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Soon a majority of the world’s population will live in cities. In 1950, 30 per cent of the world’s population lived in cities. By 2000, this fraction had grown to 47 per cent. It is predicted to rise to 60 per cent by 2030 (United Nations Population Division 2004). While the popular media focus on the growth of ‘mega-cities’, much urbanization occurs through the development of new cities and the growth of smaller metro areas (Henderson and Wang 2004).

People have migrated to cities in pursuit of better economic opportunities than are available in the countryside (Harris and Todaro 1970). In the past, urbanization has been viewed as representing a trade-off. Urban workers earned higher wages than rural residents but suffered from a lower quality of life. In the 1880s, the average urbanite in the United States had a life expectancy ten years lower than that of the average rural resident (Haines 2001). Frederick Engels bemoaned the density and the squalor in Britain’s manufacturing cities in the mid-19th century. Urban historians have provided indelible descriptions of US cities in the past. In the 19th century, dead horses littered the streets of New York City, and thousands of tenement-dwellers were exposed to stinking water, smoky skies, and ear-shattering din (Melosi 1982, 2001). During the 19th and early 20th centuries, the skies above such major cities as Chicago and Pittsburgh were dark with smoke from steel smelters, heavy industrial plants, and burning coal.

Since the early 20th century, many major cities in the developed world have experienced sharp improvements in quality of life. By 1940, the urban mortality premium had vanished (Haines 2001). Starting in the early 1970s, air pollution, water pollution and noise pollution have sharply fallen in many major US cities. While there are several causes of this progress, ranging from effective regulation to industrial transition from manufacturing to services and technological advance, the net result of this trend is that past ‘production cities’ are transforming themselves into ‘consumer cities’.

Cities that have high quality of life will have greater success at attracting the footloose highly educated to live there. Empirical studies have documented that a location’s stock of educated people plays an important role in generating urban growth (Glaeser et al. 1995).

First, I sketch how a city ‘produces’ quality of life. I then discuss the demand for urban quality of life using a household production function framework. While urban quality of life is a valued ‘commodity’, there are no explicit markets where it can be purchased. Utility maximizing households face a trade-off in choosing where to locate. In cities with higher quality of life, home prices are higher. Measuring this price premium for quality continues to be a major focus of much environmental and urban empirical research.

The Supply of Urban Quality of Life

Each city can be thought of as a differentiated product. Its attributes include some exogenous factors such as climate and risk of natural disasters, and endogenous factors such as average commuting times, pollution and crime. Some of these endogenous attributes are by-products of economic activity. A city of 10,000 bike-riding lawyers would have much cleaner air than another city with 500,000 old-car-driving steel workers. None of the steel workers driving old cars intends to pollute local air. Pollution represents an unintended consequence of their daily commuting mode and of local industrial production. This example highlights the importance of scale, composition and technique effects in determining local environmental quality. In the above example, scale refers to whether the city has 10,000 people or 500,000 people. Composition effects focus on consumption patterns (such as bike versus car) and industrial patterns (such as law firms versus steel plants). If one controls for a city’s scale and composition, urban environmental quality can be high due to technique effects brought about by government regulation or the free market designing new capital with low emissions (for example, hybrid cars such as the Toyota Prius).

Early research in urban economics emphasized scale effects such that the biggest cities suffered more quality-of-life degradation as they expanded (Tolley 1974). Anyone can migrate to a big city without paying an ‘entry fee’. When an extra person moves to a big city from a smaller city, this migration causes net social damage (due to extra congestion and pollution). Migrants will ignore the fact that their choice degrades local public goods in the destination city, but a benevolent planner would not. In the absence of a big city entry fee, the big city grows beyond its efficient size.

Cross-city empirical research has documented that such urban challenges as crime, pollution and congestion are all greater in big cities than in smaller cities (Glaeser 1998; Henderson 2002). But this ‘cost’ of city bigness is declining over time. In the 1990s, crime fell fastest in the largest US cities (Levitt 2004). Ambient air pollution is improving in many major cities despite a continued increase in population (Glaeser and Kahn 2004). The suburbanization of employment in all major US metropolitan areas has meant that that population ‘sprawl’ has not increased commute times.

City size is not a sufficient statistic for determining a city’s quality of life. Other relevant factors are the city’s geography, industrial and demographic composition, and government policy. A city’s geography determines its climate and its capacity for handling local pollution. Put simply, some cities have it and some cities don’t. As Billy Graham once said, ‘The San Francisco Bay Area is so beautiful, I hesitate to preach about heaven while I’m here.’

Cities differ in their ability to absorb growth without suffering urban quality-of-life degradation. World Bank researchers have recently documented the importance of climate and topological features of the city in determining how much air pollution is caused by economic growth (see Dasgupta et al. 2004). Windier cities and cities that receive more rainfall suffer less ambient pollution from a given amount of emissions.

The composition of city economic activity also plays a key role in determining the supply of quality of life. All else equal, a city that specializes in manufacturing relative to services will have a lower quality of life. Such a city will have greater levels of ambient particulate and sulphur dioxide pollution. Water pollution will be greater, and more hazardous waste sites will be created. The rise and decline of manufacturing in the US rust belt over the 20th century provides dramatic evidence documenting these effects (Kahn 1999). A similar ‘natural-experiment’ has played out as communism died. In major cities in the Czech Republic, Hungry and Poland air pollution improved in the 1990s because the phase out of energy subsidies contributed to the shutdown of communist era industrial plants (Kahn 2003). As major cities such as New York and London and Chicago have experienced an industrial transition from manufacturing to finance and services, more people work in the service and tourist industries, and these workers have a financial stake in keeping the city’s quality of life high.

A city’s demographics also play a role in determining its quality of life. A city filled with senior citizens will offer a different set of restaurants and cultural opportunities from a city filled with immigrants and young parents. If a city can attract the highly educated, then a virtuous circle can be set off. Since more highly educated people earn more income, this will attract better restaurants and other commercial amenities.

Government policy plays a role in determining a city’s quality of life. Boston’s Big Dig project has cost over US$14 billion and is intended to beautify Boston by submerging its ugly highways connecting the city centre to the waterfront and increasing the supply of green parks. Successful Clean Air Act regulation has sharply reduced vehicle emissions in Los Angeles. Rudy Giuliani, Mayor of New York City, achieved wide acclaim for improved policing that some have argued contributed to the sharp decline in the city’s crime rate in the 1990s.

The supply of urban quality of life varies across cities and within cities. Some variation such as proximity to a major park or body of water is exogenously determined, but public policy can also have differential effects on quality of life across a city’s neighbourhoods. The Clean Air Act has reduced Los Angeles’ smog by much more in inland Hispanic communities than along the Pacific Ocean (Kahn 2001). Economists are just starting to investigate the general equilibrium impacts of regulations that differentially improve urban quality of life in some parts of a city relative to other parts of the same city (Sieg et al. 2004). If the improvements in quality of life were unexpected, then homeowners in such areas will receive a windfall. Long-standing renters in communities that have experienced regulation-induced improvements in local public goods will pay higher rents and may no longer be able to afford to live in their old community.

Demand for Urban Quality of Life

The household production function approach offers a framework for modelling the demand for non-market local public goods such as climate, street safety and local environmental quality. A person gains utility from being healthy, safe and comfortable. To achieve these goals, one purchases market goods such as doctor visits, home alarm systems and home entertainment systems. In addition, this person might choose a city and a residential community within this city featuring a temperate climate, low smog levels and safe streets.

Each household must choose a city and a community within that city to live in.

Households that value quality of life face a trade-off in that each city represents a bundle of non-market attributes and economic opportunities. Some cities such as San Francisco are beautiful but home prices are very high. Other cities such as Houston offer warm winter weather and cheap housing but its residents face severe summer humidity. Market products can offset such city’s disamenities. Before the advent and diffusion of cheap air conditioning, humid cities would feature much lower home prices to compensate households for summer humidity. The diffusion of the air conditioner has allowed households to enjoy the benefits of living in warmer cities such as Houston during winter without suffering from humidity in summer (Rappaport 2003). This market product has increased the demand for living in humid cities.

Households may reveal different willingness to trade off non-market goods depending on the household’s age, income and demographic circumstances. A household with children may place greater weight on communities with good schools. Households may differ in their demand for urban attributes. Asthmatics will avoid highly polluted cities and skiers will not mind the cold New England winters. Household demand may also hinge on idiosyncratic factors; for example, an individual who grew up in a specific city may want to remain living near his childhood friends.

The Hedonic Equilibrium Approach for Valuing Urban Quality of Life

The theory of compensating differentials says that it will be more costly to live in ‘nicer’ cities (Rosen 2002). This theory is really a ‘no arbitrage’ result. If migration costs are low across urban areas and if potential buyers are fully informed about the differences in non-market urban attributes bundles, then real estate prices will adjust such that homes in cities with higher quality of life will sell for a premium.

An enormous empirical literature has estimated cross-city and within-city hedonic price functions to estimate the implicit compensating differentials for non-market goods. In these studies, the dependent variable is the price of home i in city j in community m in year t. Define Xit as home i’s physical attributes in year t. Ajt represents city j’s attributes in year t and Amjt represents the attributes of community m located in city j in the year t. Given this notation, a standard real estate hedonic regression will take the form:

$$ {\mathrm{Price}}_{\mathrm{ijmt}}={\upbeta}_0+{\upbeta}_1^{\ast }{\mathrm{X}}_{\mathrm{it}}+{\upbeta}_2^{\ast }{\mathrm{A}}_{\mathrm{jt}}+{\upbeta}_3^{\ast }{\mathrm{A}}_{\mathrm{mjt}}+{\upvarepsilon}_{\mathrm{ijmt}} $$
(1)

Multivariate regression estimates of this regression yield estimates of the compensating differentials for city level local public goods (based on β2) and community-level local public goods (based on β3). These coefficients represent the marginal implicit prices for small increases in the consumption of local public goods. Studies that control for a vector of local public goods are able to pinpoint the relative importance of different features of cities and communities ranging from climate to air pollution to urban crime. Equation (1) highlights the fact that households face a rich set of choices both across cities and across communities within the same city.

Environmental studies have used this hedonic framework to estimate compensating differentials for a myriad of different environmental local characteristics. For example, Costa and Kahn (2003) examine the compensating differential for living in nice climate in 1970 and in the year 1990. In 1970, a person would have to pay $1,288 (1990 dollars) in higher home prices per year to purchase San Francisco’s climate over Chicago’s climate. In 1990, this yearly price differential increased by $6,259 (1990 dollars) to $7,547. Chay and Greenstone (2005) use 1980 and 1990 data for all US counties find that a ten per cent reduction in ambient total suspended particulates increased home prices by three per cent. While much of the urban quality of life literature has focused on US city data, a promising research trend is examining international evidence.

Conclusion

Urban economic development policymakers have pursued very different growth strategies. Some cities subsidize sports stadiums while others build airports or downtown cultural centres. Such targeted investment is unlikely to yield the key urban anchor. This essay has argued that cities than can provide and enhance urban quality of life will attract the high-skilled. An end result of attracting this group is a more vibrant, diversified local economy. As per-capita incomes continue to rise, the demand for living and working in high quality-of-life cities will increase. The empirical literature continues to inquire into what the key components of quality of life are.

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