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Differencing versus nondifferencing in factor‐based forecasting (replication ...
This paper studies performance of factor-based forecasts using differenced and nondifferenced data. Approximate variances of forecasting errors from the two forecasts are... -
Do contractionary monetary policy shocks expand shadow banking? (replication ...
Using VAR models for the USA, we find that a contractionary monetary policy shock has a persistent negative impact on the level of commercial bank assets, but increases the... -
Transitions at Different Moments in Time: A Spatial Probit Approach (replicat...
This paper adopts a spatial probit approach to explain interaction effects among cross-sectional units when the dependent variable takes the form of a binary response variable... -
Optimal Portfolio Choice Under Decision‐Based Model Combinations (replication...
We propose a density combination approach featuring combination weights that depend on the past forecast performance of the individual models entering the combination through a... -
A Two-Stage Approach to Spatio-Temporal Analysis with Strong and Weak Cross-S...
An understanding of the spatial dimension of economic and social activity requires methods that can separate out the relationship between spatial units that is due to the effect... -
Replacing Sample Trimming with Boundary Correction in Nonparametric Estimatio...
Two-step nonparametric estimators have become standard in empirical auctions. A drawback concerns boundary effects which cause inconsistencies near the endpoints of the support... -
Using OLS to Estimate and Test for Structural Changes in Models with Endogeno...
We consider the problem of estimating and testing for multiple breaks in a single-equation framework with regressors that are endogenous, i.e. correlated with the errors. We... -
Non-Gaussian dynamic Bayesian modelling for panel data (replication data)
A first order autoregressive non-Gaussian model for analysing panel data is proposed. The main feature is that the model is able to accommodate fat tails and also skewness, thus... -
Forecast comparisons in unstable environments (replication data)
We propose new methods for comparing the out-of-sample forecasting performance of two competing models in the presence of possible instabilities. The main idea is to develop a... -
What do we learn from the price of crude oil futures? (replication data)
Despite their widespread use as predictors of the spot price of oil, oil futures prices tend to be less accurate in the mean-squared prediction error sense than no-change...
