How to fight unemployment during a recession?

Tom Bauermann

Journal of Economic Interaction and Coordination2025https://doi.org/10.1007/s11403-025-00459-xarticle
AJG 1ABDC B
Weight
0.37

Abstract

The low and (partly) negative economic growth rates in Germany since the outbreak of the energy crises and growing danger of deindustrialization sparked debates about measures to avoid growing numbers of unemployed, for example by changing the generosity of unemployment benefits (UB) or extending short-time work. This paper aims to contribute to the theoretical literature of policy responses to recessions by analyzing three prominent instruments: (a) a permanent reduction of unemployment benefits that is accompanied by increasing search efforts, (b) a fiscal stimulus package and (c) short-time work. To analyze these measures, researchers typically use DSGE models or search and matching models. In contrast, I develop an agent-based macroeconomic model (ABM). Thus, I can analyze the interplay between macro- and microeconomic effects of policies, as well as how interactions among agents shape economic outcomes. I find three main results: First, (a) has almost no effect on unemployment in the short run and negative effects in the long run. This is contrary to the canonical search and matching models, even though the simulations reveal the same "desired" effects, e.g., shorter unemployment spells in the short run. Second, in comparison with (a), policies (b) and (c) can dampen unemployment in the short run and bring employment back to the normal rate more rapidly. Third, in contrast to representative agent models, I can show that short-time work supports the economic recovery through demand stabilization and a distributive effect among heterogeneous firms. In particular, the distributive effect has not been shown in other papers so far.

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@article{tom2025,
  title        = {{How to fight unemployment during a recession?}},
  author       = {Tom Bauermann},
  journal      = {Journal of Economic Interaction and Coordination},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1007/s11403-025-00459-x},
}

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Evidence weight

0.37

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

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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