On this R-data statistics page, you will find information about the LifeCycleSavings data set which pertains to Intercountry Life-Cycle Savings Data. The LifeCycleSavings data set is found in the datasets R package. You can load the LifeCycleSavings data set in R by issuing the following command at the console data("LifeCycleSavings"). This will load the data into a variable called LifeCycleSavings. If R says the LifeCycleSavings data set is not found, you can try installing the package by issuing this command install.packages("datasets") 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 LifeCycleSavings R data set. The size of this file is about 1,881 bytes.

Intercountry Life-Cycle Savings Data

Description

Data on the savings ratio 1960–1970.

Usage

LifeCycleSavings

Format

A data frame with 50 observations on 5 variables.

R project statistics dataset table

[,1]	sr	numeric	aggregate personal savings
[,2]	pop15	numeric	% of population under 15
[,3]	pop75	numeric	% of population over 75
[,4]	dpi	numeric	real per-capita disposable income
[,5]	ddpi	numeric	% growth rate of dpi

Details

Under the life-cycle savings hypothesis as developed by Franco Modigliani, the savings ratio (aggregate personal saving divided by disposable income) is explained by per-capita disposable income, the percentage rate of change in per-capita disposable income, and two demographic variables: the percentage of population less than 15 years old and the percentage of the population over 75 years old. The data are averaged over the decade 1960–1970 to remove the business cycle or other short-term fluctuations.

Source

The data were obtained from Belsley, Kuh and Welsch (1980). They in turn obtained the data from Sterling (1977).

References

Sterling, Arnie (1977) Unpublished BS Thesis. Massachusetts Institute of Technology.

Belsley, D. A., Kuh. E. and Welsch, R. E. (1980) Regression Diagnostics. New York: Wiley.

Examples

require(stats); require(graphics)
pairs(LifeCycleSavings, panel = panel.smooth,
      main = "LifeCycleSavings data")
fm1 <- lm(sr ~ pop15 + pop75 + dpi + ddpi, data = LifeCycleSavings)
summary(fm1)

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