Leveraging Non-traditional Data for Macroeconomic Nowcasting: The Case of Morocco

IMF Working Papers, June 5, 2026

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Canonical URL: Leveraging Non-traditional Data for Macroeconomic Nowcasting: The Case of Morocco

Author: Dina M Hamed
Date: June 5, 2026
Purpose: Showcase how non-traditional data can complement official statistics and be incorporated into nowcasting models to provide early estimates of key macroeconomic variables in Morocco.
Non-traditional data types highlighted:
- Indices extracted from satellite imagery
- Google Trends
- Flight tracking information
Targeted applications:
- Agricultural gross value added (Agriculture GVA)
- Tourism revenues
- Unemployment rate

Non-traditional data substantially improves nowcasting models by:
- Enhancing predictive accuracy
- Enabling rapid generation of nowcast estimates prior to the release of official data
The approach is applied specifically to:
- Agricultural gross value added
- Tourism revenues
- The unemployment rate
Demonstrated benefit: timely signals from high-frequency and alternative data sources provide robust estimates of current-period economic indicators ahead of official releases.

Nowcasting framework: integration of a wide range of macroeconomic and high-frequency data into models to estimate current-period economic indicators ahead of official releases.
Data transformation and analysis techniques referenced in subject/keywords:
- Econometric analysis
- Time series analysis
- Machine learning
- Data transformation

For policymakers: leveraging non-traditional data provides earlier and more accurate indicators of economic activity, supporting more informed and timely policy decisions.
Practical implication: complementing official statistics with satellite imagery indices, Google Trends, and flight tracking can improve monitoring of sectoral activity (agriculture, tourism) and labor market conditions (unemployment).