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PRINCIPLES OF POLITICAL ECONOMY AND THE TAXATION OF NATIONS: ECONOMETRIC AND MACHINE-LEARNING EVALUATION OF TARIFFS
- Author(s):
- Charalampos Agiropoulos, James Ming Chen, George Galanos, Thomas Poufinas
- Date:
- 2020
- Group(s):
- Michigan State Law Review
- Item Type:
- Article
- Permanent URL:
- https://doi.org/10.17613/d4zy-py51
- Abstract:
- Demography affects the ability of countries to manage their debt levels and to make macroeconomic policy. By the same token, the demographic attributes of labor influence political decisions among nations, including international trade policy. In particular, the free movement of labor is a bedrock principle of the European Union. That legal guarantee has prompted one country to leave the Union, even as it inspires other countries to join. This Article investigates the influence of (labor) demographics on tariffs in forty-five OECD and non-OECD countries. A series of econometric models reveals evidence that the population and labor force may influence tariff levels. By contrast, migration does not. Income per capita and consumption affect tariff rates. Machinelearning methods confirm conclusions reached through conventional econometrics and shed further light on the relationship between tariff levels and their hypothesized predictors. The absence of a significant relationship between tariffs and migration undermines the common political assumption that tariff and immigration policy are mutually reinforcing levers of international policy.
- Metadata:
- xml
- Published as:
- Journal article
- Status:
- Published
- Last Updated:
- 1 year ago
- License:
- Attribution
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