Two new species of Varma Distant, 1906, V. falcata Chang & Chen, sp. n. (China: Guizhou) and V. lobata Chang & Chen, sp. n. (China: Guizhou) are described and illustrated. The female genitalia of four speices including two known species are described and illustrated for the first time. The diagnostic characters of this genus are redefined. A checklist to the species of Varma in China is given. ...

We develop and apply a method, called weighted-covariance factor decomposition (WCD), for reducing large estimated vector autoregressive moving-average (VARMA) data models of many "important" and "unimportant" variables to smaller VARMAfactor models of "important" variables and significant factors. WCD has four particularly notable features, compared to frequently used principal components deco...

This article studies a simple, coherent approach for identifying and estimating error correcting vector autoregressive moving average (EC-VARMA) models. Canonical correlation analysis is implemented for both determining the cointegrating rank, using a strongly consistent method, and identifying the short-run VARMA dynamics, using the scalar component methodology. Finite sample performances are ...

This paper proposes an extension to scalar component methodology for the identification and estimation of VARMA models. The complete methodology determines the exact positions of all free parameters in any VARMA model with a predetermined embedded scalar component structure. This leads to an exactly identified system of equations that is estimated using full information maximum likelihood.

In this paper, we argue that there is no compelling reason for restricting the class of multivariate models considered for macroeconomic forecasting to VARs given the recent advances in VARMA modelling methodology and improvements in computing power. To support this claim, we use real macroeconomic data and show that VARMA models forecast macroeconomic variables more accurately than VAR models.