Special Issue "Celebrated Econometricians: Katarina Juselius and Søren Johansen"

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

Deadline for manuscript submissions: closed (30 September 2018).

Special Issue Editors

Paolo Paruolo
Website
Guest Editor
European Commission, Joint Research Centre, IT
Interests: econometrics (theory and applications), counterfactual methods
Rocco Mosconi
Website
Guest Editor
Politecnico di Milano, IT
Interests: Time series, financial econometrics

Special Issue Information

Dear Colleagues,

Contributions for this Special Issue in honour of Katarina Juselius and Søren Johansen should relate to an area of research to which they have made significant contributions. These include, but are certainly not limited to, econometric theory and applications related to the following questions:

  1. How many common trends are there in a given set of time series?
  2. What is the set of equilibria relations, or, dually what characterizes the attractor set for the common trends?
  3. How is one variable adjusting to the (dis-)equilibrium or going back to the attractor?
  4. Is the VAR compatible with agents being learning or rational?
  5. What would have happened if a different policy intervention had been implemented?

Katarina Juselius and Søren Johansen contributed to these fundamental issues by developing new methodology, and by providing inspiring paradigmatic applications to several empirical economics problems; the latter range from the study of international parity relationships, to the analysis of monetary policy, unemployment, climatology, and optimal hedging, to name a few. The former include, but are not restricted to: representation, inference and testing in I(1) and I(2) and fractional systems, nonlinear time series, structural breaks, (mis)-specification testing, identification of linear system of equations.

This Special Issue aims to collect state of the art applications and theory developments in these areas, as well as in all other areas to which Katarina Juselius and Søren Johansen have contributed.

Informal enquiries regarding the scope and suitability of a potential submission should first be made to the guest editors (emails on the top of this page).

Rocco Mosconi
Paolo Paruolo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Econometrics is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Cointegration
  • Common trends
  • Error-correcting adjustment
  • Estimation and hypothesis testing in cointegrated models
  • Fractional integration
  • Imperfect knowledge and expectation formation
  • Macroeconomic fluctuations and transmission mechanisms
  • Mis-specification testing
  • Representation theory of I(1), I(2) systems
  • Short-run and long-run impact
  • Vector Autoregressive Processes

Published Papers (9 papers)

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Research

Open AccessFeature PaperArticle
Cointegration and Error Correction Mechanisms for Singular Stochastic Vectors
Econometrics 2020, 8(1), 3; https://doi.org/10.3390/econometrics8010003 - 04 Feb 2020
Abstract
Large-dimensional dynamic factor models and dynamic stochastic general equilibrium models, both widely used in empirical macroeconomics, deal with singular stochastic vectors, i.e., vectors of dimension r which are driven by a q-dimensional white noise, with q < r . The present paper [...] Read more.
Large-dimensional dynamic factor models and dynamic stochastic general equilibrium models, both widely used in empirical macroeconomics, deal with singular stochastic vectors, i.e., vectors of dimension r which are driven by a q-dimensional white noise, with q < r . The present paper studies cointegration and error correction representations for an I ( 1 ) singular stochastic vector y t . It is easily seen that y t is necessarily cointegrated with cointegrating rank c r q . Our contributions are: (i) we generalize Johansen’s proof of the Granger representation theorem to I ( 1 ) singular vectors under the assumption that y t has rational spectral density; (ii) using recent results on singular vectors by Anderson and Deistler, we prove that for generic values of the parameters the autoregressive representation of y t has a finite-degree polynomial. The relationship between the cointegration of the factors and the cointegration of the observable variables in a large-dimensional factor model is also discussed. Full article
(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)
Open AccessArticle
Partial Cointegrated Vector Autoregressive Models with Structural Breaks in Deterministic Terms
Econometrics 2019, 7(4), 42; https://doi.org/10.3390/econometrics7040042 - 06 Oct 2019
Abstract
This paper proposes a class of partial cointegrated models allowing for structural breaks in the deterministic terms. Moving-average representations of the models are given. It is then shown that, under the assumption of martingale difference innovations, the limit distributions of partial quasi-likelihood ratio [...] Read more.
This paper proposes a class of partial cointegrated models allowing for structural breaks in the deterministic terms. Moving-average representations of the models are given. It is then shown that, under the assumption of martingale difference innovations, the limit distributions of partial quasi-likelihood ratio tests for cointegrating rank have a close connection to those for standard full models. This connection facilitates a response surface analysis that is required to extract critical information about moments from large-scale simulation studies. An empirical illustration of the proposed methodology is also provided. Full article
(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)
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Open AccessArticle
A Parametric Factor Model of the Term Structure of Mortality
Econometrics 2019, 7(1), 9; https://doi.org/10.3390/econometrics7010009 - 11 Mar 2019
Cited by 2
Abstract
The prototypical Lee–Carter mortality model is characterized by a single common time factor that loads differently across age groups. In this paper, we propose a parametric factor model for the term structure of mortality where multiple factors are designed to influence the age [...] Read more.
The prototypical Lee–Carter mortality model is characterized by a single common time factor that loads differently across age groups. In this paper, we propose a parametric factor model for the term structure of mortality where multiple factors are designed to influence the age groups differently via parametric loading functions. We identify four different factors: a factor common for all age groups, factors for infant and adult mortality, and a factor for the “accident hump” that primarily affects mortality of relatively young adults and late teenagers. Since the factors are identified via restrictions on the loading functions, the factors are not designed to be orthogonal but can be dependent and can possibly cointegrate when the factors have unit roots. We suggest two estimation procedures similar to the estimation of the dynamic Nelson–Siegel term structure model. First, a two-step nonlinear least squares procedure based on cross-section regressions together with a separate model to estimate the dynamics of the factors. Second, we suggest a fully specified model estimated by maximum likelihood via the Kalman filter recursions after the model is put on state space form. We demonstrate the methodology for US and French mortality data. We find that the model provides a good fit of the relevant factors and, in a forecast comparison with a range of benchmark models, it is found that, especially for longer horizons, variants of the parametric factor model have excellent forecast performance. Full article
(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)
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Open AccessArticle
Asymptotic Theory for Cointegration Analysis When the Cointegration Rank Is Deficient
Econometrics 2019, 7(1), 6; https://doi.org/10.3390/econometrics7010006 - 18 Jan 2019
Cited by 1
Abstract
We consider cointegration tests in the situation where the cointegration rank is deficient. This situation is of interest in finite sample analysis and in relation to recent work on identification robust cointegration inference. We derive asymptotic theory for tests for cointegration rank and [...] Read more.
We consider cointegration tests in the situation where the cointegration rank is deficient. This situation is of interest in finite sample analysis and in relation to recent work on identification robust cointegration inference. We derive asymptotic theory for tests for cointegration rank and for hypotheses on the cointegrating vectors. The limiting distributions are tabulated. An application to US treasury yields series is given. Full article
(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)
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Open AccessArticle
Cointegration and Adjustment in the CVAR(∞) Representation of Some Partially Observed CVAR(1) Models
Econometrics 2019, 7(1), 2; https://doi.org/10.3390/econometrics7010002 - 10 Jan 2019
Abstract
A multivariate CVAR(1) model for some observed variables and some unobserved variables is analysed using its infinite order CVAR representation of the observations. Cointegration and adjustment coefficients in the infinite order CVAR are found as functions of the parameters in the CVAR(1) model. [...] Read more.
A multivariate CVAR(1) model for some observed variables and some unobserved variables is analysed using its infinite order CVAR representation of the observations. Cointegration and adjustment coefficients in the infinite order CVAR are found as functions of the parameters in the CVAR(1) model. Conditions for weak exogeneity for the cointegrating vectors in the approximating finite order CVAR are derived. The results are illustrated by two simple examples of relevance for modelling causal graphs. Full article
(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)
Open AccessArticle
The Stochastic Stationary Root Model
Econometrics 2018, 6(3), 39; https://doi.org/10.3390/econometrics6030039 - 21 Aug 2018
Abstract
We propose and study the stochastic stationary root model. The model resembles the cointegrated VAR model but is novel in that: (i) the stationary relations follow a random coefficient autoregressive process, i.e., exhibhits heavy-tailed dynamics, and (ii) the system is observed with measurement [...] Read more.
We propose and study the stochastic stationary root model. The model resembles the cointegrated VAR model but is novel in that: (i) the stationary relations follow a random coefficient autoregressive process, i.e., exhibhits heavy-tailed dynamics, and (ii) the system is observed with measurement error. Unlike the cointegrated VAR model, estimation and inference for the SSR model is complicated by a lack of closed-form expressions for the likelihood function and its derivatives. To overcome this, we introduce particle filter-based approximations of the log-likelihood function, sample score, and observed Information matrix. These enable us to approximate the ML estimator via stochastic approximation and to conduct inference via the approximated observed Information matrix. We conjecture the asymptotic properties of the ML estimator and conduct a simulation study to investigate the validity of the conjecture. Model diagnostics to assess model fit are considered. Finally, we present an empirical application to the 10-year government bond rates in Germany and Greece during the period from January 1999 to February 2018. Full article
(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)
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Open AccessArticle
The Relation between Monetary Policy and the Stock Market in Europe
Econometrics 2018, 6(3), 36; https://doi.org/10.3390/econometrics6030036 - 05 Aug 2018
Cited by 2
Abstract
We use a cointegrated structural vector autoregressive model to investigate the relation between monetary policy in the euro area and the stock market. Since there may be an instantaneous causal relation, we consider long-run identifying restrictions for the structural shocks and also used [...] Read more.
We use a cointegrated structural vector autoregressive model to investigate the relation between monetary policy in the euro area and the stock market. Since there may be an instantaneous causal relation, we consider long-run identifying restrictions for the structural shocks and also used (conditional) heteroscedasticity in the residuals for identification purposes. Heteroscedasticity is modelled by a Markov-switching mechanism. We find a plausible identification scheme for stock market and monetary policy shocks which is consistent with the second-order moment structure of the variables. The model indicates that contractionary monetary policy shocks lead to a long-lasting downturn of real stock prices. Full article
(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)
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Open AccessArticle
Johansen’s Reduced Rank Estimator Is GMM
Econometrics 2018, 6(2), 26; https://doi.org/10.3390/econometrics6020026 - 18 May 2018
Cited by 4
Abstract
The generalized method of moments (GMM) estimator of the reduced-rank regression model is derived under the assumption of conditional homoscedasticity. It is shown that this GMM estimator is algebraically identical to the maximum likelihood estimator under normality developed by Johansen (1988). This includes [...] Read more.
The generalized method of moments (GMM) estimator of the reduced-rank regression model is derived under the assumption of conditional homoscedasticity. It is shown that this GMM estimator is algebraically identical to the maximum likelihood estimator under normality developed by Johansen (1988). This includes the vector error correction model (VECM) of Engle and Granger. It is also shown that GMM tests for reduced rank (cointegration) are algebraically similar to the Gaussian likelihood ratio tests. This shows that normality is not necessary to motivate these estimators and tests. Full article
(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)
Open AccessFeature PaperArticle
Evaluating Forecasts, Narratives and Policy Using a Test of Invariance
Econometrics 2017, 5(3), 39; https://doi.org/10.3390/econometrics5030039 - 01 Sep 2017
Cited by 3
Abstract
Economic policy agencies produce forecasts with accompanying narratives, and base policy changes on the resulting anticipated developments in the target variables. Systematic forecast failure, defined as large, persistent deviations of the outturns from the numerical forecasts, can make the associated narrative false, which [...] Read more.
Economic policy agencies produce forecasts with accompanying narratives, and base policy changes on the resulting anticipated developments in the target variables. Systematic forecast failure, defined as large, persistent deviations of the outturns from the numerical forecasts, can make the associated narrative false, which would in turn question the validity of the entailed policy implementation. We establish when systematic forecast failure entails failure of the accompanying narrative, which we call forediction failure, and when that in turn implies policy invalidity. Most policy regime changes involve location shifts, which can induce forediction failure unless the policy variable is super exogenous in the policy model. We propose a step-indicator saturation test to check in advance for invariance to policy changes. Systematic forecast failure, or a lack of invariance, previously justified by narratives reveals such stories to be economic fiction. Full article
(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)
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