We are interested in an XML representation for programming languages. Could content markup of MathML be used for this purpose, especially in the setting of a functional programming language? In order to address this question we have developed an interpreter for a Scheme-like language encoded in XML. We demonstrate that, with some degree of extension to its core elements, syntax and default sema...

We study cross-country differences in monetary policy transmission across the largest euro area economies (France, Germany, Italy, and Spain) using a large Bayesian vector autoregressive (BVAR) model with endogenous prior selection. Drawing on posterior distributions of impulse responses other tests, we find real output money supply to respond more strongly Germany than countries. Whereas, pric...

This paper discusses three modelling techniques, which apply to multiple time series data that correspond to different spatial locations (spatial time series). The first two methods, namely the Space-Time ARIMA (STARIMA) and the Bayesian Vector Autoregressive (BVAR) model with spatial priors apply when interest lies on the spatio-temporal evolution of a single variable. The former is better sui...

Models based on economic theory have serious problems at forecasting exchange rates better than simple univariate driftless random walk models, especially at short horizons. Multivariate time series models suffer from the same problem. In this paper, we propose to forecast exchange rates with a large Bayesian VAR (BVAR), using a panel of 33 exchange rates vis-a-vis the US Dollar. Since exchange...

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The use of renewable energy reduces environmental pollution and leads to achievement of sustainable development. The current study investigates the dynamic interrelationship between sustainable development, renewable and non-renewable energies and environment nexus by applying Bayesian vector autoregression (BVAR) and impulse response functions in Iran with an annual data frequency for the time...

Monitoring economic conditions in real time, or nowcasting, and Big Data analytics share some challenges, sometimes called the three “Vs”. Indeed, nowcasting is characterized by use of a large number time series (Volume), complexity data covering various sectors economy, with different frequencies precision asynchronous release dates (Variety), need to incorporate new information continuously t...