The Impact of Demographics on the Level of Tariffs

James Ming Chen (), Thomas Poufinas, Charalampos Agiropoulos and George Galanos
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James Ming Chen: College of Law, Michigan State University
Thomas Poufinas: Department of Economics, Democritus University of Thrace
Charalampos Agiropoulos: Department of International and European Studies, University of Piraeus
George Galanos: Department of International and European Studies, University of Piraeus

Chapter Chapter 4 in Debt in Times of Crisis, 2021, pp 101-131 from Springer

Abstract: Abstract Demography almost surely affects the ability of countries to manage their debt levels as part of their overall macroeconomic policy. By the same token, the demographic attributes of labor influence political decisions among nation-states, including international trade policy. In particular, the free movement of labor is a bedrock principle of the European Union and a reason to join it or withdraw from it. This study investigates the influence of (labor) demographics on tariffs in 45 OECD and non-OECD countries. Through a series of econometric models and machine learning techniques we find evidence that the population and labor force may influence the level of tariffs, depending on the model and the database. By contrast, migration does not. Income per capita and consumption affect the tariff rate as well. Machine learning methods confirm conclusions reached through conventional econometrics and shed further light on the relationship between tariff levels and their hypothesized predictors.

Keywords: Tariffs; Demographics; Labor; Migration; Population; Machine learning (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-74162-4_4

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DOI: 10.1007/978-3-030-74162-4_4

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