The global financial crisis of 2007–2009 helped usher in a stronger consensus about the central role that housing plays in shaping economic activity, particularly during large boom and bust episodes. The latest research regards the causes, consequences, and policy implications of housing crises with a broad focus that includes empirical and structural analysis, insights from the 2000s experience in the United States, and perspectives from around the globe. Even with the significant degree of heterogeneity in legal environments, institutions, and economic fundamentals over time and across countries, several common themes emerge. Research indicates that fundamentals such as productivity, income, and demographics play an important role in generating sustained movements in house prices. While these forces can also contribute to boom-bust episodes, periods of large house price swings often reflect an evolving housing premium caused by financial innovation and shifts in expectations, which are in turn amplified by changes to the liquidity of homes. Regarding credit, the latest evidence indicates that expansions in lending to marginal borrowers via the subprime market may not be entirely to blame for the run-up in mortgage debt and prices that preceded the 2007–2009 financial crisis. Instead, the expansion in credit manifested by lower mortgage rates was broad-based and caused borrowers across a wide range of incomes and credit scores to dramatically increase their mortgage debt. To whatever extent changing beliefs about future housing appreciation may have contributed to higher realized house price growth in the 2000s, it appears that neither borrowers nor lenders anticipated the subsequent collapse in house prices. However, expectations about future credit conditions—including the prospect of rising interest rates—may have contributed to the downturn. For macroeconomists and those otherwise interested in the broader economic implications of the housing market, a growing body of evidence combining micro data and structural modeling finds that large swings in house prices can produce large disruptions to consumption, the labor market, and output. Central to this transmission is the composition of household balance sheets—not just the amount of net worth, but also how that net worth is allocated between short term liquid assets, illiquid housing wealth, and long-term defaultable mortgage debt. By shaping the incentive to default, foreclosure laws have a profound ex-ante effect on the supply of credit as well as on the ex-post economic response to large shocks that affect households’ degree of financial distress. On the policy front, research finds mixed results for some of the crisis-related interventions implemented in the U.S. while providing guidance for future measures should another housing bust of similar or greater magnitude reoccur. Lessons are also provided for the development of macroprudential policy aimed at preventing such a future crisis without unduly constraining economic performance in good times.
Carlos Garriga and Aaron Hedlund
Ching-mu Chen and Shin-Kun Peng
For research attempting to investigate why economic activities are distributed unevenly across geographic space, new economic geography (NEG) provides a general equilibrium-based and microfounded approach to modeling a spatial economy characterized by a large variety of economic agglomerations. NEG emphasizes how agglomeration (centripetal) and dispersion (centrifugal) forces interact to generate observed spatial configurations and uneven distributions of economic activity. However, numerous economic geographers prefer to refer to the term new economic geographies as vigorous and diversified academic outputs that are inspired by the institutional-cultural turn of economic geography. Accordingly, the term geographical economics has been suggested as an alternative to NEG. Approaches for modeling a spatial economy through the use of a general equilibrium framework have not only rendered existing concepts amenable to empirical scrutiny and policy analysis but also drawn economic geography and location theories from the periphery to the center of mainstream economic theory. Reduced-form empirical studies have attempted to test certain implications of NEG. However, due to NEG’s simplified geographic settings, the developed NEG models cannot be easily applied to observed data. The recent development of quantitative spatial models based on the mechanisms formalized by previous NEG theories has been a breakthrough in building an empirically relevant framework for implementing counterfactual policy exercises. If quantitative spatial models can connect with observed data in an empirically meaningful manner, they can enable the decomposition of key theoretical mechanisms and afford specificity in the evaluation of the general equilibrium effects of policy interventions in particular settings. Several decades since its proposal, NEG has been criticized for its parsimonious assumptions about the economy across space and time. Therefore, existing challenges still require theoretical and quantitative models on new microfoundations pertaining to the interactions between economic agents across geographical space and the relationship between geography and economic development.
Urban sprawl in popular sources is vaguely defined and largely misunderstood, having acquired a pejorative meaning. Economists should ask whether particular patterns of urban land use are an outcome of an efficient allocation of resources. Theoretical economic modeling has been used to show that more not less, sprawl often improves economic efficiency. More sprawl can cause a reduction in traffic congestion. Job suburbanization can generally increase sprawl but improves economic efficiency. Limiting sprawl in some cities by direct control of the land use can increase sprawl in other cities, and aggregate sprawl in all cities combined can increase. That urban population growth causes more urban sprawl is verified by empirically implemented general equilibrium models, but—contrary to common belief—the increase in travel times that accompanies such sprawl are very modest. Urban growth boundaries to limit urban sprawl cause large deadweight losses by raising land prices and should be seen to be socially intolerable but often are not. It is good policy to use corrective taxation for negative externalities such as traffic congestion and to implement property tax reforms to reduce or eliminate distortive taxation. Under various circumstances such fiscal measures improve welfare by increasing urban sprawl. The flight of the rich from American central cities, large lot zoning in the suburbs, and the financing of schools by property tax revenues are seen as causes of sprawl. There is also evidence that more heterogeneity among consumers and more unequal income distributions cause more urban sprawl. The connections between agglomeration economies and urban sprawl are less clear. The emerging technology of autonomous vehicles can have major implications for the future of urban spatial structure and is likely to add to sprawl.