Date: 2010
Type: Thesis
Identification and estimation of sources of common fluctuations : new methodologies and applications
Florence : European University Institute, 2010, EUI, ECO, PhD Thesis
MACIEJOWSKA, Katarzyna, Identification and estimation of sources of common fluctuations : new methodologies and applications, Florence : European University Institute, 2010, EUI, ECO, PhD Thesis - https://hdl.handle.net/1814/14190
Retrieved from Cadmus, EUI Research Repository
This thesis addresses the problem of how to identify and model sources of common fluctuations of economic variables. It is an interesting question not only for researchers but also for policy makers and other authorities. The literature presents two approaches. The first one is based on an assumption that the important structural shocks can be captured by a small set of macroeconomic variables. The most popular models used in this context are structural vector autoregression models (SVAR). The second approach follows from a belief that there exists a small number of factors that affect many economic processes. Therefore, it involves analysis of large data sets, with both time and cross- sectional dimensions large enough to describe the factor structure. We dedicate the first part of the thesis to the problem of identification and estimation of structural shocks in small SVAR models. We follow the ideas of Rigobon (2003) and Lanne and Lütkepohl (2008), which show that the statistical property of the data may provide enough information to identify the structure of the model. The papers argue that a shift in the error covariance matrix allows for the estimation of the structural parameters of interest. The literature concentrates on models in which the shift is a result of a structural brake or a mixed distribution of errors.
Additional information:
Defense date: 28 May 2010; Examining Board:
Professor Helmut Lütkepohl, EUI, Supervisor
Professor Massimiliano Marcellino, EUI
Professor Joerg Breitung, University of Bonn
Professor George Kapetanios, Queen Mary University of London
Cadmus permanent link: https://hdl.handle.net/1814/14190
Full-text via DOI: 10.2870/19341
Series/Number: EUI; ECO; PhD Thesis
Publisher: European University Institute
LC Subject Heading: Business cycles; Instrumental variables (Statistics); Economics -- Statistical models