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Journal ArticleDOI

Estimating private savings behaviour in Greece

George Hondroyiannis
- 01 Oct 2004 - 
- Vol. 31, Iss: 5, pp 457-476
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TLDR
In this article, the authors investigated the long and short run determinants of aggregate private savings in Greece employing data over the period 1961-2000 and found a long run saving function sensitive to fertility changes, old dependency ratio, real interest rate, liquidity and public finances.
Abstract
This paper investigates the long‐ and short‐run determinants of aggregate private savings in Greece employing data over the period 1961‐2000. The long‐run savings function is estimated based on an extended life‐cycle hypothesis taking into account the economic and demographic developments during this period. A long‐run saving function sensitive to fertility changes, old dependency ratio, real interest rate, liquidity and public finances is found to exist and the importance of short‐run deviations is presented using vector error‐correction model estimation. The empirical evidence suggests the existence of a stable long‐run savings function in Greece both in the long‐ and short‐run periods and the policy implications of such a relationship are presented.

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Citations
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References
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Journal ArticleDOI

Co-integration and Error Correction: Representation, Estimation and Testing

TL;DR: The relationship between co-integration and error correction models, first suggested in Granger (1981), is here extended and used to develop estimation procedures, tests, and empirical examples.
Journal ArticleDOI

Distribution of the Estimators for Autoregressive Time Series with a Unit Root

TL;DR: In this article, the limit distributions of the estimator of p and of the regression t test are derived under the assumption that p = ± 1, where p is a fixed constant and t is a sequence of independent normal random variables.
Journal ArticleDOI

Testing for a Unit Root in Time Series Regression

TL;DR: In this article, the authors proposed new tests for detecting the presence of a unit root in quite general time series models, which accommodate models with a fitted drift and a time trend so that they may be used to discriminate between unit root nonstationarity and stationarity about a deterministic trend.
Journal ArticleDOI

Statistical analysis of cointegration vectors

TL;DR: In this paper, the authors consider a nonstationary vector autoregressive process which is integrated of order 1, and generated by i.i.d. Gaussian errors, and derive the maximum likelihood estimator of the space of cointegration vectors and the likelihood ratio test of the hypothesis that it has a given number of dimensions.
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