We investigate the evolution of the monetary policy transmission mechanism in the Czech Republic over the 1996-2010 period by employing a time-varying parameters Bayesian vector autoregression model with stochastic volatility. We evaluate whether the response of GDP and the price level to...

The short-run increase in prices following an unexpected tightening of monetary policy represents a frequently reported puzzle. Yet the puzzle is surprisingly easy to explain away when all published models are quantitatively reviewed. We collect about 1,000 point estimates of impulse responses...

We collect 2,735 estimates of the elasticity of intertemporal substitution in consumption from 169 published studies that cover 104 countries during different time periods. The estimates vary substantially from country to country, even after controlling for 30 aspects of study design. Our...

We identify a set of "rules of thumb" that characterise economic, financial and structural conditions preceding the onset of banking and currency crises in 36 advanced economies over 1970–2010. We use the Classification and Regression Tree methodology (CART) and its Random Forest (RF)...

Using a panel of 40 EU and OECD countries for the period 1970-2010 we construct an early warning system. The system consists of a discrete and a continuous model. In the discrete model, we collect an extensive database of various types of economic crises called CDEC 40-40 and examine potential...

Monitoring a suitable set of early warning indicators is crucial for the optimal timing of macroprudential measures aimed at reducing the risk of financial crises or at least mitigating their impact on the economy. This article sets out to identify the indicators that should be monitored and to...

The transmission of monetary policy to the economy is generally thought to have long and variable lags. In this paper we quantitatively review the modern literature on monetary transmission to provide stylized facts on the average lag length and the sources of variability. We collect 67...