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This paper aims to use statistical analyses to understand the trends on housing liquidity and pricing by accounting for macroeconomic factors that vary at national level and at metropolitan statistical area level for all metropolitan statistical areas in Texas. In addition, the authors test for seasonality in all the metropolitan statistical areas in Texas.

Using publicly available data from Zillow a listing website, the authors conduct an analysis of all housing markets at metropolitan statistical area level in Texas to understand the factors that drive the liquidity and pricing. The authors use two measures for liquidity, namely, time to sell the house and sales to list ratio. The authors also try to understand the decision to lower the price of the listed houses. In addition, the authors conduct a test for seasonality within the year in these housing markets.

The analyses conclude that there is a significant impact of listing prices, unemployment rates, 30-year mortgage rates, consumer sentiment and oil price changes on the liquidity of the housing markets and decisions of sellers to adjust the prices down. In addition, the authors provide evidence of the existence of seasonality in most metropolitan statistical areas in Texas both for pricing and volume of transactions.

This is the first study to look at housing liquidity and pricing trends for about 25 markets in Texas. In addition, the authors provide evidence of the importance of oil prices for the housing markets in Texas metropolitan statistical areas.

Spatial bibliometrics and scientometrics have traditionally focused on examining both country and regional levels; however, in recent years, numerous spatial analyses on the city level have been carried out. While city-level scientometric analyses have gained popularity among policymakers and statistical/economic research organizations, researchers in the field of bibliometrics are divided regarding whether it is possible to observe the spatial unit “city” through bibliometric and scientometric tools. The purpose of this paper is to reveal the most significant challenges ahead of spatial scientometrics focusing on the city level by examining relevant scientometric studies.

This analysis involves the most significant spatial scientometric studies focusing on the city level and carefully examines how they collect bibliometric and/or scientometric data, what methodologies they employ to process bibliometric data and most importantly, how they approach the spatial unit “city”.

After systematically scrutinizing relevant studies in the field, three major problems have been identified: there is no standardized method of how cities should be defined and how metropolitan areas should be delineated; there is no standardized method of how bibliometric and scientometric data on the city level should be collected and processed; and it is not clearly defined how cities can profit from the results of bibliometric and scientometric analysis focusing on them.

This is the first study that compiles a “database” of scientometric studies focusing on the city level. The paper not only reveals major challenges ahead of city level spatial analysis but recommends some possible solution as well.

The purpose of the study is to examine the long-run convergence properties of condominium prices based on the ripple effect for five major US metropolitan areas (Boston, Chicago, Los Angeles, New York and San Francisco). Specifically, we test for both overall convergence in condominium prices and the possibility of distinct convergence clubs to ascertain the interdependence of geographically dispersed metropolitan condominium markets.

Our analysis uses two approaches to identify the convergence properties of condominium prices: the Lee and Strazicich (2003) unit root test with endogenous structural breaks and the Phillips and Sul (2007, 2009) time-varying nonlinear club convergence tests.

The Lee and Strazicich (2003) unit root tests identify two structural breaks in 2006 and 2008 with the rejection of the null hypothesis of a unit root and long-run convergence in condominium prices in the cases of Boston and New York. The Phillips and Sul (2007, 2009) club convergence test reveals the absence of overall convergence in condominium prices across all metropolitan areas, but the emergence of two distinct convergence clubs with clear geographical segmentation: on the east coast with Boston and New York and the west coast with Los Angeles and San Francisco while Chicago exhibits a non-converging path.

The results highlight the distinct geographical segmentation of metropolitan condominium markets, which provides useful information to local policymakers, financial institutions, real estate developers and real estate portfolio managers. The limitations of the research are the identification of the underlying sources for the convergence clubs identified due to the availability of monthly data for a number of potential variables.

The absence of overall convergence in condominium prices, but the emergence of distinct convergence clubs that reflects the geographical segmentation of metropolitan condominium markets raises the potential for portfolio diversification.

Unlike previous studies that have focused on single-family housing, this is the first study to examine the convergence of metropolitan area condominium prices.

This chapter examines the effects that airports have had on economic development in cities from 1950 to 2010. It uses a novel dataset consisting of previously unexploited data on the origins and history of the aviation system in the United States. Applying the method of synthetic controls to a set of medium and small airports, I examine both the overall impacts and the heterogeneity within the outcomes of various airports. Then, I use regression analysis to determine key factors differentiating successful airports from less successful ones, as it pertains particularly to population and employment growth. I find that, first, on average, cities have benefited from airports over this period. Airports, overall, provided a causal contribution of 0.2– 0.6% per year on population and employment growth over the time period. Second, I show that city-level factors contributing to airport success include: (1) closer proximity to a major research university, (2) a capital city location, and (3) climate factors, particularly higher January mean temperatures and/or hours of sunshine. City size is a consideration as well; cities in larger metropolitan areas, with larger shares of employment in nontradables in the 1950s, were also better positioned to reap the benefits that airports provided on city growth. Significant differences were not found across regions, airport governance structures, or other factors.

A developing body of research has demonstrated the impact of racial residential segregation on a variety of negative health outcomes. However, little is known about the effect of residential segregation on access to health care.

This study utilizes multilevel binary logit models based on individual-level health data from the 2008 Behavioral Risk Factor Surveillance System linked to metropolitan-area level data to examine the association between Black-White segregation in 136 metropolitan statistical areas in the United States and health-care coverage.

Overall, an increase in Black-White segregation is related to a decrease in the likelihood of having health insurance for Black residents and an increase in the Black-White gap in health-care coverage. These effects are substantial even when controlling for the effects of educational, social, and economic factors.

This study is the first to examine the impact of segregation on an individual's ability to access health-care coverage, which is an essential starting point for accessing health care in the United States.

The purpose of this paper is to focus upon the financial performance of firms that maintain headquarters in the largest cities and firms based in smaller metropolitan areas. Big city locations offer numerous opportunities. On the other hand, maintaining headquarters in big cities is more costly than in less congested locations and the opportunities for distractions tend to be higher. A third alternative is that location does not matter.

The study, the first of its type, applies a multivariate analysis to a large sample of Compustat firms. The analysis tests for the industry-adjusted return on investment as a function of population density.

The results, which are both statistically and economically significant, show that firms headquartered in smaller cities tend to outperform those located in major business centers.

These results suggest at least two implications for financial managers. One is that headquarters location should be considered as a key element of financial management strategy. The second is that businesses should very carefully consider decisions to move headquarters to the very largest cities.

Theory suggests that business success should increase with the size of the city. This paper, the first large-sample examination of major US firms, shows that businesses with headquarters in smaller locations tend to enjoy greater financial success.

The rules of the economic development game have changed. Companies were the force behind the old game. Cities and suburbs gauged their status by the number of corporate headquarters within their borders. Economic developers used financial and other incentives to lure companies to their communities. Now, however, people are the center of the action. High human capital individuals – or as we like to call them, talent – are the key to success in this new era of economic growth. Their ideas and creativity are the most important ingredients in the economic success of a firm or region.

Purpose – To provide a demographic portrait of Latinos in the Washington Metropolitan Area.

Design/methodology/approach – This is a descriptive analysis using published results from the 2010 U.S. Census and authors’ tabulations from the U.S. Census Bureau's 2009 American Community Survey.

Findings – According to the 2010 U.S. Census, more than 700,000 Latinos lived in the Washington metropolitan area. In many ways, Washington's Latino population is unique when compared to Latino populations in other U.S. metropolitan areas. For example, unlike other metropolitan areas, no single Hispanic origin group is in the majority in Washington. And while the largest Hispanic origin group in other metropolitan areas is often of Mexican, Puerto Rican, Cuban, or Dominican origin, in the Washington metro area Salvadorans are the largest group. In other ways too, the Capital Region's Latino population is unique. It has the nation's largest Bolivian community. It has a greater share of immigrants than Latino populations in most other metropolitan areas. It has a higher share of college graduates among its Latino population than any other metropolitan area nationwide. And it is dynamic – growing fast and dispersing across the region.

Originality/value – This chapter provides a detailed demographic portrait of Latinos in the Washington, DC, area using the latest data sources available.