Todd Gabe

This paper examines the connection between measures of a U.S. metropolitan area's new urban crisis (i.e., unaffordable housing, economic inequality, and residential segregation) and its year-over-year employment change in the period immediately before and during the COVID-19 pandemic. Results show that measures of the new urban crisis did not generally have a statistically significant association with year-over-year employment change between January and September of 2020, which captures the period before COVID-19 and the beginning of the pandemic (e.g., shutdown). The severity of a region's economic segregation and inequality, however, are associated with higher rates of employment decline in the early recovery months of October to December of 2020. These findings suggest that places that rate worse for indicators of the new urban crisis were less able to recover from the negative economic shocks related to COVID-19.

Although location quotients are widely used to analyze local industry specialization and identify industry clusters in regions of all size, past studies have noted issues related to the accuracy of location quotients in small places. This paper examines the stability of location quotients in response to a marginal (i.e., one-unit) increase in the number of business establishments, with a focus on small regions. The analysis considers location quotients calculated for cities and towns in Maine, as well as all U.S. counties, and uses a range of industry classifications (e.g., 1-digit and 3-digit NAICS categories). Results show that the stability of location quotients increases with the population size of regions, but they do not uncover a single, universal population size cutoff for the reliable use of location quotients. Rather, the analysis shows that population size, the level of industry aggregation (e.g., 1-digit versus 3-digit NAICS) and even how the data are collected matter in determining the stability of location quotients.

This paper examines the relationship between a region’s population size and the match of college-educated workers to jobs that require a degree. Results show a positive relationship between degree match and county population size in the United States, with a 100,000-person increase in population associated with a 1.3-percentage point increase in the likelihood of a match. The analysis uses a person’s grade point average in college to account for the potential sorting of higher-skilled workers into larger urban areas and the dataset has individuals across a wide range of regions from small rural areas to big cities.

This paper examines the features of photographs that affect the memorability of landmarks that tourists walk past while visiting a place. Empirical results, based on surveys of cruise passengers that visited Bar Harbor, Maine, suggest that a mix of salient images (e.g., the ocean) and unique characteristics of a place (e.g., architectural elements) increase a visitor’s likelihood of remembering a landmark. An extension to the analysis shows that survey respondents are unlikely to attribute “fake” landmarks from different places to their day spent in Bar Harbor. The methods from this study can be employed in other places to examine the behavior and perceptions of tourists, and, more generally, photographs can be used to learn about how people interact with the places around them.

This paper examines the effects of the COVID-related Stay-at-Home order on hospitality sales and automobile traffic counts in the State of Maine, USA. Empirical results show that the Stay-at-Home order did not have a statistically significant impact on either measure of state economic activity. Instead, households adjusted their behavior as a result of COVID-19 in advance of the Stay-at-Home order. This is an important public policy issue given the large health and economic impacts of the pandemic, and widespread use of Stay-at-Home orders. Even beyond the COVID pandemic, however, the extent to which people respond to government restrictions is important for policy development and implementation.

This paper examines the use of location quotients, a measure of regional business activity relative to the national benchmark, as an indicator of sectoral agglomeration in small cities and towns, and as a measure of industry specialization that might impact the number of new business startups in these places. Using establishment-level data on businesses located in Maine, our findings suggest that the addition of one "hypothetical" establishment in very small towns leads to a dramatic change in the magnitude of the region-industry location quotient. At population sizes of about 4,100 or more people, however, location quotients are reasonably stable. Regression results from an analysis of the relationship between new business activity and regional industry specialization show that the effect of location quotients on business startups switches from "inelastic" to "elastic" at a population size cutoff of about 2,600 residents. Overall, our findings suggest that researchers and practitioners should exercise caution when using location quotients to study small regions.

Regional scientists and planners are interested in congestion, both vehicular and pedestrian. This paper examines pedestrian congestion on sidewalks in the tourism district of Bar Harbor, Maine, with a focus on the effects of cruise passengers. The analysis considers pedestrian counts and the effects of passengers on walking speeds. Cruise passengers increase sidewalk pedestrian traffic overall, but the effects on walking speeds are mixed. For both indicators of sidewalk congestion, cruise passenger impacts decrease at greater distances from the passenger point‐of‐entry into Bar Harbor. The methods presented in the paper can be applied to sidewalk congestion related to a wide range of facilities and events (e.g., transportation hubs, museums and concert halls, sporting events, large pilgrimage events).