Special Issue "Recent Developments in Cointegration"

A special issue of Econometrics (ISSN 2225-1146).

Deadline for manuscript submissions: closed (28 February 2017)

Special Issue Editor

Guest Editor
Prof. Katarina Juselius

Department of Economics, University of Copenhagen, Copenhagen K, Denmark
Website | E-Mail
Interests: empirical econometrics; the cointegrated VAR; empirical methodology; international macro

Special Issue Information

Dear Colleagues,

This Special Issue contains recent contributions to empirical and theoretical cointegration models. Methodologically oriented papers that combine the two are particularly welcome. I envision papers that, for example, apply cointegration in a novel way, suggest a new way of testing hypotheses in a Cointegrated VAR model, derive new tests motivated by empirical applications, use cointegration analysis to solve interesting problems in macroeconomics and finance, such as the puzzling long, persistent swings around long-run equilibrium values. Papers dealing with near integration (near I(1) and near I(2)) are much welcome. Additionally, papers applying the I(2) cointegration and the fractional cointegration model to relevant economic problems are of great interest and so are theoretical advancements to these models. Cointegration models that address the problem of time-varying coefficients, changes in the equilibrium mean and changes in the mean growth rates are all within the scope of this Special Issue.

More generally, the purpose of the Special Issue is to advance cointegration techniques needed to properly address recent problems in macroeconomics and finance, in particular, problems that became painfully visible during the great recession. For example, using cointegration as a means to address self-reinforcing feed-back loops could potentially add valuable information about some of the mechanisms that generated the recent crisis.

Prof. Katarina Juselius
Guest Editor

Manuscript Submission Information

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Keywords

  • Cointegrated VAR models for I(1), I(2), fractionally integrated and explosive root data
  • Inference in near integrated processes
  • Hypothesis testing
  • Structure analysis
  • Time-varying coefficients
  • Modelling changes in equilibrium means and mean growth rates

Published Papers (2 papers)

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Research

Open AccessArticle Maximum Likelihood Estimation of the I(2) Model under Linear Restrictions
Econometrics 2017, 5(2), 19; doi:10.3390/econometrics5020019
Received: 27 February 2017 / Revised: 2 May 2017 / Accepted: 8 May 2017 / Published: 15 May 2017
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Abstract
Estimation of the I(2) cointegrated vector autoregressive (CVAR) model is considered. Without further restrictions, estimation of the I(1) model is by reduced-rank regression (Anderson (1951)). Maximum likelihood estimation of I(2) models, on the other hand, always requires iteration. This paper presents a new
[...] Read more.
Estimation of the I(2) cointegrated vector autoregressive (CVAR) model is considered. Without further restrictions, estimation of the I(1) model is by reduced-rank regression (Anderson (1951)). Maximum likelihood estimation of I(2) models, on the other hand, always requires iteration. This paper presents a new triangular representation of the I(2) model. This is the basis for a new estimation procedure of the unrestricted I(2) model, as well as the I(2) model with linear restrictions imposed. Full article
(This article belongs to the Special Issue Recent Developments in Cointegration)
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Open AccessArticle Panel Cointegration Testing in the Presence of Linear Time Trends
Econometrics 2016, 4(4), 45; doi:10.3390/econometrics4040045
Received: 15 May 2016 / Revised: 28 September 2016 / Accepted: 20 October 2016 / Published: 1 November 2016
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Abstract
We consider a class of panel tests of the null hypothesis of no cointegration and cointegration. All tests under investigation rely on single-equations estimated by least squares, and they may be residual-based or not. We focus on test statistics computed from regressions with
[...] Read more.
We consider a class of panel tests of the null hypothesis of no cointegration and cointegration. All tests under investigation rely on single-equations estimated by least squares, and they may be residual-based or not. We focus on test statistics computed from regressions with intercept only (i.e., without detrending) and with at least one of the regressors (integrated of order 1) being dominated by a linear time trend. In such a setting, often encountered in practice, the limiting distributions and critical values provided for and applied with the situation “with intercept only” are not correct. It is demonstrated that their usage results in size distortions growing with the panel size N. Moreover, we show which are the appropriate distributions, and how correct critical values can be obtained from the literature. Full article
(This article belongs to the Special Issue Recent Developments in Cointegration)

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