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Inference in the Presence of Stochastic and Deterministic Trends

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Chevillon, Guillaume () (ESSEC Business School)

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Abstract

The focus of this paper is inference about stochastic and deterministic trends when both types are present. We show that, contrary to asymptotic theory and the existing literature, the parameters of the deterministic components must be taken into account in finite samples. We analyze the ubiquitous Likelihood Ratio test for the rank of cointegration in vector processes. Here, we directly control the parameters of the data generating process so that a local-asymptotic framework accounts for small sample interactions between stochastic and deterministic trends. We show that the usual corrections are invalid as they take no account of the relative magnitudes of these two types of trends. Block-local models provide an embedding framework which provides a rationale for consistent estimation and testing of the whole set of parameters. In an empirical application to European GDP series, we show that using usual corrections leads to underestimating the number of stochastic trends.

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Publisher Info
Paper provided by ESSEC Research Center, ESSEC Business School in its series ESSEC Working Papers with number DR 07021.

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Length: 42 pages
Date of creation: Aug 2007
Date of revision:
Handle: RePEc:ebg:essewp:dr-07021

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Postal: ESSEC Research Center, BP 105, 95021 Cergy, France
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Related research
Keywords: Block Local Models; Cointegration; Finite Samples; Likelihood Ratio; Weak Trends;

Find related papers by JEL classification:
C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions
C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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