Carlos Garriga and Aaron Hedlund
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.
Anthony J. Venables
Economic activity is unevenly distributed across space, both internationally and within countries. What determines this spatial distribution, and how is it shaped by trade? Classical trade theory gives the insights of comparative advantage and gains from trade but is firmly aspatial, modeling countries as points and trade (in goods and factors of production) as either perfectly frictionless or impossible. Modern theory places this in a spatial context in which geographical considerations influence the volume of trade between places. Gravity models tell us that distance is important, with each doubling of distance between places halving the volume of trade. Modeling the location decisions of firms gives a theory of location of activity based on factor costs (as in classical theory) and also on proximity to markets, proximity to suppliers, and the extent of competition in each market. It follows from this that—if there is a high degree of mobility—firms and economic activity as a whole may tend to cluster, providing an explanation of observed spatial unevenness. In some circumstances falling trade barriers may trigger the deindustrialization of some areas as activity clusters in fewer places. In other circumstances falling barriers may enable activity to spread out, reducing inequalities within and between countries. Research over the past several decades has established the mechanisms that cause these changes and placed them in full general equilibrium models of the economy. Empirical work has quantified many of the important relationships. However, geography and trade remains an area where progress is needed to develop robust tools that can be used to inform place-based policies (concerning trade, transport, infrastructure, and local economic development), particularly in view of the huge expenditures that such policies incur.
Despite the drop in transport and commuting costs since the mid-19th century, sizable and lasting differences across locations at very different spatial scales remain the most striking feature of the space-economy. The main challenges of the economics of agglomeration are therefore (a) to explain why people and economic activities are agglomerated in a few places and (b) to understand why some places fare better than others.
To meet these challenges, the usual route is to appeal to the fundamental trade-off between (internal and external) increasing returns and various mobility costs. This trade-off has a major implication for the organization of the space-economy: High transport and commuting costs foster the dispersion of economic activities, while strong increasing returns act as a strong agglomeration force.
The first issue is to explain the existence of large and persistent regional disparities within nations or continents. At that spatial scale, the mobility of commodities and production factors is critical. By combining new trade theories with the mobility of firms and workers, economic geography shows that a core periphery structure can emerge as a stable market outcome.
Second, at the urban scale, cities stem from the interplay between agglomeration and dispersion forces: The former explain why firms and consumers want to be close to each other whereas the latter put an upper limit on city sizes. Housing and commuting costs, which increase with population size, are the most natural candidates for the dispersion force. What generates agglomeration forces is less obvious. The literature on urban economics has highlighted the fact that urban size is the source of various benefits, which increase firm productivity and consumer welfare.
Within cities, agglomeration also occurs in the form of shopping districts where firms selling differentiated products congregate. Strategic location considerations and product differentiation play a central role in the emergence of commercial districts because firms compete with a small number of close retailers.
Pei-Ju Liao and Chong Kee Yip
In the past century, many developing countries have experienced rapid economic development, which is usually associated with a process of structural transformation and urbanization. Rural–urban migration, shifting the labor force from less productive agricultural sectors to more productive industrial sectors in cities, plays an important role in the growth process and thus has drawn economists’ attention. For instance, it is recognized that one of the important sources of China’s growth miracle is rural–urban migration.
At the early stage of economic development, an economy usually relies on labor-intensive industries for growth. Rural–urban migrants thus provide the necessary labor force to urban production. Since they are more productive in industrial sectors than in agricultural sectors, aggregate output increases and economic growth accelerates. In addition, abundant migrants affect the rates of return to capital by changing the capital–labor ratio. They also change the skill composition of the urban labor force and hence the relative wage of skilled to unskilled workers. Therefore, rural–urban migration has wide impacts on growth and income distribution of the macroeconomy.
What are the forces that drive rural–urban migration? It is well understood that cities attract rural migrants because of better job opportunities, better career prospects, and higher wages. Moreover, enjoying better social benefits such as better medical care in cities is another pull factor that initiates rural–urban migration. Finally, agricultural land scarcity in the countryside plays an important role on the push side for moving labor to cities.
The aforementioned driving forces of rural–urban migration are work-based. However, rural–urban migration could be education-based, which is rarely discussed in the literature. In the past decade, it has been proposed that cities are the places for accumulating human capital in work. It is also well established that most of the high-quality education institutions (including universities and specialized schools for art and music) are located in urban areas. A youth may first move to the city to attend college and then stay there for work after graduation. From this point of view, work-based migration does not paint the whole picture of rural–urban migration. In this article, we propose a balanced view that both the work-based and education-based channels are important to rural–urban migration. The migration story could be misleading if any of them is ignored.
Albert N. Link and John T. Scott
Science parks, also called research parks, technology parks, or technopolis infrastructures, have increased rapidly in number as many countries have adopted the approach of bringing research-based organizations together in a park. A science park’s cluster of research and technology-based organizations is often located on or near a university campus. The juxtaposition of ongoing research of both the university and the park tenants creates a two-way flow of knowledge; knowledge is transferred between the university and firms, and all parties develop knowledge more effectively because of their symbiotic relationship.
Theory and evidence support the belief that the geographic proximity provided to the participating organizations by a science park creates a dynamic cluster that accelerates economic growth and international competitiveness through the innovation-enabling exchanges of knowledge and the transfer of technologies. The process of creating innovations is more efficient because of the agglomeration of research and technology-based firms on or near a university campus. The proximity of a park to multiple sources of knowledge provides greater opportunities for the creation and acquisition of knowledge, especially tacit knowledge, and the geographic proximity therefore reduces the search and acquisition costs for that knowledge.
The clustering of multiple research and technology-based organizations within a park enables knowledge spillovers, and with greater productivity from research resources and lower costs, prices for new technologies can be lower, stimulating their use and regional development and growth. In addition to the clustering of the organizations within a park, the geographic proximity of universities affiliated with a park matters too. Evidence shows that a park’s employment growth is greater, other things being the same, when its affiliated university is geographically closer, although evidence suggests that effect has lessened in the 21st century because of the information and communications technology revolution. Further stimulating regional growth, university spin-off companies are more prevalent in a park when it is geographically closer to the affiliated university. The two-way flow of knowledge enabled by clusters of research and technology-based firms in science parks benefits firms located on the park and the affiliated universities.
Understanding the mechanisms by which the innovative performance of research and technology-based organizations is increased by their geographic proximity in a science park is important for formulating public and private sector policies toward park formations because successful national innovation systems require the two-way knowledge flow, among firms in a park and between firms and universities, that is fostered by the science park infrastructure.
The geography of economic activity refers to the distribution of population, production, and consumption of goods and services in geographic space. The geography of growth and development refers to the local growth and decline of economic activity and the overall distribution of these local changes within and across countries. The pattern of growth in space can vary substantially across regions, countries, and industries. Ultimately, these patterns can help explain the role that spatial frictions (like transport and migration costs) can play in the overall development of the world economy.
The interaction of agglomeration and congestion forces determines the density of economic activity in particular locations. Agglomeration forces refer to forces that bring together agents and firms by conveying benefits from locating close to each other, or for locating in a particular area. Examples include local technology and institutions, natural resources and local amenities, infrastructure, as well as knowledge spillovers. Congestion forces refer to the disadvantages of locating close to each other. They include traffic, high land prices, as well as crime and other urban dis-amenities. The balance of these forces is mediated by the ability of individuals, firms, good and services, as well as ideas and technology, to move across space: namely, migration, relocation, transport, commuting and communication costs. These spatial frictions together with the varying strength of congestion and agglomeration forces determines the distribution of economic activity. Changes in these forces and frictions—some purposefully made by agents given the economic environment they face and some exogenous—determine the geography of growth and development.
The main evolution of the forces that influence the geography of growth and development have been changes in transport technology, the diffusion of general-purpose technologies, and the structural transformation of economies from agriculture, to manufacturing, to service-oriented economies. There are many challenges in modeling and quantifying these forces and their effects. Nevertheless, doing so is essential to evaluate the impact of a variety of phenomena, from climate change to the effects of globalization and advances in information technology.
Charles Ka Yui Leung and Cho Yiu Joe Ng
This article summarizes research on the macroeconomic aspects of the housing market. In terms of the macroeconomic stylized facts, this article demonstrates that with respect to business cycle frequency, there was a general decrease in the association between macroeconomic variables (MV), such as the real GDP and inflation rate, and housing market variables (HMV), such as the housing price and the vacancy rate, following the global financial crisis (GFC). However, there are macro-finance variables, such as different interest rate spreads, that exhibited a strong association with the HMV following the GFC. For the medium-term business cycle frequency, some but not all patterns prevail. These “new stylized facts” suggest that a reconsideration and refinement of existing “macro-housing” theories would be appropriate. This article also provides a review of the corresponding academic literature, which may enhance our understanding of the evolving macro-housing–finance linkage.
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.