Meet the Author

Kyle Fee |

Economic Analyst

Kyle Fee

Kyle Fee is an economic analyst in the Research Department of the Federal Reserve Bank of Cleveland. His research interests include economic development, regional economics and economic geography.

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Meet the Author

Daniel Hartley |

Research Economist

Daniel Hartley

Daniel Hartley is a research economist in the Research Department of the Federal Reserve Bank of Cleveland. He is primarily interested in urban/regional economics and labor economics. His current work focuses on crime, public housing, and neighborhood housing market dynamics.

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04.14.11

Economic Trends

Growing Cities, Shrinking Cities

Kyle Fee and Daniel Hartley

As the 2010 census data rolls out, researchers will be conducting extensive analysis on a variety of issues. So far we have only been privy to the re-apportionment (population) data, which have generated their fair share of media coverage. Regardless of the media spin, a clearer picture of how cities’ populations have changed from 2000 to 2010 is emerging. What are some of the characteristics of the cities that grew, and how do they compare to those of the cities that shrank?

First, a lot of attention has been devoted to the fact that cities in warmer climates have been growing faster than those in colder climates. Examining the 64 cities in the United States with a population over 250,000 (excluding New Orleans, which lost a large percentage of its population after Hurricane Katrina), shows that cities located in states that experience warmer weather during the month of January grew more on average than cities located in colder states. Average January temperature explains 11 percent of the variation in population growth. It is interesting to note that the cities losing the most people (Detroit, Cleveland, Buffalo, Cincinnati, Pittsburgh, Toledo, St. Louis, and Chicago, all with population losses of more than 5 percent) are located in the Midwest or Great Lakes regions. The fastest-growing cities (Raleigh, Fort Worth, Charlotte, Las Vegas, Albuquerque, Austin, Riverside, Aurora, San Antonio, Fresno, Colorado Springs, and El Paso, with growth of more than 15 percent) are located in the South or West.

Another factor related to population trends is the decline in manufacturing employment in the U.S. On average, cities with large concentrations of employment in the manufacturing sector at the beginning of the decade experienced less population growth. The fraction of employment in the manufacturing sector in 2000 explains 10 percent of the variation in population growth.

On average, cities that had a higher median household income in 2000 saw larger population growth from 2000 to 2010. The log of median household income in 2000 explains 19 percent of the variation in population growth.

On average, more highly educated cities experienced more growth. The fraction of residents with a bachelor’s degree or higher in 2000 explains 13 percent of the variation in population growth.

Together, the four factors mentioned above explain about 33 percent of the variation in population growth. However, the education variable does not add much explanatory power to the other three variables. Temperature, manufacturing employment, and household incomes explain 32 percent of the variation in population growth. Furthermore, each of the above three factors is related to population growth even when the other two factors are held constant.

As one would expect, growth in the number of jobs in the MSA in which the city is located is correlated with population growth. In fact, MSA payroll employment growth can explain about 42 percent of the variation of city population growth. However, it is interesting to note that two of the other four variables mentioned—temperature and household incomes—explain an additional 15 percentage points of the variation in city population growth on top what is explained by MSA payroll employment growth (manufacturing employment and education do not add much explanatory power).

While it may be tempting to conclude that people are moving to places with job growth, it is equally possible to conclude that jobs are moving to places where city population is growing. Most likely it is a combination of both. What is interesting is that even controlling for job growth in the MSA, warmer cities grew more than colder cities. If retirees are more likely to move to warmer climes, the growth of these cities could be due to the growing fraction of retirees in the population. Another possible explanation is that the populations of colder MSAs are becoming more concentrated in the suburbs relative to warmer MSAs. Finally, the fact that cities with low household incomes in 2000 had population losses, even controlling for job growth in the MSA, may be due to a deterioration public goods such as safety and high-quality schools stemming from a diminished tax-base.