Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/259963 
Erscheinungsjahr: 
2008
Schriftenreihe/Nr.: 
Working Paper No. 2008:18
Verlag: 
Lund University, School of Economics and Management, Department of Economics, Lund
Zusammenfassung: 
Economic theory commonly distinguishes between different time horizons such as the short run and the long run, each with its own relationships and its own dynamics. Engle (1974) proposed a bandspectrum regression to estimate such models. This paper proposes a new estimator for non-stationary panel data models, a bandspectrum cointegration estimator. The bandspectrum cointegration estimator uses first differenced data to avoid spurious results. Such estimates are, however, less efficient than estimates from a model with non-stationary data. Still, simulation results in the paper show that the bandspectrum cointegration estimator is more efficient than common time domain estimators, for example VECM and OLS levels estimators, if the data generating process contains more than one time horizon. The BSCE furthermore identifies all horizons in the data generating process and estimates an individual parameter vector for each, a property that neither time domain estimator possesses.
Schlagwörter: 
Cointegration
Bandspectrum Regression
Simulations
Wavelets
Frequency domain
JEL: 
C14
C15
C23
Dokumentart: 
Working Paper

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