Building capacity to help Africa trade better

Running the numbers: making extractives count for Africa


Running the numbers: making extractives count for Africa

Running the numbers: making extractives count for Africa
Photo credit: AFP

As African resource-rich countries battle with the macroeconomic impact of the dip in global commodity prices, many look back at the 2004-2013 upswing in the commodity cycle and consider whether African countries, and their citizens, made the best out of them.

Asymmetric information between governments and private investors, as well as weaknesses in designing fiscal frameworks are among the reasons why the benefits of extraction might have fallen short of expectations. How can African governments equip themselves to reap a larger slice of rewards when commodity prices start climbing again?

A new study, jointly produced by the African Natural Resources Center of the African Development Bank (AfDB) and OpenOil, a boutique financial advisory firm, starts with the simple premise that no investor would make an investment decision on an extractive project without the support of a comprehensive financial model. Such a model would link the expected production profile, prices, capital and operating expenditure and corporate tax rates to the projected cash flow of the project and its profitability. This allows investors to determine the key factors that will affect the return to investment.

Strikingly, those sitting on the other side of the negotiating table – “governments operating as trustees for natural resources on behalf of their citizens” – have traditionally used these tools far less frequently. Only recently has the importance of financial models in informing governments policy stance come to the fore. This is because of the emphasis, in the global arena, on bolstering negotiation support for developing countries including through dedicated entities such as the African Legal Support Facility.

The use of financial models should go well beyond the negotiation stage however, in order to inform a range of policy decisions across the extractives policy cycle. This starts before negotiations, with the design of fiscal frameworks and model contracts (where models can help estimate the fiscal impact of changes to the tax regime); includes improving fiscal forecast for revenues from extraction (where models can provide a granular assessment of the impact of fluctuations in prices and production, as in this example from Ghana); and carrying out a comparison between projected and realized revenues (“tax gap analysis”) to highlight red flags and risk areas in tax collection.

Financial models along the extractives policy cycle

But if this is the theory, how in practice are financial models currently used by governments? Is there sufficient data available to produce robust results? Is the information produced fully utilized to inform decisions?

The AfDB and OpenOil’s research, the first of its kind in Africa, interviewed 50 officials from 19 resource-rich African countries, to assess the current use of financial models and outline a set of actions for governments and development partners to close capacity gaps and maximize impact. The research finds that the use of models is increasing among African governments. However, its use is still not fully integrated into policy processes and, often, models are applied in a once off manner and mostly only at the negotiation stage.

Garbage in, garbage out: access to data is key. Crucially, results are only as good as the data going into the model. Lack of access to robust data to input in the model is a key weakness noted in the research, especially concerning capital and operating costs of projects. This is especially important as this missing data is also a key vulnerability when it comes to profit shifting and abuse of transfer pricing. If data is weak, then policymakers and modelers need to find alternative sources of data such as market benchmarks, publicly available data (OpenOil’s Aleph search tool of public corporate document can be an important source) and the targeted use of commercial databases.

Communication and business management are important. Models attempt to describe a complex reality and this requires multi-sectoral and multi-disciplinary expertise (typically the mining or petroleum ministry, the Ministry of Finance, the tax agency, but often also other actors such as the presidency, the prime ministers office or the state owned natural resources companies). Moreover, after a model is run, its outputs are only useful if they reach the right decision makers. A model needs to become a catalyst for a cross-cutting government process. About half of the countries sampled in the research have inter-ministerial committees that input into and receive the output of models; however, the other half of respondents do not share outputs of the model outside the agency that produces them, possibly missing important opportunities for intelligence sharing.

Own it and use it: if financial modelling is to be embedded into government processes, it needs to be fully owned by the civil servants who use it regularly. The research found that in nearly three countries out of four, models used were developed through external support (typically a development partner but in some cases the private investors themselves). More concerning for ownership is the fact that only about half of the respondents were deemed to have received adequate training for the use of models, with over 40% judging their training to be insufficient. Furthermore, models are still far from being embedded into routine government processes  such as forecasting and, in 80% of cases, models are not run according to a predetermined schedule, but are rather used in an ad hoc manner as the need arises.

Launched at the Inter-Governmental Forum on Mining Minerals, Metals and Sustainable Development on 19 October 2017, the AfDB/OpenOil report calls for further investment by development partners and governments in capacity building for model use across the policy value chain. It also calls for a coordinated approach to improve access to key project data and/or robust data benchmarking. Data gap analysis needs to be a key component of any training programme on the use of models, setting out strategies to overcome the information gaps. Better use of data from published extractive contracts, from global initiatives such as the Extractive Industries Transparency Initiative, and possibly an investment in open access databases with comparators for project costs can go a long way in strengthening the hand of African governments in appropriating a fairer share of benefits from extractive projects. To maximize economies of scale, governments could adopt multi-country and regional initiatives, training officials on common standards and leveraging inter-governmental bodies such as the African Tax Administration Forum, the Collaborative African Budget Reform Initiative or the Macroeconomic and Financial Institute of Southern and Eastern Africa.


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