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As of today, estimating interest rate reaction functions for the Euro Area is hampered by the short time span since the conduct of a single monetary policy. In this paper we circumvent the common use of aggregated data before 1999 by estimating interest rate reaction functions based on a panel including actual EMU Member States. We find that exploiting the cross-section dimen- sion of a multi-country panel and accounting for cross-country heterogeneity in advance of the single monetary policy pays off with regard to the estimated reaction functions' ability to describe actual interest rate dynamics. We retrieve a panel reaction function which is demonstrated to be a valuable tool for evaluating episodes of monetary policy since 1999. JEL - Klassifikation: E43 , E58 , C33
This thesis is concerned with the derivation of new methods for the analysis of nonstationary, cross correlated panels. The suggested procedures are carefully quantified by means of Monte Carlo experiments. Typical applications of the developed methods consist in multi-country studies, with several countries observed over a couple of decades. The empirical applications implemented here are the testing for trends in the investment share in European GDPs and the examination of OECD interest rates. In the first chapter, a panel test for the presence of a linear time trend is proposed. The test is applicable in cross-correlated, heterogeneous panels and it can also be used when the integration order of innovations is unknown, by means of subsampling. In the next chapter a cointegration test having asymptotic standard normal distributiun and not requiring exogeneity assumptions is derived. In panels exhibiting cross-correlation or cointegration, individual test statistics are asymptotically independent, which leads to a panel test statistic robust to dependence across units. The third chapter examines in an econometric context the simple idea of combining p-values from a series of statistical tests and improves its applicability in the presence of cross-correlation. The last chapter applies recent panel techniques to OECD long-term interest rates and differentials thereof, finding only rather week evidence in favor of stationarity when allowing for cross-correlation.