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Assessment of Energy Policy and Practices

Macro assessment

Central to the macro assessment are indicators measuring the extent to which a country has the necessary attributes in place to achieve the 3 A's. This Energy Policy and Practices Index (EPPI) is built around the four Supports and the Building Blocks in Figure 1. The first support measures the capacity of a country to design and implement high-quality policy and practices. The second support predominantly measures the strength and flexibility of the economy, supplemented by the ability to implement energy security (Availability). The final two relate to current performance in addressing different elements and characteristics of the remaining two 3 A's, Accessibility and Acceptability.

The four Supports, illustrated in Figure 1  above, are composed of 13 Building Blocks:

  1. A. Institutions is composed of Institutions and Regulation (A1) and Goods and Factors Markets (A2).

  2. B. Economy is composed of Macro-economy (B1), Innovation (B2), Energy Markets (B3), Investment (B4), Infrastructure (B5), and Energy Security (B6).

  3. C. Social Capacity and Equity is composed of Education (C1), Health and Safety (C2), and Equity (C3).

  4. D. Environment is composed of Climate Change (D1) and Other Environmental Factors (D2).

Each Building Block is defined by a set of relevant indicators (see Annexes 1 and 2 for details on both building blocks and indicators). All of the data are sourced from international institutions, national statistical organisations, and national energy institutes. All data are then validated by the individual member committees.

Once the data for the indicators are collected, the results are aggregated through weighting to obtain an index.

The weighting reflects the relative importance of the factors shaping a country's overall energy policy and practices.

In this Assessment, a Principal Components Analysis (PCA)²  is used to estimate the weighting to be applied, a common tool in other index studies. However, using such a statistical technique has its limitations, and going forward we will review other approaches which may lead to revision of weightings. A working list of weightings is presented in Annex 2.

 


² PCA serves to link indicators through measures of co-variance, and by a statistical estimation process apportions weights systematically. See James l Kenkel (1996) Statistics for management and economics, ISBN 0-534-20370-1