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.
Defence Industry
There are a number of principal criteria that drive our forecasts for each defence variable.
Defence Budget And Expenditure
Figures for the defence budget (but not expenditure) are based, where possible, on primary government/ministry sources and official data. Where these are unavailable, defence budget/expenditure forecasts are based on a range of variables including:
- Stated expenditure and procurement plans;
- Likely increases to expenditure owing to security threats;
- Political factors (likely government changes, influence of the military);
- Readiness of the military;
- Commitments of the armed forces.
Expenditure per capita, percentage of GDP and percentage of fiscal budget are calculated using BMI’s own macroeconomic and demographic forecasts.
Employment In Arms Production
Forecast based on following criteria:
- The growth or otherwise of the defence industry;
- Company results and expansion plans.
Arms Imports And Exports
Forecast based on following criteria:
- Arms ordered and not yet delivered,
- Stated procurement plans,
- Military needs (based on the security situation and the readiness of the military),
- Occasionally, realpolitik (orders from major allies, foreign military sales from the US etc.).
Sources
Sources used in defence reports include local defence ministries, officially released company results and figures, established think tanks and institutes, such as SIPRI, IISS and RUSI, and international and national news agencies.
