nep-ets New Economics Papers
on Econometric Time Series
Issue of 2017‒05‒28
four papers chosen by
Yong Yin
SUNY at Buffalo

  1. Origins of Spurious Long Memory By Leschinski, Christian; Sibbertsen, Philipp
  2. Estimating non-stationary common factors : Implications for risk sharing By Ruiz Ortega, Esther; Poncela, Pilar; Corona, Francisco
  3. An Efficient Bayesian Approach to Multiple Structural Change in Multivariate Time Series By Maheu, John M; Song, Yong
  4. Generalizing Smooth Transition Autoregressions By Emilio Zanetti Chini

  1. By: Leschinski, Christian; Sibbertsen, Philipp
    Abstract: We consider a large class of structural change processes that generate spurious long memory. Among others, this class encompasses structural breaks as well as random level shift processes and smooth trends. The properties of these processes are studied based on a simple representation of their discrete Fourier transform. We find, that under very general conditions all of the models nested in this class generate poles in the periodogram at the zero frequency. These are of order $O(T)$, instead of the usual $O(T^2d)$ for long memory processes and $O(T^2)$ for a random walk. This order arises whenever both the mean changes and sample fractions at which they occur are non-degenerate, asymptotically.
    Keywords: Long Memory; Spurious Long Memory; Structural Change
    JEL: C18 C32
    Date: 2017–05
  2. By: Ruiz Ortega, Esther; Poncela, Pilar; Corona, Francisco
    Abstract: In this paper, we analyze and compare the finite sample properties of alternative factor extraction procedures in the context of non-stationary Dynamic Factor Models (DFMs). On top of considering procedures already available in the literature, we extend the hybrid method based on the combination of principal components and Kalman filter and smoothing algorithms to non-stationary models. We show that, unless the idiosyncratic noise is non-stationary, procedures based on extracting the factors using the nonstationary original series work better than those based on differenced variables. The results are illustrated in an empirical application fitting non-stationary DFM to aggregate GDP and consumption of the set of 21 OECD industrialized countries. The goal is to check international risk sharing is a short or long-run issue.
    Keywords: Risk sharing; Resilience; Principal components; Kalman filter; Non-stationary Dynamic Factor Models; Long-run/Short-run estimation; Consumption smoothing
    Date: 2017–05
  3. By: Maheu, John M; Song, Yong
    Abstract: This paper provides a feasible approach to estimation and forecasting of multiple structural breaks for vector autoregressions and other multivariate models. Due to conjugate prior assumptions we obtain a very efficient sampler for the regime allocation variable. A new hierarchical prior is introduced to allow for learning over different structural breaks. The model is extended to independent breaks in regression coefficients and the volatility parameters.Two empirical applications show the improvements the model has over benchmarks. In a macro application with 7 variables we empirically demonstrate the benefits from moving from a multivariate structural break model to a set of univariate structural break models to account for heterogeneous break patterns across data series.
    Keywords: multivariate hierarchical prior, change point, forecasting
    JEL: C1 C11 C32 C53 E32
    Date: 2017–05
  4. By: Emilio Zanetti Chini (Department of Economics and Management, University of Pavia)
    Abstract: We introduce a new time series model capable to parametrize the joint asymmetry in duration and length of cycles - the dynamic asymmetry - by using a particular generalization of the logistic function. The modelling strategy is discussed in detail, with particular emphasis on two asymmetry tests and relative diagnostics, whose power properties are explored via Monte Carlo experiments. Several case studies illustrate the high versatility of the new model, which is able to characterize the dynamic asymmetry in the cycle in different fields. In a rolling forecasting exercise our model beats its linear and conventional nonlinear competitors in point forecasting, while this superiority becomes less evident in density forecasting, specially when relying on robust measures. Finally, dynamic asymmetry is an important feature to take in account in uncertain environments.
    Keywords: trend inflation, monetary-fiscal policy interactions, Markov-switching, determinacy Dynamic asymmetry, Nonlinear time series, Econometric Modelling, Point forecasts, Density forecasts, Evaluating forecasts, Combining forecasts, Uncertainty.
    JEL: C22 C51 C52
    Date: 2017–05

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