We study the identification of policy shocks in Bayesian proxy VARs for the case that the instrument consists of sparse qualitative observations indicating the signs of certain shocks. We propose two identification schemes, i.e. linear discriminant analysis and a non-parametric sign concordance...

We study state dependence in the impact of monetary policy shocks over the leverage cycle for a panel of 10 euro area countries. We use a Bayesian Threshold Panel SVAR with regime classifications based on credit and house prices cycles. We find that monetary policy shocks trigger a smaller...

We present a quarterly narrative database of important labour market reforms in selected euro area economies in between 1995 and 2018 covering 60 events. We provide legal adoption and implementation dates of major reforms to employment protection legislation and unemployment benefits. Estimates...

Since the global financial crises, many countries have implemented macroprudential policies with the aim to render the financial system more resilient to shocks and limit the procyclicality of the financial system. We present theoretical and empirical evidence on the effectiveness of...

Using new quarterly narrative evidence, this paper examines the macroeconomic impact of reforms of unemployment benefits (UB) and employment protection legislation (EPL) in the euro area from a Bayesian narrative panel VAR. The approach complements existing micro-econometric evidence by aligning...

The paper investigates real-time output gap estimates for the euro artea obtained from various unobserved components (UOC) models. Based on a state space modelling framework, three criteria are used to evaluate real-time estimates, I.e. standard errors, unbiasedness and conditional inflation...

The first official data releases of quarterly real GDP for the euro area are published about eight weeks after the end of the reference quarters. Meanwhile, ongoing economic developments must be assessed from various, more readily available, monthly indicators. We examine in the context of...

We derive forecast weights and uncertainty measures for assessing the role of individual series in a dynamic factor model (DFM) to forecast euro area GDP from monthly indicators. The use of the Kalman filter allows us to deal with publication lags when calculating the above measures. We find...

I estimate network dependence effects in the euro area unsecured overnight interbank market during the financial crisis. I use linear spatial regressions to estimate the dependence of individual banks?trading volumes (and interest rates) on the trading volumes (and interest rates) of their...

Forecasts from dynamic factor models potentially benefit from refining the data set by eliminating uninformative series. The paper proposes to use prediction weights as provided by the factor model itself for this purpose. Monte Carlo simulations and an empirical application to short-term...