earns

Data loads lazily. Type data(earns) into the console.

datasets

Economics students new to both econometrics and R may find the
simultaneous introduction to both challenging. In particular, the process of
loading and preparing data before building one's first model can present
challenges. The `wooldridge` data package aims to lighten the task by loading
any data set from the text into the current working environment with a single command.
The package contains documentation for each set and all data has been
compressed to 62.73% of its original size. Just install the package, load it,
and use the `data()` function to call the data set you need to work with.
In addition, a wooldridge-vignette illustrates solutions to examples from
each chapter of the text, offering a relevant introduction to econometric
modelling with R. The vignette also includes an Appendix to helpful resources
about using R for econometrics. Note: Data sets are from the 5th edition
(Wooldridge 2013, ISBN-13:978-1-111-53104-1), and are compatible with others.

Justin Shea

wooldridge

105 Data Sets from "Introductory Econometrics: A Modern
Approach" by Jeffrey M. Wooldridge

earns function

A data.frame with 41 rows and 14 variables:<ul>
<li>year. 1947 to 1987</li>
<li>wkearns. avg. real weekly earnings</li>
<li>wkhours. avg. weekly hours</li>
<li>outphr. output per labor hour</li>
<li>hrwage. wkearns/wkhours</li>
<li>lhrwage. log(hrwage)</li>
<li>loutphr. log(outphr)</li>
<li>t. time trend: t=1 to 47</li>
<li>ghrwage. lhrwage - lhrwage[_n-1]</li>
<li>goutphr. loutphr - loutphr[_n-1]</li>
<li>ghrwge_1. ghrwage[_n-1]</li>
<li>goutph_1. goutphr[_n-1]</li>
<li>goutph_2. goutphr[_n-2]</li>
<li>lwkhours. log(wkhours)</li>
</ul>

earns: earns

Description

Usage

Arguments

Format

Examples