利用非传统数据进行宏观经济预测：以摩洛哥为例

Leveraging Non-traditional Data forMacroeconomicNowcasting: The Caseof Morocco Dina Hamed WP/26/108 IMF Working Papersdescribe research inprogress by the author(s) and are published toelicit comments and to encourage debate.The views expressed in IMF Working Papers arethose of the author(s) and do not necessarilyrepresent the views of the IMF, its Executive Board,or IMF management. 2026JUN IMF Working Paper Middle East and Central Asia Department Leveraging Non-traditional Data for Macroeconomic Nowcasting: The Case of MoroccoPrepared byDina Hamed* Authorized for distribution by Laura Jaramillo MayorJune2026 IMF Working Papersdescribe research in progress by the author(s) and are published to elicitcomments and to encourage debate.The views expressed in IMF Working Papers are those of theauthor(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management. ABSTRACT:Making informed policy decisions is contingent upon the availability of reliable and timely data.The use of non-traditional data has been shown to be a powerful tool in allowing policymakers to achieverobust nowcasting—the practice of estimating the current period’s economic indicator(s), ahead of officialreleases, using a wide range of macroeconomic and high-frequency data. This paper showcases how differenttypes of non-traditional data, such as indices extracted from satellite imagery, Google Trends, and flighttracking information, can be leveraged to complement official statistics and monitor economic activity, and howthese timely signals can be incorporated into nowcasting models to provide early estimates of keymacroeconomic variables in Morocco. The approach is applied to agricultural gross value added, tourismrevenues, and the unemployment rate. The results demonstrate that non-traditional data substantially improvesnowcasting models by enhancing predictive accuracy and enabling the rapid generation of nowcast estimatesprior to the release of official data. RECOMMENDED CITATION:Hamed, D. (2026). Leveraging Non-traditional Data for MacroeconomicNowcasting: The Case of Morocco. Working Paper. International Monetary Fund WP/26/20 WORKING PAPERS Leveraging Non-traditional Datafor Macroeconomic Nowcasting:The Case of Morocco Prepared byDina Hamed Contents 3.1 Agriculture Value Added.........................................................................................................................103.2 Tourism Revenues.................................................................................................................................153.3. Unemployment Rate..............................................................................................................................18 4.1. Data Transformation and Processing....................................................................................................194.1.1. Agriculture Value Added..............................................................................................................194.1.2. Tourism Revenues......................................................................................................................194.1.3. Unemployment Rate....................................................................................................................19 4.2.1 Models..........................................................................................................................................204.2.2. Hyperparameter Tuning and Model Evaluation...........................................................................224.2.3. Robustness Checks.....................................................................................................................23 5. Results...........................................................................................................................................................23 5.1. Agriculture Value Added........................................................................................................................245.2. Tourism Revenues................................................................................................................................265.3 Unemployment Rate...............................................................................................................................27 FIGURES 1. Agricultural Stress Index (ASI) Heatmap by District........................................................................................122. Precipitation in Morocco, January 2025 vs. January 2026..............................................................................123. Correlation between NDVI and Cereal Production..........................................................................................134. Nighttime Lights, 2015 vs. 2025......................................................................................................................135. Correlations between Satellite Ind