nep-ets New Economics Papers
on Econometric Time Series
Issue of 2007‒10‒13
four papers chosen by
Yong Yin
SUNY at Buffalo

  1. Bayesian Analysis of Determinisitic Time Trend and Changes in Persistence Using a Generalised Stochastic Unit Root Model By Fuyu Yang
  2. Theory and Inference for a Markov-Switching GARCH Model By Taoufik Bouezmarni; Jeroen V.K. Rombouts
  3. Change in persistence tests for panels By Cerqueti, Roy; Costantini, Mauro; Gutierrez, Luciano
  4. Bayesian Methods in Nonlinear Time Series By Korenok Oleg

  1. By: Fuyu Yang
    Abstract: This paper makes use of the novel Generalized Stochastic Unit Root (GSTUR) model, Bayesian model estimation and model comparison techniques to investigate the presence of a deterministic time trend in economic series. The model is specified to allow for changes in persistence over time, such as shifts from stationarity I(0) to nonstationarity I(1) or vice versa. This uncertainty raises the crucial question about how sure one can be that an economic time series has a deterministic trend when there is a change in the underlying properties. Empirical analysis indicates that the GSTUR model could provide new insights on time series studies.
    Keywords: Stochastic Unit Root; MCMC; Bayesian
    Date: 2007–11
  2. By: Taoufik Bouezmarni; Jeroen V.K. Rombouts
    Abstract: We develop a Markov-switching GARCH model (MS-GARCH) wherein the conditional mean and variance switch in time from one GARCH process to another. The switching is governed by a hidden Markov chain. We provide sufficient conditions for geometric ergodicity and existence of moments of the process. Because of path dependence, maximum likelihood estimation is not feasible. By enlarging the parameter space to include the state variables, Bayesian estimation using a Gibbs sampling algorithm is feasible. We illustrate the model on SP500 daily returns.
    Keywords: GARCH, Markov-switching, Bayesian inference
    JEL: C11 C22 C52
    Date: 2007
  3. By: Cerqueti, Roy; Costantini, Mauro; Gutierrez, Luciano
    Abstract: In this paper we propose a set of new panel tests to detect changes in persistence. These statistics are used to test the null hypothesis of stationarity against the alternative of a change in persistence from I(0) to I(1) or viceversa. Alternative of unknown direction is also considered. The limiting distributions of the panel tests are derived and small sample properties are investigated by Monte Carlo experiments under the hypothesis that the individual series are cross-sectionally independently distributed. These tests have a good size and power properties. Cross-sectional dependence is also considered. A procedure of de-factorizing proposed by Stock and Watson (2002) is applied. Monte Carlo analysis is conducted and the defactored panel tests show to have good size and power. The empirical results obtained from applying these tests to a panel covering 15 European countries between 1970 and 2006 suggest that inflation rate changes from I(1) to I(0) when cross-correlation is considered.
    Keywords: Persistence, Stationarity, Panel data
    JEL: C12 C23
    Date: 2007–10–01
  4. By: Korenok Oleg (Department of Economics, VCU School of Business)
    Abstract: This paper reviews the analysis of the threshold autoregressive, smooth threshold autoregressive, and Markov switching autoregressive models from the Bayesian perspective. For each model we start by describing a baseline model and discussing possible extensions and applications. Then we review the choice of prior, inference, tests against the linear hypothesis, and conclude with models selection. A short discussion of recent progress in incorporating regime changes into theoretical macroeconomic models concludes our survey.
    Keywords: Threshold, Smooth Threshold, Markov-switching
    JEL: C11 C22 C52
    Date: 2007–03

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