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To meet the SDGs by 2030, more data is needed and collecting it can be time-consuming and expensive. Governments can select the data collection methods and analytical tools that will best help them reach their SDG targets.
Fortunately, there are several approaches to this. Longitudinal data on household expenditure can be a better way of measuring poverty and income inequality in Asia and the Pacific compared to the cross-sectional data analysis currently used across the region. Longitudinal data tracks the same kinds of data over long periods of time. Cross-sectional data is collected from many subjects at a single point in time.