Working Paper: CEPR ID: DP2201
Authors: Fabio Canova
Abstract: The paper proposes a technique to test jointly for groupings of unknown size in the cross-sectional dimension of a panel and estimates the parameters of each group, applying it to identifying convergence clubs in income per-capita. The approach uses the predictive density of the data, conditional on the parameters of the model. The steady state distribution of European regional data clusters around four poles of attraction with different economic features. The distribution of income per-cpaita of OECD countries has two poles of attraction and each group has clearly identifiable economic characteristics.
Keywords: Heterogeneities; Panel Data; Predictive Density; Income Inequality
JEL Codes: C11; D90; O47
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| initial income conditions (F40) | convergence speed (O47) |
| initial income conditions (F40) | long-term income trajectories (J17) |
| initial income (E25) | long-term income stability (D15) |
| poor units (I32) | clustering around low-income pole (I32) |
| convergence clubs (D71) | income per capita (D31) |