This paper takes a panel cointegration approach to the estimation of short-and longrun exchange rate pass-through (ERPT) to import prices in the European countries. Although economic theory suggests a long-run relationship between import prices and exchange rate, in recent empirical studies its existence has either been overlooked or it has proven difficult to establish. Resorting to novel tests for panel cointegration, we find support for the equilibrium relationship hypothesis. Exchange rate pass-through elasticities, estimated by two different techniques for cointegrated panel regressions, give insight into the most recent development of the ERPT. Keywords Exchange rate pass-through • Import prices • Panel cointegration • Cross-sectional dependence • Common factors JEL Classification C12 • C23 • F31 The author is grateful to Boris Blagov and to the participants at the 25th International Panel Data Conference in Vilnius, Lithuania, for helpful discussions and to two anonymous referees and the Associate Editor for their constructive comments and suggestions.

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This paper proposes a new likelihood-based panel cointegration rank test which extends the test ofÖrsal and Droge (2012) (henceforth Panel SL test) to allow for crosssectional dependence. The dependence is modelled by unobserved common factors which affect the variables in each cross-section through heterogeneous loadings. The common components are estimated following the panel analysis of nonstationarity in idiosyncratic and common components (PANIC) approach of Bai and Ng (2004) and the estimates are subtracted from the observations. The cointegrating rank of the defactored data is then tested by the Panel SL test. A Monte Carlo study demonstrates that the proposed testing procedure has reasonable size and power properties in finite samples.JEL classification: C12, C15, C33 Keywords: panel cointegration rank test, cross-sectional dependence, common factors, likelihoodratio, time trend * Financial support by the German Research Foundation (DFG) through the project "Likelihood-based panel cointegration methodology and its applications in macroeconomics and financial market analysis" is gratefully acknowledged. †