R/fringe.R

In JustinMShea/wooldridge: 115 Data Sets from "Introductory Econometrics: A Modern Approach, 7e" by Jeffrey M. Wooldridge

#' fringe
#'
#' Wooldridge Source: F. Vella (1993), “A Simple Estimator for Simultaneous Models with Censored Endogenous Regressors,” International Economic Review 34, 441-457. Professor Vella kindly provided the data. Data loads lazily.
#'
#' @section Notes: Currently, this data set is used in only one Computer Exercise – to illustrate the Tobit model. It can be used much earlier. First, one could just ignore the pileup at zero and use a linear model where any of the hourly benefit measures is the dependent variable. Another possibility is to use this data set for a problem set in Chapter 4, after students have read Example 4.10. That example, which uses teacher salary/benefit data at the school level, finds the expected tradeoff, although it appears to less than one-to-one. By contrast, if you do a similar analysis with FRINGE.RAW, you will not find a tradeoff. A positive coefficient on the benefit/salary ratio is not too surprising because we probably cannot control for enough factors, especially when looking across different occupations. The Michigan school-level data is more aggregated than one would like, but it does restrict attention to a more homogeneous group: high school teachers in Michigan.
#'
#' Used in Text: page 624-625
#'
#' @docType data
#'
#' @usage data('fringe')
#'
#' @format A data.frame with 616 observations on 39 variables:
#' \itemize{
#'  \item \strong{annearn:} annual earnings, $
#'  \item \strong{hrearn:} hourly earnings, $
#'  \item \strong{exper:} years work experience
#'  \item \strong{age:} age in years
#'  \item \strong{depends:} number of dependents
#'  \item \strong{married:} =1 if married
#'  \item \strong{tenure:} years with current employer
#'  \item \strong{educ:} years schooling
#'  \item \strong{nrtheast:} =1 if live in northeast
#'  \item \strong{nrthcen:} =1 if live in north central
#'  \item \strong{south:} =1 if live in south
#'  \item \strong{male:} =1 if male
#'  \item \strong{white:} =1 if white
#'  \item \strong{union:} =1 if union member
#'  \item \strong{office:} 
#'  \item \strong{annhrs:} annual hours worked
#'  \item \strong{ind1:} industry dummy
#'  \item \strong{ind2:} 
#'  \item \strong{ind3:} 
#'  \item \strong{ind4:} 
#'  \item \strong{ind5:} 
#'  \item \strong{ind6:} 
#'  \item \strong{ind7:} 
#'  \item \strong{ind8:} 
#'  \item \strong{ind9:} 
#'  \item \strong{vacdays:} $ value of vac. days
#'  \item \strong{sicklve:} $ value of sick leave
#'  \item \strong{insur:} $ value of employee insur
#'  \item \strong{pension:} $ value of employee pension
#'  \item \strong{annbens:} vacdays+sicklve+insur+pension
#'  \item \strong{hrbens:} hourly benefits, $
#'  \item \strong{annhrssq:} annhrs^2
#'  \item \strong{beratio:} annbens/annearn
#'  \item \strong{lannhrs:} log(annhrs)
#'  \item \strong{tenuresq:} tenure^2
#'  \item \strong{expersq:} exper^2
#'  \item \strong{lannearn:} log(annearn)
#'  \item \strong{peratio:} pension/annearn
#'  \item \strong{vserat:} (vacdays+sicklve)/annearn
#' }
#' @source \url{https://www.cengage.com/cgi-wadsworth/course_products_wp.pl?fid=M20b&product_isbn_issn=9781111531041}
#' @examples  str(fringe)
"fringe"