My da|ra Login

Detailed view

metadata language: English

Unionization rates by Commuting Zone in the United States

Version
1
Resource Type
Dataset : administrative records data, survey data
Creator
  • Connolly, Marie (Université du Québec à Montréal)
Publication Date
2019-02-27
Free Keywords
unionization; qwi; Current Population Survey
Description
  • Abstract

    This is a computation of predicted unionization rates by 1990 Commuting Zones in the United States. The predictions are for the year 2000.

    Issue: union status is available in the Current Population Survey (Outgoing Rotation Groups), but the CPS does not have county identifiers for the whole population, which are necessary to assign the CZ a CPS respondent lives in. Moreover, even with access to restricted CPS data files, the CPS is meant to be representative at the state level, so estimates at the CZ level may not be accurate.

    Solution: use the CPS Merged Outgoing Rotation Groups (CPS MORG) from 2000 to estimate the probability of being unionized by state, sex, age group and 3-digit industry. Then, use the Quarterly Workforce Indicators (QWI) to get employment figures by county, sex, age group and 3-digit industry. Impute the estimated probability from the CPS MORG at the state, sex, age group and 3-digit industry. Assign each county to its CZ. Then compute weighted average of probability of being unionized by CZ, where employment counts are used as weights.
Temporal Coverage
  • 2000-01-01 / 2000-12-31
    Time Period: Sat Jan 01 00:00:00 EST 2000--Sun Dec 31 00:00:00 EST 2000 (2000)
Geographic Coverage
  • United States
Sampled Universe
Employed individuals in the United States from the private or government sector (excluding self-employed or without pay).
.
Availability
Download
This study is freely available to the general public via web download.

Update Metadata: 2020-10-18 | Issue Number: 1 | Registration Date: 2020-10-18

Connolly, Marie (2019): Unionization rates by Commuting Zone in the United States. Version: 1. ICPSR - Interuniversity Consortium for Political and Social Research. Dataset. https://doi.org/10.3886/E108625V1-46600