The bidirectional relationship between population and employment is analyzed across 377 US metropolitan areas during 4 overlapping decades in the period 1990-2015. Applying 2SLS regression to the regional adjustment model, current population depends on lagged population, current employment, and various natural and human-created amenities. Likewise, current employment depends on current population, lagged employment, and a series of economic attributes (wages, professional workers, etc.), including self-employment (entrepreneurship) and patenting (inventiveness). Pooled estimation shows that “people followed jobs” before 2000 but then “jobs followed people” afterward. Amenities (+) invariably affected population numbers while wages (-) invariably affected job numbers. Once endogenized, self-employment had a strong impact on job numbers during the entire 25-year period, while patenting had a much weaker and uneven impact on those numbers. Special consideration is given to spatial lag effects, which were found to be mostly negative (indicating competition) in both instances.
Gordon F. Mulligan
This chapter examines (utility) patents across US metropolitan areas in 1990–2015, a period when patent volumes became increasingly concentrated in the nation’s largest places. To begin, estimates of these volumes are made at five-year intervals using only population size as an explanatory variable. Other cross-sectional patenting estimates follow, based on twenty-plus metropolitan attributes, including: education of the workforce, industrial specialization, location (climate), average wages, per capita GDP, and various human-created amenities. A multivariate approach captures some of the key differences in the metropolitan innovation ecosystems. (Ordinal) performance scores are estimated for six separate orthogonal factors and, together, they provide a performance vector for each metropolitan economy. Linear regression next indicates that three factors, Economic Size, Location, and Industrial Specialization, have become especially important in US metropolitan patent generation during recent times. The pattern of estimates for patent densities, or per capita patenting volumes, is shown to be remarkably similar.
John I. Carruthers and Gordon F. Mulligan
The lack of scientific evidence in urban and regional policymaking is problematic: in order for policy to be credible it must be guided by evidence, not ideology. Benefit–cost analysis has long been the workhorse of policy analysis, but other methods are needed too. This chapter advances one method – the regional adjustment model – and explains how it has been applied within and among regions. Along the way, it delivers an empirical example, by applying the framework to growth and development within the American constellation of metropolitan areas. The chapter concludes that regional adjustment models ought to be used as an instrument of evidence-based policy to address questions related to anthropogenic climate change.