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Anchoring the yield curve using survey expectations (replication data)
The dynamic behavior of the term structure of interest rates is difficult to replicate with models, and even models with a proven track record of empirical performance have... -
Have Standard VARS Remained Stable Since the Crisis? (replication data)
Small vector autoregressions are commonly used in macroeconomics for forecasting and evaluating shock transmission. This requires VAR parameters to be stable over the evaluation... -
Density Forecasts With Midas Models (replication data)
We propose a parametric block wild bootstrap approach to compute density forecasts for various types of mixed-data sampling (MIDAS) regressions. First, Monte Carlo simulations... -
Spotting the Danger Zone: Forecasting Financial Crises With Classification Tr...
This paper introduces classification tree ensembles (CTEs) to the banking crisis forecasting literature. I show that CTEs substantially improve out-of-sample forecasting... -
Modeling and Forecasting Large Realized Covariance Matrices and Portfolio Cho...
We consider modeling and forecasting large realized covariance matrices by penalized vector autoregressive models. We consider Lasso-type estimators to reduce the dimensionality... -
Forecasting with Bayesian Vector Autoregressions Estimated Using Professional...
We propose a Bayesian shrinkage approach for vector autoregressions (VARs) that uses short-term survey forecasts as an additional source of information about model parameters.... -
Forecast Rationality Tests in the Presence of Instabilities, with Application...
This paper proposes a framework to implement regression-based tests of predictive ability in unstable environments, including, in particular, forecast unbiasedness and... -
The Measurement and Behavior of Uncertainty: Evidence from the ECB Survey of ...
We examine matched point and density forecasts of output growth, inflation and unemployment from the ECB Survey of Professional Forecasters. We construct measures of uncertainty... -
Bayesian VARs: Specification Choices and Forecast Accuracy (replication data)
In this paper we discuss how the point and density forecasting performance of Bayesian vector autoregressions (BVARs) is affected by a number of specification choices. We adopt... -
CONSTRUCTING OPTIMAL DENSITY FORECASTS FROM POINT FORECAST COMBINATIONS (repl...
Decision makers often observe point forecasts of the same variable computed, for instance, by commercial banks, IMF and the World Bank, but the econometric models used by such... -
Assessing the prudence of economic forecasts in the EU (replication data)
We estimate the EU Commission loss preferences for major economic forecasts of 12 Member States. Based on a recently proposed method by Elliott, Komunjer and Timmermann (2005)... -
Modelling multi-period inflation uncertainty using a panel of density forecas...
This paper examines the determinants of inflation forecast uncertainty using a panel of density forecasts from the Survey of Professional Forecasters (SPF). Based on a dynamic... -
Valuation ratios and long-horizon stock price predictability (replication data)
Using annual data for 1872-1997, this paper re-examines the predictability of real stock prices based on price-dividend and price-earnings ratios. In line with the extant... -
Exchange rates and monetary fundamentals: what do we learn from long-horizon ...
The use of a new bootstrap method for small-sample inference in long-horizon regressions is illustrated by analysing the long-horizon predictability of four major exchange... -
NUMERICAL METHODS FOR ESTIMATION AND INFERENCE IN BAYESIAN VAR-MODELS (replic...
In Bayesian analysis of vector autoregressive models, and especially in forecasting applications, the Minnesota prior of Litterman is frequently used. In many cases other prior...
