For a number of reasons, including the potential for rapid changes in world prices, revenues from natural resources can be highly volatile. To ensure the effective and efficient use of those revenues, governments need accurate models that can predict future revenue flows. Thanks to extensive information disclosure, civil society in Peru built such a revenue forecasting tool, and regional governments have used it successfully to improve budget planning.

Peru is rich in natural resources, which accounted for 5.3% of its Gross Domestic Product (GDP), 70% of exports, and more than 20% of budget revenues in 2010, as well as for much of the country’s recent economic growth. The country’s collection of taxes and royalties is highly centralised at the national level. The national government distributes a portion of mining income tax and oil royalties to producing regions, including to regional governments, municipalities and national universities. The centralised nature of resource revenues, combined with their volatility, make it challenging for regional and municipal authorities to engage in efficient mid- to long-term planning, which often leads to wasteful and ineffective spending.

In 2008, the Revenue Watch Institute (RWI, now the Natural Resources Governance Institute), and a Peruvian consortium of local NGOs, Grupo Propuesta Ciudadana (GPC), designed a revenue forecasting tool for regional budgets. They used data from government and corporate websites, including extensive project-level information, which allowed for accurate multi-year forecasting. The tool was first applied in 2010 in two extractive regions, Arequipa and Piura.

There are multiple advantages of this model of revenue forecasting. First, government authorities can more accurately plan budgets for new investment projects beyond the standard annual planning cycle. If future revenues are projected to be low, they can avoid launching long-term projects for which they may not have sufficient resources to complete. Or, if sufficient revenues are projected, they can launch long-term investments that may have previously seemed too financially demanding. Second, revenue forecasts allows for better monitoring of financial flows and for the identification of money leakages.
Regional governments can dispute governmental transfers if they fall short of their forecasts.

Using this forecasting model, authorities in the Arequipa and Piura regions started identifying investment gaps, planning long-term development projects and integrating regional initiatives into national plans. Better forecasting contributed to an increase of more than 5% for both regions in the percentage of the allocated budget actually spent between 2009 and 2011. Higher budget shares were allocated to priority development sectors, such as education and health care. In Piura, for instance, budget allocations for education and health increased by 12.7% and 27.8% respectively between 2009 and 2011.

In parallel, RWI and its local counterpart GPC made efforts to empower local communities and transform regional budget planning into a more participatory process. At the national level, a multi-stakeholder group drafted and submitted to Congress a fiscal decentralisation proposal that is expected to lead to higher revenues for development purposes to most Peruvian regions, not just to regions rich in natural resources. At the local level, civil society monitoring allows for permanent independent oversight of how extractive money is allocated and spent in the annual budget cycle.

Key Lessons:

  • Extractive rents forecasting is critical for sub-national authorities to engage in mid- to long-term budgeting and investment planning in scenarios plagued by volatility.
  • Accurate forecasting demands free and quick access to data regarding both external demand and prices and internal investment and production data.
  • Public officials’ capacity building efforts demand equally capable civil society activists to ensure sustainability of change after authorities and officials change as a result of political cycles.

Photo credit: Elbuenminero