Is Subsidizing Electric Cars an Effective Way to Slow Climate Change?

Some governments have been subsidizing purchases of electric vehicles, or more broadly, fuel-efficient vehicles to slow climate change. How well do such policies work? Are they more or less efficient than other policies intended to reduce carbon dioxide emissions? 

A subsidy is a payment by the government that provides an incentive for people to take an action they otherwise wouldn’t, such as buying an electric car. Subsidies have the potential downside that they may involve payments to people to do something they would have done anyway.  For instance, in the United States in 2021, buyers of electric cars were eligible for a credit of up to $7,500 against their federal income taxes. Suppose that you become aware of this subsidy only after you have already purchased an electric car. In that case, the federal government has wasted $7,500 because you would have bought the electric car even without the subsidy. The same would be true if you knew about the subsidy before you bought but because of the subsidy you bought a higher-priced electric car rather than a lower-priced one.

These complications make it difficult for policymakers to assess the efficiency of subsidizing fuel-efficient cars as a means of slowing climate change. Two recent academic papers address this difficulty.  

Chia-Wen Chen of Academia Sinica in Taiwan, We-Min Hu of National Chengchi University in Taiwan, and Christopher Knittel of the Massachusetts Institute of Technology have analyzed a Chinese government program that subsidizes the purchase of fuel-efficient cars. Because the study used data from 2010 and 2011, these vehicles were fuel-efficient gasoline powered cars rather than electric cars.  They find that only about 44 percent of the subsidies went to car buyers who would otherwise not have bought a fuel-efficient car. “Thus, about 56 percent of the program’s payments were ineffective ….” 

The authors calculate that the subsidy cost about $89 per metric ton of carbon dioxide reduced, which is high relative to other policies, such as a carbon tax. With a carbon tax, the government taxes energy consumption on the basis of the carbon content of the energy. (We discuss a carbon tax in the opener to Chapter 5.) The authors conclude: “Paying more than $89 for a metric ton of carbon dioxide is not a cost effective way to reduce carbon dioxide; if the main policy objective of China’s subsidy program on fuel-efficient vehicles was to reduce carbon dioxide emissions, then our results suggest that it was an ineffective way to achieve this goal.”

Jianwei Xing of Peking University, Benjamin Leard of Resources for the Future, and Shanjun Li of Cornell University analyze the efficiency of the U.S. federal income tax credit for purchasing an electric vehicle. As with the study just discussed, they find that consumers who use the credit to buy an electric vehicle were likely to have otherwise bought a hybrid vehicle (a vehicle that combines an electric motor with a gasoline engine) or a relatively fuel-efficient gasoline powered car. They also find, as with the other study, that the federal subsidy is inefficient because while it increased electric vehicle sales by 29 percent, “70 percent of the [tax] credits were obtained by households that would have bought an EV without the credits.”

Because the design of a particular subsidy for buying an electric car will affect the subsidy’s efficiency, these studies are not conclusive evidence that all programs of subsidizing electric cars will be inefficient. But their results show that two existing programs in large markets—China and the United States—are, in fact, inefficient.  

As we note in Chapter 5, many economists favor a carbon tax as a way to reduce carbon emissions rather than policies, such as the federal electric vehicle tax credit, that target a particular source of carbon emissions. Economists can contribute to debates over public policy by using economic principles to identify programs that are more or less likely to efficiently achieve policy goals. They can also, as the authors of these two papers do, use statistical methods to analyze the effects of particular policies. 

Sources: Chia-Wen Chen, We-Min Hu, and Christopher R. Knittel, “Subsidizing Fuel-Efficient Cars: Evidence from China’s Automobile Industry,” American Economic Journal: Economic Policy, Vo. 13, No. 4, November 2021, pp. 152-184; Jianwei Xing, Benjamin Leard, and Shanjun Li, “What Does an Electric Vehicle Replace,” National Bureau of Economic Research, Working Paper 25771, February 2021.

10/24/20 Podcast – Authors Glenn Hubbard & Tony O’Brien discuss the economics of issues raised during the Final 2020 Presidential Debate.

Authors Glenn Hubbard and Tony O’Brien discuss the economic impacts of what was discussed in the final Presidental debate on 10/22/20. They discuss wide-ranging topics that were raised in the debate from reopening the economy & schools, decreasing participation of women in the workforce due to COVID, healthcare, environment, and general tax policy. Listen to gain economic context on these important items. Click HERE for the New York Times article discussed during the Podcast:

Just search Hubbard O’Brien Economics on Apple iTunes and subscribe!

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COVID-19 Update: Externalities During a Pandemic

Supports:  Hubbard/O’Brien, Chapter 5, Externalities, Environmental Policy, and Public Goods; Essentials of Economics Chapter 4, Market Efficiency & Market Failure

Apply the Concept: Should the Government Use Command-and-Control Policies to Deal with Epidemics?

Here’s the key point:   To deal with the negative externalities from an epidemic, a command-and-control policy may be more effective than a market-based policy.

The Externalities of Spring Break during the Coronavirus Epidemic

            When we think of negative externalities, we are typically thinking of externalities in production.   For example, a utility company that produces energy by burning coal causes a negative externality by emitting air pollution that imposes costs on people who may not be customers of that utility company.   During the coronavirus epidemic, some public health experts identified a significant negative externality in consumption.

            The coronavirus epidemic became widespread in the United States during March 2020—when many colleges were on spring break.  By mid-March several states including California, Washington state, and New York closed non-essential businesses such as hotels and restaurants, as well as parks and beaches. But many hotels, restaurants, and beaches in spring break destinations such as Florida remained open and   were packed with college students.  Many students realized that because of the crowds, they might catch the virus.

Why take the risk? There are two possible explanations.   First, many students likely agreed with an American University senior who was quoted in the Wall Street Journal as saying, “It’s a risk to be down here with crowds … [but] it’s my last spring break. I want to live it up as best I can.”  Second, some spring breakers were relying on early reports that people in their 20s who caught the virus would experience only mild symptoms or none at all.  But even young people with mild symptoms could spread the virus to others, including people older than 60 for whom the disease might be fatal.

            So, in March 2020 there was an externality in consumption from college students taking spring break beach vacations because people in large crowds spread the virus. In other words, the students’ marginal private benefit from being on the beach was greater than the marginal social benefit, taking into account that being on the beach might spread the virus.

            The following figure shows the market for spring break beach vacations. The price of a vacation includes transportation costs, renting a hotel room, meals, and any fees to use the beach.  Demand curve D1 is the market demand curve and represents the marginal private benefit to students from vacationing on a crowded beach during spring break.  But spring breakers don’t bear all the cost of potentially contracting the coronavirus by being on a crowded beach because the cost of their spreading the virus is borne by others. So, there is negative externality from vacationing on the beach equal to the vertical distance between D1, which represents the marginal private benefit, and D2, which represents the marginal social benefit, including the chance of spreading the virus by contracting it on a crowded beach.

Because of the externality, the actual number of people taking spring break beach vacations in March 2020, QMarket, was greater than the efficient number, QEfficient.  In Section 5.3 of the Hubbard and O’Brien textbook, we show that when there is an externality in production, a tax equal to the per unit cost of the externality will result in the efficient level of output because the tax causes firms to internalize the externality.  In a similar way, a tax on spring break beach vacations equal to the per unit cost of the externality would shift the marginal private benefit curve, D1, down to where it became the same as the marginal social benefit curve, D2.  By leading spring breakers to internalize the cost of the externality, the tax would cause the market quantity of beach vacations to decline to the efficient quantity, QEfficient.

In practice, however, imposing a tax on people taking a beach vacation would be difficult for two key reasons: (1) In March 2020, there were many aspects of the coronavirus, including how it spread and its fatality rate, that made calculating the value of the negative externality difficult, and  (2) collecting a tax on the many spring breakers crowded on beaches would have been administratively difficult. In the face of these factors, governors and mayors used the command-and-control approach in March of closing beaches, hotels, and restaurants rather than the market-based approach of levying a tax.

Sources: Arian Campo-Flores and Craig Karmin, “The Last Place to be Hit With Coronavirus Worries? Florida Beaches,” Wall Street Journal, March 21, 2020; Aimee Ortiz, “Man Who Said, ‘If I Get Corona, I Get Corona,’ Apologizes,” New York Times, March 24, 2020; and Ryan W. Miller, “’If I Get Corona, I Get Corona’: Coronavirus Pandemic Doesn’t Slow Spring Breakers’ Party,”, March 21, 2020.


According to news reports, some college students on spring break in March 2020 were unaware that partying on the beach put them at risk of contracting the coronavirus. Many also assumed that no one younger than 30 was at risk of becoming seriously ill from the virus, although, in fact, the virus did kill people in their 20s. Suppose that every student on spring break were completely informed about the risks of partying on the beach.  Using the figure above, briefly explain how each of the following would have been affected. Draw a graph to illustrate your answer.

a. the demand curve, D1

b. the demand curve, D2

c. QMarket

d. QEfficient

e. PMarket

f. PEfficient

g. Size of the deadweight loss

Instructors can access the answers to these questions by emailing Pearson at and stating your name, affiliation, school email address, course number.