Automotive: Automotive industry data
In REAT: Regional Economic Analysis Toolbox
Description
Usage
Format
Source
References
Examples
Description
Top 20 automotive industry companies, including their manufacturing quantity and turnovers (Table from wikipedia)
Usage
1
data("Automotive")
Format
A data frame with 20 observations on the following 8 variables.
RankRank of the company
CompanyName of the company (German)
CountryOrigin county of the company (German)
Quantity2014Quantity of produced vehicles in 2014
Quantity2014_carQuantity of produced cars in 2014
Turnover2008Annual turnover 2008 (in billion dollars)
Turnover2012Annual turnover 2012 (in billion dollars)
Turnover2013Annual turnover 2013 (in billion dollars)
Source
Wikipedia (2018): “Automobilindustrie — Wikipedia, Die freie Enzyklopaedie”. https://de.wikipedia.org/wiki/Automobilindustrie (accessed October 14, 2018). Own postprocessing.
References
Wikipedia (2018): “Automobilindustrie — Wikipedia, Die freie Enzyklopaedie”. https://de.wikipedia.org/wiki/Automobilindustrie (accessed October 14, 2018).
Examples
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# Market concentration in automotive industry
data(Automotive)
gini(Automotive$Turnover2008, lsize=1, lc=TRUE, le.col = "black",
lc.col = "orange", lcx = "Shares of companies", lcy = "Shares of turnover / cars",
lctitle = "Automotive industry: market concentration",
lcg = TRUE, lcgn = TRUE, lcg.caption = "Turnover 2008:", lcg.lab.x = 0, lcg.lab.y = 1)
# Gini coefficient and Lorenz curve for turnover 2008
gini(Automotive$Turnover2013, lsize=1, lc = TRUE, add.lc = TRUE, lc.col = "red",
lcg = TRUE, lcgn = TRUE, lcg.caption = "Turnover 2013:", lcg.lab.x = 0, lcg.lab.y = 0.85)
# Adding Gini coefficient and Lorenz curve for turnover 2013
gini(Automotive$Quantity2014_car, lsize=1, lc = TRUE, add.lc = TRUE, lc.col = "blue",
lcg = TRUE, lcgn = TRUE, lcg.caption = "Cars 2014:", lcg.lab.x = 0, lcg.lab.y = 0.7)
# Adding Gini coefficient and Lorenz curve for cars 2014
Example output
[1] 0.3202108
[1] 0.3736389
[1] 0.4351418
REAT documentation built on Sept. 5, 2021, 5:18 p.m.
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Description Usage Format Source References Examples
Description
Top 20 automotive industry companies, including their manufacturing quantity and turnovers (Table from wikipedia)
Usage
1 | data("Automotive")
|
Format
A data frame with 20 observations on the following 8 variables.
RankRank of the company
CompanyName of the company (German)
CountryOrigin county of the company (German)
Quantity2014Quantity of produced vehicles in 2014
Quantity2014_carQuantity of produced cars in 2014
Turnover2008Annual turnover 2008 (in billion dollars)
Turnover2012Annual turnover 2012 (in billion dollars)
Turnover2013Annual turnover 2013 (in billion dollars)
Source
Wikipedia (2018): “Automobilindustrie — Wikipedia, Die freie Enzyklopaedie”. https://de.wikipedia.org/wiki/Automobilindustrie (accessed October 14, 2018). Own postprocessing.
References
Wikipedia (2018): “Automobilindustrie — Wikipedia, Die freie Enzyklopaedie”. https://de.wikipedia.org/wiki/Automobilindustrie (accessed October 14, 2018).
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | # Market concentration in automotive industry
data(Automotive)
gini(Automotive$Turnover2008, lsize=1, lc=TRUE, le.col = "black",
lc.col = "orange", lcx = "Shares of companies", lcy = "Shares of turnover / cars",
lctitle = "Automotive industry: market concentration",
lcg = TRUE, lcgn = TRUE, lcg.caption = "Turnover 2008:", lcg.lab.x = 0, lcg.lab.y = 1)
# Gini coefficient and Lorenz curve for turnover 2008
gini(Automotive$Turnover2013, lsize=1, lc = TRUE, add.lc = TRUE, lc.col = "red",
lcg = TRUE, lcgn = TRUE, lcg.caption = "Turnover 2013:", lcg.lab.x = 0, lcg.lab.y = 0.85)
# Adding Gini coefficient and Lorenz curve for turnover 2013
gini(Automotive$Quantity2014_car, lsize=1, lc = TRUE, add.lc = TRUE, lc.col = "blue",
lcg = TRUE, lcgn = TRUE, lcg.caption = "Cars 2014:", lcg.lab.x = 0, lcg.lab.y = 0.7)
# Adding Gini coefficient and Lorenz curve for cars 2014
|
Example output
[1] 0.3202108
[1] 0.3736389
[1] 0.4351418
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