Carolina Mattsson (p), Frank Takes

see extended abstract

Laszlo Czaller (p)

Morgan Frank

We develop a simple model of research collaborations with heterogeneous researchers that is consistent with several stylized facts of interregional research collaborations in Europe. We show that the impact of transaction costs associated with collaborative research can be decomposed into the intensive and extensive margins, where the former refers to the research intensity of collaboration between partner regions (edge weight) and the latter refers to the number of region pairs with positive ties (edge formation). We use the model to derive a two-stage gravity equation that accounts for self-selection into interregional research in the first stage and estimates research intensities in the second stage. We implement this procedure parametrically by estimating the probability of collaboration between any two regions using a probit model and then correcting for selection in the second stage. Since collaboration intensities are measured by using count data on joint publications, the Possion pseudo-maximum likelihood estimator is used to provide consistent estimates in the second stage of the procedure. We show that prior estimates on interregional research collaboration intensities are likely to be biased due to self-selection and the omission of the extensive margin. In addition, most of the variables that are often associated in the literature with the strength of interregional collaboration relations (e.g. geographical distance, social and intitutional proximty etc.) differ in whether they act through the intensive or the extensive margin.

Morgan Frank (p), Esteban Moro, Alex Pentland, Alex Rutherford, Manuel Cebrian, Iyad Rahwan

Laszlo Czaller

Cities are the innovation centers of the US economy, but technological disruptions can exclude workers and inhibit a middle class. Therefore, urban policy must promote the jobs and skills that increase worker pay, create employment, and foster economic resilience. In this paper, we model labor market resilience with an ecologically-inspired job network constructed from the similarity of occupations’ skill requirements. This framework reveals that the economic resilience of cities is universally and uniquely determined by the connectivity within a city’s job network. US cities with greater job connectivity experienced lower unemployment during the Great Recession. Further, cities that increase their job connectivity see increasing wage bills, and workers of embedded occupations enjoy higher wages than their peers elsewhere. Finally, we show how job connectivity may clarify the augmenting and deleterious impact of automation in US cities. Policies that promote labor connectivity may grow labor markets and promote economic resilience.

Tomaz Dentinho (p)

Morgan Frank

This papers aims to frame the complexity of spatial interactions using the structure of space imagined as a network of spatial channels built up by interacting flows. The first assumption is that space is a productive system represented by flows that justify, build up and maintain the channels, the same way as income justifies, constructs and preserves capital. The second assumption is that either there is (self-adapting) evolution of the territory that maximizes the size of channels, like a city that puts most of its income in urban infrastructure, or there is human rationality that optimizes the size of the channels to maximize human interaction flows. Using an entropy function, we can explain the relation between channel sizes and the flows that move along them. On the other hand, we use the integral of the entropy function to explain how the size of channels are built-up through the accumulated flows they generate. Finally, entropy functions that explain flows and channels open up to include distance constraints and external impacts. The paper demonstrates the capacity of spatial interaction models to explain and operationalize complex spatial networked systems with organic and human interaction within space. The application looks into the evolution of the Spanish city-regions since the civil war to see if the complementarity and substitutability between them follows an organic rule that maximizes the size of major cities or a rational rule that maximizes the interaction between city regions.

Morgan Frank (p), Esteban Moro, Tobin South, Alex Rutherford, Alex Pentland, Bledi Taska, Iyad Rahwan

Tomaz Dentinho

Career mobility requires desirable workplace skills and access to relevant labor markets.
Division of labor suggests that workers should specialize their skills over their careers but standard skill classifications of "cognitive" or "college educated" can obfuscate career dynamics. Here, we model career transitions as a network of occupations connected by the similarity occupations' skill requirements. Using a nationally representative survey and two resume data sets each representing 100 million individual workers, we show that skill similarity predicts transition rates between occupations and that predictions improve with increasingly-granular skill data. These observations inform a new measure for skill specialization from a worker's embeddedness in their economy's occupation network. Job changes and/or relocations that decrease embeddedness correspond to increased wages and workers tend to decrease their embeddedness over their careers. While low-embeddedness workers may leverage their locally-rare skills in wage negotiations, employers might also offer higher wages as an incentive for skilled workers to relocate. We find evidence for the latter since the combined embeddedness of city pairs corresponds to increased Census migration and increased flows of enplaned passengers according to the US Bureau of Transportation Statistics. This study directly connects workplace skills to workers’ career mobility and spatial mobility, thus offering new insights into skill specialization and current urbanization trends.