nep-ets New Economics Papers
on Econometric Time Series
Issue of 2007‒07‒13
five papers chosen by
Yong Yin
SUNY at Buffalo

  1. Second Generation Panel Unit Root Tests By Christophe Hurlin; Valérie Mignon
  2. A Unifying Framework for Analysing Common Cyclical Features in Cointegrated Time Series By Gianluca Cubadda
  3. Band Spectral Estimation for Signal Extraction By Tommaso Proietti
  4. Polynomial Cointegration between Stationary Processes with Long Memory By Marco Avarucci; Domenico Marinucci

  1. By: Christophe Hurlin (LEO - Laboratoire d'économie d'Orleans - [CNRS : UMR6221] - [Université d'Orléans]); Valérie Mignon (CEPII - Centre d'études prospectives et d'informations internationales - [Université de Paris X - Nanterre], EconomiX - [CNRS : UMR7166] - [Université de Paris X - Nanterre])
    Abstract: This article proposes an overview of the recent developments relating to panel unit root tests. After a brief review of the first generation panel unit root tests, this paper focuses on the tests belonging to the second generation. The latter category of tests is characterized by the rejection of the cross-sectional independence hypothesis. Within this second generation of tests, two main approaches are distinguished. The first one relies on the factor structure approach and includes the contributions of Bai and Ng (2001), Phillips and Sul (2003a), Moon and Perron (2004a), Choi (2002) and Pesaran (2003) among others. The second approach consists in imposing few or none restrictions on the residuals covariance matrix and has been adopted notably by Chang (2002, 2004), who proposed the use of nonlinear instrumental variables methods or the use of bootstrap approaches to solve the nuisanceparameter problem due to cross-sectional dependency.
    Keywords: Nonstationary panel data; unit root, heterogeneity; cross-sectional dependencies
    Date: 2007–07–04
  2. By: Gianluca Cubadda (SEFEMEQ, Universita’ di Roma "Tor Vergata")
    Abstract: This paper provides a unifying framework in which the coexistence of different form of common cyclical features can be tested and imposed to a cointegrated VAR model. This goal is reached by introducing a new notion of common cyclical features, namely the weak form of polynomial serial correlation common features, which encompasses most of the previous ones. Statistical inference is obtained by means of reduced-rank regression, and alternative forms of common cyclical features are detected by means of tests for over-identifying restrictions on the parameters of the new model. Some iterative estimation procedures are then proposed for simultaneously modelling different forms of common features. Concepts and methods are illustrated by an empirical investigation of the US business cycle indicators.
    Keywords: Common Cyclical Features, Reduced Rank Regression.
    JEL: C32
    Date: 2007–05–21
  3. By: Tommaso Proietti (SEFEMEQ, Universita’ di Roma "Tor Vergata")
    Abstract: The paper evaluates the potential of band spectral estimation for extracting signals in economic time series. Two situations are considered. The first deals with trend extraction when the original data have been permanently altered by routine operations, such as prefiltering, temporal aggregation and disaggregation, and seasonal adjustment, which modify the high frequencies properties of economic time series. The second is when the measurement model is only partially specified, in that it aims at fitting the series in a particular frequency range, e.g. at interpreting the long run behaviour. These issues are illustrated with reference to a simple structural model, namely the random walk plus noise model.
    Keywords: Temporal Aggregation, Seasonal Adjustment, Trend Component, Frequency Domain.
    JEL: C22 E3
    Date: 2007–05–21
  4. By: Marco Avarucci (SEFeMEQ, University of Rome “Tor Vergata”); Domenico Marinucci (Department of Mathematics, University of Rome “Tor Vergata”)
    Abstract: In this paper we consider polynomial cointegrating relationships between stationary processes with long range dependence. We express the regression functions in terms of Hermite polynomials and we consider a form of spectral regression around frequency zero. For these estimates, we establish consistency by means of a more general result on continuously averaged estimates of the spectral density matrix at frequency zero.
    Keywords: Nonlinear cointegration, Long memory, Hermite polynomials, Spectral regression, Diagram formula.
    Date: 2007–03–05
  5. By: Jan P.A.M. Jacobs; Kenneth F. Wallis
    Abstract: Cointegration ideas as introduced by Granger (1981) are commonly embodied in empirical macroeconomic modelling through the vector error correction model (VECM). It has also become common practice in these models to treat some variables as weakly exogenous, resulting in conditional VECMs. This paper studies the consequences of different approaches to weak exogeneity for the dynamic properties of such models, in the context of two models of the UK economy, one a national-economy model, the other the UK submodel of a global model. Impulse response and common trend analyses are shown to be sensitive to these assumptions and other specification choices.
    JEL: C32 C51 C52
    Date: 2007–06

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