BMI Forecast Modelling
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.
Chemicals And Petrochemicals Industry
Plant Capacity
The ability of a country to produce basic chemical products depends on domestic plant capacity. The number and size of ethylene crackers determines both a country’s likely output and also its relative efficiency as a producer. We therefore examine:
- Stated year-end capacity for key petrochemical products, mainly ethylene but also propylene, polypropylene, polyethylene and so forth. Government, company and third-party sources are used;
- Specific company and/or government capacity expansion projects aimed at increasing the number and/or size of crackers and downstream processing facilities.
Chemicals Supply
A mixture of methods is used to generate supply forecasts, applied as appropriate to each individual country:
- Basic plant capacity and historic utilisation rates. Unless a company imports chemicals products for domestic re-sale, supply will be governed by production capacity;
- Underlying economic growth trends. The chemicals industry is highly cyclical. Strong domestic or regional demand will be met by increased supply and higher plant utilisation rates;
- Third party projections from national and international industry trade associations.
Chemicals Demand
Various methods are used to generate demand forecasts, applied as appropriate to each individual country:
- Underlying economic growth trends. The chemicals industry is highly cyclical. Strong domestic or regional demand will require larger volumes of either domestically-produced or imported olefins (ethylene, propylene), polyolefins (polyethylene, polypropylene) or downstream products;
- Trends in end-user industries. Strong demand for motor vehicles, construction materials, packaging products and pharmaceuticals implies rising demand for basic chemicals;
- Government/industry projections;
- Third party forecasts from national and international industry trade associations etc.
Cross Checks
Whenever possible, we compare government and/or third party agency projections with the declared spending and capacity expansion plans of the companies operating in each individual country. Where there are discrepancies, we use company-specific data as physical spending patterns ultimately determine capacity and supply capability. Similarly, we compare capacity expansion plans and demand projections to check the chemicals balance of each country. Where the data suggest imports or exports, we check that necessary capacity exists or that the required investment in infrastructure is taking place.
