Why Climate Change should be considered within Financial Programming framework?

Abstract

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.