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It’s an election year, and Americans are debating big issues: capitalism and socialism, the role of government, the future of health care. These issues reflect what some see as a conflict between individual well-being and the greater public good. Do we want an up-by-your-bootstraps society where people mostly look after their own, or do we want a strong safety net for those who fall on hard times
Now the coronavirus is upon us. In its shadow, the line between individual well-being and the public good is harder to see.
The future sustainability of cities is contingent on economic resilience. Yet, urban resilience is still not well understood, as cities are frequently disrupted by shocks, such as natural disasters, economic recessions, or changes in government policies. These shocks can significantly alter a city’s economic structure. Yet the term economic structure is often used metaphorically and is often not understood sufficiently by those having to implement policies. Here, we operationalized the concept of economic structure as a weighted network of interdependent industry sectors. For 938 U.S.
The COVID-19 pandemic of 2020 fundamentally changed the way we interact with and engage in commerce. Social distancing and stay-at-home orders leave businesses and cities wondering how future economic activity moves forward. The reduction in face-to-face interactions creates an impetus to understand how social interactivity influences economic efficiency and rates of innovation. Here, we create a measure of the degree to which a workforce engages in social interactions, analyzing its relationships to economic innovation and efficiency. We do this by decomposing U.S.
Cities are frequently subjected to shocks, such as natural disasters, economic recessions, or changes in government policies. Those shocks are often accompanied by economic impacts that can alter the city’s economic structure. Yet the term economic structure is often used metaphorically and is often not understood in sufficient detail by those having to implement policies. Here we operationalize the concept of economic structure as a quantified network of interdependent industry sectors. For each U.S.
Urbanization has resulted in over half of humanity now living in cities. A key driver of this process is the pursuit of economic opportunities unique to urban areas. One of those opportunities is the promise of higher wages in larger cities, a phenomenon known as the urban wage premium. While the urban wage premium has been well‐documented among U.S. metropolitan areas, little is known about its existence among micropolitan areas, which represent an important link between rural and dense urban areas and likely influence both urbanization and deurbanization.
We analyze how a region’s industrial structure affects its productivity and its resilience to shocks. Using co-occurrence analysis, we construct an interdependence network of U.S. industries. For each U.S. metropolitan area, we then calculate an aggregate metric of this network called economic tightness, which captures the interconnectedness among a region’s industries.
The extent to which employees change jobs, known as the job mobility rate, has been steadily declining in the US for decades. This decline is understood to have a negative impact on both productivity and wages, and econometric studies fail to support any single cause brought forward. This decline coincides with decreases in household savings, increases in household debt and wage stagnation.
The Firm Ecosystem Model is a dynamical model based on the empirical finding that firm characteristics, such as the tendency to innovate and competitive advantages, vary according to firm size. Firm dynamics leading to various population distributions are considered as a competition-colonization scenario in a spatially defined market, where firms of differing sizes are treated as separate species with different competition and colonization characteristics.
The innovation of modeling firm search behavior using NK fitness landscapes is twenty years old, but despite the potential of this method its adoption remains sparse. This is likely be due to three reasons. First, many questions of current interest are not amenable to the classic NK model formulation, especially those involving the structure of interactions within firms. Second, rugged landscapes for larger N values are impossible to conceptualize. Third, generating landscapes of significant scale can be computationally intensive.
Cities are among the best examples of complex systems. The adaptive components of a city, such as its people, firms, institutions, and physical structures, form intricate and often non-intuitive interdependencies with one another. These interdependencies can be quantified and represented as links of a network that give visibility to otherwise cryptic structural elements of urban systems. Here, we use aspects of information theory to elucidate the interdependence network among labor skills, illuminating parts of the hidden economic structure of cities.