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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.

Some US counties are more likely to generate entrepreneurial opportunities. This paper aims to determine whether US micropolitan counties with disproportionately high nonfarm proprietorship (NFP) employment levels are systematically linked to specific attributes of the entrepreneurial ecosystem. A limited amount of research has been conducted on the geography of entrepreneurship in small to medium-sized micropolitan counties where rates of growth and change can be quite dramatic.

NFP employment data from the US Bureau of Economic Analysis (BEA) is used as a dependent variable proxy for entrepreneurship. NFP data are widely used in the entrepreneurship literature. Data on all independent variables were obtained from the US Census Bureau’s American Community Survey and BEA by county and subject to stepwise linear regression.

Results revealed a strong positive relationship between the percent of NFP employment by micropolitan county and percent construction employment, percent real estate, and rental and leasing employment, and the percent elderly. It is argued that the combination of predictors captures primarily a self-employment of opportunity (e.g., thriving land and real estate markets).

In attempting to encourage NFP employment, policymakers should be more alert to the key predictors that shape micropolitan entrepreneurial ecosystems when attempting to enhance competitive advantage in small- to medium-sized communities. Better understanding how micropolitan counties function relative to larger metropolitan places can help local policymakers more efficiently enhance the overall quality of life in smaller communities.

The focus on smaller micropolitan communities and the explicit spatial context of this paper has sometimes been overlooked in the traditional entrepreneurship literature and this research helps to fill that gap.

The entrepreneurial process is a result of an interaction between an individual entrepreneur and the surrounding entrepreneurial ecosystem. The purpose of this paper is to determine whether US metropolitan areas with disproportionately high shares of entrepreneurs are systematically linked to particular attributes of the entrepreneurial support system?

In this paper, non-farm proprietorship (NFP) employment data from the US Bureau of Economic Analysis is used as a dependent variable proxy for entrepreneurship. NFP data are widely used in the entrepreneurship literature. Data on all independent variables were obtained from the Census Bureau’s American Community Survey and the Bureau of Labor Statistics by metropolitan area and subject to a stepwise linear regression analysis.

The relative share of NFP employment by metropolitan area exhibited a strong positive relationship with percentage of employment in finance, insurance and real estate, median age, percentage of Hispanic population and median home value. It is argued that the combination of significant predictors captures both out-of-necessity self-employment (e.g. low-skilled Hispanic and aging populations) and a self-employment of opportunity (e.g. access to capital).

Public policies focused on nurturing entrepreneurial ecosystems must account for these divergent explanatory frameworks when attempting to encourage NFP employment.

The paper has an explicit spatial context that tends to be overlooked in the traditional entrepreneurship literature. The focus on out-of-necessity versus opportunity-based entrepreneurship, and how it is shaped by some key predictors at the metropolitan scale, is a relatively new angle.

The purpose of this paper is to demonstrate significant problems in the US' development pattern of regional automobile‐dependent sprawl and local growth management and to make suggestions about adopting a regional growth management model that might better provide for more sustainable development of the built environment.

This paper reviews trends in the USA and elsewhere to determine the negative effects of the current system of sprawl and the potential benefits of developing higher‐density urban centers. The paper also looks to models in some US cities and Europe to further analyze potential legal and political issues related to this type of regional sustainable development.

Unsustainable, automobile‐dependent regional sprawl is a result of local zoning, growth management, and parking programs and has negative effects both now and for the future. The result has been more time, money, and resources wasted in automobile transit instead of new planning models that would lead to a more sustainable and less automobile‐dependent future.

A metropolitan sustainable development governing framework for growth management in the twenty‐first century is essential for a sustainable future. This includes higher‐density urban centers, transit‐oriented development centers, and a change in public attitude away from “not in my back yard” thinking.

This paper provides the potential benefits of creating a metropolitan governing framework to identify and regulate “growth areas” in a region. It further demonstrates how linking these areas to regional transit planning will help achieve the development of higher‐density, mixed use, and intensive urban core job/housing areas where people could live, work, shop, and play without the use of the automobile.

Purpose – Evidence suggests that during the 1990s, many US metropolitan areas saw fundamental changes in the spatial distribution of household income. Following two decades of increasing economic segregation, many metropolitan neighborhoods saw declines in economic segregation, particularly those neighborhoods located within central cities and rural areas. This paper adapts the Spatial Ordering Index proposed by Dawkins (2007b) to explore these trends.

Methodology/Approach – Using US Census data, I calculate economic segregation indices for a sample of 205 US metropolitan areas in 1990 and 2000 and decompose changes in the indices into portions attributable to changes in the spatial distribution of households and portions capturing changes in the spatial distribution of aggregate income. I also examine regional variations in the decompositions.

Findings – The results suggest that changes in the spatial distribution of households and of income each influenced metropolitan economic segregation in different ways during the 1990s. Furthermore, the spatial dynamics of income segregation exhibited significant regional heterogeneity.

Originality/Value of paper – This paper presents a new approach to measuring the dynamics of economic segregation.

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.

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.