In systems of variables with a specified or already identified cointegrating rank, stationarity of component variates can be tested by a simple restriction test. The implied decision is often in conflict with the outcome of unit root tests on the same variables. Using a framework of Bayes...

Bivariate time series data often show strong relationships between the two components, while both individual variables can be approximated by random walks in the short run and are obviously bounded in the long run. Three model classes are considered for a time-series model selection problem:...

Empirical evidence suggests a sharp volatility decline of the growth in U.S. gross domestic product (GDP) in the mid-1980s. Using Bayesian methods, we analyze whether a volatility reduction can also be detected for the German GDP. Since statistical inference for volatility processes critically...

This paper analyzes the evolution of the degree of global cyclical interdependence over the period 1960-2005. We categorize the 106 countries in our sample into three groups: industrial countries, emerging markets, and other developing economies. Using a dynamic factor model, we then decompose...

Distinguishing pure supply effects from other determinants of price and quantity in the market for loans is a notoriously difficult problem. Using German data, we employ Bayesian vector autoregressive models with sign restrictions on the impulse response functions in order to enquire the role of...

This paper analyzes credit supply and demand shocks for the Swiss economy. Using a medium scale BVAR model we are able to take into account various interactions of housing prices, credit supply and demand, interest rates and real activity measures. To identify meaningful economic shocks, we used...

This study analyzes the elasticities of demand and income from electricity for domestic and industrial use, for Colombia (2000-2011), by estimating demand equations by OLS. The impacts on macroeconomic variables, which generate changes in the price of electricity, are also estimated by using a...

The Reversible Jump Markov Chain Monte Carlo (RJMCMC) method can enhance Bayesian DSGE estimation by sampling from a posterior distribution spanning potentially nonnested models with parameter spaces of different dimensionality. We use the method to jointly sample from an ARMA process of unknown...

This paper examines the effects of monetary policy shocks on UK regional economic growth and dispersion in a novel Constrained Mixed Frequency Vector Autoregressive framework. Compared to a standard MFVAR, the model partially accounts for missing quarterly observations for regional growth by...

This paper studies the role of global and regional variations in economic activity and policy in developed world in driving portfolio capital flows (PCF) to emerging markets (EMs) in a Factor Augmented Vector Autoregressive (FAVAR) framework. Results suggest that PCFs to EMs depend mainly on...