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Recurrent conditional heteroskedasticity (replication data)
We propose a new class of financial volatility models, called the REcurrent Conditional Heteroskedastic (RECH) models, to improve both in-sample analysis and out-of-sample... -
A regularization approach to common correlated effects estimation (replicatio...
Cross-section average-augmented panel regressions introduced by Pesaran (2006) have been a popular empirical tool to estimate panel data models with common factors. However, the... -
Interpretation of point forecasts with unknown directive (replication data)
Point forecasts can be interpreted as functionals (i.e., point summaries) of predictive distributions. We extend methodology for the identification of the functional based on... -
Is euro area lowflation here to stay? Insights from a time‐varying parameter ...
We build a time-varying parameter model that jointly explains the dynamics of euro area inflation and inflation expectations. Our goal is to explain the weak inflation during... -
Unobserved components with stochastic volatility: Simulation‐based estimation...
The unobserved components time series model with stochastic volatility has gained much interest in econometrics, especially for the purpose of modelling and forecasting... -
Multivariate fractional integration tests allowing for conditional heterosked...
We introduce a new joint test for the order of fractional integration of a multivariate fractionally integrated vector autoregressive (FIVAR) time series based on applying the... -
Testing for overconfidence statistically: A moment inequality approach (repli...
We propose a moment inequality approach to test for the presence of overconfidence using data from ranking experiments where subjects rank themselves relative to other... -
A factor‐augmented vector autoregressive (FAVAR) approach for monetary policy...
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Understanding the economic determinants of the severity of operational losses...
We investigate a novel database of 10,217 extreme operational losses from the Italian bank UniCredit. Our goal is to shed light on the dependence between the severity... -
How the baby boomers' retirement wave distorts model‐based output gap estimat...
This paper illustrates, based on an example, the importance of consistency between empirical measurement and the concept of variables in estimated macroeconomic models. Since... -
Dynamic factor model with infinite‐dimensional factor space: Forecasting (rep...
The paper compares the pseudo real-time forecasting performance of three dynamic factor models: (i) the standard principal component model introduced by Stock and Watson in... -
Bayesian model comparison for time‐varying parameter VARs with stochastic vol...
We develop importance sampling methods for computing two popular Bayesian model comparison criteria, namely, the marginal likelihood and the deviance information criterion (DIC)... -
Loan Supply Shocks and the Business Cycle (replication data)
This paper provides empirical evidence on the role played by loan supply shocks over the business cycle in the euro area, the UK and the USA from 1980 to 2011 by estimating... -
Tests of Predictive Ability for Vector Autoregressions Used for Conditional F...
Many forecasts are conditional in nature. For example, a number of central banks routinely report forecasts conditional on particular paths of policy instruments. Even though... -
Forecasting Tail Risks (replication data)
This paper presents an early warning system as a set of multi-period forecasts of indicators of tail real and financial risks obtained using a large database of monthly US data... -
Combining Time Variation and Mixed Frequencies: an Analysis of Government Spe...
In this paper, we propose a time-varying parameter vector autoregression (VAR) model with stochastic volatility which allows for estimation on data sampled at different... -
The Contribution of Structural Break Models to Forecasting Macroeconomic Seri...
This paper compares the forecasting performance of models that have been proposed for forecasting in the presence of structural breaks. They differ in their treatment of the... -
POSTERIOR‐PREDICTIVE EVIDENCE ON US INFLATION USING EXTENDED NEW KEYNESIAN PH...
Changing time series properties of US inflation and economic activity, measured as marginal costs, are modeled within a set of extended New Keynesian Phillips curve (NKPC)... -
TIME VARIATION IN THE DYNAMICS OF WORKER FLOWS: EVIDENCE FROM NORTH AMERICA A...
Vector autoregressive methods have been used to model the interrelationships between job vacancy rates, job separation rates and job-finding rates using tools such as impulse...
