Occupational Prestige Ratings

The ratings by job title and job field are provided below. Fields are aggregated groupings of related job titles. See the main page for an overview of this project. More complete description is provided in the following manuscript:

[— citation blinded for review —]

See here for a crosswalk of these ratings to older prestige ratings.

library(here) # for engaging with working environment
library(Hmisc) # for weighted means
library(DT) # for viewing data tables
library(tidyverse) # for data cleaning and manipulation
library(dataverse)
library(data.table)

# There are two options for loading the data
# The first option is to download the data manually
# It's on Dataverse at the doi link below
# https://doi.org/10.7910/DVN/G1E4BF
 
# Then load it from the local hard drive
# opratings = read.csv(here("data/opratings.csv"))

# The second option is to scrap the data file in directly
Sys.setenv("DATAVERSE_SERVER" = "dataverse.harvard.edu")
writeBin(get_file("OccupationalPrestigeRatings.tab", "doi:10.7910/DVN/G1E4BF"), "OccupationalPrestigeRatings.tab")
OccupationalPrestigeRatings.tab <- fread("OccupationalPrestigeRatings.tab", na.strings=getOption("<NA>","NA"))
opratings <- as.data.frame(OccupationalPrestigeRatings.tab)
rm(OccupationalPrestigeRatings.tab)

colnames(opratings) <- gsub(".", " ", colnames(opratings), fixed=TRUE)

opratings_db = opratings[,c("OPR Job Title", "OPR Job Rating", "OPR Field Title", "OPR Field Rating", "ONET SOC 2018 Code", "ONET SOC 2018 Title")] %>%
  DT::datatable( # put into interactive HTML table
    colnames = c("OPR Job Title", "OPR Job Rating", "Job Field Title", "Avg Field Rating", "ONET-SOC Code*", "ONET-SOC Title*"), #colnames
    options = list(
      lengthMenu = list(c(10, 50, -1), c('10', '50', 'All')),
        pageLength = 10
    ),
    filter = "top", # can filter
    rownames = F # don't need rownames
  )
opratings_db

* Note that the ONET-SOC Codes and ONET-SOC Titles shown here are based on the values from 2018. These codes and labels are updated periodically. The raw data file also contains the codes and labels from 2010.

Click here to download this database.