Nowcasting GDP Growth for Kenya
IMF Working Papers, February 20, 2026
Source details
- Canonical URL
- Nowcasting GDP Growth for Kenya
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Bibliographic details
- Authors: Nikolay Danov, Domenico Giannone, Alain N. Kabundi, Cedric I Okou, Antonio Spilimbergo
- Published: February 20, 2026
- Series: IMF Working Papers
- DOI: https://doi.org/10.5089/9798229038584.001
Overview
- Title: Nowcasting GDP Growth for Kenya
- Authors: Nikolay Danov, Domenico Giannone, Alain N. Kabundi, Cedric I Okou, Antonio Spilimbergo
- Publication date: February 20, 2026
- Aim: Develop a nowcasting model to produce timely estimates of quarterly GDP growth for Kenya by combining official monthly indicators with digital transaction data.
Methodology
- Modeling approach:
- Uses dynamic factor models exploiting strong comovement of macroeconomic time series.
- Summarizes aggregate dynamics with a few latent factors to enhance forecasts.
- Data inputs:
- Official monthly indicators.
- Digital transaction data.
- Update procedure:
- Model is updated with each data release.
- Revisions are decomposed into predictable and news components.
Key findings
- Performance:
- Results demonstrate robust performance of the nowcasting model in data-constrained environments.
- Nowcasting is shown to be applicable to low-income countries.
- Practical implications:
- Combining traditional indicators with digital transaction data improves timeliness and accuracy of quarterly GDP growth estimates.
- Latent-factor summarization effectively captures aggregate dynamics in Kenyan macroeconomic time series.
Model updating and revisions
- Update frequency:
- The model is updated with each data release to refine nowcasts.
- Revision analysis:
- Revisions to nowcasts are decomposed into:
- Predictable components.
- News components.
Content in this bundle
- Working Paper