Person:

Glaeser, Edward

In this article the author examines aspects of U.S. housing policy in the aftermath of the global financial crisis of 2008-09. The author notes that between the years 2000 and 2010 the U.S. housing market underwent extremes of prosperity and financial failure as home prices rose precipitously, and then fell following the financial crisis. A number of topics are addressed including fluctuations in the construction industry, the sharp increase in home prices in Las Vegas, Nevada, and Phoenix, Arizona, and the tax deduction for mortgage interest on homes.

This paper reviews recent academic work on the spatial concentration of entrepreneurship and innovation in the United States. We discuss rationales for the agglomeration of these activities and the economic consequences of clusters. We identify and discuss policies that are being pursued in the United States to encourage local entrepreneurship and innovation. While arguments exist for and against policy support of entrepreneurial clusters, our understanding of what works and how it works is quite limited. The best path forward involves extensive experimentation and careful evaluation.

The most fundamental fact about rental housing in the United States is that rental units are overwhelmingly in multifamily structures. This fact surely reflects the agency problems associated with renting single-family dwellings, and it should influence all discussions of rental housing policy. Policies that encourage homeowning are implicitly encouraging people to move away from higher density living; policies that discourage renting are implicitly discouraging multifamily buildings. Two major distortions shape the rental housing market, both of which are created by the public sector. Federal pro-homeownership policies, such as the home mortgage interest deduction, weaken the rental market and the cities where rental markets thrive. Local policies that discourage tall buildings likewise ensure that Americans have fewer rental options. The economic vitality of cities and the environmental consequences of large suburban homes with long commutes both support arguments for reducing these distortions.

According to a standard principle in free speech law, the remedy for falsehoods is "more speech," not enforced silence. But empirical research demonstrates that corrections of falsehoods can actually backfire, by increasing people’s commitment to their inaccurate beliefs, and that presentation of balanced information can promote polarization, thus increasing preexisting social divisions. We attempt to explain these apparently puzzling phenomena by reference to what we call Asymmetric Bayesianism: purported corrections may be taken to establish the truth of the proposition that is being denied, and the same information can have diametrically opposite effects if those who receive it have opposing antecedent convictions. In our primary model, recipients whose beliefs are buttressed by the message, or a relevant part, rationally believe that it is true, while recipients whose beliefs are at odds with that message, or a relevant part, rationally believe that the message is false (and may reflect desperation). We also show that the same information can activate radically different memories and associated convictions, thus producing polarized responses to that information, or what we call a memory boomerang. These explanations help account for the potential influence of "surprising validators." Because such validators are credible to the relevant audience, they can reduce the likelihood of Asymmetric Bayesianism, thus ensuring that corrections are persuasive and also promoting agreement.

For over thirty years, Republican and Democratic presidents have required executive agencies to assess the costs and benefits of significant regulations, and to proceed only if the benefits justify the costs (to the extent permitted by law). The goals of the resulting processes have been to constrain unjustified regulation, to promote interagency coordination, and to allow a degree of centralized management of what can be a cumbersome bureaucratic apparatus. Unfortunately, state and local governments sometimes impose costly requirements, undisciplined by careful analysis of their likely consequences. New institutions at the state level, producing such analysis, could be highly beneficial, replacing processes sometimes driven by anecdotes, dogmas, emotions, and interest-group pressures with a form of Regulatory Moneyball.

OBJECTIVES: We explain why traits of interest to behavioral scientists may have a genetic architecture featuring hundreds or thousands of loci with tiny individual effects rather than a few with large effects and why such an architecture makes it difficult to find robust associations between traits and genes. METHODS: We conducted a genome-wide association study at 2 sites, Harvard University and Union College, measuring more than 100 physical and behavioral traits with a sample size typical of candidate gene studies. We evaluated predictions that alleles with large effect sizes would be rare and most traits of interest to social science are likely characterized by a lack of strong directional selection. We also carried out a theoretical analysis of the genetic architecture of traits based on R.A. Fisher's geometric model of natural selection and empirical analyses of the effects of selection bias and phenotype measurement stability on the results of genetic association studies. RESULTS: Although we replicated several known genetic associations with physical traits, we found only 2 associations with behavioral traits that met the nominal genome-wide significance threshold, indicating that physical and behavioral traits are mainly affected by numerous genes with small effects. CONCLUSIONS: The challenge for social science genomics is the likelihood that genes are connected to behavioral variation by lengthy, nonlinear, interactive causal chains, and unraveling these chains requires allying with personal genomics to take advantage of the potential for large sample sizes as well as continuing with traditional epidemiological studies.

Measures of entrepreneurship, such as average establishment size and the prevalence of start-ups, correlate strongly with employment growth across and within metropolitan areas, but the endogeneity of these measures bedevils interpretation. Chinitz (1961) hypothesized that coal mines near Pittsburgh led that city to specialization in industries, like steel, with significant scale economies and that those big firms led to a dearth of entrepreneurial human capital across several generations. We test this idea by looking at the spatial location of past mines across the United States: proximity to historical mining deposits is associated with bigger firms and fewer start-ups in the middle of the 20th century. We use mines as an instrument for our entrepreneurship measures and find a persistent link between entrepreneurship and city employment growth; this connection works primarily through lower employment growth of start-ups in cities that are closer to mines. These effects hold in cold and warm regions alike and in industries that are not directly related to mining, such as trade, finance and services. We use quantile instrumental variable regression techniques and identify mostly homogeneous effects throughout the conditional city growth distribution.

Gary Becker, who died on 3 May 2014 at the age of 83, redefined economics both in its methodology and scope. He radically expanded the sphere of economic analysis. As the range of issues and especially data in economics increased over the last half century, Becker's approach became more and more relevant and modern. He was awarded the 1992 Nobel Prize in Economics for “having extended the domain of microeconomic analysis to a wide range of human behavior and interaction, including nonmarket behavior.”

This paper examines segregation in American cities from 1890 to 1990. From 1890 to 1940, ghettos were born as blacks migrated to urban areas and cities developed vast expanses filled with almost entirely black housing. From 1940 to 1970, black migration continued and the physical areas of the ghettos expanded. Since 1970, there has been a decline in segregation as blacks have moved into previously all‐white areas of cities and suburbs. Across all these time periods there is a strong positive relation between urban population or density and segregation. Data on house prices and attitudes toward integration suggest that in the mid‐twentieth century, segregation was a product of collective actions taken by whites to exclude blacks from their neighborhoods. By 1990, the legal barriers enforcing segregation had been replaced by decentralized racism, where whites pay more than blacks to live in predominantly white areas.

Like many other assets, housing prices are quite volatile relative to observable changes in fundamentals. If we are going to understand boom-bust housing cycles, we must incorporate housing supply. In this paper, we present a simple model of housing bubbles that predicts that places with more elastic housing supply have fewer and shorter bubbles, with smaller price increases. However, the welfare consequences of bubbles may actually be higher in more elastic places because those places will overbuild more in response to a bubble. The data show that the price run-ups of the 1980s were almost exclusively experienced in cities where housing supply is more inelastic. More elastic places had slightly larger increases in building during that period. Over the past five years, a modest number of more elastic places also experienced large price booms, but as the model suggests, these booms seem to have been quite short. Prices are already moving back towards construction costs in those areas.