Skip to contents

An R data package containing tidy formatted summary data on vehicle trends in the United States. The primary data source is vehicle listings from marketcheck.com, which have been processed into summary statistics including depreciation curves, mileage accumulation, market concentration, and share of listings breakdowns.

For a live dashboard of the data, visit vehicletrends.us.

Installation

You can install vehicletrends from GitHub:

# install.packages("remotes")
remotes::install_github("vehicletrends/vehicletrends")

Usage

Once loaded, all datasets are available directly by name. See the datasets article for detailed data dictionaries.

Datasets

Dataset Description
vmt_age Cumulative odometer mileage quantiles by age, powertrain, and vehicle type
vmt_daily Daily vehicle miles traveled quantiles by powertrain and vehicle type
vmt_annual_type Estimated annual VMT by powertrain and vehicle type
vmt_annual_model Estimated annual VMT by make and model
depreciation Retention rate quantiles for used vehicles by age, powertrain, and vehicle type
dep_annual_type Estimated annual depreciation rate by powertrain and vehicle type
dep_annual_model Estimated annual depreciation rate by make and model
percent_listings Share of vehicle listings across powertrain, vehicle type, and price bin
percent_dealers Percentage of dealers with at least one listing by variable pairs
hhi_local_summary Local market HHI (measure of market concentration) summary statistics across all US census tracts (local market defined as dealers within 60 minute isocrhone)
p_local_summary Local market share of listings summary statistics across all US census tracts (local market defined as dealers within 60 minute isocrhone)
price_trends_new Average prices and listing counts for new vehicle inventory by state, year, and vehicle type
price_trends_used Average prices, listing counts, and depreciation rates for used vehicle inventory by state, year, and vehicle type
registrations Annual vehicle registration counts by US state and powertrain type (2016–2024)

Large Raw Data Files

The following large files are hosted on Cloudflare R2 and can be downloaded directly. The hhi_* and p_* parquet files are the census-tract-level source data used to compute the hhi_local_summary and p_local_summary package datasets. File name suffixes indicate the grouping variable (pb = price bin, pt = powertrain, vt = vehicle type) and isochrone radius (60 = 60-minute drive time).

File Description
hhi_pb_60.parquet HHI per census tract, grouped by price bin (60-min isochrone)
hhi_pt_60.parquet HHI per census tract, grouped by powertrain (60-min isochrone)
hhi_vt_60.parquet HHI per census tract, grouped by vehicle type (60-min isochrone)
p_pb_60.parquet Market share (p) per census tract, grouped by price bin (60-min isochrone)
p_pt_60.parquet Market share (p) per census tract, grouped by powertrain (60-min isochrone)
p_vt_60.parquet Market share (p) per census tract, grouped by vehicle type (60-min isochrone)
tracts.rds US census tract geometries (full resolution)
tracts_simplified.rds US census tract geometries (simplified for faster rendering)
hhi_tracts.pmtiles HHI per census tract as PMTiles for interactive map visualization

Citation information

If you use this package in a publication, please cite it! You can get the citation by typing citation("vehicletrends") into R:

citation('vehicletrends')
#> To cite vehicletrends in publications use:
#> 
#>   John Paul Helveston (2026). vehicletrends: Data on Vehicle Trends in
#>   the USA. R package version 0.0.3.
#>   https://github.com/vehicletrends/vehicletrends
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Manual{,
#>     title = {vehicletrends: Data on Vehicle Trends in the USA},
#>     author = {John Paul Helveston},
#>     year = {2026},
#>     note = {R package version 0.0.3},
#>     url = {https://github.com/vehicletrends/vehicletrends},
#>   }