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Shannon, M. (2011). The employment effects of lower minimum wage rates for young workers: Canadian evidence. Industrial Relations, 50(4), 629. Between 1986 and 1998, six of the ten Canadian provinces abolished their lower minimum wage rates for younger teenage workers. Using data from the Canadian Labour Force Survey, this paper evaluates the effects of abolition on the employment and weekly hours worked of 15- to 16-year-olds using teenagers in provinces where there is no legislative change and young people above the age to which youth rates applied as control groups. The results provide some evidence that abolishing these youth rates significantly lowered employment and work hours of 15- to 16- year-olds, but the lack of evidence for some jurisdictions and patterns of effects using age controls do raise some questions regarding the interpretation of the results. [PUBLICATION ABSTRACT] Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story? 2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite. 3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story? 1

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Shannon, M. (2011). The employment effects of lower minimum wage rates for young workers: Canadian evidence. Industrial Relations, 50(4), 629.

Between 1986 and 1998, six of the ten Canadian provinces abolished their lower minimum wage rates for younger teenage workers. Using data from the Canadian Labour Force Survey, this paper evaluates the effects of abolition on the employment and weekly hours worked of 15- to 16-year-olds using teenagers in provinces where there is no legislative change and young people above the age to which youth rates applied as control groups. The results provide some evidence that abolishing these youth rates significantly lowered employment and work hours of 15- to 16-year-olds, but the lack of evidence for some jurisdictions and patterns of effects using age controls do raise some questions regarding the interpretation of the results. [PUBLICATION ABSTRACT]

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

1

Kimmel, J., & Powell, L. (1999). Moonlighting trends and related policy issues in Canada and the United States. Canadian Public Policy, 25(2), 207-231.

Abstract:

An attempt is made to provide a detailed Canada-US cross-country comparison of moonlighting trends and to assess the possible underlying causes of such trends. The statistics show that both countries have experienced strong increases in moonlighting rates for women, never-married individuals, young persons, and service workers, while university-educated persons consistently have maintained high rates. US moonlighters remain more likely to combine a full-time job with a part-time job, while Canadians are increasingly becoming holders of multiple part-time jobs. The degree to which changes in moonlighting rates are driven by labor force compositional effects, labor supply-side factors, and labor demand-side factors is examined. Labor market policy recommendations are made with respect to welfare-to-work transitions childcare, payroll taxes, and non-wage benefits.

… Let us now turn our attention to moonlighting trends. The Canadian data for our trend analyses are drawn from the Survey of Work Arrangements for the year 1991 and. the Labour Force Survey for the years 1981, 1985, and 1995. The US data for the years 1981, 1985, and 1991 are drawn from the May supplement of the Current Population Survey (CPS). Statistics for 1994 come from unpublished tables from the US Bureau of Labor Statistics.' We include in our sample individuals aged 17-64 with positive hours of work (including students) and we omit un- paid family workers.

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

2

3

Cahill, I. G., & Gager, M. P. (2014). Explaining Canadian regional wage differentials. Review Of Regional Studies, 44(2), 125-152.

We explore the potential of a human capital model augmented with controls for industry and occupation in explaining Canadian regional wage differentials. We place our approach in a broader theoretical context by first reviewing the literature on potential explanations for regional wage differences and also on the related issues of migration, population growth, industrial location, and agglomeration economies. We then estimate an econometric model using subprovincial wage data from the Statistics Canada Labour Force Survey. A striking finding is that subprovincial wage differences, including the urban-rural divide, can be explained by our model, but that the differences between broad regions defined by provincial boundaries cannot.

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

4

Tiagi, R. (2010). Public sector wage premium in canada: Evidence from labour force survey. Labour, 24(4), 456-473.

Although previous research has pointed to a public/private sector wage gap for men and women in Canada, the extent of this gap has not been measured in recent years. Using data from the Canadian Labour Force Survey for September 2008, and using an endogenous switching regression framework to control for self-selection, I find that both men and women earn a wage premium in the public sector in Canada, although the premium is higher for women. The pure wage premium or economic rent that public sector workers receive relative to their counterparts in the private sector is $1.09, or 5.4 per cent for men and $3.15, or 20 per cent for women. An analysis of selection in the pubic/private sector reveals that public sectors workers are 'positively selected' on observables and consist of the 'cream of the crop'.[PUBLICATION ABSTRACT]

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

5

Abramson, Z. (2007). Masked symptoms: Mid-life women, health, and work. Canadian Journal on Aging, 26(4), 295-303.

Data from the Canadian Labour Force Survey (1997) reveal that relatively few mid-life women offer ill health as a reason for leaving their job or downshifting to part-time employment, implying that the role of ill health may be inconsequential in effecting changing patterns in mid-life women's labour force activity. In contrast, interviews with 30 mid-life women (aged 40 to 54 years) illustrate that, although they do not offer illness as their main reason for leaving their job or working part-time, health is a determining factor. This research also maps the complex relationship between work and ill health, showing that stressful working conditions (due to funding cuts and policy changes) affected the mental and physical health of this group of mid-life women, which, in turn, influenced their decision to change their labour force activity. The author concludes that policy makers must recognize that ill health may be under-reported among mid-life women in large surveys and that research is needed that specifically examines women's working conditions as they relate to health. Such research should not be based solely on large surveys but must also include qualitative studies that capture women's experiences.

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

6

Heisz, A. (1999). Changes in job duration in canada. Relations Industrielles, 54(2), 365-387.

Using monthly data from the Canadian Labour Force Survey, changes in the complete duration of new job spells from 1981 through 1996 are investigated. While the average complete length of new jobs did not increase or decrease over a period, investigation of the distribution of complete job lengths reveals 2 important changes. First, the probability that a new job would end within 6 months rose during the 1980s, but then reversed during the 1990s, meaning that there was little net change over the period as a whole. Second, the conditional probability that a job that had lasted 6 months would continue on past 5 years rose through the whole period. This pattern of change was found among virtually all demographic subgroups examined, suggesting that an economy-wide explanation must be sought.

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

7

Thenuwara, W., & Morgan, B. (2016). Labour supply behaviour of married women in toronto. Journal of Economic Studies, 43(3), 418-431.

Purpose - The purpose of this paper is to investigate the connection between labour supply and the wages of married women of different ages in Toronto using data from the 2010 Labour Force Survey of Canada. Design/methodology/approach - The authors employ three econometric techniques, ordinary least square, 2 stage least square and the Heckman two-step method to estimate the supply elasticities. The first two focus on the wage rate and hours conditional on the subjects being employed whereas the third method controls for sample selectivity bias by including the unemployed. Bootstrap test statistics are produced when the normality assumption for the error terms is found to be violated. Findings - The aggregate labour supply elasticity for married women in Toronto is estimated to be 0.053 which similar to value found for Canada for a whole in a previous study even though Toronto is much more diverse culturally than average. The labour supply elasticities for 25-34 year old and 35-44 year old married are estimated to be 0.108 and 0.079, respectively. The supply elasticity for married women aged 45-59 is not significantly different from 0. Originality/value - The paper shows that younger married women in Toronto are more responsive to an increase in wages than older women. The estimation procedure and the testing of the significance of coefficients are more rigorous than previous studies.

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

8

Schirle, T. (2015). The gender wage gap in the canadian provinces, 1997-2014. Canadian Public Policy, 41(4), 309.

This study examines the gender gaps in average hourly wages facing private sector full-time employees in the Canadian provinces, using data from the Canadian Labour Force Survey. Over the 1997-2014 period, all provinces have made progress toward narrowing the gender wage gap, though notably little progress was made in Newfoundland and Alberta. Much of the variation across provinces in the gender gap is eliminated once we account for gender differences in individual and job characteristics in each province. Decomposition results suggest a large portion of the wage gap in each province is explained by gender differences in industry and occupation. The unexplained portion of the wage gap has been reduced in many provinces as gender differences in industry and occupation play an increasingly important role.

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

9

Shannon, M. (2009). Canadian lone mother employment rates, policy change and the US welfare reform literature. Applied Economics, 41(19), 2463.

The article examines the rise in Canadian lone mother employment rates during the 1990s using data from the Canadian Labour Force Survey and methods borrowed from the United States welfare reform literature. Patterns of lone mother employment rate increases in Canada are found to be similar to those in the United States. Income support policies in both countries changed in similar directions and in both cases increased the incentive to work. Despite these parallel changes it appears that, unlike the United States, policy reforms account for only a small part of the rise in Canadian lone mother employment rates. [PUBLICATION ABSTRACT]

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

10

MacPhail, F., & Bowles, P. (2008). Temporary work and neoliberal government policy: Evidence from british columbia, canada. International Review of Applied Economics, 22(5), 545.

We examine the impact of government policy on the incidence of temporary work by analysing the case of British Columbia (BC), Canada. The analysis is based upon the Canadian Labour Force Survey 1997-2004; temporary work is defined as work that is not expected to last for more than 6 months and includes seasonal, fixed-term, casual, and temporary help agency work. A case study of BC provides a valuable opportunity to assess the impacts of neoliberal government policy, designed to increase labour market flexibility, on the extent of temporary work because we are able to compare labour market trends in BC both before and after the reforms introduced in 2001 and to compare BC with other provinces in Canada that were not subject to such large changes in their policy environments. We find that the shift to neoliberal policies in BC led to significant increases in the likelihood of workers finding themselves in temporary employment. We also find that the likelihood of being a temporary worker in BC in the post-policy change period increases relative to all other provinces over the same period. Taken together, these results indicate that government policy is a key determinant of the level of temporary work. As such, the level of temporary work should be seen as a policy-sensitive variable, rather than as a phenomenon determined solely by the exogenous forces of globalization and technological change. [PUBLICATION ABSTRACT]

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

11

Akbari, A. H. (1996). Provincial income disparities in canada: Does the quality of education matter? The Canadian Journal of Economics, 29, S337-S339.

The standard human capital earnings model (Mincer 1974) is used to measure systematic provincial earnings differences among individuals. Microdata obtained from the 1991 Survey of Consumer Finances (SCF) census family files, are utilized. The SCF is conducted annually by Statistics Canada and employs the Labour Force Survey sample. This is a multi-stage stratified probability sample that represents approximately 98% of the population. The analysis conducted suggests that persistent earnings differences among Canadian provinces may be largely due to differences in the working environment among provinces. To investigate this issue further, various measures of educational quality for Canadian provinces were compared.

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

12

Ariizumi, H., Hu, Y., & Schirle, T. (2015). Stand together or alone? family structure and the business cycle in canada. Review of Economics of the Household, 13(1), 135-161.

In this paper we examine the relationship between business cycle fluctuations and family formation and structure, using Canadian vital statistics and Labour Force Survey data. Similar to US studies, we find that a 1 percentage point increase in the unemployment rate of men is associated with a 13 % decline in the number of marriages formed per thousand single females each quarter. Unlike US studies, we do not find a significant relationship between unemployment rates and aggregate flows into divorce. Using stock measures of marital status and family type, we show that the importance of the business cycle varies substantially by age group. Among 25-44 year olds, there is a significant increase in single parents with children under 18 when unemployment rates rise. Among 35-54 year olds, there is a significant increase in those living alone. There is some evidence of elderly parents joining the households of 45-54 year olds and young adults (18-24) remaining with their single parents during recessions. Overall, the observed decline in marriages during recessions appears driven by a decline in remarriages rather than a decline in first marriages.

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

13

Fortin, N. M., & Lemieux, T. (2015). Changes in wage inequality in canada: An interprovincial perspective. The Canadian Journal of Economics, 48(2), 682.

This paper uses the Canadian Labour Force Survey to understand why the level and dispersion of wages have evolved differently across provinces from 1997 to 2013. The faster increase in the level of wages and the decline in wage dispersion in Newfoundland, Saskatchewan and Alberta are the starkest interprovincial differences. We find that they are accounted for by the growth in the extractive resources sectors, which benefited less-educated and younger workers the most. Increases in minimum wages since 2005 are found to be the main reason why wages at the very bottom grew more than those in the middle of the distribution.

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

14

Brochu, P. (2013). The source of the new canadian job stability patterns. The Canadian Journal of Economics, 46(2), 412.

This paper explores the causes of recent changes in Canadian job stability. Using the Labour Force Survey master files (1977-2010), I find that the increases in job stability first observed in the 1990s were, in fact, long lasting. Results indicate that compositional changes and the increased job stability of women within age and education groups play important roles in explaining the aggregate job stability patterns that emerge. [PUBLICATION ABSTRACT]

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

15

Amine, S. (2012). 'Low-skilled' work in canada. The Economic and Labour Relations Review : ELRR, 23(4), 91-100.

This research note focuses on the situation of workers classed in Canada as low-skilled. Using data from the Labour Force Survey conducted by Statistics Canada, we seek to answer the following questions: are workers classed as low-skilled disproportionately affected by rising unemployment rates? What types of jobs are classed as low-skilled? Are these jobs predominantly full-time or part-time? Within this category of low-skilled workers, we will also focus on the situation of women who, according to several recent studies including those by the OECD, are increasingly employed in precarious jobs. [PUBLICATION ABSTRACT]

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

16

Shandro, J., Koehoorn, M., Scoble, M., Ostry, A., & al, e. (2011). Mental health, cardiovascular disease and declining economies in british columbia mining communities. Minerals, 1(1), 30-48.

The purpose of this study was to investigate the relationship between community-level exposure to changes in economic conditions and the incidence and prevalence of mental disorders and cardiovascular disease in 29 resource-based communities (with a focus on mining communities) in British Columbia (BC) during a period of time marked by an economic downturn (1991-2002) The investigation relied on Labour Force Survey (LFS) and Statistics Canada Census data, and health records from the British Columbia Ministry of Health (MoH). Age and sex adjusted prevalence and incidence rates were calculated for each community from 1991 to 2002 and the development of an economic change indicator defined using Census data and industry/government documents allowed for yearly assessment of community-level exposure to economic conditions. The relationship between exposure to economic change and rates of acute and chronic cardiovascular disease and mental disorders across the 29 study communities was investigated using a generalized linear model (stratified by type of community, and adjusted for the effect of the community). Findings indicate an impact on the prevalence rates for acute cardiovascular disease (CVD) during periods of economic decline (rate increased by 13.1 cases per 1,000 population, p < 0.0001 as compared with stable periods) and bust conditions (rate increased by 30.1 cases per 1,000 population, p < 0.0001 as compared with stable conditions) and mental disorders (rate increased by 13.2 cases per 1,000 population, p = 0.0001) in mining communities during declining economic conditions as compared to steady periods of mining employment. This is not observed in other resource-based communities. The paper concludes by highlighting implications for the mining industry to consider as they begin to recognize and commit to mining community health.

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

17

Friesen, J. (2002). The effect of unemployment insurance on weekly hours of work in Canada. The Canadian Journal of Economics, 35(2), 363-384.

Major revisions to the Canadian unemployment insurance program in 1997 created a benefit structure that effectively provides more insurance to workers who are employed for longer workweeks. This anomaly creates an incentive for workers and firms to tailor their weekly work schedules to maximize net program benefits. Analysis of Labour Force Survey data shows that workers and firms responded to these changes by altering weekly hours as expected. This behavioural response demonstrates the sensitivity of hours of work decisions to labour market policies.

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

18

Smith, P. M., & Koehoorn, M. (2016). Measuring gender when you don't have a gender measure: constructing a gender index using survey data. International Journal For Equity In Health, 151-9.

Background: Disentangling the impacts of sex and gender in understanding male and female differences is increasingly recognised as an important aspect for advancing research and addressing knowledge gaps in the field of work-health. However, achieving this goal in secondary data analyses where direct measures of gender have not been collected is challenging. This study outlines the development of a gender index, focused on gender roles and institutionalised gender, using secondary survey data from the Canadian Labour Force survey. Using this index we then examined the distribution of gender index scores among men and women, and changes in gender roles among male and female labour force participants between 1997 and 2014.

Methods: We created our Labour Force Gender Index (LFGI) using information in four areas: responsibility for caring for children; occupation segregation; hours of work; and level of education. LFGI scores ranged from 0 to 10, with higher scores indicating more feminine gender roles. We examined correlations between each component in our measure and our total LFGI score. Using multivariable linear regression we examined change in LFGI score for male and female labour force participants between 1997 and 2014.

Results: Although women had higher LFGI scores, indicating greater feminine gender roles, men and women were represented across the range of LFGI scores in both 1997 and 2014. Correlations indicated no redundancy between measures used to calculate LFGI scores. Between 1997 and 2014 LFGI scores increased marginally for men and decreased marginally for women. However, LFGI scores among women were still more than 1.5 points higher on average than for men in 2014. Conclusions: We have described and applied a method to create a measure of gender roles using survey data, where no direct measure of gender (masculinity/femininity) was available. This measure showed good variation among both men and women, and was responsive to change over time. The article concludes by outlining an approach to use this measure to examine the relative contribution of gender and sex on differences in health status (or other outcomes) between men and women. [ABSTRACT FROM AUTHOR]

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

19

Campolieti, M., Gunderson, M., & Lee, B. (2014). MINIMUM WAGE EFFECTS ON PERMANENT VERSUS TEMPORARY MINIMUM WAGE EMPLOYMENT. Contemporary Economic Policy, 32(3), 578.c

We estimate the effect of minimum wages on employment using the Master Files of the Canadian Labour Force Survey over the recent period 1997-2008. Particular attention is paid to the differences between permanent and temporary minimum wage workers -- an important distinction not made in the existing literature. Our estimates for permanent and temporary minimum wage workers combined are at the lower end of estimates based on Canadian studies estimated over earlier time periods, suggesting that the adverse employment effects are declining over time for reasons discussed. Importantly, the adverse employment effects are substantially larger for permanent compared to temporary minimum wage workers; in fact they fall almost exclusively on permanent minimum wage workers

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

20

Fuller, S. (2005). Public Sector Employment and Gender Wage Inequalities in British Columbia: Assessing the Effects of a Shrinking Public Sector. Canadian Journal Of Sociology, 30(4), 405-439.

The public sector is an important employer of women in Canada, particularly at the provincial level. As a result, recent initiatives to cut employment in this sector have the potential to impact broader gender inequalities in the labour market. This study uses data from the Labour Force Survey to estimate provincial-level public and private sector wage differentials in British Columbia for men and women, and to assess the degree to which declines in public sector employment in B.C. may affect the overall gender wage gap. Results confirm that provincial public sector employment is both relatively more prevalent and advantageous for women than for men. Substantial declines in employment in this sector therefore have the potential to noticeably increase the gender wage gap. [ABSTRACT FROM AUTHOR]

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

21

Osberg, L. (1993). Fishing in Different Pools: Job-Search Strategies and Job-Finding Success in Canada in the Early 1980's. Journal Of Labor Economics, 11(2), 348.

This article examines the job-search methods of jobless workers and emphasizes sample selectivity in choice of job-search strategies (especially use of public employment agencies) Longitudinal data from the Labour Force Survey of Canada for 1981, 1983, and 1986 indicate that job-search methods change with the business cycle and that many people find jobs without any reported search The determinants of job-search success also vary substantially over the business cycle, implying a substantial social return to public employment agencies at the 1983 trough of the recession but no noticeable benefits when aggregate unemployment is relatively low [ABSTRACT FROM AUTHOR]

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

22

PALACIOS, M., LAMMAM, C., REN, F., & CLEMENS, J. (2016). COMPARING GOVERNMENT AND PRIVATE SECTOR COMPENSATION IN CANADA. Journal Of Self-Governance & Management Economics, 4(1), 95-127.

Using aggregated monthly data from Statistics Canada's Labour Force Survey from January to December 2013, this study estimates wage differentials between the government and private sector in Canada. It also evaluates four available non-wage benefits in an attempt to quantify compensation differences between the two sectors. While a lack of non-wage benefits data mean that there is insufficient information to make a definitive comparison of total compensation, the available data indicate that the government sector enjoys a clear wage premium. After controlling for various wage-determining factors, government workers in Canada (including federal, provincial, and local government workers) were found to enjoy a 9.7 percent wage premium, on average, over their private sector counterparts in 2013. When unionization status is factored into the analysis, the wage premium for the government sector declines to 6.2 percent. There are also strong indications that the government sector as a whole has more generous non-wage benefits than the private sector including higher rates of pension coverage, higher rates of defined benefit pensions, earlier ages of retirement, lower rates of job loss, and higher absence rates. Overall, government workers in Canada enjoy higher wages and probably higher non-wage benefits than comparable workers in the private sector. [ABSTRACT FROM AUTHOR]

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

23

Abramson, Z. (2000) Homeward Bound: An examination of midlife women’s labour force inactivity and part-time employment. (Doctoral dissertation). York University, Toronto, ON.

This dissertation examines midlife women’s labour force inactivity and part-time employment. The research is situated in a theoretical perspective that connects structural influences and women’s experiences. Hence, the patterns of midlife women’s labour force activity are examined by analyzing large databases (Census 1996 and the Labour Force Survey 1997) and conducting in-depth interviews.

The quantitative analysis examines factors (marital status, age of youngest children living at home, education, ethnicity, other household incomes and occupational groupings) that affect midlife women’s labour force inactivity and part-time employment, and reasons offered for job loss and part-time employment. The qualitative research (30 interviews) reflects personal experiences and probes issues that large data samples cannot easily address.

… The research on part-time employment shows that part-timers are a diverse group drawn to part-time work for a broad range of reasons and motivations. Although results from the quantitative data suggest that the majority of midlife women are working part-time for reasons of personal preference, the interview data suggest that personal preference needs to be contextualized in relation to health, job satisfaction, job opportunities, family responsibilities and socio-economic status.

The findings of this dissertation support the conclusion that age is a critical factor in women’s lives and that their reduced labour force activity has serious implications for their economic status in midlife and beyond. Social policy makers must recognize and address this factor.

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

24

Schanzer, D. L., Zheng, H., & Gilmore, J. (2011). Statistical estimates of absenteeism attributable to seasonal and pandemic influenza from the Canadian Labour Force Survey. BMC Infectious Diseases, 11(1), 90-98.

Background: As many respiratory viruses are responsible for influenza like symptoms, accurate measures of the disease burden are not available and estimates are generally based on statistical methods. The objective of this study was to estimate absenteeism rates and hours lost due to seasonal influenza and compare these estimates with estimates of absenteeism attributable to the two H1N1 pandemic waves that occurred in 2009.

Methods: Key absenteeism variables were extracted from Statistics Canada's monthly labour force survey (LFS). Absenteeism and the proportion of hours lost due to own illness or disability were modelled as a function of trend, seasonality and proxy variables for influenza activity from 1998 to 2009. Results: Hours lost due to the H1N1/09 pandemic strain were elevated compared to seasonal influenza, accounting for a loss of 0.2% of potential hours worked annually. In comparison, an estimated 0.08% of hours worked annually were lost due to seasonal influenza illnesses. Absenteeism rates due to influenza were estimated at 12% per year for seasonal influenza over the 1997/98 to 2008/09 seasons, and 13% for the two H1N1/09 pandemic waves. Employees who took time off due to a seasonal influenza infection took an average of 14 hours off. For the pandemic strain, the average absence was 25 hours. Conclusions: This study confirms that absenteeism due to seasonal influenza has typically ranged from 5% to 20%, with higher rates associated with multiple circulating strains. Absenteeism rates for the 2009 pandemic were similar to those occurring for seasonal influenza. Employees took more time off due to the pandemic strain than was typical for seasonal influenza.

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

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Breslin, FC. P. Smith. (2006) “Trial by fire: a multivariate examination of the relation between job tenure and work injuries.” Occupational and Environmental Medicine. 63(1): 27–32.

Abstract

AimsThis study examined the relation between months on the job and lost time claim rates, with a ‐particular focus on age related differences.MethodsWorkers' compensation records and labour force survey data were used to compute claim rates per 1000 full time equivalents. To adjust for potential confounding, multivariate analyses included age, sex, occupation, and industry, as well job tenure as predictors of claim rates.Results

At any age, the claim rates decline as time on the job increases. For example, workers in the first month on the job were over four times more likely to have a lost time claim than workers with over ‐one year in their current job. The job tenure injury associations were stronger among males, the goods industry, manual occupations, and older adult workers.Conclusions

The present results suggest that all worker subgroups examined show increased risk when new on the job. Recommendations for improving this situation include earlier training, starting workers in low hazard conditions, reducing job turnover rates in firms, and improved monitoring of hazard exposures that new workers encounter.

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

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Chan, W., Lu, Y., & Morissette, R. (2014). Wages, Youth Employment, and School Enrollment: Recent Evidence from Increases in World Oil Prices (No. 2014353e). Statistics Canada, Analytical Studies Branch.

Canada's oil reserves are concentrated in three Canadian provinces: Alberta, Saskatchewan, and Newfoundland and Labrador. Oil prices received by Canadian oil producers more than doubled between 2001 and 2008. The proportion of young men employed in the oil industry differs markedly across provinces and education levels. Taken together, these facts suggest that the increases in world oil prices observed between 2001 and 2008 may have induced cross-educational and cross-provincial variation in labour demand and male wage growth in Canada. Using data from the Canadian Labour Force Survey, this study exploits this variation in wage growth in order to estimate the elasticity of young men's labour market participation and school enrollment with respect to wages.

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

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Gomez, R., & Lamb, D. (2016). Unions and Traditionally Disadvantaged Workers: Evidence from Union Wage Premiums in Canada 2000 to 2012. E-Journal of International and Comparative Labour Studies, 5(3).

Abstract. It is well documented that unionised workers earn significantly more than their non-union counterparts. However, over the last three decades, the union wage premium along with overall union coverage has fallen in most industrialized economies. Though the principal causes are still under dispute, the effects of technological change, managerial opposition, globalization and other factors have clearly lessened the bargaining power of labour with respect to employers. Given the commensurate rise of non-standard work and inequality in most developed nations, this paper examines the extent to which unions can still provide some immunity against the pressures of these “new labour market realities”. Using data from the Canadian Labour Force Survey for the years 2000 – 2012 inclusive, we estimate union wage premiums amongst historically disadvantaged groups: i.e., youth, women, low wage workers, immigrants, Aboriginals and workers in non-standard jobs. The results suggest that across almost every dimension of vulnerability or disadvantage used in the paper, unions are associated with a larger than average positive impact on workers’ earnings. The findings support the powerful redistributive role that unions still play in contemporary economies especially for the most vulnerable.

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

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Reitz, Jeffery G., and Anil Verma. 2004. "Immigration, Race, and Labor: Unionization and Wages in the Canadian Labor Market." Industrial Relations 43, no. 4: 835-854. Business Source Premier, EBSCOhost (accessed April 9, 2017).

Abstract:In Canada, most racial minorities have lower rates of unionization than do members of the majority workforce. Data from the Survey of Labour and Income Dynamics (N = 32,634) show that racial minority immigrants assimilate into unionization over time. However, unionization reduces net minority wage disadvantages only slightly. Union race relations policies should place more emphasis on collective bargaining as well as on unionization. [ABSTRACT FROM AUTHOR]

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

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Milligan, K., & Schirle, T. (2016). Health Capacity to Work at Older Ages: Evidence from Canada. In Social Security Programs and Retirement Around the World: The Capacity to Work at Older Ages. University of Chicago Press.

Abstract: We study the health-capacity to work among older workers in Canada. We estimate work capacity using two methods. The first uses age-specific mortality rates to proxy for overall health, comparing employment rates at similar levels of mortality. The second method uses a mix of health measures to estimate a health-employment relationship at ages 50 to 54, then uses these estimates to project the employment capacity of older workers. Our results suggest a substantial unused capacity for work among older Canadians.

Introduction: Health and longevity have improved substantially and continuously in Canada since the 1970s. Public pensions in Canada have not kept pace with these changes up to now.1 In the 1980s, for example, the earnings-related Canada and Quebec Pension Plans facilitated earlier retirement by introducing an early retirement option as young as age 60 so that Canadians no longer had to wait until age 65 to take up benefits. …

But to what extent are older individuals able to work longer? In this study we are concerned with measuring individuals’ health capacity for work. As health improves and people live longer, to what extent are they able to work more? Of course, one’s capacity to work is not directly measurable. We take two separate and distinct approaches to measuring health capacity for work among older men and women in this study. …

… The mortality data used in this analysis has been retrieved from the Human Mortality Database. Our employment data is from the Canadian Labour Force Survey (LFS).5 The period we consider is 1976 through 2011, as these are the years for which we have both employment and mortality data available. 5 Confidential microdata files made available through the Statistics Canada Research Data Centres program are used to construct age-gender-specific employment rates. … .

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

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Koebel, K., & Schirle, T. (2016). The Differential Impact of Universal Child Benefits on the Labour Supply of Married and Single Mothers. Canadian Public Policy, 42(1), 49-64.

AbstractWe examine the effects of the Universal Child Care Benefit on the labour supply of mothers. The benefit has a significant negative effect on the labour supply of legally married mothers, reducing their likelihood of participation in the labour force by 1.4 percentage points and hours worked by nearly one hour per week. In contrast, the likelihood of participation by divorced mothers rises by 2.8 percentage points when receiving the benefit and does not affect hours worked. Moreover, the benefit does not have a statistically significant effect on the participation of common-law married mothers or never-married mothers.

… In this study, we follow Schirle (2015) and use a differences-in-differences estimator to compare the labour market activity of mothers whose youngest child is aged zero to five to mothers whose youngest child is aged 6–17 before and after the introduction of the UCCB in July 2006. Our analysis separately assesses the activities of legally married, common-law, never-married, and divorced/separated mothers, using the Canadian Labour Force Survey (LFS) monthly data from 2003 to 2009.

Our results present an interesting puzzle: while legally married mothers are likely to reduce their labour supply on extensive and intensive margins when receiving the UCCB, divorced/separated mothers are likely to increase their participation in the labour force when receiving the UCCB. Any positive response on the hours margin is not statistically significant. The labour supply of mothers in common-law relationships and never-married mothers does not appear to be affected by UCCB receipt. We suggest the response differential between married and divorced mothers is clearly identified and may relate to differences in each household’s reliance on formal child care, the nature of intrahousehold bargaining, and potential labelling effects of child benefits. …

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

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Gupta, N. et al (2003) Assessing human resources for health: what can be learned from labour force surveys? Human Resources for Health 1:5.

AbstractBackgroundHuman resources are an essential element of a health system's inputs, and yet there is a huge disparity among countries in how human resource policies and strategies are developed and implemented. The analysis of the impacts of services on population health and well-being attracts more interest than analysis of the situation of the workforce in this area. This article presents an international comparison of the health workforce in terms of skill mix, sociodemographics and other labour force characteristics, in order to establish an evidence base for monitoring and evaluation of human resources for health.

MethodsProfiles of the health workforce are drawn for 18 countries with developed market and transitional economies, using data from labour force and income surveys compiled by the Luxembourg Income Study between 1989 and 1997. Further descriptive analyses of the health workforce are conducted for selected countries for which more detailed occupational information was available.

ResultsConsiderable cross-national variations were observed in terms of the share of the health workforce in the total labour market, with little discernible pattern by geographical region or type of economy. Increases in the share were found among most countries for which time-trend data were available. Large gender imbalances were often seen in terms of occupational distribution and earnings. In some cases, health professionals, especially physicians, were overrepresented among the foreign-born compared to the total labour force.Conclusions

While differences across countries in the profile of the health workforce can be linked to the history and role of the health sector, at the same time some common patterns emerge, notably a growing trend of health occupations in the labour market. The evidence also suggests that gender inequity in the workforce remains an important shortcoming of many health systems. Certain unexpected patterns of occupational distribution and educational attainment were found that may be attributable to differences in health care delivery and education systems; however, definitional inconsistencies in the classification of health occupations across surveys were also apparent.

Researchers are wondering … 1. What’s the story here? Identify the basic LFS data elements that are key to this story?

2. What’s the relationship between the data elements? i.e. when one measure goes up, the other goes up too, or the opposite.

3. Does the story draw on additional datasets, beyond the LFS? What data elements do they add to the story?

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