background-image: url("images/blue.jpg") background-size: cover class: inverse <br><br><br><br> ## Quantifying Plug-in Electric Vehicle<br>Mileage and Resale Value **.white[John Paul Helveston]**, George Washington University<br> Eliese Ottinger, George Washington University<br> Lujin Zhao, George Washington University<br> Laura Roberson, George Washington University October 6, 2023 --- class: middle background-color: #fff ### .center[.font90[Electrifying the passenger vehicle fleet is a critical climate goal]] <center> <img src="images/ghg_emissions.png" width=850> </center> --- # .center[Two Studies, One Dataset] .leftcol[ ### Measuring Electric Vehicle<br>**Mileage** in the United States Lujin Zhao (Ph.D. Student)<br> Eliese Ottinger (Undergraduate RA)<br> **Status**: Paper submitted for review soon ] .rightcol[ ### Measuring Electric Vehicle<br>**Resale Value** in the United States Laura Roberson (Ph.D. Student)<br><br> **Status**: Exploratory phase ] --- background-color: #fff ### .center[**Data**: ~13M used vehicle listings from 60k dealerships (2016 - 2022)] <center> <img src="images/table-data-summary.png" width=850> </center> --- class: middle, inverse ## Going the Distance:<br>Quantifying Electric Vehicle Mileage in the United States Lujin Zhao (Ph.D. Student)<br> Eliese Ottinger (Undergraduate RA)<br> John Paul Helveston, Ph.D. The George Washington University --- # .center[We really need to understand PEV usage] <br> -- ### - PEV emissions reduction benefit **depends on vehicle usage**<br>.font80[[Jenn (2020)](https://www.nature.com/articles/s41560-020-0632-7)] -- ### - Modelers typically assume **BEV miles = CV miles** -- ### - Revenue from proposed mileage tax **depends on vehicle usage**<br>.font80[[Metcalf et al. (2022)](https://doi.org/10.1086/722672); [Zhao and Mattauch (2022)](https://doi.org/10.1016/j.jeem.2022.102747); [Davis and Sallee (2020)](https://doi.org/10.1086/706793)] -- ### - PEV adoption depends on **how well PEVs substitute for CVs**<br>.font80[[Xing et al. (2021)](https://doi.org/10.1016/j.jeem.2021.102432)] --- background-image: url("images/table-lit1.png") background-size: cover ### .center[Conflicting prior results on BEV mileage] --- background-image: url("images/table-lit2.png") background-size: cover ### .center[.blue[Conflicting prior results on BEV mileage]] --- background-image: url("images/table-lit3.png") background-size: cover ### .center[.red[Inconsistent data quality in prior studies]] --- class: center background-color: #fff ## BEVs are driven significantly less than other powertrains <center> <img src="images/mileage-all.png" width=100%> </center> --- background-color: #fff class: center ### Teslas driven more than non-Tesla BEVs (but not as much as CVs) <center> <img src="images/mileage-bev.png" width=800> </center> --- class: center background-color: #fff ## BEVs are driven significantly less than other powertrains <center> <img src="images/mileage-all.png" width=100%> </center> `\(mileage = \beta_0 + \beta_1age+\beta_2{age*powertrain}+\beta_3{age}*cents\_p\_mile+\epsilon_i\)` --- background-color: #fff .leftcol80[ <center> <img src="images/table-reg-pooled.png" width=100%> </center> ] --- background-color: #fff .leftcol80[ <center> <img src="images/table-reg-pooled1.png" width=100%> </center> ] .rightcol20[ ### .red[BEVs driven 4,500 miles less than CVs on average] ] --- background-color: #fff .leftcol80[ <center> <img src="images/table-reg-pooled2.png" width=100%> </center> ] .rightcol20[ ### BEVs driven 4,500 miles less than CVs on average ### .red[Non-Tesla BEVs:<br>-5,400 miles] ### .blue[Tesla:<br>-2,800 miles] ] --- background-color: #fff <center> Cars <img src="images/mileage-scatter-cars.png" width=100%> </center> <br> <center> SUVs <img src="images/mileage-scatter-suvs.png" width=100%> </center> ??? BEVs:<br>~7k mi/yr All others:<br>~11k - 12k mi/yr Far less variability in BEV mileage than CV mileage --- background-color: #fff .leftcol65[ <center> <img src="images/table-reg-powertrain-zoom.png" width=100%> </center> ] --- background-color: #fff .leftcol65[ <center> <img src="images/table-reg-powertrain-zoom1.png" width=100%> </center> ] .rightcol35[ **Non-linear range effect**: +10 mi range: .red[Low range (<100 mi):<br>+640 mi/yr] .red[Mid range (100-200 mi):<br>+420 mi/yr] .red[High range (\>200 mi):<br>+90 mi/yr] ] --- background-color: #fff .leftcol65[ <center> <img src="images/table-reg-powertrain-zoom2.png" width=100%> </center> ] .rightcol35[ **Non-linear range effect**: +10 mi range: .red[Low range (<100 mi):<br>+640 mi/yr] .red[Mid range (100-200 mi):<br>+420 mi/yr] .red[High range (\>200 mi):<br>+90 mi/yr] <br> .blue[Tesla effect isn't just from range] ] --- background-color: #fff ### .center[BEV mileage less sensitive to operating cost than CV mileage] <center> <img src="images/table-reg-powertrain-cpm.png" width=1000> </center> 1 cent increase in operating cost: BEV: -69 mi/yr<br> CV: -136 mi/yr<br> --- background-color: #fff ### .center[BEV mileage less sensitive to operating cost than CV mileage] <center> <img src="images/table-reg-powertrain-cpm.png" width=1000> </center> .leftcol70[ <center> <img src="images/cost-per-mile.png" width=600> </center> ] .rightcol30[ 1 cent increase in operating cost: BEV: -69 mi/yr<br> CV: -136 mi/yr<br> .blue[BEVs have much lower operating costs] ] --- name: why-vmt class: center, middle, inverse # Why low BEV mileage? --- # Why low BEV mileage? .leftcol40[ ### **Intra-household substitution?** Maybe current adopters have multiple cars? Perhaps, but NHTS data suggests **secondary cars are only driven 1,000 - 2,000 miles less per year**. ] .rightcol60[ <center> <img src="images/table-nhts.png" width=100%> </center> ] --- # Why low BEV mileage? .leftcol40[ ### **Maybe newer models are driven more?** Some (limited) evidence this may be the case (MY 2019: only 10,484 listings, max age of 3.2 years old) ] .rightcol60[ <center> <img src="images/table-my-zoom.png" width=100%> </center> ] --- # Why low BEV mileage? .leftcol40[ ### **Selection bias?** Maybe current adopters just have lower driving needs? No way for us to measure this, but it seems very plausible ] .rightcol60[ <center> <img src="images/plane.jpg" width=100%> </center> ] --- ## Key takeaways -- ### - BEVs are driven significantly less than other powertrains:<br>.red[Non-Tesla BEVs: -5,400 miles]; .blue[Tesla: -2,800 miles] -- ### - Far less variability in BEV mileage than CV mileage<br>(BEVs only substituting for lower-mileage CV usage) -- ### - BEV mileage less sensitive to operating cost than CV mileage -- ### - Can't say **why** low BEV mileage, but still relevant for policy --- class: middle, inverse ### Battery-Powered Bargains?<br>Measuring Electric Vehicle Resale Value in the United States Laura Roberson (Ph.D. Student)<br> John Paul Helveston, Ph.D. --- background-color: #fff class: center ## The vehicle resale market is critically important -- .leftcol[ ## 70% of sales are<br>used vehicles <center> <img src="images/resale-sales.png" width=100%> </center> ] -- .rightcol[ ## Used vehicles are more affordable (pre-covid) <center> <img src="images/resale-prices.png" width=100%> </center> ] --- # .center[We really need to understand PEV resale value] -- <br> ### - Depreciation is a key component in "Total Cost of Ownership" (TCO) models, e.g. [ANL's TCO Study](https://publications.anl.gov/anlpubs/2021/05/167399.pdf) -- ### - "Resale anxiety" a potential obstacle to electric vehicle adoption [Brückmann et al. (2021)](https://doi.org/10.1088/1748-9326/ac3531) -- ### - BEV buyers nervous about depreciation tend to lease rather than buy [Dua et al. (2019)](https://www.sciencedirect.com/science/article/pii/S235248471930068X) --- ## .center[Questions we hope to answer with this study] <br> -- ### Are PEVs depreciating faster than CVs? -- ### Which PEV features matter for retaining value? -- ### Is this changing over time? -- ### What is the impact of **new** car subsidies on pricing in the **used** market? --- class: center ### We think PEV subsidies for new cars should impact used car pricing -- .leftcol[ ### New Market <center> <img src="images/nissan-leaf.png" width=80%> </center> (MSRP - Subsidy = Price)<br> $30,000 - $7,500 = **$22,500**<br> .font70[.left[Image source: https://www.pngwing.com/en/free-png-yaftj]] ] -- .rightcol[ ### Used Market <center> <img src="images/nissan-leaf.png" width=80%> </center> (Assuming adequate supply)<br> Max Price = **$22,500**<br> Max RR = **75%** ] --- class: center background-color: #fff ## BEVs & PHEVs are depreciating worse than CVs and HEVs ## (Except Tesla) <center> <img src="images/rr-all.png" width=100%> </center> Data: All listings between 2016 - 2019 (inclusive) --- class: middle, center background-color: #fff ## How you compute retention rate (RR) matters .leftcol[ ### `\(\frac{Price}{MSRP}\)` <center> <img src="images/rr-bev.png" width=95%> </center> ] -- .rightcol[ ### `\(\frac{Price}{MSRP - Subsidy}\)` <center> <img src="images/arr-bev.png" width=95%> </center> ] --- class: center # Modeling retention rate as exponential decay # `$$r = \alpha \exp ( \boldsymbol\beta \mathrm{\mathbf{x}} )$$` # $$\log(r) = \alpha + \boldsymbol\beta \mathrm{\mathbf{x}} $$ -- # Interpretation: `$$\Delta r= \exp (\hat{\beta}) - 1$$` --- background-color: #fff <center> <img src="images/table-rr-slope.png" width=100%> </center> --- background-color: #fff <center> <img src="images/rr-models-zoom.png" width=100%> </center> --- background-color: #fff class: center ## Newer PEVs are holding value better than older PEVs <br> <center> <img src="images/tyo-all.png" width=100%> </center> --- background-color: #fff class: center ## Newer PEVs are holding value better than older PEVs <br> <center> <img src="images/tyo-select-models.png" width=100%> </center> --- background-color: #fff class: center .leftcol80[ <center> <img src="images/rr-range.png" width=100%> </center> ] .rightcol20[ #### Longer-range BEVs hold value better Slopes are predictions after controlling for model years ] --- background-color: #fff class: center .leftcol80[ <center> <img src="images/covid-2019.png" width=100%> </center> ] .rightcol20[ #### Mean used PEV price still lower than CVs post-COVID Inflation-adjusted constant 2019 dollars ] --- background-color: #fff class: center .leftcol80[ <center> <img src="images/covid-real.png" width=100%> </center> ] .rightcol20[ #### Mean used PEV price still lower than CVs post-COVID Unadjusted real dollars ] --- ## .center[Questions we hope to answer with this study] <br> -- ### Are PEVs depreciating faster than CVs? .red[Yes!] -- ### Which PEV features matter for retaining value? .red[Range & Model Year!] -- ### Is this changing over time? .red[Yes! Newer better than older!] -- ### What is the impact of **new** car subsidies on pricing in the **used** market? .red[A little pass through! (3%)] --- class: inverse background-image: url("images/blue.jpg") background-size: cover <br><br><br><br><br><br><br><br><br><br> # Thanks! ### Slides: ### https://slides.jhelvy.com/2023-rit-visit/ .footer-large[.white[.right[ @jhelvy@fediscience.org
<br> @JohnHelveston
<br> @jhelvy
<br> jhelvy.com
<br> jph@gwu.edu
]]]