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The Federal Reserve’s output gap: The unreliability of real-time reliability ...
Data Set and Online Appendix for: Josefine Quast and Maik H. Wolters, "The Federal Reserve’s Output Gap: The Unreliability of Real-Time Reliability Tests", Journal of Applied... -
Fiscal targets: A guide to forecasters? (replication data)
We formulate and estimate empirical models for a selection of EU countries (Germany, France, Italy, Spain, Portugal and Ireland) to show that ex-ante government (consumption)... -
Density Forecasting with BVAR Models under Macroeconomic Data Uncertainty (re...
This dataset has no description
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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... -
An automated prior robustness analysis in Bayesian model comparison (replicat...
It is well-known that the marginal likelihood, the gold standard for Bayesian model comparison, can be sensitive to prior hyperparameter choices. However, most models require... -
Uncertain Kingdom: Nowcasting Gross Domestic Product and its revisions (repli...
We propose a release-augmented dynamic factor model (RA-DFM) that allows to quantify the role of a country's data flow in nowcasting both early Gross Domestic Product (GDP)... -
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... -
Exogenous uncertainty and the identification of structural vector autoregress...
We provide necessary and sufficient conditions for the identification (point-identification) of structural vector autoregressions (SVARs) with external instruments considering... -
A factor‐augmented vector autoregressive (FAVAR) approach for monetary policy...
This dataset has no description
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Does global inflation help forecast inflation in industrialized countries? (r...
Ciccarelli and Mojon (CM; Review of Economics and Statistics, 2010, 92(3), 524-535) propose an inflation forecasting model incorporating a global inflation factor and show that... -
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)... -
Identifying contagion (replication data)
Identifying contagion effects during periods of financial crisis is known to be complicated by the changing volatility of asset returns during periods of stress. To untangle...
