Figure III.1. Forecasts and Adjustments for GDP Growth in 2020

The same approach is repeated for the year 2020. In this scenario, in-sample forecast error predictions, and both forecasted and realized growth rates, are compared for the year 2020. The findings are presented in figure III.1 Panel B. For all countries, the January growth forecast was much higher than the realized growth, indicating overly optimistic growth forecasts across the board. Compared to Panel A, the forecast intervals in Panel B are much larger, reflecting the large and unexpected global shock of the pandemic in 2020. The realized growth rates for 9 of 14 economies still falls within the bounds of uncertainty indicated by the lower and upper bounds. Moreover, the adjusted forecast growth based on the predicted forecast errors for 2020 (the diamonds) are closer to the realized growth, compared to the 2020 January forecasts. Although the bands of uncertainty and the error corrections are larger in 2020 than in 2019, both sets of estimates suggest that accounting for several factors increases the accuracy and reduces the optimism of growth forecasts.

Figure III.1. Forecasts and Adjustments for GDP Growth in 2020

Panel A. Forecasts and Adjustments, 2019

Growth rates Panel B. Forecasts and Adjustments, 2020

Growth rates

15 10 5 0 -5 -10 -15 -20 Algeria Egypt,Arab Rep. Iran, Islamic Rep. IraqJordanTunisiaMorocco UnitedArab EmiratesBahrainKuwaitOmanQatar SaudiArabiaLebanon

J January Growth Forecast 2019 Q Adjusted Growth Forecast 2019 ▬ Realized Growth 15 10 5 0 -5 -10 -15 -20 Algeria Egypt,Arab Rep. Iran, Islamic Rep. IraqJordanTunisiaMorocco UnitedArab EmiratesBahrainKuwaitOmanQatar SaudiArabiaLebanon

J January Growth Forecast 2020 Q Adjusted Growth Forecast 2020 ▬ Realized Growth

Source: Authors’ calculations from World Bank Global Economic Prospects, January 2019 and January 2020. Note: Adjusted growth forecasts for most countries are obtained by the subtraction of the predicted forecast errors from the January GEP GDP growth forecasts. For Egypt, June GEP growth forecasts are used because of fiscal year considerations (July to June) – it is the only country in the MENA region that provides GDP for the fiscal year instead of the calendar year. The intervals are calculated using in-sample predicted absolute forecast errors for 2019 (panel A) and 2020 (panel B), respectively. Predicted absolute forecast errors for 2019 are added and subtracted from January GEP 2019 growth forecast to obtain the upper and lower bounds of the interval for 2019 (panel A). This is repeated for the year 2020 (panel B). The underlying regressions for the predicted forecast error are the same as in chapter II with the inclusion of a MENA region dummy variable. Findings do not change with the inclusion or exclusion of the MENA regional dummy variable. The R-square of the regression ranges from 0.49 to 0.53. Roughly about 50 percent of variation in the forecast errors are explained by the observable covariates. The Countries excluded from these figures are also excluded from regressions analysis. West Bank and Gaza does not have data on export commodity shocks. Real GDP per capita data (constant 2010 US$) is unavailable for Djibouti. January GEP growth forecasts for 2019 and 2020 are missing for Libya, Syria and Yemen.

The breakout of the Ukraine crisis pushes the region into another year of uncertainty stemming from unanticipated events. To demonstrate different scenarios of plausible economic growth rates for the year 2022, the discussion considers three different scenarios for adjusting the January 2022 growth forecasts. The first scenario assumes 2022 will play out as 2019, characterized by low uncertainty. The adjustments to growth forecasts in this scenario are based on the 2019 predicted forecast errors and absolute forecast errors. The results from applying this set of forecast uncertainty are shown in figure III.2 Panel A. The second scenario assumes 2022 will play out as in 2020, the year of the pandemic-induced extreme uncertainty (hopefully an unlikely scenario for 2022). The results from applying this set of forecast errors are shown in figure III.2 Panel B.

The third scenario is presented in figure III.2 Panel C. This scenario depicts the forecast uncertainty bounds under the assumption that 2022 will turn out to be a typical (median) year drawn from data covering last 5 to 11 years (depending on each country’s data availability on forecasts from the past). In this scenario, the typical or median of historical forecast errors is used to make the adjustments, instead of using predictions of forecast uncertainty from the regression