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Dissertation zugänglich unter
URN: urn:nbn:de:gbv:18-35576
URL: http://ediss.sub.uni-hamburg.de/volltexte/2008/3557/

On the endogeneity of macroeconomic volatility

Über die Endogenität makroökonomischer Volatilität

Posch, Olaf

 Dokument 1.pdf (2.020 KB) 

Basisklassifikation: 83.12
Institut: Wirtschaftswissenschaften
DDC-Sachgruppe: Wirtschaft
Dokumentart: Dissertation
Hauptberichter: Lucke, Bernd (Prof. Dr.)
Sprache: Englisch
Tag der mündlichen Prüfung: 24.01.2008
Erstellungsjahr: 2007
Publikationsdatum: 04.02.2008
Kurzfassung auf Englisch: This book contributes to the literature on the determinants of macro volatility. It starts with a theoretical examination using a stochastic model of endogenous growth and fluctuations. In this setup, an analytical measure of macro volatility based on cyclical components is derived. The measure is shown to depend on three channels: the range of the cyclical component, the expected length of a cycle, and on the importance of the innovations. Taxes affect these channels and therefore potentially explain patterns in the observed heterogeneity of macro volatility. This study proceeds with comparing the theoretical results to empirical measures of macro volatility, where among others qualitative and quantitative effects of taxes are being computed. Using panel estimation techniques, tax ratios à la Mendoza et al. (1994) are identified as robust explanatory variables for different measures of macro volatility. Together with other controls, tax rates account for substantial parts of its variation. For example, tax changes can explain three quarter of the observed volatility decline in the UK. In accordance with theory, taxes on labor and corporate income are found to be negatively related to empirical measures of macro volatility whereas the capital tax ratio has positive effects. Finally, this analysis takes the stochastic macro model directly to the data in order to estimate parameters of interest. Using extensive Monte Carlo experiments, it is shown that parameters of the underlying data generating process can be recovered. Using growth rates of industrial production, strong empirical evidence for jumps is provided.


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