What does this research mean for the field?

A nowcasting model effectively produces timely estimates of quarterly GDP growth for Kenya using a combination of official monthly indicators and digital transaction data. Novelty: ClaimNovelty.NOVEL_FINDING. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

The aim is to develop a nowcasting model to generate timely estimates of quarterly GDP growth for Kenya.

February 22, 2026Open Access

Nowcasting GDP Growth for Kenya

Key Points

The aim is to develop a nowcasting model to generate timely estimates of quarterly GDP growth for Kenya.
Developed nowcasting model using monthly indicators and digital transaction data.
Utilized latent factors to summarize macroeconomic dynamics.
Updated the model with each new data release to refine forecasts.
The nowcasting model demonstrates robust performance in environments with limited data.
Effective decomposition of revisions into predictable and news components was achieved.
Nowcasting proves to be relevant for low-income nations like Kenya.

Abstract

This paper develops a nowcasting model to produce timely estimates of quarterly GDP growth for Kenya. Nowcasting combines official monthly indicators with digital transaction data. Exploiting strong comovement of macroeconomic time series, a few latent factors summarize aggregate dynamics and enhance forecasts. The model is updated with each data release, decomposing revisions into predictable and news components. Results demonstrate robust performance of the nowcasting model in data-constrained environments and show that nowcasting is applicable to low-income countries.

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