New research on the impact of energy taxes and the EU’s cap-and-trade system has been released. Both articles were published by the American Economic Journal in 2020.
In “Energy Cost Pass-Through in US Manufacturing: Estimates and Implications for Carbon Taxes,” the authors study the welfare effects of changes in energy input costs—such as energy taxA tax is a mandatory payment or charge collected by local, state, and national governments from individuals or businesses to cover the costs of general government services, goods, and activities. changes—on manufacturing producers and consumers, accounting for incomplete pass-through, imperfect competition, and substitution among inputs. In doing so, they focus on six manufacturing industries.
In “Adopt or Innovate: Understanding Technological Responses to Cap-and-Trade,” Georgetown University economist Raphael Calel measures the impact of cap-and-trade programs on carbon emissions as well as R&D spending and patenting. He focuses on the response of firms to the 2005 introduction of the European Union Emissions Trading System (EU ETS).
Energy Cost Pass-Through
In “Energy Cost Pass-Through” Ganapati et al. (April 2020) ultimately conclude that the welfare cost to consumers resulting from higher energy taxes is smaller than previously estimated.
In order to do this, they examine price changes in the box, bread, cement, concrete, gasoline refining, and plywood industries from 1972-1997, using the natural variation in fuel prices as a proxy for policy change.
Diverging from previous literature, they do not assume that goods markets are perfectly competitive. In a perfectly competitive market, firms make no profit and increased input prices are passed on in their entirety to consumers. Under monopoly, there is only a single profit-maximizing seller in the market. In oligopolistic conditions, there are only a few sellers of a product and the market is not completely competitive.
Under perfect competition assumptions, in the box, cement, and plywood industries, consumers bear 144 percent, 181 percent, and 107 percent of the welfare burden, respectively, as costs in excess of 100 percent are passed through to consumers. In the bread industry, consumers bear 68 percent of the welfare burden, while in the concrete and gasoline industries, consumers bear 78 percent and 32 percent of the welfare burden, respectively.
However, under more realistic oligopoly assumptions, the consumer share of the higher energy cost burden was lower than under perfect competition in every case. The consumer share was 63 percent for boxes, 43 percent for bread, 46 percent for cement, 58 percent for concrete, 31 percent for gasoline, and 64 percent for plywood.
Under monopoly assumptions, which are also a more realistic assumption than perfect competition in these industries, consumers also fare better than under perfect competition. The consumer share of the energy cost burden under monopoly is 59 percent for the box industry, 41 percent for bread, 64 percent for cement, 44 percent for concrete, 24 percent for gasoline, and 52 percent for plywood.
Differences in pass-on rates among industries can be attributed to the sensitivity of consumers to price change. For this reason, the lower pass-through rate for the gasoline refining industry implies that consumers of gasoline products are relatively sensitive to price changes, making gasoline products relatively elastic goods. The energy costs of bread manufacturing also have relatively low pass-on rates.
Overall, by moving away from the strong assumption of perfect competition, Ganapati et al. can show that the pass-through percentage of energy costs are lower than previously found in the short to medium term.
They do not expect that their use of some intermediate goods industries has significant impact on their conclusions, asserting that the literature shows that tax on intermediate rather than final goods has an equal impact on consumer surplus.
However, they caution against generalizing their findings to other industries, citing divergence in the cement industry from others.
Cap-and-Trade Effect on Emissions and R&D Spending
EU ETS is a cap-and-trade program, which means that it works by setting a cap on carbon emission quantities. Companies can trade for carbon emissions permits, which creates a market for carbon emissions permits and thus indirectly puts a price on carbon emissions. Cap-and-trade is designed to incentivize companies to reduce emissions.
In his paper, Calel (August 2020) finds that EU ETS did not encourage substantial adoption of already-existing carbon-reduction technology but rather encouraged firms to undertake low-carbon R&D and patenting.
In fact, firms under EU ETS increased carbon dioxide (CO2) output by 20.7 percent. However, since this relationship is based on few firms, it should not be read as strong evidence that the EU ETS has led to increased CO2 intensity. Instead, it adds to other studies that find no evidence that the EU ETS has reduced CO2 intensity. EU ETS did encourage an approximately 10 percent increase in low-carbon patenting from capped firms. In addition, Calel evaluates that EU ETS prompted an average spending increase of £514,00 (US $655,612) per firm on low-carbon R&D, amounting to a 3 percent R&D increase. Calel estimates that low-carbon patenting increased by 25 percent as a result of EU ETS.
Calel briefly examines the literature on previous cap-and-trade programs, which were implemented in the 1980s and ’90s and primarily focused on non-carbon emissions such as sulfur dioxide (SO2), various nitrogen oxides (NOX), lead, and ozone-depleting substances. He finds that most firms would simply adopt already-existing emission-reducing technology. Important technological advancements that occurred while the programs were in place were created from prior investments, allowing businesses to simply implement already-existing technology rather than developing new ones.
Calel approximates climate innovation output by measuring Y02 class patents, which are patents tagged by the European Patent Office as relating to climate change mitigation.
He can estimate the impact of the EU ETS against a counterfactual scenario by taking advantage of some of its specific design elements, as it only covers “large” plants, irrespective of the total size of the company managing them. It also has different eligibility criteria than other climate-reduction programs.
Calel notes that there is not much data available on the impact of cap-and-trade programs and recognizes that the sample size used is small.
Conclusion
In all, findings indicate that the pass-on rates of energy price hikes to consumers are lower than previously expected.
The EU ETS has also been found to be effective in stimulating low-carbon R&D spending and patenting of carbon-reduction technology. Compared to previous cap-and-trade systems, this can be seen as a shift in resources from technology adoption to technology innovation.
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