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IFDP Notes

December 3, 2013

The Energy Boom and Manufacturing in the United States: A First Look


Will Melick

Over the past eight years, the production of both crude oil and natural gas has increased sharply in the United States. To the extent that the energy market is localized, especially true for natural gas, the energy boom will provide a competitive advantage to those U.S. manufacturers that are intensive users of energy. I use industry-level data on investment, production, employment, prices and trade flows to offer a preliminary empirical assessment of the energy boom's impact on U.S. manufacturing.

A positive supply shock for an important input such as energy will lead manufacturers to increase output, in turn pushing out the industry supply curve and lowering prices. To the extent that energy and labor are complementary inputs, manufacturing employment will also increase. Exports of manufactured products should also increase while imports should fall. Investment in the manufacturing sector should increase as existing firms expand and reorient their production processes and new firms enter the sector. All of these effects on industry activity should vary with the energy-intensity of the industry. Thus, I look for relationships between an industry's energy intensity and measures of activity in that industry.

The measure of energy intensity for the manufacturing sector is derived from the Manufacturing Energy Consumption Survey (MECS) conducted by the Department of Energy. Table 1 displays the measures of total energy intensity and natural gas intensity by industry as of the 2006 survey. Because the resurgence in U.S. energy production began around 2006 these data offer a good indication of which industries stand to benefit the most from the positive energy supply shock.

Table 1
Energy Consumption by Industry in the 2006 Manufacturing Energy Consumption Survey
(Thousand BTUs per $ of Value Added)
NAIC Code Industry Total Energy Natural Gas NAIC Code Industry Total Energy Natural Gas
311 Food 5.0 2.7 3254 Pharmaceuticals and Medicines 0.7 0.4
3112 Grain and Oilseed Milling 17.5 6.0 325412 Pharmaceutical Preparation 0.6 0.3
311221 Wet Corn Milling 43.6 12.7 325992 Photographic Film, Paper,
Plate, and Chemicals
3.8 NA
31131 Sugar Manufacturing 31.3 6.5 326 Plastics and Rubber Products 3.7 1.3
3114 Fruit and Vegetable Preserving
and Specialty Foods
5.5 4.5 327 Nonmetallic Mineral Products 17.5 6.4
3115 Dairy Products 4.3 3.4 327211 Flat Glass 34.5 28.4
3116 Animal Slaughtering
and Processing
4.4 2.7 327212 Other Pressed and Blown
Glass and Glassware
39.5 NA
312 Beverage and Tobacco Products 1.4 0.5 327213 Glass Containers 24.3 19.4
3121 Beverages 2.4 0.9 327215 Glass Products from
Purchased Glass
9.8 8.2
3122 Tobacco 0.3 0.1 327310 Cements 52.5 2.8
313 Textile Mills 8.6 3.8 327410 Lime 120.1 4.9
314 Textile Product Mills 4.6 3.0 327420 Gypsum 18.7 16.6
315 Apparel 1.0 0.4 327993 Mineral Wool 12.7 8.7
316 Leather and Allied Products 1.1 0.3 331 Primary Metals 20.0 7.4
321 Wood Products 10.4 2.0 331111 Iron and Steel Mills 37.7 NA
321113 Sawmills 15.1 NA 331112 Electrometallurgical
Ferroalloy Products
36.1 NA
3212 Veneer, Plywood, and
Engineered Woods
17.6 4.3 3312 Steel Products from Purchased Steel 5.0 3.6
3219 Other Wood Products 5.6 1.2 3313 Alumina and Aluminum 22.7 10.5
322 Paper 28.9 5.9 331314 Secondary Smelting and
Alloying of Aluminum
16.1 11.4
322110 Pulp Mills 113.2 7.4 331315 Aluminum Sheet, Plate and Foils 13.6 NA
322121 Paper Mills, except Newsprint 35.3 NA 331316 Aluminum Extruded Products 8.6 7.0
322122 Newsprint Mills 40.8 NA 3314 Nonferrous Metals, except Aluminum 6.7 3.3
322130 Paperboard Mills 64.4 12.0 3315 Foundries 8.0 4.1
323 Printing and Related Support 1.5 0.6 331511 Iron Foundries 12.0 NA
324 Petroleum and Coal Products 27.0 6.7 331521 Aluminum Die-Casting Foundries 9.8 NA
324110 Petroleum Refineries 29.2 7.1 331524 Aluminum Foundries,
except Die-Casting
7.9 NA
324199 Other Petroleum and Coal
Products
82.7 3.8 332 Fabricated Metal Products 2.6 1.4
325 Chemicals 9.4 5.1 333 Machinery 1.2 0.5
325110 Petrochemicals 29.8 4.1 334 Computer and Electronic Products 0.7 0.2
325120 Industrial Gases 21.6 12.1 334413 Semiconductors and
Related Devices
1.2 0.3
325181 Alkalies and Chlorine 61.9 32.6 335 Electrical Equip., Appliances,
and Components
1.8 0.7
325182 Carbon Black 25.0 29.6 336 Transportation Equipment 1.7 1.0
325188 Other Basic Inorganic Chemicals 16.8 5.6 336111 Automobiles 1.5 0.8
325192 Cyclic Crudes and Intermediates 8.8 NA 336112 Light Trucks and Utility Vehicles 1.3 0.7
325193 Ethyl Alcohol 23.7 NA 3364 Aerospace Product and Parts 0.9 0.4
325199 Other Basic Organic Chemicals 26.7 NA 336411 Aircraft 0.6 0.2
325211 Plastics Materials and Resins 24.9 13.5 337 Furniture and Related Products 1.1 0.4
325212 Synthetic Rubber 17.8 11.5 339 Miscellaneous 0.6 0.3
325222 Noncellulosic Organic Fibers 20.1 NA
325311 Nitrogenous Fertilizers 131.1 210.7
325312 Phosphatic Fertilizers 15.3 15.1

Note: The Total Intensities are taken directly from the MECS while the Natural Gas Intensities are calculated using MECS data on natural gas usage and ASM data on value added. Thus the two columns are not completely consistent. The only apparent discrepency is for nitrogenous fertilizers.

The energy intensity data are matched with industry-level data on investment, output, prices, employment and trade flows. Exhibit 1 provides a visual summary of the logic behind the analysis. In the two panels of the exhibit, the percentage change over the past several years in a measure of economic activity for manufacturing industries is plotted against natural gas intensity in these industries. All else equal, one would expect to see a generally positive relationship whereby firms that use natural gas intensively undertake greater investment (top panel) and increase production (bottom panel). Both figures show a slight positive scatter, but it is far from overwhelming.1 

Exhibit 1
Figure 1 provides a visual summary of the logic behind the analysis in Table 1.  In the two panels of the exhibit, the percentage change over the past several years in a measure of economic activity for manufacturing industries is plotted against natural gas intensity in these industries.  All else equal, one would expect to see a generally positive relationship whereby firms that use natural gas intensively undertake greater investment (top panel) and increase production (bottom panel).  Both figures show a slight positive scatter, but it is far from overwhelming.

However, the absence of control variables in the scatter plots may be obscuring the impact of the energy boom. Therefore, a regression strategy is used to determine if the energy boom is playing out as expected. The regressions estimate the long-run effect of a drop in natural gas prices on industry activity, allowing for larger effects in the more energy-intensive industries. Control variables include oil prices, commodity prices, U.S. GDP, aggregate foreign GDP and the real exchange rate.

The estimated effects should be negative and significant in the regressions for capital expenditure, output, employment, and exports because a drop in natural gas prices will lead firms to invest more, produce more, hire more and export more. Conversely, the estimated effects should be positive and significant in the price and import equations as a drop in natural gas prices will lead firms to lower prices and discourage imports from foreign manufactures. 

Results are presented in Table 2 and show the percentage impact on the six activity measures given a 50 percent drop in natural gas prices. For each activity measure the estimate is calculated three times: for the industry that is the least intensive user of natural gas, for the median industry, and for the industry that is the most intensive user of natural gas. Probability values for a test that the effect of a change in natural gas prices is equal to zero are also shown. As an example, the estimates indicate that a 50 percent decline in natural gas prices is associated with an almost 8 percent increase in employment for the most natural gas intensive industry.

Table 2
Percentage Effect of a 50 Percent Decline in Natural Gas Prices on Industry Economic Activity
Activity Variable Expected Sign Estimate at Minimum Intensity Estimate at Median Intensity Estimate at Maximum Intensity p-Value
Output ( + ) 0.011 0.570 33.525 0.00
Prices ( - ) -0.014 -0.680 -29.277 0.00
Employment ( + ) 0.045 1.081 7.669 0.00
Exports ( + ) 0.011 0.543 31.651 0.14
Imports ( - ) -0.015 -0.771 -32.524 0.01
Capital Expenditure ( + ) 0.001 0.066 3.420 0.90

Estimated effects are calculated from regressions of the change in activity variables on the change in natural gas prices interacted with intensity of natural gas use and control variables. Data are annual from 1997 through 2012, except for Capital Expenditures which is through 2011. Estimates in bold are statistically significant at the five percent level.

 

With regard to economic significance, the estimated effects of a 50 percent decline in natural gas prices for the median industry (Column 4) are quite modest, ranging from a bit more than one percent increase in employment to a roughly three-quarters of a percent decline in imports. For the most intensive industry (Column 5) the estimated effects are much larger, ranging from an almost 35 percent increase in output to an almost 35 percent decline in imports. For every activity measure the estimated effects are of the expected sign, and for four of the six measures the estimated effects are statistically significant (in bold). 

The estimates in Table 2 suggest that the energy boom has had a relatively small impact in the manufacturing sector as a whole. For most industries the 50 percent decline in natural gas prices over the past eight years is estimated to induce a perhaps one to two percent change in activity. Results are quite a bit stronger for the most intensive users of natural gas.

These results point to two possible conclusions. On the one hand, it could be that the energy boom will only ever be noticeable for the most intensive users of natural gas. These intensive users make up a fairly small piece of the manufacturing sector so that the overall impact on the entire sector will be relatively modest. For example, the four most intensive users of natural gas account for 0.5 percent of value added in manufacturing. 

Alternatively, the timing of manufacturers' adjustment to more abundant natural gas will also surely vary by the intensity of natural gas usage. Early impacts should be seen in the most intensive industries, with others to follow. Perhaps the impact of the energy boom has yet to fully play out, calling for continued monitoring and analysis of developments in the manufacturing sector.


1. The nitrogenous fertilizers industry stands out due to its use of methane from natural gas to produce ammonia and thereby nitric acid. Return to text

Disclaimer: IFDP Notes are articles in which Board economists offer their own views and present analysis on a range of topics in economics and finance. These articles are shorter and less technically oriented than IFDP Working Papers.

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Last update: December 3, 2013