We develop a global vector autoregressive model to study the transmission of information between currency spot markets. Our model accounts for both simultaneous and dynamic interactions between exchange rates and order flows using historical data from the Reuters Dealing 2000 – 1 platform for...

The recent plunge in the price of oil affected many countries, especially major oil producers and exporters, such as the Gulf Corporation Council (GCC), which accounts for half of the global oil reserves. This paper examines the impact of oil price changes on GCC stock markets, including...

The current study examines the relationships between several home country-specific macroeconomic factors and the level of the outward FDI of China and India using multiple time-series data from 1982 to 2006 and from 1980 to 2006, respectively. With the use of a vector autoregressive model...

The current study examines the relationships between several home country-specific macroeconomic factors and the level of the outward FDI of China and India using multiple time-series data from 1982 to 2006 and from 1980 to 2006, respectively. With the use of a vector autoregressive model...

This paper presents a generalized two-step maximum likelihood estimation method for partially identified vector autoregressive models. We suggest a likelihood ratio test for over-identification in a sub-system and derive the asymptotics for impulse responses and forecast-error variance...

Starting from the theoretical observation that the identification problem of SVAR models is fundamentally a problem of variable aggregation, we propose a new identification method based on nowcasted macroeconomic data, i.e. on macroeconomic series reconstructed at high-frequency. The idea is...

We develop a similarity-based structural vector autoregressive (SVAR) model using the similar clusters of data relevant for the prevailing initial macroeconomic conditions of interest. Our computationally attractive simple approach enables us to uncover time-varying effects of structural...

Detrending within structural vector autoregressions (SVAR) is directly linked to the shock identification. We investigate the consequences of trend misspecification in an SVAR using both standard real business cycle models and bi-variate SVARs as data generating processes. Our bias decomposition...

We propose a Bayesian infinite hidden Markov model to estimate time-varying parameters in a vector autoregressive model. The Markov structure allows for heterogeneity over time while accounting for state-persistence. By modelling the transition distribution as a Dirichlet process mixture model,...

It is now an accepted fact that the majority of financial markets worldwide are neither normal nor constant, and South Africa is no exception. One idea that can be used to understand such markets and has been gaining popularity recently is that of regimes and regime-switching models. In this...