| Autor: |
Corrado, L., Stengos, T., Weeks, M., Ege Yazgan, M. |
| Rok vydání: |
2019 |
| Předmět: |
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| DOI: |
10.17863/cam.35572 |
| Popis: |
In many applications common in testing for convergence the number of cross-sectional units is large and the number of time periods are few. In these situations asymptotic tests based on an omnibus null hypothesis are characterised by a number of problems. In this paper we propose a multiple pairwise comparisons method based on an a recursive bootstrap to test for convergence with no prior information on the composition of convergence clubs. Monte Carlo simulations suggest that our bootstrap-based test performs well to correctly identify convergence clubs when compared with other similar tests that rely on asymptotic arguments. Across a potentially large number of regions, using both cross-country and regional data for the European Union we find that the size distortion which afflicts standard tests and results in a bias towards finnding less convergence, is ameliorated when we utilise our bootstrap test. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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