Budgeting for SDGs: A Data-driven Approach

Governments occupy the centre stage when it comes to achieving the Sustainable Development Goals (SDGs) set by the United Nations. To succeed, they must effectively integrate these global goals into their budget process. This involves strategically allocating financial resources that are directly linked to the SDGs. This linkage between public spending and development goals is key for informing development plans, but is hardly observable in real-world data due to the complexity introduced through SDG interdependencies and potential spillovers across development programmes. This research aims to provide a flexible data-driven framework to analyse the relationship between the allocation of public investments and improvement in SDGs indicators. First, we use information on the historical trends of development indicators and public expenditure to build a model that can effectively predict an improvement in the SDGs indicators. Then, we identify those expenditure categories that are the most relevant to our predictive model. Such a framework could complement contextual expertise and assist treasuries around the world in making the best use of their resources to achieve the SDGs and help thinking about potential spillover effects of budget programmes across different goals.