On this Picostat.com statistics page, you will find information about the USFinanceIndustry data set which pertains to US Finance Industry Profits. The USFinanceIndustry data set is found in the Ecdat R package. You can load the USFinanceIndustry data set in R by issuing the following command at the console data("USFinanceIndustry"). This will load the data into a variable called USFinanceIndustry. If R says the USFinanceIndustry data set is not found, you can try installing the package by issuing this command install.packages("Ecdat") and then attempt to reload the data. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the USFinanceIndustry R data set. The size of this file is about 4,073 bytes.

US Finance Industry Profits

Description

A data.frame giving the profits of the finance industry in the United States as a proportion of total corporate domestic profits.

Usage

data(USFinanceIndustry)

Format

A data.frame with the following columns:

year

integer year starting with 1929

CorporateProfitsAdj

Corporate profits with inventory valuation and capital consumption adjustments in billions of current (not adjusted for inflation) US dollars

Domestic

Domestic industries profits in billions

Financial

Financial industries profits in billions

Nonfinancial

Nonfinancial industries profits in billions

restOfWorld

Profits of the "Rest of the world" in their contribution to US Gross Domestic Product in billions

FinanceProportion

= Financial/Domestic

Details

This is extracted from Table 6.16 of the National Income and Product Accounts (NIPA) compiled by the Bureau of Economic Analysis of the United States federal government. This table comes in four parts, A (1929-1947), B (1948-1987), C (1987-2000), and D (1998-present). Parts A, B, C and D contain different numbers of data elements, but the first five have the same names and are the only ones used here. The overlap between parts C and D (1998-2000) have a root mean square relative difference of 0.7 percent; there were no differences between the numbers in the overlap period between parts B and C (1987).

This was created using the following command:

demoDir <- system.file('demoFiles', package='Ecdat') demoCsv <- dir(demoDir, pattern='csv$', full.names=TRUE)

nipa6.16 <- readNIPA(demoCsv) USFinanceIndustry <- as.data.frame(nipa6.16) names(USFinanceIndustry) <- c('year', 'CorporateProfitsAdj', 'Domestic', 'Financial', 'Nonfinancial', 'restOfWorld') USFinanceIndustry$FinanceProportion <- with(USFinanceIndustry, Financial/Domestic)

Source

http://www.bea.gov: Under "U.S. Economic Accounts", first select "Corporate Profits" under "National". Then next to "Interactive Tables", select, "National Income and Product Accounts Tables". From there, select "Begin using the data...". Under "Section 6 - income and employment by industry", select each of the tables starting "Table 6.16". As of February 2013, there were 4 such tables available: Table 6.16A, 6.16B, 6.16C and 6.16D. Each of the last three are available in annual and quarterly summaries. The USFinanceIndustry data combined the first 4 rows of the 4 annual summary tables.

See Also

readNIPA

Examples

data(USFinanceIndustry)
plot(FinanceProportion~year, USFinanceIndustry, type='b',
     ylim=c(0, max(FinanceProportion, na.rm=TRUE)),
     xlab='', ylab='', las=1, cex.axis=2, bty='n', lwd=2,
     col='blue')# Write to a file for Wikimedia Commons
svg('USFinanceIndustry.svg')
plot(FinanceProportion~year, USFinanceIndustry, type='b',
     ylim=c(0, max(FinanceProportion, na.rm=TRUE)),
     xlab='', ylab='', las=1, cex.axis=2, bty='n', lwd=2,
     col='blue')
dev.off()

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Dataset imported from https://www.r-project.org.