North America

2018
Kosack, S., et al., 2018. Functional structures of US state governments. Proceedings of the National Academy of Sciences of the United States of America. Publisher's VersionAbstract
Governments in modern societies undertake an array of complex functions that shape politics and economics, individual and group behavior, and the natural, social, and built environment. How are governments structured to execute these diverse responsibilities? How do those structures vary, and what explains the differences? To examine these longstanding questions, we develop a technique for mapping Internet “footprint” of government with network science methods. We use this approach to describe and analyze the diversity in functional scale and structure among the 50 US state governments reflected in the webpages and links they have created online: 32.5 million webpages and 110 million hyperlinks among 47,631 agencies. We first verify that this extensive online footprint systematically reflects known characteristics: 50 hierarchically organized networks of state agencies that scale with population and are specialized around easily identifiable functions in accordance with legal mandates. We also find that the footprint reflects extensive diversity among these state functional hierarchies. We hypothesize that this variation should reflect, among other factors, state income, economic structure, ideology, and location. We find that government structures are most strongly associated with state economic structures, with location and income playing more limited roles. Voters’ recent ideological preferences about the proper roles and extent of government are not significantly associated with the scale and structure of their state governments as reflected online. We conclude that the online footprint of governments offers a broad and comprehensive window on how they are structured that can help deepen understanding of those structures.
government-structure-paper.pdf
Patterson-Lomba, O. & Gomez-Lievano, A., 2018. On the Scaling Patterns of Infectious Disease Incidence in Cities.Abstract
Urban areas with larger and more connected populations offer an auspicious environment for contagion processes such as the spread of pathogens. Empirical evidence reveals a systematic increase in the rates of certain sexually transmitted diseases (STDs) with larger urban population size. However, the main drivers of these systemic infection patterns are still not well understood, and rampant urbanization rates worldwide makes it critical to advance our understanding on this front. Using confirmed-cases data for three STDs in US metropolitan areas, we investigate the scaling patterns of infectious disease incidence in urban areas. The most salient features of these patterns are that, on average, the incidence of infectious diseases that transmit with less ease– either because of a lower inherent transmissibility or due to a less suitable environment for transmission– scale more steeply with population size, are less predictable across time and more variable across cities of similar size. These features are explained, first, using a simple mathematical model of contagion, and then through the lens of a new theory of urban scaling. These frameworks help us reveal the links between the factors that determine the transmissibility of infectious diseases and the properties of their scaling patterns across cities.
infectious_disease_incidence_rfwp_94.pdf
The Exposure of U.S. Manufacturing Industries to Exchange Rates
Thorbecke, W., 2018. The Exposure of U.S. Manufacturing Industries to Exchange Rates. International Review of Economics and Finance. Publisher's VersionAbstract
Safe asset demand and currency manipulation increase the dollar and the U.S. current account deficit. Deficits in manufacturing trade cause dislocation and generate protectionism. Dynamic OLS results indicate that U.S. export elasticities exceed unity for automobiles, toys, wood, aluminum, iron, steel, and other goods. Elasticities for U.S. imports from China are close to one or higher for footwear, radios, sports equipment, lamps, and watches and exceed 0.5 for iron, steel, aluminum, miscellaneous manufacturing, and metal tools. Elasticities for U.S. imports from other countries are large for electrothermal appliances, radios, furniture, lamps, miscellaneous manufacturing, aluminum, automobiles, plastics, and other categories. Stock returns on many of these sectors also fall when the dollar appreciates. Several manufacturing industries are thus exposed to a strong dollar. Policymakers could weaken the dollar and deflect protectionist pressure by promoting the euro, the yen, and the renminbi as alternative reserve currencies.
exchange_rates_iref_thorbecke.pdf
Thornbecke, W., 2018. The Exposure of U.S. Manufacturing Industries to Exchange Rates.Abstract
Safe asset demand and currency manipulation increase the dollar and the U.S. current account deficit. Deficits in manufacturing trade cause dislocation and generate protectionism. Dynamic OLS results indicate that U.S. export elasticities exceed unity for automobiles, toys, wood, aluminum, iron, steel, and other goods. Elasticities for U.S. imports from China are close to one or higher for footwear, radios, sports equipment, lamps, and watches and exceed 0.5 for iron, steel, aluminum, miscellaneous manufacturing, and metal tools. Elasticities for U.S. imports from other countries are large for electrothermal appliances, radios, furniture, lamps, miscellaneous manufacturing, aluminum, automobiles, plastics, and other categories. For U.S. exports and especially for U.S. imports from China, trade in more sophisticated products are less sensitive to exchange rates. Stock returns on many of the sectors with high export and import elasticities also fall when the dollar appreciates. Several manufacturing industries are thus exposed to a strong dollar. Policymakers could weaken the dollar and deflect protectionist pressure by promoting the euro, the yen, and the renminbi as alternative reserve currencies.
 
cidrfwp92.pdf
2016
Gomez-Lievano, A., Patterson-Lomba, O. & Hausmann, R., 2016. Explaining the Prevalence, Scaling and Variance of Urban Phenomena.Abstract

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.

urban_phenomena_cidwp329.pdf

This paper is published in the journal, Nature: Human Behavior.

Explaining the prevalence, scaling and variance of urban phenomena
Gomez-Lievano, A., Patterson-Lomba, O. & Hausmann, R., 2016. Explaining the prevalence, scaling and variance of urban phenomena. Nature Human Behavior. Publisher's VersionAbstract

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.

Related Content: https://www.hks.harvard.edu/centers/cid/about-cid/news-announcements/urban-theory

Russell, S., Barrios, D. & Andrews, M., 2016. Getting the Ball Rolling: Basis for Assessing the Sports Economy.Abstract

Data on the sports economy is often difficult to interpret, far from transparent, or simply unavailable. Data fraught with weaknesses causes observers of the sports economy to account for the sector differently, rendering their analyses difficult to compare or causing them to simply disagree. Such disagreement means that claims regarding the economic spillovers of the industry can be easily manipulated or exaggerated. Thoroughly accounting for the industry is therefore an important initial step in assessing the economic importance of sports-related activities. For instance, what do policymakers mean when they discuss sports-related economic activities? What activities are considered part of the "sports economy?" What are the difficulties associated with accounting for these activities? Answering these basic questions allows governments to improve their policies.

The paper below assesses existing attempts to understand the sports economy and proposes a more nuanced way to consider the industry. Section 1 provides a brief overview of existing accounts of the sports economy. We first differentiate between three types of assessments: market research accounts conducted by consulting groups, academic accounts written by scholars, and structural accounts initiated primarily by national statistical agencies. We then discuss the European Union’s (EU) recent work to better account for and understand the sports economy. Section 2 describes the challenges constraining existing accounts of the sports economy. We describe two major constraints - measurement challenges and definition challenges - and highlight how the EU's work has attempted to address them. We conclude that, although the Vilnius Definition improves upon previous accounts, it still features areas for improvement.

Section 3 therefore proposes a paradigm shift with respect to how we understand the sports economy. Instead of primarily inquiring about the size of the sports economy, the approach recognizes the diversity of sports-related economic activities and of relevant dimensions of analysis. It therefore warns against attempts at aggregation before there are better data and more widely agreed upon definitions of the sports economy. It asks the following questions: How different are sports-related sectors? Are fitness facilities, for instance, comparable to professional sports clubs in terms of their production scheme and type of employment? Should they be understood together or treated separately? We briefly explore difference in sports-related industry classifications using data from the Netherlands, Mexico, and the United States. Finally, in a short conclusion, we discuss how these differences could be more fully explored in the future, especially if improvements are made with respect to data disaggregation and standardization.

cidwp_321_assessing_sports_economy.pdf