Expansionary austerity in Europe: finally an oxymoron?

Olimpia Fontana & Lino Sau

European Journal of Economics and Economic Policies: Intervention2025https://doi.org/10.4337/ejeep.2025.0152article
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What the paper says

The expansionary austerity thesis (EAT) emerged and established itself in the 1990s, based on theoretical and empirical research, and was rapidly incorporated into macroeconomic theory. In a nutshell, fiscal consolidations, aimed at stabilising or lowering the public debt-to-GDP ratio, can stimulate growth, even during a recession. Simply put, expansionary austerity materialises. This is a counter-intuitive effect that can significantly be defined as ‘non-Keynesian’. In this article, we attempt to summarise the debates around the EAT and argue for its critical evaluation through a discussion of its assumptions and functioning, with specific reference to the European Union. Although much of the criticism has addressed various shortcomings of econometric techniques, less attention has been paid to the logical robustness of the theoretical underpinnings of the EAT. We provide an in-depth examination of austerity in terms of its evolution in economic thought and consider Europe as a reference point, highlighting the link between the Washington Consensus and the Berlin-Brussels Consensus. We conclude that the EAT ultimately proved to be an oxymoron, but the risks of fiscal austerity could recur again in the EU, undermining the need for expansionary fiscal policy in times of crisis.

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https://doi.org/https://doi.org/10.4337/ejeep.2025.0152

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@article{olimpia2025,
  title        = {{Expansionary austerity in Europe: finally an oxymoron?}},
  author       = {Olimpia Fontana & Lino Sau},
  journal      = {European Journal of Economics and Economic Policies: Intervention},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.4337/ejeep.2025.0152},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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