise two-toll policy that has tolls below the socially optimal level in order to overcome some of the problems of the other policies. Specifically, it provides more benefits overall than the HOV or HOT lane policies, but compared to the optimal two-toll policy it greatly reduces the percentage of drivers who suffer large welfare losses as a result of the policy change. The reason for this is that it takes greater advantage of consumers' varying preferences. It provides a choice between two quite different combinations of price and amount of congestion, while still lowering congestion for everyone compared to the situation with no express lanes.
One of the toughest challenges facing American schools is the achievement gap between black and white children. Recent tabulations by economists Ronald G. Fryer and Steven D. Levitt cast light on the size and persistence of this gap among students in the early years of schooling. When youngsters enter kindergarten, the average language arts score of black children is already 0.40 standard deviations below the average score obtained by white kindergartners. The test-score gap is even larger (0.60 standard deviations) in tests of mathematical reasoning. Even more distressing is Fryer and Levitt's finding that the test-score gap increases steadily in each of the first four years of primary school, rising by approximately 0.10 standard deviations a year. Virtually none of the initial gap or its year-on-year increases can be explained by traditional measures of school resources. That is, the achievement differences between black and white schoolchildren remain essentially the same even when the researchers take account of the differences in school resources available to black and white youngsters.
In their paper in this volume, Richard J. Murnane, John B. Willett, Kristen L. Bub, and Kathleen McCartney replicate and extend Fryer and Levitt's earlier analysis. Their article, "Understanding Trends in the Black-White Achievement Gaps during the First Years of School," is based on a much richer source of information about the family backgrounds of schoolchildren and the classroom environments in which they are educated. When the authors use the same data file analyzed in the earlier study, they duplicate Fryer and Levitt's findings. However, when they replicate Fryer and Levitt's analytical methods using a different and richer data set, their findings differ in three important ways from the earlier results. First, Murnane and his coauthors show that family background variables, which apparently explain much of the black-white achievement gap in kindergarten in the Fryer and Levitt data set, are less successful in explaining the gap in the alternative, richer data file. As Murnane and his colleagues point out, this finding is consistent with most past research on the influence of family background variables. Even after analysts account for the influence of family income and parental education on kindergartners' achievement, most previous studies find there is an important unexplained difference between the achievement scores of black and white school children. Murnane and his coauthors speculate that Fryer and Levitt obtain a different result because they examine results from achievement tests focusing on a very narrow set of skills. When broader measures of achievement are used, the black-white test score gap cannot be explained using simple measures of family background.
Second, Murnane and his coauthors fail to find any evidence in their alternative data file of a substantial rise in the black-white achievement gap in the first few years of primary school. In fact, the gap actually declines on tests of mathematical reasoning. Although the achievement gap in language arts grows, the increase is much smaller than found in the data set analyzed by Fryer and Levitt. Murnane and his colleagues find little evidence that the resources available to black and white schoolchildren differ noticeably. In one respect, however, there is a difference in the classroom environment. Compared with white schoolchildren, black youngsters are more likely to be taught by a teacher with very little classroom experience, a difference that is apparent in both data sets. It has disquieting implications for student achievement, since most studies find that teachers with little classroom experience are significantly less effective in boosting student achievement than teachers with more experience. This finding suggests one way to improve black youngsters' achievement is to increase the percentage of students who are taught by experienced teachers.
The authors find no evidence for the idea that smaller class size will boost the absolute or relative performance of black schoolchildren. Nor do they find any evidence showing that a master's degree improves the effectiveness of classroom teachers. Based on their analysis of the richer data set, they do find evidence that teachers can improve youngsters' math scores by devoting more time to math instruction, but the authors acknowledge this lesson will be hard for school administrators to put into practice. Legislators and school managers can adopt policies that change average class size or increase the percentage of classroom teachers who have master's degrees, but it is much harder for them to influence teachers' time allocation in the classroom.
High unemployment and low rates of labor force participation are common in lower-income urban neighborhoods. A number of theories have been advanced to explain the exceptionally low employment rates of residents in high-poverty neighborhoods. One theory, usually dubbed the spatial mismatch hypothesis, explains low employment as a by-product of the physical isolation of high-poverty neighborhoods. According to this theory, residents of low-income neighborhoods are geographically isolated from areas in a metropolitan region where job opportunities are plentiful. Since many residents in these neighborhoods do not own a car, they must rely on public transportation to get to work. If job openings are not easily accessible along public transportation routes, neighborhood residents may find it hard to locate or hold on to a job. Another theory explains low employment rates as a consequence of the social norms that prevail in many low-income communities. People who live in high-poverty neighborhoods may be isolated from norms elsewhere in the metropolitan area-norms that place very high valuation on the importance of holding a steady job. If their social contacts are limited to people in the immediate neighborhood who are also jobless, residents of high-poverty neighborhoods may be deprived of information or job referrals that can be helpful in finding employment.
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