1. Workplace and Employee Survey
Marie Drolet
WES Research Manager
Business and Labour Market Analysis Division
Statistics Canada

2. Outline of today’s presentation
General survey overview
Why a linked survey?
Survey content
Potential research questions
Collection
Methodology
Data Access
Comparative Research:
Can the workplace explain gender pay differentials?

3. Goals of WES To develop an ongoing survey that will
link workers and workplaces at the micro level
provide information from both the demand and supply sides of the labour market
==> enriching research studies
provide longitudinal information allowing researchers to control for both individual and workplace effects that are not possible in other data sets
improve survey infrastructure

4. Survey Content Employee outcomes: Hours polarization; Wages;
Training received;
Workplace characteristics:
Technology implemented;
Operating revenues, expenditures, payroll,
Employment; hiring, vacancies
Business strategies;
Work organization
Compensation schemes;
Training provided;
Occupation mix
Organizational change;
Subjective measures of productivity, profitability
Type of competition
Worker/job characteristics;
Education;
Age/gender;
Occupation, management responsibilities;
Work history, tenure;
Family characteristics;
Unionization;
Use of technology;
Participation in decision making;
Wages and fringe benefits;
Work schedule/arrangements;
Training taken
Workplace outcomes;
Employment, revenue growth;
Organizational change;
Implementation of technologies.

5. Potential research questions
Are unionized workers more actively involved in workplace decision-making and employee participation programs?
Are there industrial sectors that are replacing less skilled workers with higher skilled workers?
What are the characteristics of workers leaving their jobs, thereby creating job vacancies?
Do alternative work practices such as job rotation and participation in work groups reduce quit rates?

6. Methodology: Target Population
All business locations in Canada that have paid employees EXCEPT employers in
Yukon, Northwest Territories
agricultural, fishing, hunting, trapping,
public administration
religious organizations
military
Employee content
receives a T4 slip from Revenue Canada

7. Methodology: Sampling frame
Stratified 2 stage design
Workplace component
physical location of business with paid workers
frame stratified by industry, region, size
size cut-offs are different for industry / region combinations ==> model based approach
sampling weights assigned to each unit = the inverse probability of selection with adjustment*
Worker Component
lists of employee made available by employers

8. Methodology: Longitudinal strategy for workplaces *** up to 6 years

9. Methodology: Longitudinal strategy for workers *** 2 years

10. Methodology: Weighting and Estimation
To produce estimates from a sample that relates to a population of interest requires the use of survey weights
Weights are adjusted for
complete non-response
stratum jumpers
calibration or “benchmark” to known totals from the Survey of Employment, Payroll and Hours
linked analysis weights adjusted for live units with no responding employees

11. Methodology: How to compute variances that take into account the complex survey design of WES?
Not done in most statistical packages
Use bootstrap weights provided
(100 in total for each observation, each based on 50 iterations)
idea: re-sampling technique to capture variability
To calculate the variance
produce an estimate based on each set of bootstrap weights
compute the variance estimate
apply an adjustment to make the variance design consistent (50/100)

12. Methodology: Why is taking account of the complex survey design of WES SOOOO important?
NOT taking into account of the design effect results in an UNDERESTIMATION of the variance
Hypothesis testing and constructing confidence intervals requires accurate standard errors
May erroneously report that a statistic is significantly different from zero when it is not.
Rules of Thumb: NO

13. Response Rates

14. Data Access Research Data Centres Remote Access SSRHC application
evaluated by 3 member peer committee
judged on scientific merit, viability of methods, appropriateness of data
deemed employees of STC
research falls within the mandate of STC
Remote Access
proposal sent to WES research manager
dummy data set sent to researcher
programs sent to Statistics Canada
designed primarily for multivariate analyses

15. Important websites Statistics Canada: www.statcan.ca WES site
General Information:
(English)
(French)
Questionnaires ( )
Workplace Evolving Series
MIE/free.htm

16. Can the workplace explain Canadian gender pay differentials?
Marie Drolet
Canadian Public Policy, Summer 2002
Evolving Workplace Series, No

17. Objectives
To move beyond ‘traditional’ analyses by incorporating workplace characteristics in the wage outcomes of men and women
household data = focus on worker
To determine the contribution of the workplace in ‘explaining’ the gender wage gap
linked employee-employer data = focus on gender segregation

18. Determinants of wages Usual suspects New WES variables
human capital, demographic, job
New WES variables
high performance workplace practices
self directed workgroups
performance pay
foreign ownership
non profit organizations
quantity and timing of labour demanded and supplied
required & actual education match
training costs per employee
workplace rate of part-time employment
industry / occupation / firm size

19. Do wages differ by workplace characteristics?
expected robust association between wages and ‘established’ variables
impact of workplace variables
(-) percent working part-time
(+) training expenditures per employee
(+) foreign ownership
(+) self directed workgroups
(+) workers receiving performance-based pay
(+) quantity and timing of labour
(+) undereducated
(-) overeducated
(NS) non-profit organizations

20. Are the workplaces of men and women different? * significantly different

21. Main Finding #1: Women are concentrated in low wage workplaces
When usual suspects are taken into account ….
Pooled OLS model:
women earn 15% less men when there are NO controls for the workplace
Workplace fixed effects model*
women earn 8% less than men when controls for the workplace are included

22. Main Finding #2: Industry measure in WES ‘explains’ more of gender pay differentials
Using ONLY Worker characteristics + industry & occupation
58% of gender wage gap ‘explained’
industry ‘explains’ 34% of gender wage gap
significantly different from other studies
Using Survey of Labour and Income Dynamics 1997:
50% is explained
industry accounts for 15%

23. Main Finding #3: The workplace accounts for more of the gap than the worker

24. Main Finding #4: The contribution of specific workplace characteristics in ‘explaining’ the gap based on Oaxaca decomposition method, base = male pay structure

25. Main Finding #5: Despite addition of new variables, a substantial portion of gap is unexplained
In most detailed specification about 40% of the gap is unexplained
Adjusted: women earn 92% of male average hourly wage rate
Differs from analyses using SLID
unexplained: 51%
adjusted: 89%

26. Important from a public policy perspective
Current research necessary since policies tend to address different components of the gap
Knowledge of contribution of workplace to gender pay differentials is essential since workplace contributes more to explaining differentials than the worker