European Central Bank

About: European Central Bank is a government organization based out in Frankfurt am Main, Germany. It is known for research contribution in the topics: Monetary policy & Interest rate. The organization has 1172 authors who have published 4703 publications receiving 231896 citations. The organization is also known as: ECB.

Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach

Abstract: Using a Bayesian likelihood approach, we estimate a dynamic stochastic general equilibrium model for the US economy using seven macro-economic time series. The model incorporates many types of real and nominal frictions and seven types of structural shocks. We show that this model is able to compete with Bayesian Vector Autoregression models in out-of-sample prediction. We investigate the relative empirical importance of the various frictions. Finally, using the estimated model we address a number of key issues in business cycle analysis: What are the sources of business cycle fluctuations? Can the model explain the cross-correlation between output and inflation? What are the effects of productivity on hours worked? What are the sources of the "Great Moderation"?

An estimated dynamic stochastic general equilibrium model of the euro area

Abstract: This paper develops and estimates a dynamic stochastic general equilibrium (DSGE) model with sticky prices and wages for the euro area. The model incorporates various other features such as habit formation, costs of adjustment in capital accumulation and variable capacity utilization. It is estimated with Bayesian techniques using seven key macroeconomic variables: GDP, consumption, investment, prices, real wages, employment, and the nominal interest rate. The introduction of ten orthogonal structural shocks (including productivity, labor supply, investment, preference, cost-push, and monetary policy shocks) allows for an empirical investigation of the effects of such shocks and of their contribution to business cycle e uctuations in the euro area. Using the estimated model, we also analyze the output (real interest rate) gap, dee ned as the difference between the actual and model-based potential output (real interest rate). (JEL: E4, E5)

CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles *

Abstract: Value at Risk (VaR) has become the standard measure of market risk employed by financial institutions for both internal and regulatory purposes. VaR is defined as the value that a portfolio will lose with a given probability, over a certain time horizon (usually one or ten days). Despite its conceptual simplicity, its measurement is a very challenging statistical problem and none of the methodologies developed so far give satisfactory solutions. Interpreting the VaR as the quantile of future portfolio values conditional on current information, we propose a new approach to quantile estimation which does not require any of the extreme assumptions invoked by existing methodologies (such as normality or i.i.d. returns). The Conditional Autoregressive Value-at-Risk or CAViaR model moves the focus of attention from the distribution of returns directly to the behavior of the quantile. We specify the evolution of the quantile over time using a special type of autoregressive process and use the regression quantile framework introduced by Koenker and Bassett to determine the unknown parameters. Since the objective function is not differentiable, we use a differential evolutionary genetic algorithm for the numerical optimization. Utilizing the criterion that each period the probability of exceeding the VaR must be independent of all the past information, we introduce a new test of model adequacy, the Dynamic Quantile test. Applications to simulated and real data provide empirical support to this methodology and illustrate the ability of these algorithms to adapt to new risk environments.

Asymmetric Dynamics in the Correlations of Global Equity and Bond Returns

Abstract: This paper proposes a new generalized autoregressive conditionally heteroskedastic (GARCH) process, the asymmetric generalized dynamic conditional correlation (AG-DCC) model The AG-DCC process extends previous specifications along two dimensions: it allows for series-specific news impact and smoothing parameters and permits conditional asymmetries in correlation dynamics The AG-DCC specification is well suited to examine correlation dynamics among different asset classes and investigate the presence of asymmetric responses in conditional variances and correlations to negative returns We employ the AG-DCC model to analyze the behavior of international equities and government bonds While equity returns show strong evidence of asymmetries in conditional volatility, little is found for bond returns However, both equities and bonds exhibit asymmetries in conditional correlations, with equities responding stronger than bonds to joint bad news The article also finds that, during periods of financial turmoil, equity market volatilities show important linkages, and conditional equity correlations among regional groups increase dramatically Furthermore, in January 1999 with the introduction of the euro, we document significant evidence of a structural break in correlation although not in

Systemic Banking Crises: A New Database

Abstract: This paper presents a new database on the timing of systemic banking crises and policy responses to resolve them. The database covers the universe of systemic banking crises for the period 1970-2007, with detailed data on crisis containment and resolution policies for 42 crisis episodes, and also includes data on the timing of currency crises and sovereign debt crises. The database extends and builds on the Caprio, Klingebiel, Laeven, and Noguera (2005) banking crisis database, and is the most complete and detailed database on banking crises to date.