S vector autoregressions have become one of the major ways of extracting information about the macro economy. One might cite three major uses of them in macroeconometric research: for quantifying impulse responses to macroeconomic shocks; for measuring the degree of uncertainty about the impulse responses or other quantities formed from them; and for deciding on the contribution of different sh...

Suppose that a dataset with N time series is available. N1 < N of those are the variables of interest. You want to estimate a vector autoregression (VAR) with the variables of interest. Which of the remaining N−N1 variables, if any, should you include in the VAR with the variables of interest? We develop a Bayesian methodology to answer this question. This question arises in most applications o...

A seasonal additive nonlinear vector autoregression (SANVAR) model is proposed for multivariate seasonal time series to explore the possible interaction among the various univariate series. Significant lagged variables are selected and additive autoregression functions estimated based on the selected variables using spline smoothing method. Conservative confidence bands are constructed for the ...

onvolutive blind source separation (BSS) usually encounters two difficulties – the filter indeterminacy in the recovered sources and the relatively high computational load. In this paper we propose an efficient method to convolutive BSS, by dealing with these two issues. It consists of two stages, namely, multichannel blind deconvolution (MBD) and learning the postfilters with the minimum filte...

Purpose The purpose of the research is to assess risk financial market in digital economy through quantitative analysis model big data era. It a challenge for government carry out management Design/methodology/approach In this study, generalized autoregressive conditional heteroskedasticity-vector autoregression (GARCH-VaR) constructed analyze economy. Additionally, correlation test and station...

VAR models [13] are a type of multi-equation model that linearly describe the simultaneous interactions and behaviour among a group of variables using only their own past. More specifically, a VAR is a model of simultaneous equations formed by a system of equations in which the contemporary values of model variables do not appear in any explanatory variable in the equations. The set of explanat...

This study aims to test hypotheses and interpret each research variable by performing statistical analysis. The variables used in this are Natural Resources (SDA), Urbanization Indonesian Human Capital. technique is use the Vector Autoregression (VAR) model technique. VAR does not differentiate between exogenous endogenous variables. All so that equation has same number of regressions. Based on...

We develop a global vector autoregressive model GVAR to analyze macroeconomic shock transmission among the East African Community countries. The results suggest that there is a signi…cant growth and in‡ation shock transmissions from Kenya to the rest of the member countries while the transmission in the opposite direction is insigni…cant. The macroeconomic shocks are re‡ected more on prices tha...