Methodologies

Data sources

The Global Household Energy Database of the World Health Organization (WHO) was used for data related to cooking indicators. The database contained 824 household surveys collected from 161 countries (including high-income countries) between 1970 and 2014. The countries provided for cooking are only those with underlying data, so there are no estimates for Turkey and Libya.

Population data from the World Bank’s World Development Indicators were used for all countries except the Cook Islands and Anguilla (not in that database), so United Nations Population Division data were used. The World Development Indicators database does not have 2013–14 data for Eritrea, 1992–94 data for Kuwait, or 1990–97 data for Sint Maarten, so the 2011, 1991, and 1998 populations were used as proxies.

Estimating missing values

Since household surveys are conducted irregularly, a multilevel nonparametric modeling approach developed by the WHO was adopted to estimate missing values in between surveys for both databases.

For clean cooking fuels, only the model estimates are used due to large variances in survey results.

Multilevel nonparametric modeling takes into account the hierarchical structure of the data: survey points are correlated within countries, which are then clustered within regions. Time is the only explanatory variable; no covariates are used. Regional grouping are based on WHO regions and used for cooking.

Calculating the annual growth rate

In contrast to earlier editions, the 2017 GTF uses a simpler, more intuitive annual increase in the access rate, calculated as the difference between the access rate in year 2 and that in year 1, divided by the number of years to annualize the value:

(Access Rate Year 2 – Access Rate Year 1) / (Year 2—Year 1)

This approach takes population growth into account by working with the final national access rate.

Data sources

Survey data from the World Bank’s Global Electrification Database (GED) was used for electrification indicators, which compiles some 500 nationally representative household survey data, and occasionally census data, from sources going back as far as 1990.

Population data from the World Bank’s World Development Indicators were used for all countries except the Cook Islands and Anguilla (not in that database), so UN Population Division data were used. WDI does not include 2013–14 data for Eritrea, 1992–1994 data for Kuwait, or 1990–1997 data for Sint Maarten, so the 2011, 1991, and 1998 populations were used as proxies.

Estimating missing values

A multilevel nonparametric modeling approach, which was developed by the World Health Organization for estimating clean fuel useand has already been widely used for access to cooking, was adapted to electricity access and used to fill in the missing data points for 1990–2014.

Multilevel nonparametric modeling takes into account the hierarchical structure of the data: survey points are correlated within countries, which are then clustered within regions. Time is the only explanatory variable; no covariates are used. Regional groupings are based on UN regions, with Sub-Saharan Africa further divided into Eastern Africa, Central Africa, Southern Africa, and Western Africa.

The model is applied for all countries with at least one data point. But to use as much as real data as possible, results based on real survey data are reported in their original form for all years available.

Bangladesh, for example, had 10 surveys between 1994 and 2014 comprising Demographic and Health Surveys, Multiple Indicator Cluster Surveys, and other national surveys; the remaining 15 years are filled in with estimates.

This may lead to significant discontinuity from one year to the next as the basis for the reported number shifts from actual data to model estimates.

In practice this meant applying the statistical model on total and rural electrification rates. The residual was assigned to urban rates. The statistical model was not used for all three – total, rural and urban as there was no guarantee that rural and urban rates would add up to reflect the total.

Countries considered "developed" by the UN are assumed to have an electrification rate of 100%, since such data are not typically collected or reported for these countries. Furthermore, countries are assumed to have an electrification rate of 100% from the year in which they were classified as High Income Countries.

Calculating the annual change in access rate

The annual change in access rate is calculated as the difference between the access rate in year 2 and the rate in year 1, divided by the number of years in order to annualize the value:

(Access Rate Year 2 – Access Rate Year 1) / (Year 2 – Year 1)

This approach takes population growth into account by working with the final national access rates.

Ratio between energy consumption in agriculture (including forestry and fishing) and agricultural sector value added measured at purchasing power parity.

Data sources: Energy balances from IEA and World Bank’s World Development Indicators (WDI), supplemented by United Nations Statistical Division for countries not covered by IEA or WDI.

Ratio between energy consumption in industry (including energy industry own use) and industry sector value added measured at purchasing power parity.

Data sources: Energy balances from IEA and World Bank’s World Development Indicators (WDI), supplemented by United Nations Statistical Division for countries not covered by IEA or WDI.

Energy intensity of TPES=  {Primary energy supply (MJ)} over {GDP (2011 PPP $)}

Ratio between energy supply and gross domestic product measured at purchasing power parity. Energy intensity is an imperfect proxy for energy efficiency. It indicates how much energy is used to produce one unit of economic output. Lower ratio indicates that less energy is used to produce one unit of economic output.

Ratio between energy consumption in residential sector and population.

Data sources: Energy balances from IEA, supplemented by United Nations Statistical Division for countries not covered by IEA, and United Nations Population Division.

Energy intensity of service sectors (MJ/$2011): A ratio between energy consumption in services (including commercial and public services) and services sector value added measured at purchasing power parity.

Data sources: Energy balances from IEA and World Bank’s World Development Indicators (WDI), supplemented by United Nations Statistical Division for countries not covered by IEA or WDI.

 

 

A ratio between final energy consumption and gross domestic product measured at purchasing power parity. Energy intensity is an indication of how much energy is used to produce one unit of economic output. Lower ratio indicates that less energy is used to produce one unit of output.

GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. GDP is measured at purchasing power parity at constant 2011 US dollars.

Data source: World Bank’s World Development Indicators (WDI)

 

where,

FEIt1: final energy intensity in year t1

FEIt2: final energy intensity in year t2

 

Compound annual growth rate (CAGR) of final energy intensity between two years. Represents the average annual growth rate during the period. Negative values represent improvements in energy intensity (less energy is used to produce one unit of economic output), while positive numbers indicate declining energy intensity (more energy is used to produce one unit of economic output).

where,

PEIt1: primary energy intensity in year t1

PEIt2: primary energy intensity in year t2

 

Compound annual growth rate (CAGR) of primary energy intensity between two years. Represents the average annual growth rate during the period. Negative values represent improvements in energy intensity (less energy is used to produce one unit of economic output), while positive numbers indicate declining energy intensity (more energy is used to produce one unit of economic output).

Sum of energy consumption by the different end-use sectors, excluding non-energy uses of fuels. TFEC is broken down into energy demand in the following sectors: industry, transport, residential, services, agriculture, and others. It excludes international marine and aviation bunkers, except at world level where it is included in the transport sector.

Data sources: Energy balances from IEA, supplemented by United Nations Statistical Division for countries not covered by IEA

As defined by the International Energy Agency (IEA), total primary energy supply is production plus net imports minus international marine and aviation bunkers plus/minus stock changes.

Data sources: Energy balances from the IEA, supplemented by United Nations Statistical Division for countries not covered by IEA

Methodology

IEA statistical data and United Nations Statistics Division data serve as the underlying data used to calculate the indicator.

The indicator used in this report to track RE within an energy system is the share of RE in TFEC and is expressed as a percentage (%RENTFEC).

This share is calculated as the ratio of final energy consumption of renewables after allocation (AFECREN) to TFEC, calculated from the flows in the energy balances.

The denominator (TFEC) is calculated as the sum of total final consumption minus non-energy use for all energy sources, or equally, the sum of the energy consumed in the industry, transport, and other sectors. The numerator (AFECREN), on the other hand, is not a direct summation of the underlying raw data but a series of calculations reflecting the fact that monitoring occurs at the final energy level. At this level in the energy balance, electricity and heating are secondary energy obtained by different primary energy sources, of which some are renewable. Assumptions need to be made in order to fully account for the renewable component of such secondary sources. It was decided to allocate the final consumption of electricity and heating to renewables based on the share of renewables in gross production.

Final consumption of modern biomass. Modern biomass is defined as all uses of solid biomass not considered traditional.

This is total renewable energy consumption minus traditional consumption/use of biomass. It covers all forms of RE directly measured, including wind, hydro, solar, geothermal, marine, biogas, liquid biofuel, RE waste, and modern biomass.

This indicator includes RE consumption of all technologies: hydro, biomass, wind, solar, liquid biofuels, biogas, geothermal, marine and renewable wastes

This indicator is derived from national energy balance statistics and is equivalent to a country’s total final consumption excluding non-energy uses of fuels.

Final consumption of traditional uses of biomass. Biomass uses are considered traditional when biomass is consumed in the residential sector in non-Organisation for Economic Co-operation and Development (OECD) countries. It includes the following categories in International Energy Agency (IEA) statistics: primary solid biomass, charcoal and non-specified primary biomass and waste.

Note: This is a convention, and traditional consumption/use of biomass is estimated rather than measured directly.