Explaining the Prevalence, Scaling and Variance of Urban Phenomena
The prevalence of many urban phenomena changes systematically with population size1. We propose a theory that unifies models of economic complexity2, 3 and cultural evolution4 to derive urban scaling. The theory accounts for the difference in scaling exponents and average prevalence across phenomena, as well as the difference in the variance within phenomena across cities of similar size. The central ideas are that a number of necessary complementary factors must be simultaneously present for a phenomenon to occur, and that the diversity of factors is logarithmically related to population size. The model reveals that phenomena that require more factors will be less prevalent, scale more superlinearly and show larger variance across cities of similar size. The theory applies to data on education, employment, innovation, disease and crime, and it entails the ability to predict the prevalence of a phenomenon across cities, given information about the prevalence in a single city.
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This paper is published in the journal, Nature: Human Behavior.
Last updated on 12/10/2021
Inter-industry Labor Flows
Labor flows across industries reallocate resources and diffuse knowledge among economic activities. However, surprisingly little is known about the structure of such inter-industry flows. How freely do workers switch jobs among industries? Between which pairs of industries do we observe such switches? Do different types of workers have different transition matrices? Do these matrices change over time?
Using German social security data, we generate stylized facts about inter-industry labor mobility and explore its consequences. We find that workers switch industries along tight paths that link industries in a sparse network. This labor-flow network is relatively stable over time, similar for workers in different occupations and wage categories and independent of whether workers move locally or over larger distances. When using these networks to construct inter-industry relatedness measures they prove better predictors of local industry growth rates than co-location or input-based alternatives. However, because industries that exchange much labor typically do not have correlated growth paths, the sparseness of the labor-flow network does not necessarily prevent a smooth reallocation of workers from shrinking to growing industries. To facilitate future research, the inter-industry relatedness matrices we develop are made available as an online appendix to this paper.
Last updated on 11/22/2019
Agents of Structural Change: The role of firms and entrepreneurs in regional diversification
Who introduces structural change in regional economies: Entrepreneurs or existing firms? And do local or non‐local founders of establishments create most novelty in a region? Using matched employer/employee data for the whole Swedish workforce, we determine how unrelated and therefore how novel the activities of different establishments are to a region’s industry mix. Up‐ and downsizing establishments cause large shifts in the local industry structure, but these shifts only occasionally require an expansion of local capabilities because the new activities are often related to existing local activities. Indeed, these incumbents tend to align their production with the local economy, deepening the region’s specialization. In contrast, structural change mostly originates via new establishments, especially those with non‐local roots. Moreover, although entrepreneurs start businesses more often in activities unrelated to the existing regional economy, new establishments founded by existing firms survive in such activities more often, inducing longer‐lasting changes in the region.
Implied Comparative Advantage
The comparative advantage of a location shapes its industrial structure. Current theoretical models based on this principle do not take a stance on how comparative advantages in different industries or locations are related with each other, or what such patterns of relatedness might imply about the underlying process that governs the evolution of comparative advantage. We build a simple Ricardian-inspired model and show this hidden information on inter-industry and inter-location relatedness can be captured by simple correlations between the observed patterns of industries across locations or locations across industries. Using the information from related industries or related locations, we calculate the implied comparative advantage and show that this measure explains much of the location’s current industrial structure. We give evidence that these patterns are present in a wide variety of contexts, namely the export of goods (internationally) and the employment, payroll and number of establishments across the industries of subnational regions (in the US, Chile and India). The deviations between the observed and implied comparative advantage measures tend to be highly predictive of future industry growth, especially at horizons of a decade or more; this explanatory power holds at both the intensive as well as the extensive margin. These results suggest that a component of the long-term evolution of comparative advantage is already implied in today’s patterns of production.
Country diversification, product ubiquity, and economic divergence
Countries differ markedly in the diversification of their exports. Products differ in the number of countries that export them, which we define as their ubiquity. We document a new stylized fact in the global pattern of exports: there is a systematic relationship between the diversification of a country’s exports and the ubiquity of its products. We argue that this fact is not implied by current theories of international trade and show that it is not a trivial consequence of the heterogeneity in the level of diversification of countries or of the heterogeneity in the ubiquity of products. We account for this stylized fact by constructing a simple model that assumes that each product requires a potentially large number of non-tradable inputs, which we call capabilities, and that a country can only make the products for which it has all the requisite capabilities. Products differ in the number and specific nature of the capabilities they require, as countries differ in the number/nature of capabilities they have. Products that require more capabilities will be accessible to fewer countries (i.e., will be less ubiquitous), while countries that have more capabilities will have what is required to make more products (i.e., will be more diversified). Our model implies that the return to the accumulation of new capabilities increases exponentially with the number of capabilities already available in a country. Moreover, we find that the convexity of the increase in diversification associated with the accumulation of a new capability increases when either the total number of capabilities that exist in the world increases or the average complexity of products, defined as the number of capabilities products require, increases. This convexity defines what we term as aquiescence trap, or a trap of economic stasis: countries with few capabilities will have negligible or no return to the accumulation of more capabilities, while at the same time countries with many capabilities will experience large returns – in terms of increased diversification – to the accumulation of additional capabilities. We calibrate the model to three different sets of empirical data and show that the derived functional forms reproduce the empirically observed distributions of product ubiquity, the relationship between the diversification of countries and the average ubiquity of the products they export, and the distribution of the probability that two products are co-exported. This calibration suggests that the global economy is composed of a relatively large number of capabilities – between 23 and 80, depending on the level of disaggregation of the data – and that products require on average a relatively large fraction of these capabilities in order to be produced. The conclusion of this calibration is that the world exists in a regime where the quiescence trap is strong.