MSA Level Research Articles

Synthetic cap rate indices (1991-Covid era)

We introduce a method that combines Euclidean distancing and OLS techniques to project synthetic capitalization rate indices (‘SCXs’) for metropolitan statistical areas in the US. SCXs are projected independently of market prices, asset specific characteristics and geographic location (ex-ante). In contrast to market cap rates, driven by geographic proximity and market comparables, our new method is driven by economic proximity. We find SCXs provide better forward guidance than market cap rates for commercial real estate (‘CRE’) defaults and CRE values before and during the Covid pandemic. Our method establishes CRE benchmark cap rate indices across property types that explicitly connect CRE valuation at the MSA level to macroeconomic indicators through economic proximity.

Education-occupation mismatch and social networks for Hispanics in the U.S.: role of citizenship

ABSTRACT Using a sample of college-educated Hispanics from the 2016–2017 American Community Survey we examine the role of potential social networks on the education-occupation mismatch for Hispanics in the U.S. To do this, we use a novel data-driven index to measure the degree of education-occupation mismatch, while potential networks are measured using the share of Hispanics at the MSA level. We find that networks improve job-match quality for college-educated Hispanics, with effects that are significantly larger for Hispanic citizens when networks consist of the proportion of Hispanics with college degrees. Our findings are robust to other indices of education mismatch.

Institutions and incarceration: The role of economic freedom at the MSA level

AbstractObjectiveWe evaluate the relationship between economic freedom and incarceration at the U.S. metropolitan statistical area level.MethodWe use economic freedom data at the metropolitan statistical area unit and local incarceration data from the Vera Institute in 5‐year intervals from 1977 through 2017.ResultsOur evidence suggests that greater economic freedom is associated with lower rates of incarceration in jails for the overall population. The channel tends to be through both the first and second economic freedom components (“size of government” and “taxation,” respectively). Finally, the results for juvenile incarcerated populations are largely driven by labor market freedoms.ConclusionTo the extent that reducing incarceration rates continue to be viewed as a positive outcome in line with recent trends, this study suggests that promoting laws and policies aimed at enhancing economic freedom could be an avenue to advancing that goal. For proponents, this policy implication has the rare advantage of bipartisan appeal.

Defining ‘metropolitan’ poverty: Isolation gradients in major US urban areas

As suburban poverty has become more prevalent in recent years, low-income neighbourhoods have emerged outside of many central cities. In many regions, however, there remains a stark divide between the core city and outlying areas. Measuring poverty concentrations, therefore, depends on the choice of geographic scale. Widespread urban poverty results in low measures of poverty concentration inside core cities, and whether this increases or decreases once suburbs are considered depends on specific regional characteristics. This study calculates ‘isolation gradients’ for the population in poverty in the 50 largest US Metropolitan areas (MSAs), extending from the core city to beyond the MSA level. A variety of patterns emerge, including sharp increases in isolation scores outside the city (as in Detroit) as well as decreases (for Atlanta). An econometric analysis of the ratio of MSA-level to core-city isolation scores finds that, controlling for land area and core-city poverty rates, much of the variance is explained by per-capita income and differences in racial segregation. A comparison of gradients in 2000 and 2015–2019 for a subset of cities shows additional patterns of suburban and urban convergence and divergence.

Institutions and Incarceration: The Role of Economic Freedom at the MSA Level

Institutions and Incarceration: The Role of Economic Freedom at the MSA Level

Reprint of “The Startup Cartography Project: Measuring and mapping entrepreneurial ecosystems”

This paper presents the Startup Cartography Project (SCP), which offers a new set of entrepreneurial ecosystem statistics for the United States from 1988 to 2016. The SCP combines state-level business registration records with a predictive analytics approach to estimate the probability of “extreme” growth (IPO or high-value acquisition) at or near the time of founding for the population of newly-registered firms. The results highlight the ability of predictive analytics to identify high-potential start-ups at founding (using a variety of different approaches and measures). The SCP then leverages estimates of entrepreneurial quality to develop four entrepreneurial ecosystem statistics, including the rate of start-up formation, average entrepreneurial quality, the quality-adjusted quantity of entrepreneurship, and the entrepreneurial ecosystem performance associated with a given start-up “cohort.” These statistics offer sharp insight into patterns of regional entrepreneurship, the correlation of quality (but not quantity) with subsequent regional economic growth and the evolution of entrepreneurial ecosystems over time. The SCP includes both a public-access dataset at the state, MSA, county, and zip code level, as well as an interactive map, the U.S. Startup Map, that allows academic and policy users to assess entrepreneurial ecosystems at an arbitrary level of granularity (from the level of states down to individual street addresses). The SCP and accompanying datasets may be found at: https://www.startupcartography.com/ .

The Housing Boom and Selection into Entrepreneurship

We provide evidence that the boom in housing prices occurred in the early 2000 distorted the selection of individuals that opened a business. A simple model of collateral financing predicts an increase in entry into entrepreneurship for house-owners and, particularly, for individuals with lower entrepreneurial ability and higher probability of failure. We support the predictions of the model using panel data at the individual level including restricted access information on the MSA of residence of an individual. We combine this data with geographic information about house prices at the MSA level. We confirm that the increase in house prices had a larger impact on the decision of becoming an entrepreneur for lower ability house-owners.

The Startup Cartography Project: Measuring and mapping entrepreneurial ecosystems

This paper presents the Startup Cartography Project (SCP), which offers a new set of entrepreneurial ecosystem statistics for the United States from 1988 to 2016. The SCP combines state-level business registration records with a predictive analytics approach to estimate the probability of “extreme” growth (IPO or high-value acquisition) at or near the time of founding for the population of newly-registered firms. The results highlight the ability of predictive analytics to identify high-potential start-ups at founding (using a variety of different approaches and measures). The SCP then leverages estimates of entrepreneurial quality to develop four entrepreneurial ecosystem statistics, including the rate of start-up formation, average entrepreneurial quality, the quality-adjusted quantity of entrepreneurship, and the entrepreneurial ecosystem performance associated with a given start-up “cohort.” These statistics offer sharp insight into patterns of regional entrepreneurship, the correlation of quality (but not quantity) with subsequent regional economic growth and the evolution of entrepreneurial ecosystems over time. The SCP includes both a public-access dataset at the state, MSA, county, and zip code level, as well as an interactive map, the U.S. Startup Map, that allows academic and policy users to assess entrepreneurial ecosystems at an arbitrary level of granularity (from the level of states down to individual street addresses). The SCP and accompanying datasets may be found at: https://www.startupcartography.com/.

House Price Growth Synchronization and Business Cycle Alignment

Using four decades of data, we provide novel evidence that the increasing interstate synchronization of house price growth leads to higher business cycle alignment across U.S. states. The relation is stronger between states with similar banking development and in non-tradable sectors, and is channeled through both the collateral and direct wealth effects. Results also hold at the MSA level and are robust to various endogeneity controls, including a Bartik-type instrument. Overall, our findings suggest that the housing market integration across regions can lead to amplified business cycles associated with an increased systemic economic risk at the country level.

Household Income, Asset Location and Real Estate Value: Evidence from REITs

This article investigates the extent to which the market valuation of properties is related to the income growth of their asset locations. Based on the income tax data from the Internal Revenue Service (IRS) and the individual property information of US equity real estate investment trusts (REITs) from 1995-2018, I construct an aggregated measure of income growth for each REIT based on its asset locations in different metropolitan areas. The results show that REITs’ market value and stock return are positively correlated with their previous-year household income growth. Further analysis provides evidence that income growth enhances shareholder value mainly through wages & salaries growth, not investment income growth. Moreover, firm-level operational efficiency is also found to be positively related to household income growth and wages & salaries growth. Additional tests such as splitting REITs into demand services and supply jobs subsample, controlling GDP growth and population growth, and analyzing real estate value growth at the MSA level are conducted. The results are largely consistent. Overall, these findings suggest that household income growth has a significant impact on real estate value and that the asset allocation strategy of a portfolio can play an important role in its long-term prospects.

The Importance of Micro-Location for Pricing Real Estate Assets: The Case of Hotels

Traditionally, hedonic pricing studies focusing on commercial real estate control for spatial effects with macro-location dummy variables, for example, at the MSA or submarket level, and predominantly rely on OLS regression. This approach ignores the importance of micro-location characteristics for predicting sales prices. Additionally, spatial dependencies in transaction prices and error terms violate OLS assumptions. We propose an alternative approach that replaces macro-location dummy variables with four location area characteristic (LAC) variables, defined as population, median home value, homeownership rate, and average land gradient within a polygon of a 20-minute driving distance around each property in our sample. We compare the location dummy and LAC approach using OLS regression, spatial autoregression (SAR), and spatial autoregression with autoregressive errors (SARAR) for a sample of hotels sold between 2015 and 2017. We find models that include LAC variables to have a superior fit to models with MSA dummy variables, irrespective of estimation method. Additionally, the inclusion of individual LAC variables allows a reduction of spatial lags and errors.

Mobility and Engagement Following the SARS-Cov-2 Outbreak

We develop a Social Distancing Index (SDI) based on a range of mobility metrics from Safegraph geolocation data, and validate the index with mobility data from Google and Unacast. We construct SDIs at the county, MSA, state and nationwide level, and link these measures to indicators of economic activity. According to our measures, the bulk of social distancing occurred during the week of March 15 and simultaneously across the U.S. At the national peak of social distancing in early April, localities that engaged in 10% more social distancing than average saw an additional 0.6% of their populations claiming unemployment insurance, an additional 2.8 pp reduction in small businesses employment, an additional 2.6 pp increase in small business closures, and an additional 3.2 pp reduction in new-business applications. A gradual and broad-based reduction in social distancing started in the third week of April.

Using repeated cross-sectional data to examine the role of immigrant birth-country networks on unemployment duration: an application of Guell and Hu (2006) approach

Guell and Hu (J Econom 133:307–341, 2006) propose a robust econometric estimator using repeated cross-sectional data in the context of duration/survival analysis where otherwise limited or no results are possible because reliable panel data at an individual level are missing. We present a detailed exposition of the Guell and Hu (GH) strategy and show a Monte Carlo simulation for unemployment duration where the GH method produces better estimates compared to panel data with individual matching errors. We further apply the GH model to examine the immigrant unemployment duration in the USA using the Current Population Survey data from 2001 to 2013 and focus on the role of the birth-country networks on the unemployment duration around the Great Recession. We find that birth-country networks measured at the state level significantly lower unemployment duration for all immigrants, and this effect is stronger during the pre- and post-recession periods than during the recession. We also find that networks are more effective in lowering duration for immigrants unemployed for 1–2 months than for immigrants who are unemployed for longer periods, and this effect is the strongest during the post-recession period. The findings are robust to different specifications and measures of networks including those measured at the local MSA level.

Prospects for inflation in a high pressure economy: Is the Phillips curve dead or is it just hibernating?

As the US labor market has tightened beyond full employment with relatively little evidence of inflation pressure, observers are increasingly inclined to declare the demise of the Phillips curve, that is, the flattening of its slope to zero. This paper reviews a substantial range of empirical evidence on this point, by assessing the performance of the conventional expectations-augmented Phillips curve for both prices and wages, based on both historical macro or national level data and panel data for states and MSAs (cities). National data going back to the 1950s and 60s yield strong evidence of negative slopes and significant nonlinearity in those slopes, with slopes much steeper in tight labor markets than in easy labor markets. This evidence of both slope and nonlinearity weakens dramatically based on macro data since the 1980s for the price Phillips curve, but not the wage Phillips curve. However, the endogeneity of monetary policy and the lack of variation of the unemployment gap, which has few episodes of being substantially below zero in this sample period, makes the price Phillips curve estimates from this period less reliable. At the same time, state level and MSA level data since the 1980s yield significant evidence of both negative slope and nonlinearity in the Phillips curve. The difference between national and city/state results in recent decades can be explained by the success that monetary policy has had in quelling inflation and anchoring inflation expectations since the 1980s. We also review the experience of the 1960s, the last time inflation expectations became unanchored, and observe both parallels and differences with today. Our analysis suggests that reports of the death of the Phillips curve may be greatly exaggerated.

The Industrial Revolution in Services

The rise in national industry concentration in the US between 1977 and 2013 is driven by a new industrial revolution in three broad non-traded sectors: services, retail, and wholesale. Sectors where national concentration is rising have increased their share of employment, and the expansion is entirely driven by the number of local markets served by firms. Firm employment per market has either increased slightly at the MSA level, or decreased substantially at the county or establishment levels. In industries with increasing concentration, the expansion into more markets is more pronounced for the top 10\% firms, but is present for the bottom 90\% as well. These trends have not been accompanied by economy-wide concentration. Top U.S. firms are increasingly specialized in sectors with rising industry concentration, but their aggregate employment share has remained roughly stable. We argue that these facts are consistent with the availability of a new set of fixed-cost technologies that enable adopters to produce at lower marginal costs in all markets. We present a simple model of firm size and market entry to describe the menu of new technologies and trace its implications.

Okun’s Law at the Florida MSA Level

This paper applies a fixed effects panel data spatial econometric model of Okun’s law to FloridaMetropolitan Statistical Areas (MSAs) over the period 1990 to 2015. The regression coefficients are used to estimate the impact of increases in output on unemployment and each MSA’s potential rate of output growth. Results indicate that Okun’s coefficient ranges from -0.19 to -0.24 at the MSA level. Between one-half to two-thirds of changes in local unemployment occur as a spillover effect from neighboring MSA output growth. Each MSA’s potential real output growth rate averages between 1.7 to 2.7 percent.

The End of the American Dream? Inequality and Segregation in US Cities

Over the last 40 years, the US has experienced a large increase in inequality. At the same time there has been a substantial increase in residential segregation by income and education. What is the link between inequality and residential and educational choice? We first document a strong correlation between inequality and residential segregation at the MSA level, especially in MSA with higher percentage of families with children. Then we develop a general equilibrium overlapping generations model where parents choose the neighborhood where they live with their children. The key ingredient of the model is that there is a spillover effect: children's future wage is expected to be higher if they live in richer neighborhoods. We model such a spillover effect as a black box that can be explained by different quality of public schools, peer effect, learning from neighbors' experience and so forth. This generates a general equilibrium effect through which the residential choice amplifies future inequality: the higher is inequality, the higher is residential segregation which, due to the spillover effect, generates higher inequality. Is this the end of the American dream? We then calibrate the model, using the elasticities found in Chetty and Hendren (2016) and quantify how much residential segregation has contributed to increase inequality. (We attach slides of a preliminary version of the paper, as the current version is still on progress).

Year-round record of bulk and size-segregated aerosol composition in central Antarctica (Concordia site) – Part 2: Biogenic sulfur (sulfate and methanesulfonate) aerosol

Abstract. Multiple year-round (2006–2015) records of the bulk and size-segregated composition of aerosol were obtained at the inland site of Concordia located in East Antarctica. The well-marked maximum of non-sea-salt sulfate (nssSO4) in January (100 ± 28 ng m−3 versus 4.4 ± 2.3 ng m−3 in July) is consistent with observations made at the coast (280 ± 78 ng m−3 in January versus 16 ± 9 ng m−3 in July at Dumont d'Urville, for instance). In contrast, the well-marked maximum of MSA at the coast in January (60 ± 23 ng m−3 at Dumont d'Urville) is not observed at Concordia (5.2 ± 2.0 ng m−3 in January). Instead, the MSA level at Concordia peaks in October (5.6 ± 1.9 ng m−3) and March (14.9 ± 5.7 ng m−3). As a result, a surprisingly low MSA-to-nssSO4 ratio (RMSA) is observed at Concordia in mid-summer (0.05 ± 0.02 in January versus 0.25 ± 0.09 in March). We find that the low value of RMSA in mid-summer at Concordia is mainly driven by a drop of MSA levels that takes place in submicron aerosol (0.3 µm diameter). The drop of MSA coincides with periods of high photochemical activity as indicated by high ozone levels, strongly suggesting the occurrence of an efficient chemical destruction of MSA over the Antarctic plateau in mid-summer. The relationship between MSA and nssSO4 levels is examined separately for each season and indicates that concentration of non-biogenic sulfate over the Antarctic plateau does not exceed 1 ng m−3 in fall and winter and remains close to 5 ng m−3 in spring. This weak non-biogenic sulfate level is discussed in the light of radionuclides (210Pb, 10Be, and 7Be) also measured on bulk aerosol samples collected at Concordia. The findings highlight the complexity in using MSA in deep ice cores extracted from inland Antarctica as a proxy of past dimethyl sulfide emissions from the Southern Ocean.

House Price Shocks and Individual Divorce Risk in the United States

Households in the United States hold a significant portion of their total wealth in owner-occupied housing. Thus, changes in housing prices may have an important impact on the marital surplus the household enjoys. What happens to marriages of homeowners when there is a shock to housing prices? This question was addressed using household data from the panel study of income dynamics (PSID) and a quarterly MSA level house price index from the Federal Housing Finance Agency, controlling for local labor market conditions. House price shocks were calculated as the cumulative sum of residuals of a second order autoregressive model from the previous four years. Results showed that positive house price shocks stabilized marriage for all couples. A one standard deviation increase in the house price shock decreased the risk of divorce in the following year by about 13–18%. The results were driven by the younger cohort of households in the PSID, those with lower educational attainment, and those with relatively low family income. The findings are discussed in the context of theories on changes in marital surplus, and changes in the transaction costs surrounding divorce.

Location, Location, Location: Estimating Impacts of Sports Venues and Other Attractions

This paper presents a novel approach for analyzing spatially differentiated impacts of a variety of entertainment attractions, including professional sports venues, convention centers, destination retail, and mega-events. Public finding is often based on the potential for such projects to stimulate economic growth. Although, the literature fails to uncover evidence of growth benefits, the analysis is typically of net aggregate benefits at the MSA level where as large attractions are likely to have differential impacts across geographic locations as well as industry types. This paper extends previous research by exploiting a unique micro dataset; the National Establishment Times series (NETs). This allows for spatial panel analysis with a focus on industries most likely to be impacted by the attraction. I find evidence of spatially differentiated impacts associated with the relocation of the National Basketball Association franchise from Seattle (SuperSonics) to Oklahoma City (Thunder). The franchise relocation attracted retail sales to the downtown area of OKC but may have decreased sales outside of downtown.