E
Elias Tzavalis
Researcher at Athens University of Economics and Business
Publications - 123
Citations - 2799
Elias Tzavalis is an academic researcher from Athens University of Economics and Business. The author has contributed to research in topics: Unit root & Autoregressive model. The author has an hindex of 20, co-authored 117 publications receiving 2451 citations. Previous affiliations of Elias Tzavalis include Athens State University & University of Exeter.
Papers
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Inference for unit roots in dynamic panels where the time dimension is fixed
Richard Harris,Elias Tzavalis +1 more
TL;DR: In this article, the authors derived similar unit root tests for first-order autoregressive panel data models, assuming that the time dimension of the panel is fixed, and showed that the limiting distributions of the test statistics are normal.
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Explaining the Failures of the Term Spread Models of the Rational Expectations Hypothesis of the Term Structure
TL;DR: In this paper, the authors show that the term spread between long and short rates fails to forecast future movements of long-term rates although its forecasts of future shortterm rates are in the correct direction.
Posted Content
The Influence of VAR Dimensions on Estimator Biases
TL;DR: In this article, the influence of the number and nature of the system's variates on parameter estimates of VARs has been investigated and it has been shown that the variance increases with the dimension of the VAR, hence increasing the variance of the estimator.
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Policy regime changes and the long-run sustainability of fiscal policy: an application to Greece
TL;DR: In this paper, the authors use the Zivot-Andrews sequential integratibility testing procedure to evaluate the long-run fiscal sustainability of the Greek economy and identify the cause of this failure as a deterministic policy regime shift taking place in 1979.
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The influence of VAR dimensions on estimator biases
TL;DR: In this article, the influence of the number and nature of the system's variates on parameter estimates of VARs has been investigated and it has been shown that the variance increases with the dimension of the VAR, hence increasing the variance of the estimator.