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

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Presentation on theme: "Workplace and Employee Survey Marie Drolet WES Research Manager Business and Labour Market Analysis Division Statistics Canada"— Presentation transcript:

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

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

3 Goals of WES n 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 ¹ 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 n Are unionized workers more actively involved in workplace decision-making and employee participation programs? n Are there industrial sectors that are replacing less skilled workers with higher skilled workers? n What are the characteristics of workers leaving their jobs, thereby creating job vacancies? n Do alternative work practices such as job rotation and participation in work groups reduce quit rates?

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

7 Methodology: Sampling frame n Stratified 2 stage design Ê 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* Ë 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 n To produce estimates from a sample that relates to a population of interest requires the use of survey weights n 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? n Not done in most statistical packages n Use bootstrap weights provided (100 in total for each observation, each based on 50 iterations) idea: re-sampling technique to capture variability n 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? n NOT taking into account of the design effect results in an UNDERESTIMATION of the variance n Hypothesis testing and constructing confidence intervals requires accurate standard errors n May erroneously report that a statistic is significantly different from zero when it is not. n Rules of Thumb: NO

13 Response Rates

14 Data Access n Research Data Centres 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 n 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 n Statistics Canada : n WES site General Information: –http://www.statcan.ca/english/survey/business/workpl ace/workplace.htm (English) –http://www.statcan.ca/francais/survey/business/work place/workplace_f.htm ( French ) Questionnaires ( ) –http://www.statcan.ca/english/concepts/wes.htm –http://www.statcan.ca/francais/concepts/wes_f.htm Workplace Evolving Series –http://www.statcan.ca/english/freepub/ MIE/free.htm –http://www.statcan.ca/francais/freepub/ MIF/free_f.htm

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

17 Objectives n To move beyond ‘traditional’ analyses by incorporating workplace characteristics in the wage outcomes of men and women  household data = focus on worker n 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 n Usual suspects human capital, demographic, job n 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? n expected robust association between wages and ‘established’ variables n 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 n 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 n 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 n In most detailed specification about 40% of the gap is unexplained n Adjusted: women earn 92% of male average hourly wage rate n Differs from analyses using SLID unexplained: 51% adjusted: 89%

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


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