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Freight Transport 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.

Freight Transport Industry

There are a number of principal criteria that drive our forecasts for each transport variable:

GDP Growth

As transport activity is heavily influenced by real GDP growth, this factor is examined to ascertain its relationship with overall trade volumes. Projected GDP growth is calculated using BMI’s own macroeconomic and demographic forecasts.

Real Trade Volumes

The sum of imports and exports plays a particularly important role in developing countries with a small domestic industrial sector. In particular, the focus is on goods, as services do not employ transport. The volumes are forecast based on the following criteria:

• Trends manifested through historical data;
• The impact of future step changes to the economy (such as future membership of the EU or some other regional body).

Port Traffic

Port traffic levels act as a ‘second opinion’ on trade volumes. However, this check needs to be used with caution, as trade values and volumes do not always move over time in the same way.

Market Share

The market share of each mode (road, rail, inland waterway, coastal shipping) for future years is based upon:

• Trends in historical modal split data;
• Evidence of government policy favouring one or more modes over others;
• Government and or private sector investment plans in specific modes.

Sources

Sources used in Freight Transport reports include local transport ministries, officially released company results and figures, established think tanks and institutes and donor agencies such as the World Bank and the Asian Development Bank.

Freight Transport Business Environment Ratings Methodology

Ratings Overview

Conceptually, BMI’s Freight Transport 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 Freight Transport 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:
• Freight Transport Market: 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%
- Freight Transport Market	- 50%
- Country Structure	- 30%
Risks to Realisation of Potential Returns	30%
- Tendering process	- 40%
- Country Risk	- 60%

 

Indicators

The following indicators have been used. Overall, the rating uses four subjectively-measured indicators, and over 20 separate indicators/datasets.

Indicator	Rationale
Limits to potential returns
Freight Transport Market
Total trade, US$bn	Indicator denotes market size. Large markets score higher than smaller ones.
Trade growth, % y-o-y	Indicator denotes sector dynamism. Scores are based on annual average growth over our 5-yr forecast period.
Transport intensity	Indicator denotes sector dynamism. Scores are based on annual average growth over 10-yr forecast period.
Competitive environment	Subjective evaluation of level of private/public sector market dominance.
Country Structure
Trade concentration	Rating from BMI’s Country Risk Ratings (CRR). It measures the market share of top three export destinations and, consequently, is a measure of vulnerability to export market structure.
Trade bureaucracy	Rating from BMI’s CRR. It evaluates the level of bureaucracy faced by importers/exporters.
Export sector reliance	Rating from BMI’s CRR. It measures proportion of exports accounted for by largest sector and, consequently, is a measure of vulnerability to commodity markets/specific industries.
Risks to potential returns
Market Risks
Market Orientation	Subjective evaluation of government policy towards sector against BMI-defined criteria. Protectionist states are marked down.
Regulatory environment	Subjective evaluation of policy transparency – regulations and enforcement – against BMI-defined criteria.
Country Risk
Short Term Economic Risk	Rating from BMI’s CRR. It denotes the state’s vulnerability to a crisis over a two-year forecast time horizon.
Short Term Policy Continuity Risk	Rating from BMI’s CRR. It evaluates the risk of a sharp change in the broad direction of government policy.
Legal framework	Rating from BMI’s CRR, to denote strength of legal institutions in each state – security of investment can be a key risk in some EM.
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.

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