-
Combining density forecasts using focused scoring rules (replication data)
We investigate the added value of combining density forecasts focused on a specific region of support. We develop forecast combination schemes that assign weights to individual... -
Loss functions for predicted click-through rates in auctions for online adver...
We characterize the optimal loss functions for predicted click-through rates in auctions for online advertising. Whereas standard loss functions such as mean squared error or... -
Efficient estimation of Bayesian VARMAs with time‐varying coefficients (repli...
Empirical work in macroeconometrics has been mostly restricted to using vector autoregressions (VARs), even though there are strong theoretical reasons to consider general... -
Model selection with estimated factors and idiosyncratic components (replicat...
This paper provides consistent information criteria for the selection of forecasting models that use a subset of both the idiosyncratic and common factor components of a big... -
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... -
A Theoretical Foundation for the Nelson-Siegel Class of Yield Curve Models (r...
Yield curve models within the popular Nelson-Siegel class are shown to arise from formal low-order Taylor approximations of the generic Gaussian affine term structure model.... -
ESTIMATING FISCAL LIMITS: THE CASE OF GREECE (replication data)
This paper uses Bayesian methods to estimate a real business cycle model that allows for interactions among fiscal policy instruments, the stochastic fiscal limit and sovereign... -
A comprehensive look at financial volatility prediction by economic variables...
We investigate whether return volatility is predictable by macroeconomic and financial variables to shed light on the economic drivers of financial volatility. Our approach is... -
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)... -
Learning, forecasting and structural breaks (replication data)
We provide a general methodology for forecasting in the presence of structural breaks induced by unpredictable changes to model parameters. Bayesian methods of learning and... -
Model-free evaluation of directional predictability in foreign exchange marke...
We examine directional predictability in foreign exchange markets using a model-free statistical evaluation procedure. Based on a sample of foreign exchange spot rates and... -
An evaluation of the forecasts of the federal reserve: a pooled approach (rep...
The Federal Reserve Greenbook forecasts of real GDP, inflation and unemployment are analysed for the period 1974-1997. We consider whether these forecasts exhibit systematic... -
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... -
How quickly do forecasters incorporate news? Evidence from cross-country surv...
Using forecasts from Consensus Economics Inc., we provide evidence on the efficiency of real GDP growth forecasts by testing whether forecast revisions are uncorrelated. As the... -
Permanent vs transitory components and economic fundamentals (replication data)
Any non-stationary series can be decomposed into permanent (or trend) and transitory (or cycle) components. Typically some atheoretic pre-filtering procedure is applied to... -
Structural break threshold VARs for predicting US recessions using the spread...
This paper proposes a model to predict recessions that accounts for non-linearity and a structural break when the spread between long- and short-term interest rates is the... -
Estimating and predicting multivariate volatility thresholds in global stock ...
We propose a general double tree structured AR-GARCH model for the analysis of global equity index returns. The model extends previous approaches by incorporating (i) several... -
A forecast comparison of volatility models: does anything beat a GARCH(1,1)? ...
We compare 330 ARCH-type models in terms of their ability to describe the conditional variance. The models are compared out-of-sample using DM?$ exchange rate data and IBM... -
Modelling and forecasting stock returns: exploiting the futures market, regim...
This paper proposes a vector equilibrium correction model of stock returns that exploits the information in the futures market, while allowing for both regime-switching... -
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...
