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$)')