PhD thesis info

July 2nd, 2009 by Stephan Smeekes

PhD Thesis

Title Bootstrapping Nonstationary Time Series
Supervisors Prof.dr. Franz C. Palm, Maastricht University
Prof.dr. Jean-Pierre Urbain, Maastricht University
Defense Committee Prof.dr. Peter C. Schotman, Maastricht University (assessment committee)
Prof.dr. Bertrand Candelon, Maastricht University (assessment committee)
Prof. Anders Rygh Swensen, University of Oslo (assessment committee)
Prof. Stefano Fachin, Universit√† di Roma “La Sapienza”
Prof. A. M. Robert Taylor, University of Nottingham
Dr. Michael Eichler, Maastricht University
Dr. Stefan Straetmans, Maastricht University
Prof.dr. Stan van Hoesel, Maastricht University
Date of Defense July 2, 2009
Abstract The analysis of nonstationary time series is one of the major research topics in time series econometrics. The properties of many economic variables such as real GDP, inflation, exchange rates and stock markets change over time, making these variables nonstationary.

The objective of this thesis is to develop and analyze bootstrap methods for the analysis of nonstationary time series. The bootstrap is a statistical method that often performs better in small samples and is more robust than the asymptotic techniques that are used to analyze time series. However, the bootstrap was origi- nally not designed for the analysis of nonstationary time series. Therefore, applying the bootstrap in this setting is far from trivial and its properties have to be studied carefully.

In this thesis the theoretical validity of the bootstrap for the analysis of unit roots and cointegration is studied. It is also investigated through simulations how the bootstrap performs in finite samples. Apart from the comparison with asymptotic methods, bootstrap methods are also compared with each other.

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