Employment Insurance Coverage Survey, 2014
hdl:11272/10346UNF:5:cgA2BMraCPIPSluegQH0Tg==
Version: 3 – Released: Thu Jul 20 14:45:11 PDT 2017
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TitleEmployment Insurance Coverage Survey, 2014
Study Global IDhdl:11272/10346
Other IDStatistics Canada: 89M0025XCB
ProducerStatistics Canada (Statcan)
Production Date2016
Production PlaceOttawa
DistributorStatistics Canada (Statcan)
Distribution DateMarch 08, 2016
Deposit DateMarch 09, 2016
SeriesEICS, Employment Insurance Coverage Survey
Version2.0, June 29, 2017
Original Dataverse
Description and Scope
Description

The main purpose of this survey is to study the coverage of the employment insurance program. It provides a meaningful picture of who does or does not have access to EI benefits among the jobless and those in a situation of underemployment. The Employment Insurance Coverage Survey also covers access to maternity and parental benefits.

The survey was designed to produce a series of precise measures to identify groups with low probability of receiving benefits, for instance, the long-term jobless, labour market entrants and students, people becoming unemployed after uninsured employment, people who have left jobs voluntarily and individuals who are eligible, given their employment history, but do not claim or otherwise receive benefits. The survey provides a detailed description of the characteristics of the last job held as well as reasons for not receiving benefits or for not claiming.

Through the survey data, analysts will also be able to observe the characteristics and situation of people not covered by EI and of those who exhausted EI benefits, the job search intensity of the unemployed, expectation of recall to a job, and alternate sources of income and funds.

Survey data pertaining to maternity and parental benefits answer questions on the proportion of mothers of an infant who received maternity and parental benefits, the reason why some mothers do not receive benefits and about sharing parental benefits with their spouse. The survey also allows looking at the timing and circumstances related to the return to work, the income adequacy of households with young children and more.

Description Date2016
KeywordsCountry::Canada (ACV); Social Indicators (ACV)
Time Period CoveredJanuary 01, 2013 - December 31, 2014
Date of CollectionApril, 2014 - February, 2015
Country/NationCanada (CA)
Geographic CoverageCanada, excluding provinces
Geographic UnitRegions of Canada
Geographic BoundingWest Bounding Longitude: -141.018 East Bounding Longitude: -52.6194 North Bounding Latitude: 83.1355 South Bounding Latitude: 41.6814
Unit of AnalysisIndividuals
UniverseThe target population for this survey is a subset of the target population for the Labour Force Survey (LFS). Specifically excluded from the LFS coverage are residents of the Yukon, Northwest Territories and Nunavut, persons living on Indian Reserves, full-time members of the Canadian Armed Forces and inmates of institutions. These groups together represent an exclusion of approximately 2% of the population aged 15 or over.
Kind of DataSurvey data
Data Collection / Methodology
Time MethodCross-sectional
Data CollectorStatistics Canada
FrequencyAnnual
Sampling Procedure

The Employment Insurance Coverage Survey (EICS) is administered to a sub-sample of individuals in the Labour Force Survey, and therefore its sample design is closely tied to that of the LFS. The EICS uses the rotation groups that completed their six months in the LFS in March, June, October or December. Mothers from four additional rotation groups are also selected to obtain an adequate sample size.

The LFS sample is further stratified using the EICS types which are:

  1. persons who were unemployed during the reference week;
  2. persons employed part-time during the reference week;
  3. persons not in the labour force during the reference week but with some employment during the two years prior to the reference week and all mothers not working (including on maternity leave) and not looking for work;
  4. persons employed full-time during the reference week and who started their current job during the previous two months and
  5. mothers of infants less than one year old, who worked during the reference week.

One hundred percent of the available LFS sample available is kept for some stratum and a sub-sample of 70 or 50% is taken for others, using simple random sampling. In order to reduce the response burden within the household, a maximum of three persons per household are selected.

Only the full-time employed (Type 4) who have experienced an interruption in work in the two months prior to the survey reference week need to be interviewed. Since this information was not available from the LFS interview, all full-time workers with short job tenure at their current job were selected. The question on work interruption was asked in the EICS and respondents who worked continually over the two months prior to the reference week were not asked further questions. They are out-of-scope for the survey.

Collection Mode

Responding to this survey is voluntary.

Data are collected directly from survey respondents.

Individuals selected for the EICS are contacted three to seven weeks after their last LFS interview. All interviews are conducted over the telephone using a computer assisted interviewing application. Proxy response is not allowed in the EICS. Responses to survey questions are captured directly by the interviewer using the computerized questionnaire.

Similar to the LFS, the interviewers are asked to make all reasonable efforts to obtain the EICS interview. Refusals at first contact are followed up by a senior interviewer. However, contrary to the LFS, no letters are sent to help obtain the respondent's cooperation.

Type of Research InstrumentStructured
Actions to Minimize LossesSimilar to the LFS, the interviewers are asked to make all reasonable efforts to obtain the EICS interview. Refusals at first contact are followed up by a senior interviewer. However, contrary to the LFS, no letters are sent to help obtain the respondent's cooperation.
Weighting

The calculation of the weights for the EICS incorporates the individual weights calculated for the LFS, as well as some estimates from this survey. Further adjustments are made to the LFS individual weights to take into account special features of the EICS.

The LFS individual weights are multiplied by 6, reflecting the use of one in six rotation groups per collection cycle (for mothers, the LFS weight is multiplied by 3). Another adjustment accounts for the EICS sub sampling for some strata; non-response is compensated taking geography, respondent type (1 to 5) and gender into consideration.

A final adjustment is done using two external non-overlapping independent sources: counts for regular beneficiaries with and without earnings (for groupings of administrative regions) and LFS estimates for each respondent type (the unemployed, part-time workers, not in the labour force having worked in the past two years and some full-time workers). Mothers who do not also meet the criteria for one of these 4 groups are not impacted by the adjustment for LFS characteristics. This calibration process ensures that the estimates produced with the EICS data are comparable the counts from the external sources.

Bootstrap weights are calculated to facilitate the calculation of variance for specific estimates. The Bootstrap weights were also used to create quick reference tables for variance estimates.

Cleaning Operations

Some editing is done online at the time of the interview. Where the information entered is out of range (too large or small) of expected values, or inconsistent with the previous entries, the interviewer is prompted to seek correction of confirmation from the respondent (for instance employment earnings).

The main type of errors treated after collection was errors in questionnaire flow, where questions which did not apply to the respondent were found to contain answers or conversely, when relevant questions were missed. A computer edit automatically eliminated superfluous data. All questions not included on the valid path based on previous answers are set to Valid Skip (6, 96, 996 ...). The 'Not stated' reserved codes (9, 99, 999...) are used to identify missing data resulting from issues with the computerized questionnaire or questions that were skipped because the respondent could not answer previous filter questions (Don't Know or Refusal).

There was no other type of editing done on questionnaire items. Therefore, some internal consistency may become apparent when conducting analysis. One notable example is the item on hourly earnings (HRLYEARN) which does include a small percentage of outliers and internal inconsistencies (working individuals reporting zero earnings).

Estimates of Sampling Error

While considerable effort is made to ensure high standards throughout all stages of collection and processing, the resulting estimates are inevitably subject to a certain degree of error. These errors can be broken down into two major types: non-sampling and sampling.

The basis for measuring the potential size of sampling errors is the standard error of the estimates derived from survey results. Because of the large variety of estimates that can be produced from a survey, the standard error of an estimate is usually expressed relative to the estimate to which it pertains. This resulting measure, known as the coefficient of variation (CV) of an estimate, is obtained by dividing the standard error of the estimate by the estimate itself and is expressed as a percentage of the estimate.

Other Forms of Data AppraisalThe data was mainly evaluated against historical trends. The primary focus was the derived variables created to provide comparable historical data for the period covering 2000 to 2005. Many direct questionnaire items are not comparable for this period due to the major questionnaire redesign implemented in 2004.
Data Availability
Number of Files 12
Terms of Use
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APPENDIX II

End-use Licence Agreement for Postal CodeOM Conversion File, Postal Codes OM by Federal Ridings File and Postal CodeOM Conversion File Plus (“data product”)

The Government of Canada (Statistics Canada) is the owner or a licensee of all intellectual property rights in this data product. With your payment of the requisite fee, you (hereinafter referred to as 'the Licensee') are granted a non-exclusive, non-assignable and non-transferable licence to use this data product subject to the terms below. This licence is not a sale of any or all of the rights of the owner(s). The data product includes information taken with permission from © Canada Post Corporation. All rights reserved. Information taken with permission from Canada Post Corporation does not form part of the Government of Canada open data portal.

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(i) addressing mail;

(ii) presorting addressed mail;

(iii) preparing unaddressed mail by householder count for delivery

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TERMINATION

10.(1) Statistics Canada may, by providing ten days written notice to the Licensee, terminate this Agreement if the Licensee fails to comply with any of the terms of this Agreement and to remedy such breach within the notice period.

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AMENDMENT

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ENTIRE AGREEMENT

14. This Agreement constitutes the entire agreement between Statistics Canada and the Licensee with respect to the Licensee’s right to use the CIHI Files and related documentation.

APPROPRIATE LAW

15.This Agreement shall be governed and construed in accordance with the laws of the province of Ontario and the laws of Canada applicable therein. The parties hereby attorn to the exclusive jurisdiction of the Federal Court of Canada.


Appendix A – Approved Postal Code Data Matching Uses for DLI Accredited Canadian Post Secondary Institution

Matching Postal Code data to geography for:

  • Teaching and learning purposes.

    E.g.: Students can download PCCF on their laptop to do their assignments. This includes projects, maps, analytical papers, etc. Faculty can download and use the PCCF in teaching exercises.
  • Research purposes

    E.g.: Can be used in analysis to write articles that are published in journals. The data is not shared but the results are published. This also includes thesis for Masters or Doctorate where results are required to be public.
  • Planning purposes – where the institution can use the information in planning student recruitment activities or find out where these students are coming from.

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