  This paper considers the Split-Then-Combine (STC) approach (Arroyo and de
Juan, 2014) to combine forecasts inside the simplex space, the sample space of
positive weights adding up to one. As it turns out, the simplicial statistic
given by the center of the simplex compares favorably against the fixed-weight,
average forecast. Besides, we also develop a Combine-After-Selection (CAS)
method to get rid of redundant forecasters. We apply these two approaches to
make out-of-sample one-step ahead combinations and subcombinations of forecasts
for several economic variables. This methodology is particularly useful when
the sample size is smaller than the number of forecasts, a case where other
methods (e.g., Least Squares (LS) or Principal Component Analysis (PCA)) are
not applicable.
