North America

2018
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