Mining Forecast Methodologies
How We Generate Our Industry Forecasts
BMI’s industry forecasts are generated using the best-practice techniques of time-series modelling. The precise form of time-series model we use varies from industry to industry, in each case being determined, as per standard practice, by the prevailing features of the industry data being examined. For example, data for some industries may be particularly prone to seasonality, i.e. seasonal trends. In other industries, there may be pronounced non-linearity, whereby large recessions, for example, may occur more frequently than cyclical booms.
Our approach varies from industry to industry. Common to our analysis of every industry, however, is the use of vector autoregressions. Vector autoregressions allow us to forecast a variable using more than the variable’s own history as explanatory information. For example, when forecasting oil prices, we can include information about oil consumption, supply and capacity.
When forecasting for some of our industry sub-component variables, however, using a variable’s own history is often the most desirable method of analysis. Such single-variable analysis is called univariate modelling. We use the most common and versatile form of univariate models: the autoregressive moving average model (ARMA).
In some cases, ARMA techniques are inappropriate because there is insufficient historic data or data quality is poor. In such cases, we use either traditional decomposition methods or smoothing methods as a basis for analysis and forecasting.
It must be remembered that human intervention plays a necessary and desirable part in all our industry forecasting techniques. Intimate knowledge of the data and industry ensures we spot structural breaks, anomalous data, turning points and seasonal features where a purely mechanical forecasting process would not.
Mining Ratings Methodology
BMI’s Mining Business Environment Ratings (MBER) provides a numerically-based evaluation of prospects for the mining sector in each state that we cover. In order to do this systematically, we have isolated the factors we consider to be the principal barriers to commercial mining activity for foreign investors. Having done so, we collate relevant World Bank and sector-specific data, and we augment this with the subjective evaluation of each state provided by BMI’s Mining and Country Risk analysts. This enables us to provide a simple score out of 10 on each indicator for each country, which facilitates evaluation of states by each sub-component and the construction of a composite score.
As most of the territories that are evaluated are considered by BMI to be ‘emerging markets’, our MBER is revised on a quarterly basis. This ensures that the ratings draw upon the latest information and data from across our broad source of ranges, and the expertise of our analysts.
Breakdown Of Ratings
The MBER breaks down into three distinct components: core business environment (CBE); country risk (CR); and sector potential (SP). The overall weighting is:
- CBE: 30%
- CR: 30%
- SP: 40%
Breakdown Of Components
The main components are themselves broken down into sub-components.
CBE consists of five sub-components:
Legal framework: This incorporates World Bank data on investor protection (disclosure, director liability and shareholder suits); rule of law; and contract enforceability (cost, number of procedures, time).
Government bureaucracy: This incorporates World Bank data on the procedures (length and time) required to start and close a business; payment of taxes (number of taxes and frequency of payment); acquiring of licences (number of procedures and times); and registry of property (number of procedures, time and cost).
Trade bureaucracy: This incorporates World Bank data on the number of documents/time required for exports/imports.
Tax: This comprises World Bank data on the total amount of taxes payable by the business, except for labour taxes, as a percentage of gross profits.
Labour market infrastructure: This incorporates UNDP life expectancy data; WHO health expenditure data; UNESCO data for schooling and literacy; World Bank data on labour rigidity and hiring/firing costs; and ILO data on manufacturing wages.
CR consists of two sub-components:
Long-term political rating: This is BMI’s Country Risk team’s assessment of the structural stability of the state, incorporating analysis of 14 variables.
Long-term economic rating: This is BMI’s Country Risk team’s assessment of risks to economic stability over a seven-year period, incorporating data/forecasts on 20 separate indicators.
SP has no sub-components:
It is our mining analysts’ evaluation of growth prospects both in terms of y-o-y expansion, and the absolute potential of the state (i.e. are there thought to be unidentified reserves available).
Mining Business Environment Ratings Methodology
Ratings Overview
Conceptually, BMI’s Mining Business Environment Ratings system provides a globally-comparative, numerically-based assessment of the Risk/Return trade-off for the industry in each state covered in BMI Reports. In order to provide clients with a detailed assessment of this trade-off, the overall rating is comprised of two distinct sub-ratings:
Limits of Potential Returns: Evaluates the industry’s current size and growth potential, and also assesses broader industry/state characteristics that may enable/inhibit the industry’s development.
Risks to Realisation of Potential Returns: Evaluates issues within (a) the Mining sector, and (b) the broader political/economic/business environment, that indicate the level of uncertainty surrounding the realisation of potential returns.
These ratings are themselves comprised of sub-ratings:
- The ‘Limits’ Rating is comprised of:
- Mining Sector: This evaluates industry growth/size dynamics
- Country Structure: This evaluates the broader economic/socio-demographic environment
- The ‘Risks’ Rating is comprised:
- Market Risks: This is a subjective evaluation of industry regulatory and competitive issues
- Country Risk: This evaluates the industry’s broader Country Risk exposure, which is based on industry-specific vulnerabilities that may be assesses using any combination of the 56 components of BMI's proprietary Political, Economic and Business & Operational Risk Ratings
Weighting
Given the number of indicators/datasets used, it would be inappropriate to give all sub-components equal weight. Consequently, the following weight has been adopted.
Component |
Weighting |
Limits of Potential Returns |
70% |
- Mining Sector |
- 65% |
- Country Structure |
- 35% |
Risks to Realisation of Potential Returns |
30% |
- Market Risk |
- 50% |
- Country Risk |
- 50% |
Indicators
The following indicators have been used. Overall, the rating uses two subjectively-measured indicators, and almost 30 separate indicators/datasets.
Indicator |
Rationale |
Limits to potential returns |
|
Mining Sector |
|
Mining output, US$bn |
Current sector size is used as a proxy for resource endowment. |
Sector value growth, % y-o-y |
Rapid growth is a proxy for attractive opportunities, and is given double weighting. |
Mining sector, % of GDP |
This is used as a proxy for the extent to which the economy is already oriented towards the sector. |
Country Structure |
|
Labour market infrastructure |
Rating from BMI’s Country Risk Ratings (CRR) to denote cost/availability of labour. High costs will affect risk-returns calculations. |
Physical Infrastructure |
Rating from BMI’s CRR. Poor power/water/transport infrastructure act as bottlenecks to sector development. |
Tax |
Rating from BMI’s CRR. Punitive taxation regime limits opportunities. |
Scope of state |
Rating from BMI’s CRR. Low state control markedly increases security risks, thereby increasing costs in certain states. |
Risks to potential returns |
|
Market Risks |
|
Metals prices, 5-yr forecast ave. |
Expectations of price strength will increase investment opportunities and limit downside risks. |
Metals price forecast, ave. 5-yr growth |
The resultant score is weighted by the ave. score of the VIX index over the preceding month to incorporate uncertainty arising from global market volatility, a key risk given high cost of new investment projects. |
Regulatory Rramework |
Evaluates risks arising from environmental/land issues and the transparency/consistency of industry oversight. |
Legal Rramework |
Rating from BMI’s CRR. It denotes the strength of legal institutions in each state and therefore the predictability of the legal environment for investors. |
Country Risk |
|
Long Term External Risk |
Rating from BMI’s CRR, to denote vulnerability to external shock – principal cause of economic crises. While most output is exported, an economic shock would hit domestic value-added industry and may affect the predictability of economic/business policy-making. |
Corruption |
Rating from BMI’s CRR, to denote risk of additional illegal costs/possibility of opacity in tendering/business operations affecting companies’ ability to compete. |
Bureaucracy |
Rating from BMI’s CRR to denote ease of conducting business in the state. |
Long Term Policy Continuity |
Subjective rating from BMI’s CRR, to denote predictability of government policy across electoral cycle/government change. |
