We use global sea ice volume, atmospheric carbon dioxide (CO2) concentration, and Antarctic land surface temperature data from 798,000 to 1,000 years ago. We control for the eccentricity of the Earth’s orbit, the obliquity of Earth, and the precession of the equinoxes (i.e. Milankovitch cycles). We introduce the quasi-vector autoregressive fractionally integrated (QVAR-FI) model. We apply QVAR-FI to climate data and introduce the fractionally integrated score-driven ice-age model. We estimate QVAR-FI using the maximum likelihood (ML) method for the fractional integration parameter in the interval (-1/2,1/2). The statistical and forecasting performances of QVAR-FI are superior to QVAR and VAR. The impulse response functions (IRFs) for QVAR-FI capture the dynamic effects of shocks better than QVAR and VAR. We confirm, with more confidence than previous works for these data, that for the last 12,000-15,000 years when humanity influenced the Earth’s climate (i.e. Anthropocene), the global sea ice volume forecasts are above the observed sea ice volume, the atmospheric CO2 concentration forecasts are below the observed atmospheric CO2 concentration, and the Antarctic land surface temperature forecasts are below the observed Antarctic land surface temperature, after controlling for natural forces of climate change due to orbital variables.