Why Climate Change should be considered within Financial Programming framework?

This research aims to improve the IMF’s Financial Programming framework by inserting the
climate change factor into the analysis, neglecting the vital relationship between global
warming and the IMF's accuracy in GDP predictions. Under the climate change variable, the
study tracks carbon dioxide emissions on both global and separately national scales. The
study employs ARDL as a basis for the empirical research methodology and uses four
distinctive models with CO2 emissions and FP's two (1)/ six (2)-year global (3)/ panel (4)
GDP forecasting accuracies. Global and panel GDP forecast accuracy deviation of the
countries for six years is out of investigation due to the small sample size. The findings of
the time series show that by keeping all other variables stable, a 1% increase in the first lagged
global GDP forecast accuracy deviation for two years deteriorates the named forecast
accuracy (increases GDP forecast accuracy deviation for two years) in the short run by
0.624%, on average. The findings of the panel data, on the other hand, dictate that, ceteris
paribus, a 1% increase in carbon dioxide emissions decreases the two-year GDP forecast
accuracy deviation of paneled countries by only 0.66%, on average. Thus, albeit of statistical
essence, neither in the short term nor in the long, the CO2 emissions significantly affect the
FP's global two-year GDP forecasting accuracy in economic terms.