The last twenty years have brought a bulk of inconsistent results on the determinants of business cycle synchronization (BCS). Researchers have usually focused their attention on a limited set of possible determinants, not accounting for model uncertainty. For these reasons, Bayesian Model Averaging has been applied in this paper to the dataset with 43 potential determinants of BCS for the EU. There is strong evidence to claim that migration, exchange rate variability, similarity of production structures, TFP shocks, similarity in exchange rate policy, intra-industry trade, risk sharing, and capital mobility are robust determinants of BCS. Some well-established determinants such as bilateral trade, monetary policy similarity, gravity variables, and participation in a monetary union and free trade area have turned out to be fragile. The structure of trade is more important for BCS than its magnitude, as intra-industry trade and structural similarity are taking explanatory power away from the bilateral trade.
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