Decompensating domestically: the political economy of anti-globalism

ABSTRACT

The rise of populism across advanced industrial countries presents a challenge to the institutions and norms that make up the current global order and threatens to undo the global system that has enabled decades of free trade and investment. We outline in this paper a domestic political economy account of the contemporary crisis of the global order, rooted in disenchantment with the redistributive bargain between globalization’s winners and losers. We present individual and local-level evidence that is consistent with this account, first documenting the decline of the embedded liberal compromise over the past 40 years in Europe, and then providing individual-level evidence from the United States of growing protectionism and xenophobia in response to import exposure, particularly among respondents whose occupational profile is most risk-exposed.

KEYWORDS:

• Populism
• free trade
• globalization
• protectionism
• xenophobia
• liberalism

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Thomas B. Pepinsky http://orcid.org/0000-0002-4000-217X

Notes

1 These figures were generated from two OLS regressions that predict seats and votes as a function of trade openness, year fixed effects, and their interaction, controlling for GDP growth, GDP per capita, and country fixed effects: $y_{it}=\mathrm{T}\mathrm{r}\mathrm{a}\mathrm{d}{\mathrm{e}}_{it}+{\tau }_t+\mathrm{T}\mathrm{r}\mathrm{a}\mathrm{d}{\mathrm{e}}_{it}\times {\tau }_t+X_{it}+{\phi }_i+{\epsilon }_{it}$. Fractional logistic regressions produce qualitatively similar results. The country sample includes Australia, Austria, Belgium, Canada, Denmark, Finland, France, (West) Germany, Greece, Ireland, Italy, Japan, the Netherlands, New Zealand, Norway, Portugal, Spain, Sweden, Switzerland, the UK, and the US. Economic data are from the World Development Indicators.

2 The country list for these figures also includes former communist East and Central Europe as well as Turkey and Israel, but excludes the US, UK, Australia, New Zealand, and Japan.

3 We generate these measures by applying O*NET task-intensity measures to each occupation. For each dyad pair of occupations, we calculate the Euclidean distance based on these task-intensity vectors. We characterize occupational mobility as the Eigenvector centrality for each occupation. We invert this measure of task centrality to characterize occupational risk.

4 These figures were generated from OLS regressions that predict each response as a function of occupational risk, total layoffs, and their interaction, controlling for a range of respondent demographic characteristics and district fixed effects: $y_{id}=\mathrm{R}\mathrm{i}\mathrm{s}{\mathrm{k}}_{id}\times \mathrm{L}\mathrm{a}\mathrm{y}\mathrm{o}\mathrm{f}\mathrm{f}{\mathrm{s}}_d+X_{id}+{\delta }_d+{\epsilon }_{id}$.

Additional information

Notes on contributors

James Bisbee

James Bisbee is a postdoc at the Niehaus Center for Globalization and Governance at Princeton University.

Layna Mosley

Layna Mosley is Professor of Political Science at the University of North Carolina at Chapel Hill.

Thomas B. Pepinsky

Thomas Pepinsky is Professor of Government at Cornell University.

B. Peter Rosendorff

B. Peter Rosendorff is Professor of Politics at New York University.