**4. Data**

The source of the data we use in this paper is NBER-CES Manufacturing Industry Database, which can be accessed at http://www.nber.org/nberces/. It covers 473 six-digit 1997 NAICS manufacturing industries over 1958–2011. We split our analysis into five decades: 1958–1969 (labeled "the 1960s"), 1970–1979 (labeled "the 1970s"), 1980–1989 (labeled "the 1980s"), 1990–1999 (labeled "the 1990s"), and 2000–2011 (labeled "the 2000s").

The output *Y* of an industry is calculated as the difference between the value of industry shipments, which are based on net sales, after discounts and allowances, and the change in end-of-year inventories. The labor *L* is calculated as *PRODH* ∗ *PAY*/*PRODW*, where *PRODH* is the number of production worker hours, *PAY* is the total payroll, and *PRODW* is production workers' wages. Capital stock *K* is obtained as the sum of real equipment and real structures. Energy *E* is the expenditure on purchased fuels and electrical energy. The cost of overall materials *MATCOST* in the database includes delivered cost of raw materials, parts, and supplies put into production or used for repair and maintenance and purchased electric energy and fuels consumed for heat and power and contract work done by others for the plant. The cost excludes the costs of services used, overhead costs, or expenditures related to plant expansion. Because the overall cost of materials includes energy, the non-energy materials, *NEM* are determined as the difference between overall materials and *E*. See [9] for more details.

The paper analyzes the differences in energy use efficiency between industries that use relatively little and a lot of energy in their production. We define energy intensity *EN*\_*INTENSITY* as the ratio of the expenditures on purchased fuels and electrical energy *E* and the value of industry shipments *VSHIP*, which is the energy cost per unit of sales. The authors of [10], for example, define energy intensity as energy consumption divided by a measure of economic activity. Alternatively, one can define energy intensity as the cost of energy in total costs. We have tried this approach and the

correlation coefficient between these two measures of energy intensity was 0.98. So either of them could be used.

Table A1 shows the summary statistics for output and four inputs for 10 percent of the top and bottom energy-intensive manufacturing industries in the respective decade. The criterion to include an industry is that data on it is available for at least 4 years in a decade.
