USnewspapers {Ecdat} | R Documentation |
US newspaper revenue 1956 - 2020
Description
Advertising and circulation revenue for US newspapers since 1956 with GDP in billions of current dollars (i.e., not adjusted for inflation) plus ads as a proportion of revenue and revenue as a proportion of US Gross Domestic Product (GDP).
Usage
data("USnewspapers")
Format
A data frame with 65 observations on the following 14 variables.
- Year
-
an integer vector giving the year
c(1956:2020)
. - Ads_currentGdollars, Ads_G2012dollars, Circ_currentGdollars, Circ_G2012dollars, Revenue_currentGdollars, Revenue_G2012dollars
-
Total newspaper revenue from advertising, circulation, and combined in billions of US dollars, both current and adjusted for inflation to 2012 dollars. The data were compiled from detailed reports until 2012 and estimated since.
- AdsProportion
-
Advertising as a proportion of total revenue.
- GDP_nominalG, GDP_G2012
-
US GDP in billions of dollars, both current and adjusted for inflation to constant 2012 dollars.
- newspaperAds_p_GDP
-
Newspaper advertising revenue as a percent of GDP.
- newspapers_p_GDP
-
Newspaper revenue as a proportion of GDP.
- Population_M
-
US population in millions
- RevenuePerCap_nominal
-
Newspaper revenue per person in current dollars.
- RevenuePerCap_2012
-
Newspaper revenue per person in constant 2012 dollars.
Details
Data used by McChesney and Nichols (2021-12-13) To Protect and Extend Democracy, Recreate Local News Media (Freepress.net, p. 6, note 10) to estimate that newspaper subsidies averaged roughly 0.216 percent of GDP between 1840 and 1844.
Source
Newspaper data from "Newspapers fact sheet" published by the Pew Research Center, accessed 2021-12-18.
GDP data from Measuring Worth, accessed 2021-12-18.
References
McChesney and Nichols (2021-12-13) To Protect and Extend Democracy, Recreate Local News Media (Freepress.net, p. 6, note 10), accessed 2021-12-18.
Newspaper data from "Newspaper fact sheet" published by the Pew Research Center.
GDP data from Measuring Worth.
Examples
data(USnewspapers)
plotNewsRevenue <- function(ys=c(2, 4, 6)){
ylim. <- range(USnewspapers[ys], na.rm=TRUE)
xlim. <- range(USnewspapers$Year)
to2013 <- (USnewspapers$Year<2013)
matplot(USnewspapers$Year[to2013],
USnewspapers[to2013, ys], type='l',
log='y', xlim=xlim., ylim=ylim., las=1,
xlab='', ylab='')
matlines(USnewspapers$Year[!to2013], col=4:6,
USnewspapers[!to2013, ys])
lnms <- outer(names(USnewspapers[c(2, 4, 6)]),
c('', '-est'), paste0)
legend('bottom', lnms, col=1:6, lty=1:6,
cex=0.5)
}
plotNewsRevenue()
plotNewsRevenue(c(3, 5, 7))
plot(100*newspapers_p_GDP~Year, USnewspapers, type='l',
las=1, xlab='', ylab='newspapers percent of GDP')
plot(RevenuePerCap_nominal~Year, USnewspapers, type='l',
las=1, xlab='', ylab='Revenue per capita (nominal)')
plot(RevenuePerCap_2012~Year, USnewspapers, type='l',
las=1, xlab='', ylab='Revenue per capita (2012$)')