pool_av.S3.test {pEPA}

Computes Test for Overall Equal Predictive Ability.

Description

This function computes test of the equal predictive accuracy for the pooled average. It corresponds to S^{(3)}_{nT} statistic in the referenced paper by Akgun et al. (2024). The null hypothesis of this test is that the pooled average loss is equal in expectation for a pair of forecasts from both considered methods. The alternative one is that the differences do not average out across the cross-sectional and time-series dimensions. The test allows for strong cross-sectional dependence.

Usage

pool_av.S3.test(evaluated1,evaluated2,realized,loss.type="SE")

Arguments

evaluated1

same as in pool_av.test

evaluated2

same as in pool_av.test

realized

same as in pool_av.test

loss.type

same as in pool_av.test

Value

class htest object, list of

statistic

test statistic

alternative

alternative hypothesis of the test

p.value

p-value

method

name of the test

data.name

names of the tested data

References

Akgun, O., Pirotte, A., Urga, G., Yang, Z. 2024. Equal predictive ability tests based on panel data with applications to OECD and IMF forecasts. International Journal of Forecasting 40, 202–228.

See Also

pool_av.test, pool_av.S1.test

Examples

data(forecasts)
y <- t(observed)
# just to reduce computation time shorten time-series
y <- y[,1:40]
f.bsr <- matrix(NA,ncol=ncol(y),nrow=56)
f.dma <- f.bsr
# extract prices predicted by BSR rec and DMA methods
for (i in 1:56)
  {
    f.bsr[i,] <- predicted[[i]][1:40,1]
    f.dma[i,] <- predicted[[i]][1:40,9]
  }
t <- pool_av.S3.test(evaluated1=f.bsr,evaluated2=f.dma,realized=y,loss.type="SE")