This paper proposes two innovative algorithms to estimate a general class of N-state Markov-switching autoregressive moving-average (MS-ARMA) models with a sample of size T. To resolve the problem of NT possible routes induced by the presence of MA parameters, the first algorithm is built on...

In contrast to the results in Mayer and Riphahn (2000) where no distinction is made between the causes of economic as well as political immigrants, this paper shows that compared to native Taiwanese, the parental refugee experience results in a lower completed fertility of the children’s...

This paper considers the instrumental variables (IV) estimation of the autoregressive distributed lag (ADL) model consisting of fractionally integrated regressors and disturbance term, while allowing for part of the regressors to be endogenous. The idea of Liviatan (1963) and that of Tsay (2007)...

This paper proposes a new class of GMM estimators to increase the effciency of the coeffcient estimate relative to the ordinary least squares (OLS) estimator when all the error term and regressors having nonparametric autocorrelation. This class of GMM estimators are built on the moments...

This paper extends the MD (multiple differenced) methodology of Tsay (2006) to estimate a class of time-series-cross-section (TSCS) models consisting of stationary or nonstationary long memory regressors and errors, while allowing for correlations and heteroskedasticities in both cross-section...

This paper considers the maximum likelihood estimation of a class of stationary and invertible vector autoregressive fractionally integrated moving-average (VARFIMA) processes considered in Luceno (1996). The coverage of this class of VARFIMA processes is quite general and includes the model...

We propose a general class of Markov-switching-ARFIMA processes in order to combine strands of long memory and Markov-switching literature. Although the coverage of this class of models is broad, we show that these models can be easily estimated with the DLV algorithm proposed. This algorithm...