The rise of the Sunbelt.

• Author: Glaeser, Edward L.
• Position: Association Lecture - Economic growth - Rising prices of residential real estate - Author abstract

1. Introduction

   In the 1930s, the American South seemed trapped in the poverty and relative decline that had marked that region since the Civil War. The 11 states of the former Confederacy were depicted by William Faulkner as quaint remnants of a pre-modern world and by both Nazis and communists as embarrassing evidence of the limits to American freedom and economic opportunity. Since World War II, however, the South has been a great regional success. Figure 1 shows that the South's share of the U.S. population increased from 24% in 1950 to 30% today, with the South defined, as it is throughout this paper, as the 11 states of the former Confederacy. In 1950, the average Southern county had an income that was 76% of the average income across all counties. In 2000, the average Southern county's income was 94% of the county average. Between 1950 and 2000, the average housing price in Southern counties grew from 83 to 91% of the U.S. average.

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   The rise of the South is part of the general correlation between warmth and growth across the entire United States. The Sunbelt--all places, Southern or not, with warm winters and hot summers--has experienced a boom since the 1950s. Throughout this paper, we will consider three different proxies for Sunbelt status: high January temperatures (indicating warm winters), high July temperatures (indicating hot summers), and location in one of the states of the former Confederacy. Table 1 gives the cross-county correlations between our three proxies for Sunbelt status and the growth of population, income, and housing values decade by decade. As Table 1 shows, the correlation between population growth and warm winters was more than 10% in every post-war decade. Figure 2 shows the correlation across counties between population growth from 1950 to today and the presence of warm winters, indicated by a county's average January temperature over the 1970-2000 time period. Figure 3 shows the somewhat weaker relationship between income growth and warm winters over the same period. Figure 4 shows the relationship between housing price growth and warm winters and, although some of this relationship must be attributed to improving housing quality in the Sunbelt, this correlation is quite robust.

   While there can be little doubt that the Sunbelt boomed in the decades after World War II, the causes of this boom are less clear. In section 2, we discuss three broad possible explanations for the success of the South and the Sunbelt: increasing productivity, rising demand for Sunbelt amenities, and a more flexible housing supply. Many authors, from McDonald (1961) to Caselli and Coleman (2001), have documented the remarkable economic performance of the South during the post-war era and have suggested that strong economic growth should lead to population growth. Other authors have proposed that population growth in the Sunbelt reflects increasing demand for Southern amenities due to sun-related technological change, such as the rise of air conditioning (Borts and Stein 1964; Graves 1980; Mueser and Graves 1995). A final hypothesis is that the South has grown not because it is more attractive or more productive, but because its housing supply is far more elastic, mainly due to a pro-development regulatory system (Glaeser, Gyourko, and Saks 2006).

   Section 3 presents a framework based on Rosen (1979) and Roback (1982) that uses changes in population, income, and housing prices to assess the potential sources for Southern and Sunbelt growth. The model predicts that rising productivity will cause population, nominal income, and housing prices to rise. When productivity increases, income will rise faster than housing prices, and real incomes, defined as nominal income corrected for local prices, will also surge. Rising amenity levels or an increasing willingness to pay for the amenities of a location will cause population and housing prices to rise, but nominal and real incomes will fall. (1) An increase in housing supply will cause population to rise and both income and housing prices to fall.

   This framework enables us to estimate the relative growth of productivity, amenities, and housing supply in the Sunbelt, along with the relative contribution of these forces to the growth of the region. The framework depends critically on the spatial equilibrium assumption that assumes that different "real incomes" across space offset different amenity levels. The most problematic aspect of our application of the Rosen-Roback spatial equilibrium framework is that we ignore the forward-looking aspects of housing prices, but we hope that future work will remedy this weakness.

   In section 4, we estimate the relationship between our proxies for Sunbelt status and the growth of population, income, and housing. Since the changes in the quality of the housing stock in the South appear to be enormous, we use only the areas for which we have Office of Federal Housing Enterprise Oversight (OFHEO) repeat sales indices from 1980 onward. This limits our sample to 135 metropolitan areas and, as a result, our results differ from the correlations in Table 1, which includes all U.S. counties. We use census median housing values for years before 1980.

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   In univariate regressions across metropolitan areas, each of these variables predicts population growth in every decade since 1950, except for July temperature, indicating hot summers, which demonstrates almost no effect in the 1960s. However, across metropolitan areas, the correlation between population growth and January temperature, indicating warm winters, has declined since the 1970s. In contrast, the correlation between July temperature and growth has been rising since the 1970s. This change reflects the relative slowdown in the growth of California and the explosion of metropolitan areas such as Las Vegas, Houston, and Atlanta.

   Using the same metropolitan area--level data, we find that the correlation between income growth and the South dummy is strongly positive between 1950 and 1980 but that the relationship has weakened since then. The correlations between income growth and the other two variables are less reliable. The correlation between the South dummy and housing prices is weak, except for the 1980s, when housing price growth strongly declines with the South dummy. The correlation between January temperature and housing price growth is also somewhat weak, except for the 1970s, when housing price growth strongly rises with warm winters. Housing price growth and July temperature correlations have been negative since 1960 and are most strongly negatively correlated in the 1980s.

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   These basic findings from metropolitan area aggregate census data are corroborated by the Census Individual Public Use Micro Sample (IPUMS) data, which allow us to control for increases in the education level in the Sunbelt. Controlling for individual attributes using the micro data does not change the basic trend of rising real incomes in the South since 1970. When we control for local cost of living using American Chamber of Commerce Research Association (ACCRA) indices, we also find that real incomes in the South have risen steadily since 1970. There is also an increasing correlation between hot summers and real income, but there is a declining correlation between warm winters and real income. These differences suggest, quite plausibly, that while the amenity flows associated with warm winters are rising, the amenity flows associated with hot summers are falling.

   In section 5, we use the parameter estimates from these regressions to estimate the shocks to productivity, amenities, and housing supply. We estimate strong positive shocks to productivity in the South between 1960 and 1980 and somewhat weaker shocks after then. The association between productivity growth and warm winters is strong between 1950 and 1990, and only disappears in the 1990s. The association between productivity and hot summers is strong between 1950 and 1980 and weaker after then.

   The biggest surprise in this paper is that we estimate declining amenity flows in the South and in all places with hot summers throughout the entire post-war period. A central insight of the Rosen-Roback model is that in a spatial equilibrium, higher amenity levels must be offset by lower real wages as people become willing to accept lower wages in return for enjoying attractive amenities. Declining amenity flows are therefore implied by rising real incomes, as people demand higher wages to compensate them for the lack of amenities. One objection to this inference is that real incomes may be rising because of improvements in human capital, but over much of the recent period, rising real incomes reflect minimal housing price growth rather than strong income growth. While the amenity flows associated with the South and with hot summers have uniformly fallen, the amenity value of a warm winter rose in the 1960s and 1970s. California, for example, appears to have had robust amenity flow increases as its real wages have generally fallen since 1970. However, most of the Sunbelt is not in California, and in most areas, housing prices have increased far more modestly than income.

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   We estimate dramatic relative housing supply growth in the South and in places with hot summers between 1970 and 1990. We infer housing supply increases because the stock of housing rose dramatically but housing prices did not. Putting these estimates together, we find that population growth in the Sunbelt was driven primarily by productivity increases between 1950 and 1980, but housing supply has played an increasingly important role in the growth of the Sunbelt since then.

   The rise of Southern productivity has been well studied, but there has been far too little attention paid to the fact that the housing supply is growing so quickly in the South. In the penultimate section of the paper...