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Bandspectrum Cointegration

Andersson, Fredrik N G LU (2008)
Abstract
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... (More)
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. (Less)
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24dbfbe8-c185-466f-860b-45c9bd151af4 (old id 1852910)
date added to LUP
2011-03-18 10:29:56
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@misc{24dbfbe8-c185-466f-860b-45c9bd151af4,
  abstract     = {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.},
  author       = {Andersson, Fredrik N G},
  language     = {eng},
  title        = {Bandspectrum Cointegration},
  year         = {2008},
}