Survey of Labour and Income Dynamics (SLID) – 2009 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 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.
Free access to CANSIM tables
With this release, users now have free access to CANSIM's 202-series tables. They are available in several formats with any web browser. CANSIM tables can be found at CANSIM 202 series.
The 202 Series is also directly accessible in the Income in Canada publication using the Beyond 20/20 Table Browser (also free).
New approaches to low income
Since its inception, SLID has published statistics on low income based solely on the low income cut-offs (LICOs), even though other measures exist. To offer a better picture of all aspects of low income, Statistics Canada implements an approach that uses several different lines of low income (Low Income Lines, 2009-2010). Since last year, statistics are produced using three complementary measures: the LICOs, the low income measures (LIMs) and the market basket measure (MBM). The MBM was developed by Human Resources and Skills Development Canada1. Statistics Canada has always pointed out that these measures are not measures of poverty, but strictly measures of low income (On poverty and low income).
Though these measures differ from one another, they give a generally consistent picture of low income status over time: none should be considered 'the best'. Each contributes its own perspective and its own strengths to the study of low income. Together, the three provide a better understanding of the phenomenon of low income as a whole. This change also lets users choose the measure that best suits their needs. The MBM defines low income in relation to the cost of a predefined set of goods and services. The price of this 'basket' of goods and services takes into account regional differences in the cost of living. The LIM is based solely on the distribution of household income, and is intended as a reference for international comparisons. The LICOs are based on the relationship between the incomes and the consumption patterns of Canadian households as observed in 1992. The LICOs have been very widely used in Canada since the 1970s.
Another change in Statistics Canada's approach to low income is in the kinds of analyses being done. Since last year, statistics are no longer reported at the family level, but instead at the individual level: individuals are represented by their adjusted family income (for the LICOs and the MBM) or adjusted household income (for the LIMs). This change is directly in line with the recommendations of the Canberra Group on Household Income Statistics and complies with Statistics Canada's guidelines on income analysis. Because it is essential to portray the low income situation for the entire population, it is more appropriate to analyse individuals than families—this way, the statistics are not distorted by variations in the size of families in the various groups of interest. But this new approach still allows others to study low income according to family characteristics. For example, instead of discussing the incidence of low income in elderly families, we can discuss the incidence of low income among individuals who live in elderly families.
Lastly, some new statistics were introduced last year. For more information about these new statistics, please refer to the What you should know section on the Tables page of the 2009 Income in Canada product.
All these changes have been applied retroactively back to 1976, except the statistics based on the MBM, which were introduced in 2000, the first year the MBM was used by Human Resources and Skills Development Canada.
Use of a different equivalence factor
A family's reported income does not provide a sufficiently complete picture of its economic well-being. In addition, one needs to know how many people there are in that family. To account for the economies of scale associated with family size, an equivalence scale is used to adjust family income.
Since last year, adjusted family income is obtained by dividing family income by the square root of the number of members in the family. The estimates for past years have been revised accordingly. With respect to the LIM, the square root of the number of persons in the household will be used.
Introduction of new variables
Ontario material deprivation (OMD) data were collected for the 2009 reference year. The data are available only for households in Ontario.
The data were collected on behalf of the Ontario Government as research for their poverty reduction plan. Ontario households were asked about 10 items that were selected based on research by the Daily Bread Food Bank of Toronto, the Metcalf Foundation and the Caledon Institute of Social Policy. For each item, up to two questions were asked. The first question was whether an item was available to the household during the 2009 reference year: if it was not, the second question was if the household could not afford the item. For example, all Ontario households were asked whether they ate fresh fruit and vegetables every day; only those households that did not were asked if they did not because they could not afford to do so.
Based on households' responses to these questions, ten sets of OMD variables were produced—one set per OMD item. Each set is composed of a variable indicating whether the item was available to a household, a second variable indicating (only for households to which that item is unavailable) the reason the item was not available to the household, and a third variable flagging whether the household could not afford that item.
For further information, see
/bsolc/olc-cel/olc-cel?lang=eng&catno=75M0012X and http://news.ontario.ca/mcys/en/2009/12/ontario-deprivation-index.html.
Employment Insurance region
The household-level Employment Insurance (EI) region variable was revised to reflect 2006 Census-based geography.
Like the other household-level geography variables, the EI variable, for reference years before 1999, is derived based on the boundaries of the 1991 Census geography base. For reference years 1999 to 2004, it is derived from the 2001 Census geography base; for reference years 2005 to 2009, it is derived from the 2006 Census geography base.
Five new adjusted income variables were added at the economic family level. These variables are adjusted using the square root of the economic family size for their equivalence scale, and are available for all survey years.
Major income earner demographic information
Four new variables were added at the person level. These variables indicate the sex and age of households' and economic families' major income earner.
Changes to variables
The series of questions about courses, workshops, seminars or training related to a job was removed from the questionnaire.
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 poor' 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.
- 1. Hatfield, Michael; Pyper, Wendy, and Gustajtis, Burton. 2010 "First Comprehensive Review of the Market Basket Measure of Low Income". Applied Research Branch paper. Human Resources and Skills Development Canada. Summer. Paper version: ISBN: 978-1-100-16063-4, Cat. No.: HS28-178/2010E. PDF version: ISBN: 978-1-100-16064-1, Cat. No.: HS28-178/2010E-PDF. Departmental catalogue number: SP-953-06-10E. Copy available on request by contacting: MBM-MPC@hrsdc-rhdcc.gc.ca.
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