R Dataset / Package plm / LaborSupply

How To Create a Barplot

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How To Create a Stacked Barplot

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How To Create a Pie Chart

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How To Compute the Mean

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How To Create a Plot

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How to Compute the Median

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Boxplot

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Correlation Coefficient

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Cumulative Frequency Histogram

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Dotplot

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Hollow Histogram

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Numerical Summaries

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Pie Chart

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Plot

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Regression

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Visual Summaries

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Embed
<iframe src="https://embed.picostat.com/r-dataset-package-plm-laborsupply.html" frameBorder="0" width="100%" height="307px" />
Attachment Size
dataset-73932.csv 132.8 KB
Dataset License
GNU General Public License v2.0
Documentation License
GNU General Public License v2.0
Dataset Help

On this Picostat.com statistics page, you will find information about the LaborSupply data set which pertains to Wages and Hours Worked. The LaborSupply data set is found in the plm R package. You can load the LaborSupply data set in R by issuing the following command at the console data("LaborSupply"). This will load the data into a variable called LaborSupply. If R says the LaborSupply data set is not found, you can try installing the package by issuing this command install.packages("plm") 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 LaborSupply R data set. The size of this file is about 135,992 bytes.

Documentation

Wages and Hours Worked

Description

A panel of 532 observations from 1979 to 1988

number of observations : 5320

Usage

data(LaborSupply)

Format

A data frame containing :

lnhr

log of annual hours worked

lnwg

log of hourly wage

kids

number of children

age

age

disab

bad health

id

id

year

year

Source

Online complements to Ziliak (1997).

Journal of Business Economics and Statistics web site: http://amstat.tandfonline.com/loi/ubes20/.

References

Cameron, A.C. and P.K. Trivedi (2005) Microeconometrics : methods and applications, Cambridge, pp. 708–15, 754–6.

Ziliak, J.P. (1997) “Efficient Estimation With Panel Data when Instruments are Predetermined: An Empirical Comparison of Moment-Condition Estimators”, Journal of Business and Economic Statistics, 15(4), pp. 419–431.

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

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