Sampling Distributions of Post-sample Forecasting Errors

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The Tourism Forecasting Competition (2011, background): “• Previous studies have found the forecast intervals obtained to be too narrow; hence, the actual values fall outside the empirical forecast intervals more often than they should (see for example Makridakis and Winkler, 1989; Chatfield, 2001; Hyndman et al., 2002).”
Forecasting: theory and practice (2020, background): “variance, and in out-of-sample performance of relevance to decision making (Makridakis and Winkler, 1989; Chan et al., 1999; Barrow and Kourentzes, 2016).”
Empirical prediction intervals revisited (2014, background): “It is well known, however, that true post-sample forecast errors tend to be larger than the fitted residuals (Makridakis & Winkler 1989).”
How predictable is technological progress (2015, unknown): “Several studies have found that using residuals leads to prediction intervals which are too tight (Makridakis & Winkler 1989).”