III.2. Bounds of uncertainty around growth forecasts for 2022

the April 2022 growth forecast in comparison to the January 2022 vintage. There is no change in 2022 growth forecasts between the January vintage and the April forecast for Egypt. Note that the GDP growth forecast for Egypt is for its fiscal year from July 2021 to end-June 2022. All other countries in the table report calendar year growth. Thus, the full extent of the anticipated effects for the 2022 calendar year are not incorporated in the forecasts for Egypt to the same extent as for the other countries, since most of the fiscal year was already baked in by the end of February. However, the downside risks remain—Egypt is a net importer of both fuel and food commodities, a destination for Eastern European tourists, and recently implemented a rise in key monetary policy rates by 100 basis points in late March 2022. Thus, Egypt’s growth prospects for the 2022 calendar year may paint a different picture than that of other oil importers.

The following subsection discusses how the vintages of the January 2022 forecasts, and the April 2022 forecasts can be interpreted with caution in the context of economic, particularly global, uncertainty.

III.2. Bounds of uncertainty around growth forecasts for 2022

This wide range of possibilities speaks to the degree of uncertainty in forecasting. Forecasters do the best they can with the best information available when the forecasts were being produced. A key limitation in the MENA region is the lack of publicly-available high-frequency data, as discussed in chapter II. It is worth noting that the analysis herein excludes some conflict economies in the MENA region as they lack recent growth forecasts altogether.

As a first preliminary step, the analysis compares the uncertainty that was present in 2019 with that of 2020.

Following the econometric model presented in chapter II table X4, the model’s estimates of the band of uncertainty and biases for each country in 2019 are presented in figure III.1 Panel A. The solid vertical columns represent the real GDP growth forecasts for 2019 that were published in January of that year.25 The intervals around the solid vertical columns are based on the predicted absolute forecast errors.26 The upper bound of uncertainty is constructed as the addition of the predicted absolute forecast error to the 2019 January growth forecast. The lower bound is the subtraction of the predicted absolute forecast error from the 2019 GEP January growth forecast. The diamond represents the adjusted growth rate after the subtraction of the predicted forecast error from the January 2019 forecasted growth. The short horizontal bar in the figure marks the realized GDP growth rate for year 2019, as recorded in the World Bank’s Global Economic Prospects report of January 2021.

For almost all countries27, the January growth forecasts (solid vertical columns) appear to be higher than the realized growth (horizontal bar), which imply optimistic growth forecasts across the board. The adjusted forecasts of the GDP growth based on the predicted forecast errors (the diamonds) are adjusted downward relative to the January forecasts and are closer to the realized growth for all the MENA countries in the sample.28

25 For Egypt the solid vertical column shows the June 2018 GEP forecast as the fiscal year in Egypt begins in July and ends in June. 26 This is the predicted value of the regressions in chapter 2 with absolute forecast errors as the dependent variable. 27 Egypt is the only country in 2019, whose realized growth for year 2019 is higher than GEP January forecast. The gap is small though, by 0.6 percentage points. 28 The findings are quite similar whether the MENA regional dummy variable is excluded from the econometric estimations of forecast errors. The implication is that there are unobservable

MENA-specific variables that make it hard to forecast growth in the MENA region, but these do not substantially affect the forecasts with the observable variables explaining much of the variation in the forecast errors. The magnitude of the coefficient of the MENA region dummy is 0.39 for the Forecast Error Regressions and 0.25 for Absolute Forecast Error regressions.