Annual model-level sales of cars in European countries between 1970 and 1999.
data('eurocars')
A data.frame with 11,549 observations on 39 variables:
year: Year of the observation
market_id: Numeric identifier for geographical market
model_id: Numeric identifier for the car
model_id2: Numeric identifier for the car with unified products when model number changes
type: Car Type
brand: Brand of Manufacturer
model: Car Model
origin_id: Numeric identifier for country of origin
location_id: Numeric identifier for location
class_id: Numeric vehicle class identifier
domestic: == 1 if produced domestically
firm_id: Numeric identifier for firm that produced vehicle
qty_sold: Quantity of cars sold
displacement: Engine capacity in cc
kilowatts: Engine Power in kilowatts
weight: Vehicle weight in kilograms
n_seats: Number of seats
n_doors: Number of doors
length: Vehicle length in cm
height: Vehicle height in cm
fueleff_90: Fuel Efficiency at 90 km/hr
fueleff_90: Fuel Efficiency at 120 km/hr
fueleff_city: Fuel Efficiency when driving in city
fueleff_avg: Average Fuel Efficiency
max_speed: Maximum speed in km/hr
accel: Time taken in seconds from 0 to 100 km/hr
price: Price in local currency
price_euro: Price in Euros
exchrate_exp: Exchange rate in exporting country
exchrate_imp: Exchange rate in importing country
cpi_exp: Consumer Price Index in exporting country
ppi_exp: Producer Price Index in exporting country
cpi_imp: Consumer Price Index in importing country
ppi_imp: Producer Price Index in importing country
tax: Tax rate on purchase
population: Country of sale's population
ngdp: Nominal GDP in country of sale
rgdp: Real GDP in country of sale
Data Source: Brenkers and Verboven, 2006, "Liberalizing a Distribution System: The European Car Market", Journal of the European Economic Association
str(eurocars)#> Classes ‘tbl_df’, ‘tbl’ and 'data.frame': 11549 obs. of 39 variables: #> $ year : num 83 84 85 86 87 88 89 90 91 92 ... #> $ market_id : num 1 1 1 1 1 1 1 1 1 1 ... #> $ model_id : num 1 1 1 1 1 1 1 1 1 1 ... #> $ model_id2 : num 5 5 5 5 5 5 5 5 5 5 ... #> $ type : chr "alfa 33" "alfa 33" "alfa 33" "alfa 33" ... #> $ brand : chr "alfa romeo" "alfa romeo" "alfa romeo" "alfa romeo" ... #> $ model : chr "33" "33" "33" "33" ... #> $ origin_id : num 3 3 3 3 3 3 3 3 3 3 ... #> $ location_id : num 5 5 5 5 5 5 5 5 5 5 ... #> $ class_id : num 2 2 2 2 2 2 2 2 2 2 ... #> $ domestic : num 0 0 0 0 0 0 0 0 0 0 ... #> $ firm_id : num 1 1 1 1 4 4 4 4 4 4 ... #> $ qty_sold : num 729 1860 1771 2047 2147 ... #> $ displacement: num 1351 1351 1351 1351 1351 ... #> $ kilowatts : num 58 58 58 58 58 58 63 63 65 66 ... #> $ weight : num 890 890 890 890 910 910 910 940 940 940 ... #> $ n_seats : num 5 5 5 5 5 5 5 5 5 5 ... #> $ n_doors : num 5 5 5 5 5 5 5 5 5 5 ... #> $ length : num 402 402 402 402 402 ... #> $ width : num 161 161 161 161 161 ... #> $ height : num 130 130 130 134 134 ... #> $ fueleff_90 : num 5.8 5.8 5.8 5.8 5.8 ... #> $ fueleff_120 : num 7.9 7.9 7.9 7.9 8 ... #> $ fueleff_city: num 9.6 9.6 9.6 9.6 10 ... #> $ fueleff_avg : num 7.77 7.77 7.77 7.77 7.93 ... #> $ max_speed : num 165 165 165 167 167 167 172 176 176 178 ... #> $ accel : num NA 11.5 11.5 11.5 11.5 ... #> $ price : num 336250 348750 361000 339900 349900 ... #> $ price_euro : num 6078 5859 6126 6559 7272 ... #> $ exchrate_exp: num 1649 1818 1916 1733 1676 ... #> $ exchrate_imp: num 55.3 59.5 58.9 51.8 48.1 ... #> $ cpi_exp : num 62.7 69.5 75.9 80.3 84.1 ... #> $ ppi_exp : num 71.5 78.8 84.9 85 87.6 ... #> $ cpi_imp : num 80.8 85.9 90.1 91.3 92.7 ... #> $ ppi_imp : num 100.4 108 110.8 98.1 93.3 ... #> $ tax : num 0.25 0.25 0.25 0.25 0.25 ... #> $ population : num 9860000 9860000 9860000 9860000 9870000 ... #> $ ngdp : num 4.19e+12 4.51e+12 4.83e+12 5.08e+12 5.32e+12 ... #> $ rgdp : num 5.45e+12 5.59e+12 5.64e+12 5.73e+12 5.86e+12 ...