Survey of Labour and Income Dynamics (SLID) – 2010 Survey Overview
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The Survey of Labour and Income Dynamics (SLID) is an important source of income data for Canadian families, households and individuals. Introduced in 1993, SLID provides an added dimension to traditional surveys on labour market activity and income: the changes experienced by individuals and families through time. Among the survey's key objectives is the understanding Canadians' economic well-being.
Starting with reference year 1998, SLID officially replaced the annual Survey of Consumer Finances as the main source of information on family income. Over the 1993-to-1997 period, the two surveys were run in parallel: estimates for this period are produced by combining both samples. Together, these surveys cover a period that begins in 1976. The income content of the two surveys is similar, although SLID uses a mixed collection mode that combined survey data with data from administrative sources. As well, SLID adds a large selection of variables that capture transitions in Canadian jobs, income and family events.
As a longitudinal survey, SLID interviews the same people from one year to the next for six years. The survey's longitudinal dimension enables evaluation of concurrent and often related events. This yields greater insight on the nature and extent of low income in Canada: What socio-economic shifts do individuals and families live through? How do these shifts vary with changes in their paid work, family make-up, receipt of government transfers and other factors? What proportion of households are persistently in low income year after year, and what makes it possible for others to emerge from periods of low income?
SLID also provides information on a broad selection of human capital variables, labour force experiences and demographic characteristics such as education, family relationships and household composition. Its breadth of content, combined with its relatively large sample, makes it a unique and valuable dataset.
Historical revision of the 2006-2009 period
The 2010 release is accompanied by a historical revision for 2006 to 2009. The SLID sample weights and estimates for 2006 and the years following are now produced on the basis of population counts from the 2006 Census of Population, instead of the 2001 Census. As a result, all estimates in the CANSIM 202 series have been revised for reference years 2006 to 2009. While the actual levels of the estimates have changed in many cases, generally, the trends shown by the data remain very similar.
The following table presents the impacts of the revision on some key national estimates for the reference years 2006 and 2009. Because the impacts on 2007 and 2008 estimates were similar, they were omitted from the table. A research paper provides more information about the impact of this revision (Statistics Canada, Historical revision, 2006 to 2009). It should be noted that survey estimates prior to 2006 were not revised.
|% changeNote 1||pre-
|% changeNote 1|
|Number of earners ('000)||18,863||18,837||-0.1||19,477||19,451||-0.1|
|Number of full-time full-year earners ('000)||9,072||9,041||-0.3||8,916||8,889||-0.3|
|Median earnings, all earners (2009 constant dollars)||28,200||28,200||0.1||28,700||28,700||0.1|
|Median government transfers (2009 constant dollars)|
|Median income tax (2009 constant dollars)|
|Median after-tax income (2009 constant dollars)|
|percentage point change||pre-
|percentage point change|
|Percentage of persons in low income|
|Low Income Cut-off||10.5||10.3||-0.2||9.6||9.5||-0.1|
|Low Income Measure||12.6||12.4||-0.2||13.3||13.1||-0.1|
|Market Basket Measure||10.0||9.9||-0.1||10.6||10.5||-0.2|
|Income share by adjusted after-tax income quintile (%)|
|1. Percentage changes were calculated using unrounded numbers.|
As opposed to the Low Income Cut-offs and the Market Basket Measure which do not depend on the SLID samples, the Low Income Measures (LIMs) were recalculated for that period. The impact of the revision on the LIM is described in the 2010-2011 Low Income Lines report.
New approaches to low income: Changes to table 806
Changes have been made to table 202-0806, Transitions of persons into and out of low income, by selected characteristics, annual. These changes only affect the percentages presented in the table. Previously, the denominators of the percentages included all individuals. Now, the denominators vary depending on the concept. The new concepts are described below.
The immobility rate is the proportion of the population who stayed in low income in both years as a share of people who were in low income the previous year.
The exit rate is the proportion of the population who exited low income as a share of people who were in low income the previous year.
The entry rate is the proportion of the population who entered low income as a share of people who were not in low income the previous year.
The resistance rate is the proportion of the population who stayed out of low income in both years as a share of people who were not in low income the previous year.
These four new concepts are consistent with those used in the paper Low Income in Canada – A Multi-line and Multi-index Perspective, released earlier this year.
Introduction of new variables
Ontario material deprivation (OMD) data were collected for the 2010 reference year. The data are available only for households in Ontario. Three new variables have been derived for both the 2009 and 2010 reference years: a count variable giving the number of OMD items that were unaffordable to a household; and two flag variables showing whether a household could not afford two or more items or three or more OMD items.
Changes to variables
In addition to the 2006 to 2009 weight revision, here are the changes to the existing variables from reference year 2010:
Employment Insurance Premiums (EIPR42)
Employment Insurance Premiums for self-employed were added to the existing Employment Insurance Premiums variable.
Provincial Tax Credits (PVTXC42)
New programs were added to the existing variable:
- Nova Scotia Affordable Living Tax Credit
- Nova Scotia Poverty Reduction Tax Credit
- Ontario Sales Tax Transition Benefit (for 2010 and 2011 only)
- Ontario Sales tax Credit
- British Columbia Harmonized Sales Tax Credit
SLID is a household survey that covers all individuals in Canada, excluding residents of Yukon, the Northwest Territories and Nunavut, residents of institutions and persons living on Indian reserves or in military barracks.
The SLID sample is composed of two panels. Each panel consists of roughly 17,000 households and about 34,000 adults, and is surveyed for six consecutive years. A new panel is introduced every three years, so two panels always overlap.
Figure 1. Overlapping design of SLID sample
From January to March following the reference year, interviewers contact respondents by telephone. Interviewers collect information regarding respondents' labour market experiences, educational activity and family relationships. The demographic characteristics of family and household members represent a snapshot of the population as of the end of each calendar year. Interviewers also collect information on income. However, respondents have the option of answering income questions during the interview, or of giving Statistics Canada permission to access their income tax records. Over 80% of respondents give us their permission to consult their income tax file.
This survey could be called the 'Survey of Labour, Income and Family Dynamics', since it has complete information on complex family structures and changes. How does it capture this information?
Unlike most household surveys, which describe how household members are related to one specific reference person, SLID asks explicitly about the relationship among all members of a household. Information on complex family structures—for example, blended or multi-generational families—can help in understanding family dynamics.
However, because families change, it's impossible to present data for exactly the same families over time. Instead, the same individuals are analysed in light of their family characteristics—for example, their family's income or whether they belong to a blended family.
There are two types of recurring surveys: in most surveys, a new cross-section of people are interviewed each time; in others, the same people are interviewed over a period of time—a longitudinal survey.
The advantage of cross-sectional surveys is that they are generally more representative of the population, and they reveal the levels and trends of income or labour for the whole population or its sub-groups. But such surveys do not answer questions about changes or fluctuations faced by individuals or families: What are the fluctuations in people's labour, income or family characteristics at the micro level? What events tend to coincide? How often do people change jobs or get laid off, with what impact on their total family income? How many families split or join together in a given time period? What proportion of households is 'persistently poor' year after year, and what enables others to emerge from periods of low income? These and many similar questions can only be answered by a longitudinal survey.
In a survey like SLID, the focus extends from static cross-sectional measures to a range of longitudinal events: transitions, durations, and repeat occurrences of people's financial and work situations. These yield a number of possible longitudinal research themes.
Paradoxically, the comprehensive data that make SLID so valuable also makes the job of maintaining respondent confidentiality more complex for Statistics Canada. To comply with the strict confidentiality provisions of the Statistics Act, SLID longitudinal data are made available through special modes of dissemination (see data services).
Longitudinal respondents are the people belonging to the selected households when a new six-year panel of respondents is introduced. These respondents are interviewed once a year whether they stay, move away or split up. New joiners, called cohabitants in SLID, are interviewed as long as they continue to live with a longitudinal respondent. That is because the family make-up and family income situation of longitudinal respondents is of key interest. Interviewing cohabitants also improves the quality of cross-sectional estimates.
Children present in the original households are interviewed starting the year they reach 16 years old. People aged 70 years and older are not asked labour-related questions.
Discussions with prospective users and insights from other panel surveys with similar content helped identify seven longitudinal research themes that illustrate some of the survey's potential. Depending on the angle of study, it may make sense to use individuals, jobs, employers, or spells (of unemployment, for example) as the unit of analysis. SLID covers up to six jobs and six employers that a person might have during each calendar year.
Employment and unemployment dynamics
Labour force activity data usually show total employment, unemployment and inactivity. Changes in employment and unemployment between two months or two years are calculated by comparing these totals. SLID, however, shows the flow into each type of labour force activity experienced by individuals. Flow data of persons or jobs are possible by industry, occupation, or worker characteristics. Durations of spells may be of interest too; for example, to what extent are long spells of unemployment experienced by the same individuals? What are the major determinants? Why do people withdraw from the labour market, and what precedes a transition into self-employment?
Life cycle labour market transitions
Using SLID data, one can study major labour market transitions associated with particular stages of the life cycle, such as transitions from school to work, transitions from work to retirement and work absences taken to have or raise children. What are typical life-cycle patterns in Canada today? What are the subsequent activities of high school drop-outs, and what precedes a return to school?
SLID supports research in such areas as wage differences between men and women, underemployment, occupational mobility, earnings growth over a period of several years, as well as wage and hours polarization among the working population.
Family economic mobility
How stable is family income? What proportion of families experience a significant improvement or deterioration in income between two points in time? What are the determinants of these changes? How important are changes in family composition (divorce, remarriage) in explaining a change in financial well-being?
Dynamics of low income
This research theme concerns the prevalence and duration of spells of low income and the factors related to families moving into or out of low income. Researchers can isolate and characterize a persistently in low income sub-population, as is done using longitudinal surveys in other countries. There is also interest in looking at receipt of employment insurance benefits, social assistance and other government transfers in relation to flows into and out of low income.
Life events and family changes
Central to SLID's demographic potential is information on family relationships, which makes it possible to accurately identify blended and multi-generational families. The longitudinal aspect permits the study of life events and their determinants or impact. For example, what are the family's economic circumstances preceding a marriage breakup, and what are they for each spouse and child following a separation?
Educational advancement and combining school and work
It is possible to view educational activity and attainment in the evolving context of an individual's other activities and family circumstances? What are the family circumstances of young people pursuing post-secondary education? How much do high school or postsecondary students combine work and school?
SLID uses computer-assisted telephone interviewing (CATI) for data collection. CATI interviews are conducted by telephone and the results are simultaneously entered in a computer that guides the interviewer through the questionnaire.
Because of its complexity as a longitudinal survey, SLID benefits greatly from CATI's potential for improving data quality. For example, there are many dates to collect in the course of a labour interview—dates worked, dates of jobless spells, absences from work and so on. With CATI, interviewers can remind respondents of information they provided in a previous interview. This helps respondents remember start and end dates of jobs and reduces the tendency to incorrectly associate these dates with the beginning or end of calendar years.
Computer-assisted interviewing helps keep track of members returning to the household and individuals returning to employers, rather than treating these members or employers as completely new.
Proxy response is accepted in SLID. This procedure allows one household member to answer questions on behalf of any or all other members of the household, provided he or she is willing to do so and is knowledgeable.