nep-ets New Economics Papers
on Econometric Time Series
Issue of 2005‒05‒29
four papers chosen by
Yong Yin
SUNY at Buffalo

  2. Identifying and Forecasting the Turning Points of the Belgian Business Cycle with Regime-Switching and Logit Models By Vincent, BODART; Konstantin, KHOLODILIN; Fati, SHADMAN-MEHTA
  3. A general multivariate threshold GARCH model with dynamic conditional correlations By Fabio Trojani; Francesco Audrino
  4. Tests for cointegration in panels with regime shifts By Luciano Gutierrez

  1. By: María Concepcion Ausin; Pedro Galeano
    Abstract: In this paper, we perform Bayesian inference and prediction for a GARCH model where the innovations are assumed to follow a mixture of two Gaussian distributions. This GARCH model can capture the patterns usually exhibited by many financial time series such as volatility clustering, large kurtosis and extreme observations. A Griddy-Gibbs sampler implementation is proposed for parameter estimation and volatility prediction. The method is illustrated using the Swiss Market Index.
    Date: 2005–05
  2. By: Vincent, BODART (UNIVERSITE CATHOLIQUE DE LOUVAIN, Department of Economics); Konstantin, KHOLODILIN; Fati, SHADMAN-MEHTA (UNIVERSITE CATHOLIQUE DE LOUVAIN, Department of Economics)
    Abstract: This paper seeks to elaborate econometric models that can be used to forecast the turning points of the Belgian business cycle. We begin by suggesting three reference cycle, which we hope will fill the void of an official reference chronology for Belgium. We then construct two different types of model to estimate the probabilities of recession : Markov-switching models, and Logit models. We apply each approach to a limited set of data, which are a good representation of the economy, are available early and are subject to only minor revisions. We then select the best performing model for each chronology and type of approach. The out-of-sample results show that the models provide useful indicators of business cycle turning points. They are however far from perfect forecasting tools, especially when it comes to forecasting periods of classical recession.
    Keywords: Refrence chronologies; Markov-Switching and Logit models, forecasting business cycle turning points
    JEL: C5 E32 E37
    Date: 2005–03–15
  3. By: Fabio Trojani; Francesco Audrino
    Abstract: We propose a new multivariate DCC-GARCH model that extends existing approaches by admitting multivariate thresholds in conditional volatilities and conditional correlations. Model estimation is numerically feasible in large dimensions and positive semi-definiteness of conditional covariance matrices is naturally ensured by the pure model structure. Conditional thresholds in volatilities and correlations are estimated from the data, together with all other model parameters. We study the performance of our approach in some Monte Carlo simulations, where it is shown that the model is able to fit correctly a GARCH-type dynamics and a complex threshold structure in conditional volatilities and correlations of simulated data. In a real data application to international equity markets, we observe estimated conditional volatilities that are strongly influenced by GARCH-type and multivariate threshold effects. Conditional correlations, instead, are determined by simple threshold structures where no GARCH-type effect could be identified.
    JEL: C12 C13 C51 C53 C61
    Date: 2005–01
  4. By: Luciano Gutierrez (University of Sassari)
    Abstract: In the paper we extend Gregory and Hansen’s (1996)ADF, Za, Zt cointegration tests to panel data, using the method proposed in Maddala and Wu (1999). We test the null hypothesis of no cointegration for all the units in the panel against the alternative hypothesis of cointegration, while allowing for a one-time regime shift of unknown timing for at least some regressions. We derive the panel tests for the ADF, Za, Zt tests , and compare these tests with Pedroni’s (1999) panel cointegration tests. We show that Gregory and Hansen’s (1996) panel tests have higher power to reject null when there is a structural change in the cointegration vector. We apply the statistics to the analysis of the well known Feldstein-Horioka puzzle for a sample of sixteen OCDE countries. After we allow for a structural break in the cointegration regression, we find strong evidence of cointegration between saving and investment rates.
    Keywords: Panel data, Panel cointegration tests, Structural breaks, Feldstein-Horioka puzzle
    JEL: C22 C23 F32 F41
    Date: 2005–05–24

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