Can Co-Deployment of Machine Learning and High-Frequency Surveys Produce Reliable Real-Time Data in Data-Scarce Regions? (anglais)

Capabilities to track fast-moving economic developments remain limited in many regions of the developing world. This makes assessing changes in the development context difficult, and complicates prioritizing policies aimed at supporting vulnerable populations. To gain insight into the evolution of fluid events in a data scarce context, this paper explores the ability of recent machine-learning advances to impute ongoing surveys in near-real-time and...
Voir la suite

INFORMATION

  • Andree,Bo Pieter Johannes;
    Pape,Utz Johann;

  • 2023/02/02

  • Rapport

  • 181630

  • 1

  • Pacific Islands,

  • Asie de l’Est et Pacifique,

  • 2023/04/19

  • Disclosed

  • Can Co-Deployment of Machine Learning and High-Frequency Surveys Produce Reliable Real-Time Data in Data-Scarce Regions?

Voir la suite

LIENS CONNEXES

BOLETÍN DEL BANCO MUNDIAL

This document is being processed or is not available.