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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... -
Smoothed binary regression quantiles (replication data)
This paper extends results regarding smoothed median binary regression to general smoothed binary quantile regression, discusses the interpretation of the resulting estimators... -
Long-run monetary neutrality and long-horizon regressions (replication data)
A prominent test of long-run monetary neutrality (LRMN) involves regressing long-horizon output growth on long-horizon money growth. We obtain limited support for LRMN with this... -
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...
