Income Convergence in CESEE since EU Accession
Beta-convergence and a staggered event-study analysis
Abstract
We track real income convergence in the eleven Central, East and Southeast European (CESEE) members of the European Union since their accession waves of 2004, 2007 and 2013. A cross-sectional beta-convergence regression documents catch-up relative to long-standing members, and a staggered Sun & Abraham event study estimates the trajectory of the convergence gap around accession.
1 Introduction
The economic case for European Union enlargement rests substantially on convergence, the expectation that poorer entrants catch up to the incumbent average through trade, capital deepening, institutional anchoring and access to the single market (Barro and Sala-i-Martin 1992). This paper quantifies that catch-up for the 11 CESEE members that acceded in the waves of 2004, 2007 and 2013, using 14 long-standing members as a never-treated comparison group.
2 Data
We draw real GDP per capita (chain-linked volumes, CLV10_EUR_HAB) for the years 1995 to 2023 from Eurostat table nama_10_pc. The outcome for the event study is the convergence gap, the log of a country’s real GDP per capita minus the log of the EU aggregate, so that a rising series denotes catch-up. Country and year fixed effects absorb the common European trajectory.
3 Empirical strategy
We report two complementary objects. First, a cross-sectional beta-convergence regression relates each country’s average annual growth of real GDP per capita since 2004 to its initial log level. A negative slope is convergence. Second, a staggered difference-in-differences event study identifies the effect of EU accession on the convergence gap. Because the three accession waves imply staggered treatment timing, we use the Sun & Abraham (2021) interaction-weighted estimator (Sun and Abraham 2021), which is robust to the heterogeneity-across-cohorts bias of the conventional two-way fixed-effects specification. Identification comes from the research design, the timing of accession relative to never-treated members, not from the estimator.
4 Results
Figure 1 shows the classic convergence pattern. Countries that began the period poorer grew faster. The fitted beta slope is -0.013 (standard error 0.002), and the CESEE members sit clearly in the high-growth, low-initial-income quadrant.
The event study in Figure 2 traces the convergence gap around accession. Pre- accession coefficients are flat, consistent with parallel pre-trends. After accession the gap narrows steadily. By the fifth year the convergence gap had closed by +16.5 log points relative to the year before accession, and by the tenth year by +29.0 log points. Averaged over the post-accession horizon, the accession effect on the convergence gap is +25.8 log points (Table 1).
| Beta-convergence | Accession event study (SA) | |
|---|---|---|
| * p < 0.1, ** p < 0.05, *** p < 0.01 | ||
| The event-study column reports the Sun & Abraham (2021) interaction-weighted specification with country and year fixed effects; standard errors clustered by country. Post-accession ATT is the interaction-weighted average effect on the convergence gap, in log points. | ||
| Initial log GDP p.c. (beta) | -0.013*** | |
| (0.002) | ||
| Post-accession ATT (log points) | 25.785*** | |
| (3.881) | ||
| Num.Obs. | 25 | 725 |
| R2 | 0.611 | |
| R2 Adj. | 0.594 | |
5 Discussion
The estimates reproduce the received wisdom that EU accession is associated with measurable income catch-up. Natural extensions include a wider set of countries, an alternative price basis, and the Callaway and Sant’Anna (2021) estimator as a robustness check on the event-study results.
References
Barro, Robert J., and Xavier Sala-i-Martin. 1992. “Convergence.” Journal of Political Economy 100 (2): 223–51. https://doi.org/10.1086/261816.
Callaway, Brantly, and Pedro H. C. Sant’Anna. 2021. “Difference-in-Differences with Multiple Time Periods.” Journal of Econometrics 225 (2): 200–230. https://doi.org/10.1016/j.jeconom.2020.12.001.
Sun, Liyang, and Sarah Abraham. 2021. “Estimating Dynamic Treatment Effects in Event Studies with Heterogeneous Treatment Effects.” Journal of Econometrics 225 (2): 175–99. https://doi.org/10.1016/j.jeconom.2020.09.006.