Migration and Social Insurance

Helmuth Cremer & Catarina Goulão

Recherches Economiques de Louvain2014https://doi.org/10.3917/rel.801.0005article
ABDC B
Weight
0.34

What the paper says

Mobility across countries is often suspected to affect the coexistence of different social insurance systems. A wide variety of social protection systems exist within the EU. Some are of Beveridgean inspiration (with universal and more or less flat benefits), while others are mainly Bismarckian (with benefits related to past contributions). Concerns about the sustainability of the most generous and redistributive (Beveridgean) insurance systems are often based on the assumption of (near) perfect and costless mobility. In reality, labor mobility remains limited. Such low levels of migration rates could, mistakenly, lead to the conclusion that migration would currently not be affecting the redistributive social insurance systems. We address this issue in a two-country setting, where mobility is costly and where individuals differ in mobility cost (attachment to their native country). A Bismarckian insurance system is not affected by migration while a Beveridgean one is. Our results suggest that the race-to-the-bottom affecting tax rates may be more important under Beveridge-Beveridge competition than under Beveridge-Bismarck competition. Finally, we study the strategic choice of the type of social protection. We show that Bismarckian governments may find it beneficial to adopt a Beveridgean insurance system. JEL Classification: H23, H70.

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https://doi.org/https://doi.org/10.3917/rel.801.0005

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@article{helmuth2014,
  title        = {{Migration and Social Insurance}},
  author       = {Helmuth Cremer & Catarina Goulão},
  journal      = {Recherches Economiques de Louvain},
  year         = {2014},
  doi          = {https://doi.org/https://doi.org/10.3917/rel.801.0005},
}

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Evidence weight

0.34

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

F · citation impact0.00 × 0.4 = 0.00
M · momentum0.80 × 0.15 = 0.12
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.