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Petrochemicals 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.

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, but also its relative efficiency as a producer. We therefore examine:

• Stated year-end capacity for key petrochemicals products, mainly ethylene but also propylene, PP, PE, etc. 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 would be governed by production capacity;
• Underlying economic growth trends. The chemicals industry is highly cyclical. Strong domestic or regional demand would 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 would require larger volumes of either domestically-produced or imported olefins (ethylene, propylene), polyolefins (PE, PP) 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 reported 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.

 

Petrochemicals Business Environment Ratings Methodology

Ratings Overview

Conceptually, BMI’s Petrochemicals 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 Petrochemicals 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:
• Domestic 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%
- Petrochemicals Market	- 65%
- Country Structure	- 35%
Risks to Realisation of Potential Returns	30%
- Market Risks	- 40%
- Country Risk	- 60%

 

Indicators

The following indicators have been used. Overall, the rating uses three subjectively-measured indicators, and almost 30 separate indicators/datasets.

Indicator	Rationale
Limits to potential returns
Market structure
Cracker capacity, current year	Objective measure of sector size
Cracker capacity, 2011	Forecast of sector development
Downstream capacity, current year	Objective measure of domestic demand
Country structure
Financial infrastructure	Rating from BMI’s Country Risk Ratings (CRR) to denote ease of obtaining investment finance. Poor availability of finance will hinder company operations across the economy.
Trade bureaucracy	Rating from BMI’s CRR. Low trade restrictions is essential for this export-based industry.
Physical Infrastructure	Rating from BMI’s CRR. Given size of manufacturing units, sector development requires strong supporting power/water/transport infrastructure
Risks to potential returns
Tendering process
Industry regulatory environment	Subjective evaluation against BMI-defined criteria. This indicator evaluates predictability of operating environment.
Country Risk
Structure of economy	Rating from BMI’s CRR, to denote health of underlying economic structure, including 7 indicators such as volatility of growth; reliance on commodity imports, reliance on single sector for exports.
Long Term External Economic Risk	Rating from BMI’s CRR, to denote vulnerability to external shock – principal cause of economic crises.
Long Term External Financial Risk	Rating from BMI’s CRR, to denote vulnerability of currency/stability of financial sector.
Institutions	Subjective rating from BMI’s CRR, to denote strength of bureaucracy and legal framework. Also evaluates level of corruption.
Long Term Political Risk	Rating from BMI’s CRR, to denote strength of political environment.

 

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