Access to up-to-date socio-economic data is a widespread challenge in Papua New Guinea and Pacific Island countries. To increase data availability and promote evidence-based policymaking, the Pacific Observatory provides innovative solutions and data sources to complement existing survey data and analysis.
What We Do
To increase data availability and promote evidence-based policy making, the Pacific Observatory generates and uses non-traditional data and surveys to gain insights into economic activity, household welfare, and livelihoods in Papua New Guinea and the Pacific Island countries. These data and activities include:
· Phone surveys – Design and implementation of high frequency phone surveys to monitor indicators of household and individual wellbeing
· Big data – Production of alternative data sources and use of big data linked to household phone survey data to generate policy-relevant economic and sector statistics
In order to reflect a dynamic context, the Pacific Observatory engages with local, regional, and global stakeholders to “ground-truth” information and findings and disseminate data and knowledge.
The Pacific High Frequency Surveys collect unique data on households’ economic wellbeing, resilience, employment, and food security across the region. Regular data collection began in 2020, with more frequent monthly interviews starting from 2023. The surveys collect detailed responses from a total of over 3000 households per month, across Papua New Guinea, Solomon Islands, Tonga, and Vanuatu, with Fiji added to the collection in 2024. The project dashboard covers employment, food security, income, and access to health services, and is updated continuously as fieldwork continues:
Exploring Big Data Solutions to Answer Development Questions
The Pacific Observatory develops methods that explore the use of alternative data sources to generate new signals of information for the Pacific. Big data has the potential to generate indicators thar are timely, have high frequency and geographic granularity. New information from non-traditional data sources – such as data from satellites, cell phones, or text sources - can help provide timely evidence for pressing questions in the Pacific. By linking big data with statistics from surveys and official sources, we can better understand development challenges and propose innovative policy solutions.
Documentation
The team maintains a public GitHub repository, with annotated notebooks that document the research of various big data topics, and reproducible code to generate statistical outputs.
Feasibility note on the use of nighttime lights data to generate economic statistics (poverty, extractives output, recovery from natural disasters, electrification rates).
Machine Learning Imputation to Fresh Produce Price Surveys in Papua New Guinea
Study that applies a machine learning approach to fill data gaps in food prices in PNG, enabling real-time monitoring of local inflation.
Agriculture Monitoring with Satellite Imagery
Feasibility note that demonstrates the use of satellite imagery and climate datasets to monitor agricultural productivity.
Poverty Mapping with Alternative Data
New poverty maps using call data records and high-frequency phone survey data to understand geographic distribution of poverty.
Automatic Identification System (AIS) Data
Exploring the use of AIS data to derive high-frequency indicators on trade and fishing intensity.
Aviation Statistics for Tourism
Analysis of aviation data to monitor tourism recovery in the PICs, by estimating the number of visitors and tourism earnings.
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