# **2 Data and Descriptive Analysis**

We use three types of data for the analysis: data on total final energy consumption and the sectoral energy consumption of agriculture and industry from the International Energy Agency (IEA) World Energy Statistics and Balances database; data on GDP and value added of agriculture, services, and industry from the World Bank World Development Indicators (WDI) database; and energy price data from the IEA Energy Prices and Taxes database, the Energy Regulators Regional Association (ERRA) Tariff database, and various government reports and websites. The IEA reports after-tax industry and household electricity and natural gas prices for OECD and selected non-OECD countries. The ERRA database reports after-tax prices for residential and non-residential consumers. We use industry or nonresidential electricity price as a proxy for energy price.<sup>4</sup> When electricity price data are not available, we use the industry natural gas price as a substitute. All price and value added data are converted to 2005 U.S. prices.<sup>5</sup> For countries that have gaps in energy price data, we linearly interpolate those missing observations using the growth rate in the corresponding country’s Consumer Price Index.<sup>6</sup> Table A1 reports the countries as well as the years for which energy price data are linearly interpolated.

Our main variable of interest is energy intensity, defined as total final energy consumption divided by GDP. Sector-specific energy intensity is defined as the total final energy consumption of the sector (industry or agriculture) divided by sector value added.

Our yearly dataset consists of an unbalanced panel of 56 countries spanning the period from 1991 to 2012. We categorize the countries as high income, upper middle income, or lower middle income based on the World Bank’s income classification and the countries per capita gross national income in 2012. Table 1 lists the countries by their income level in 2012 and by data availability for different measures of energy intensity.

Table 2 reports the summary statistics. Figures 1, 2, 3, and 4 show the trends in average GDP, aggregate and sectoral energy intensity, value added shares, and energy price for each income group over the sample period, respectively. GDP and aggregate energy intensity are strongly trending in opposite directions since 1990. While GDP has steadily increased, the aggregate energy intensity of all income groups has fallen dramatically over the past two decades.<sup>7</sup> The negative correlation between GDP and aggregate energy intensity is highly significant, although it does not indicate causality or the direction of causality. Industrial

> 4 We use IEA data on industry electricity prices whenever available. We use ERRA data on non-residential electricity prices when IEA data are not available. The same approach applies to natural gas prices data.

> 5 GDP data are based on purchasing power parity.

> 6 Our main conclusions are robust to the alternative approach by which missing observations of energy prices are not interpolated.

> 7 There was a significant increase in energy intensity in middle-income countries after 1991. This is because many middle-income countries in the sample are transition economies and experienced a sharp contraction in output after the end to centrally planned production. Our main conclusions are robust when we restrict sample to observations between 1991 and 2012.

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