From mobile crowdsourcing to crowd-trusted food price in Nigeria: statistical pre-processing and post-sampling

Timely and reliable monitoring of food market prices at high spatial and temporal resolution is essential to understanding market and food security developments and supporting timely policy and decision-making. Mostly, decisions rely on price expectations, which are updated with new information releases. Therefore, increasing the availability and timeliness of price information has become a national and international priority. We present two new datasets in which mobile app-based crowdsourced daily price observations, voluntarily submitted by self-selected participants, are validated in real-time within spatio-temporal markets (pre-processed data). Then, they are re-weighted weekly using their geo-location to resemble a formal sample design and allow for more reliable statistical inference (post-sampled data). Using real-time data collected in Nigeria, we assess the accuracy and propose that our re-weighted estimates are more accurate with respect to the unweighted version. Results have important implications for governments, food chain actors, researchers and other organisations.

ARBIA Giuseppe;  SOLANO HERMOSILLA Gloria;  NARDELLI Vincenzo;  MICALE Fabio;  GENOVESE Giampiero;  AMERISE Ilaria Lucrezia;  ADEWOPO Julius; 

2024-07-01

NATURE PORTFOLIO

JRC133990

2052-4463 (online),   

https://doi.org/10.1038/s41597-023-02211-1,    https://publications.jrc.ec.europa.eu/repository/handle/JRC133990,   

10.1038/s41597-023-02211-1 (online),