Peer effects in electric vehicle adoption.
The obsession with cool new gadgets, clothes, movies, music and books has brought many people into conversation. In class, we’re still teaching an economic model that assumes rational decision-making in a world of perfect information, but how we learn about the reality of cool new things has a lot to do with social networking. You go to a birthday party and someone tells you about their shiny new Tesla! You come to work on Monday morning and the guy next door has a new iPhone.Your MBA students tell you that the new taylor swift album has declined. The response is usually “I want one too!”
From an energy economist’s perspective, we’re always thinking about how to get new, more efficient technologies into people’s hands.Meredith and Duncan Consider a heat pump. Today, I thought of electric vehicles again. If we think the future of transportation is electric, getting these cool machines into people’s hands (or under people’s butts) is key. One assumption is that spillovers matter. If Severin gets a Tesla 3 and puts it to work, Max sees it and wants one too, and is more likely to buy a Tesla Shelby GT500 He kept staring. It’s intuitive. But as our readers know, we need hard numbers.
Figuring out the magnitude of this effect is difficult. If I observe that the number of Teslas in one neighborhood grows more than the other over time, I can’t figure out if it’s a peer effect or if it’s just one neighborhood getting richer (or something else going on in a different way) method changes).What we want is some natural experiment that provides change when People choose to buy a car and information about the options. Sebastian Tebea recent visitor to our department, on the job market this year, wrote a really cool paper this way.
Sebastian takes advantage of the fact that some drivers don’t adopt new cars at random points in time, but every 36 months — when their leases expire. Actual dates vary by driver. This is very clever in the first place. But what makes this paper worth blogging about is the second part. Sebastian is able to use data from Swedish households to determine who is in your household, who lives in your community and who is in your work network (people employed by the same company in the same location). “Yes, Max, but it’s impossible for him to know what people are driving in these networks.” Sit down. Take a deep breath. he. Do. This is an absolutely insane amount of data work. Over time, he knew which cars made their way into Max’s home and work life – it wasn’t his! He then combined this with somewhat random lease renewals to examine whether people who had a larger share of electric and hybrid cars in their network at renewal were more likely to buy such cars themselves. Overwhelmed by the awe of experience.
So what we learned from this paper (yes, it’s a Swedish lease, so keep the external validity hästar):
- The paper (to me) shows compelling evidence that EV adoption in all three networks (home, community, and workplace) has significant peer effects. How big is it? One more electric car for neighbors, and 0.114 more electric cars for neighbors! Good morning my neighbors! The corresponding figures for workplaces are 0.077 and 0.014 for households.
- If calculated on a per capita basis, the household effect is the largest.So if Aunt Megan buys a Tesla 3, Grandpa won’t buy another Volvo V8 but one Polestar instead.
- Sebastian’s estimated impact suggests a continued increase in demand. These effects are multiplicative over time, which means that these networks have a powerful multiplier effect.
- The paper shows that the shift to EVs is most strongly away from diesel cars, which is good because diesel cars are annoyingly dirty engines from both a local and global pollutant standpoint.
Of course, research on how to use social networks to roll out new technologies is not new.People did some really cool experimental stuff like Kyle Emmerich, Betty Sadule and Alain de Genfrey Against the background of new varieties of rice in agriculture. The problem is the same here, and the results are no different. The web is a powerful accelerator for introducing new technologies. I’m going to put my computer down now and read more papers on this stuff (most of which are written outside of economics, not surprisingly).
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Suggested Citation: Auffhammer, Maximilian. “Cool car (W) people!” Energy Institute Blog, UC Berkeley, October 24, 2022 https://energyathaas.wordpress.com/2022/10/24/cool-car-woman/