The goal of this research is to investigate the relationship between economic growth and foreign direct investment inflows in the European Union (EU-28) in the period of the recent economic crisis. Panel data approach and Bayesian techniques are employed to solve the problem of a short set of data (2008–2014). The panel data approaches (panel vector-autoregressive model and Bayesian random effe...

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...

We examine the problem of accurate detection and classification of artifacts in continuous EEG recordings. Manual identification of artifacts, by means of an expert or panel of experts, can be tedious, time-consuming and infeasible for large datasets. We use autoregressive (AR) models for feature extraction and characterization of EEG signals containing several kinds of subject-generated artifa...

The purpose of this paper is to propose a new likelihood-based panel cointegration test in the presence of a linear time trend in the data generating process. This new test is an extension of the likelihood ratio (LR) test of Saikkonen & Lütkepohl (2000) for trend-adjusted data to the panel data framework, and is called the panel SL test. The idea is first to take the average of the individual ...

This note investigates long-run exclusion in a cointegrated vector autoregressive (VAR) model from the viewpoint of …nite-sample statistical inference. Monte Carlo experiments show that, in various circumstances, a mis-speci…ed partial VAR model, which is justi…ed by the existence of a long-run excluded variable, can lead to better …nite-sample inference for cointegrating rank than a fully-spec...

Conjugate priors allow for fast inference in large dimensional vector autoregressive (VAR) models. But at the same time, they introduce restriction that each equation features set of explanatory variables. This paper proposes a straightforward means postprocessing posterior estimates conjugate Bayesian VAR to effectively perform equation-specific covariate selection. Compared with existing tech...