Deborah Strumsky

Mobility, Skills, and the Michigan Non-Compete Experiment

Whereas a number of studies have considered the implications of employee mobility, comparatively little research has considered institutional factors governing the ability of employees to move from one firm to another. This paper explores a legal constraint on mobility---employee non-compete agreements---by exploiting Michigans apparently inadvertent 1985 reversal of its non-compete enforcement policy as a natural experiment. Using a differences-in-differences approach, and controlling for changes in the auto industry central to Michigans economy, we find that the enforcement of non-competes indeed attenuates mobility. Moreover, non-compete enforcement decreases mobility more sharply for inventors with firm-specific skills and for those who specialize in narrow technical fields. The results speak to the literature on employee mobility while offering a credibly exogenous source of variation that can extend previous research on the implications of such mobility.

Urban Scaling and Its Deviations: Revealing the Structure of Wealth, Innovation and Crime across Cities

With urban population increasing dramatically worldwide, cities are playing an increasingly critical role in human societies and the sustainability of the planet. An obstacle to effective policy is the lack of meaningful urban metrics based on a quantitative understanding of cities. Typically, linear per capita indicators are used to characterize and rank cities. However, these implicitly ignore the fundamental role of nonlinear agglomeration integral to the life history of cities. As such, per capita indicators conflate general nonlinear effects, common to all cities, with local dynamics, specific to each city, failing to provide direct measures of the impact of local events and policy. Agglomeration nonlinearities are explicitly manifested by the superlinear power law scaling of most urban socioeconomic indicators with population size, all with similar exponents (1.15). As a result larger cities are disproportionally the centers of innovation, wealth and crime, all to approximately the same degree. We use these general urban laws to develop new urban metrics that disentangle dynamics at different scales and provide true measures of local urban performance. New rankings of cities and a novel and simpler perspective on urban systems emerge. We find that local urban dynamics display long-term memory, so cities under or outperforming their size expectation maintain such (dis)advantage for decades. Spatiotemporal correlation analyses reveal a novel functional taxonomy of U.S. metropolitan areas that is generally not organized geographically but based instead on common local economic models, innovation strategies and patterns of crime.

Does Size Matter? Scaling of CO2 Emissions and U.S. Urban Areas

Urban areas consume more than 66% of the world’s energy and generate more than 70% of global greenhouse gas emissions. With the world’s population expected to reach 10 billion by 2100, nearly 90% of whom will live in urban areas, a critical question for planetary sustainability is how the size of cities affects energy use and carbon dioxide (CO2) emissions. Are larger cities more energy and emissions efficient than smaller ones? Do larger cities exhibit gains from economies of scale with regard to emissions? Here we examine the relationship between city size and CO2 emissions for U.S. metropolitan areas using a production accounting allocation of emissions. We find that for the time period of 1999–2008, CO2 emissions scale proportionally with urban population size. Contrary to theoretical expectations, larger cities are not more emissions efficient than smaller ones.

Invention as a combinatorial process: evidence from US patents

Invention has been commonly conceptualized as a search over a space of combinatorial possibilities. Despite the existence of a rich literature, spanning a variety of disciplines, elaborating on the recombinant nature of invention, we lack a formal and quantitative characterization of the combinatorial process underpinning inventive activity. Here, we use US patent records dating from 1790 to 2010 to formally characterize invention as a combinatorial process. To do this, we treat patented inventions as carriers of technologies and avail ourselves of the elaborate system of technology codes used by the United States Patent and Trademark Office to classify the technologies responsible for an inventions novelty. We find that the combinatorial inventive process exhibits an invariant rate of ‘exploitation’ (refinements of existing combinations of technologies) and ‘exploration’ (the development of new technological combinations). This combinatorial dynamic contrasts sharply with the creation of new technological capabilities—the building blocks to be combined—that has significantly slowed down. We also find that, notwithstanding the very reduced rate at which new technologies are introduced, the generation of novel technological combinations engenders a practically infinite space of technological configurations.

Using patent technology codes to study technological change

Much work on technological change agrees that the recombination of new and existing technological capabilities is one of the principal sources of technological novelty. Patented inventions can be seen as bundles of distinct technologies brought together to accomplish a specific outcome – and this is how the US Patent Office defines inventions. The technologies constituting inventions are identified by the US Patent Office through an elaborate system of technology codes. A combinatorial perspective on invention, emblematic of approaches to technological change informed by evolutionary economics and complexity science, is inherent in the use of technology codes to summarize what is technologically novel about a patented invention. The technology codes represent a set of consistent definitions of technologies and their components spanning 220 years of inventive activity, and are an underutilized data resource for identifying distinct technological capabilities, defining technology spaces, marking the arrival of technological novelty, measuring technological complexity, and empirically grounding the study of technological change. The present discussion provides an introduction to the use of patent technology codes as well as some basic empirics. Our results highlight the highly discriminating nature of the codes and their usefulness in characterizing the type of processes by which technological capabilities generate novelty.

Urban Scaling and the Production Function for Cities

The factors that account for the differences in the economic productivity of urban areas have remained difficult to measure and identify unambiguously. Here we show that a microscopic derivation of urban scaling relations for economic quantities vs. population, obtained from the consideration of social and infrastructural properties common to all cities, implies an effective model of economic output in the form of a Cobb-Douglas type production function. As a result we derive a new expression for the Total Factor Productivity (TFP) of urban areas, which is the standard measure of economic productivity per unit of aggregate production factors (labor and capital). Using these results we empirically demonstrate that there is a systematic dependence of urban productivity on city population size, resulting from the mismatch between the size dependence of wages and labor, so that in contemporary US cities productivity increases by about 11% with each doubling of their population. Moreover, deviations from the average scale dependence of economic output, capturing the effect of local factors, including history and other local contingencies, also manifest surprising regularities. Although, productivity is maximized by the combination of high wages and low labor input, high productivity cities show invariably high wages and high levels of employment relative to their size expectation. Conversely, low productivity cities show both low wages and employment. These results shed new light on the microscopic processes that underlie urban economic productivity, explain the emergence of effective aggregate urban economic output models in terms of labor and capital inputs and may inform the development of economic theory related to growth.

Scaling and universality in urban economic diversification.

Understanding cities is central to addressing major global challenges from climate change to economic resilience. Although increasingly perceived as fundamental socio-economic units, the detailed fabric of urban economic activities is only recently accessible to comprehensive analyses with the availability of large datasets. Here, we study abundances of business categories across US metropolitan statistical areas, and provide a framework for measuring the intrinsic diversity of economic activities that transcends scales of the classification scheme. A universal structure common to all cities is revealed, manifesting self-similarity in internal economic structure as well as aggregated metrics (GDP, patents, crime). We present a simple mathematical derivation of the universality, and provide a model, together with its economic implications of open-ended diversity created by urbanization, for understanding the observed empirical distribution. Given the universal distribution, scaling analyses for individual business categories enable us to determine their relative abundances as a function of city size. These results shed light on the processes of economic differentiation with scale, suggesting a general structure for the growth of national economies as integrated urban systems.business diversity Hyejin Youn,1,2,3∗, Luı́s M. A. Bettencourt, José Lobo, Deborah Strumsky, Horacio Samaniego, and Geoffrey B. West, 1 Institute for New Economic Thinking, Walton Well Rd, OX2 6ED, Oxford, 2 Mathematical Institute, University of Oxford, Woodstock Road, Oxford, OX2 6GG UK, 3 Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501 USA, 4 School of Sustainability, Arizona State University, Tempe, AZ 85287 USA, 5 Geography and Earth Sciences, University of North Carolina at Charlotte, Charlotte NC 28223 USA, 6 Facultad de Ciencias Forestales and Recursos Naturales, Universidad Austral de Chile, Valdivia, Chile ∗To whom correspondence should be addressed; E-mail: youn@maths.ox.ac.uk

The Inventive, the Educated, and the Creative: How Do They Affect Metropolitan Productivity?

A longstanding research tradition assumes that endogenous technological development increases regional productivity. It has been assumed that measures of regional patenting activity or human capital are an adequate way to capture the endogenous creation of new ideas that result in productivity improvements. This process has been conceived as occurring in two stages. First, an invention or innovation is generated, and then it is developed and commercialized to create benefits for the individual or firm owning the idea. Typically these steps are combined into a single model of the “invention in/productivity out” variety. Using data on Gross Metropolitan Product per worker and on inventors, educational attainment, and creative workers (together with other important socioeconomic controls), we unpack the model back to the two-step process and use a SEM modeling framework to investigate the relationships among inventive activity and potential inventors, regional technology levels, and regional productivity outcomes. Our results show almost no significant direct relationship between invention and productivity, except through technology. Clearly, the simplification of the “invention in/productivity out” model does not hold, which supports other work that questions the use of patents and patenting related measures as meaningful innovation inputs to processes that generate regional productivity and productivity gains. We also find that the most effective measure of regional inventive capacity, in terms of its effect on technology, productivity, and productivity growth is the share of the workforce engaged in creative activities.

Sectoral Shares, Specialisation and Metropolitan Wages in the United States, 1969-96

We investigate the effect of specialisation upon the level of metropolitan wage per worker. Specialisation is measured by the share of metropolitan earnings in each of five traded goods and services sectors. Sectoral specialisations are assumed to be determinants of location-specific productivity, which in turn is treated as a term in a metropolitan production function. Panel data are used for estimating that production function for 313 metropolitan areas in the US, over the long period 1969-96 and two shorter periods. We find that some specialisations raise average metropolitan wages, some lower it and some have no effect, and that the effects of specialisation differ by time-period.

Profiling U.S. Metropolitan Regions by Their Social Research Networks and Regional Economic Performance

On the premise that knowledge creation defines contemporary metropolitan regions, we profile them by their inventive networks, as measured by a variety of complementary social network, technology, and patenting metrics that distinguish scalar and structural aspects. Using a comprehensive, multiyear database of patent applications, we investigate whether the knowledge creation network profiles are discriminating characteristics of metropolitan regions by establishing a new urban taxonomy for metropolitan areas in the United States. The four‐class taxonomy is not only statistically significant, but it is also economically meaningful in terms of economic performance of metropolitan areas. We find that metropolitan areas benefit from a higher density of inventors in the population, and that there is a positive correlation between economic performance and metropolitan areas with inventor teams working in similar or complementary areas of technology. In fact, the structure of knowledge creation networks are fundamental to economic performance and extends to metropolitan growth rates in jobs and income.