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This monitoring report uses the Canadian Out-of-Employment Panel (COEP) survey, which collected a range of personal and employment-related information from individuals who experienced a job separation as recorded on HRDC’s Record of Employment (ROE) administrative file. COEP includes timely information about EI benefits collection, SA receipt, and other personal information about the individual’s household and financial situation.

Each survey participant was interviewed twice following the job separation that placed him or her on the survey. The first interview (wave 1) occurred one year after the job separation, and the second interview (wave 2) occurred some nine months after the first interview. Since July 1996, COEP has collected information for a total of 12 cohorts:¹

• cohorts 1 to 4 had a job separation in one of the four quarters prior to EI implementation (i.e. ,1995 Q3 to 1996 Q2);
• cohort 5 and 6 had a job separation after the EI changes of July 1996 (i.e., 1996 Q3 and 1996 Q4);
• cohorts 7 to 10 had a job separation in one of the four quarters following the EI changes of January 1997 (i.e., 1997 Q1 to 1997 Q4);
• 1 cohort with job separation during 1998 Q3, 2 years after the implementation of EI reform; and
• 1 cohort with job separation during 1999 Q3, 3 years after the implementation of EI reform.

For the purposes of this study, the pre-EI reform period (third quarter of 1995 to second quarter of 1996) is compared to the post-EI reform period (first to fourth quarter of 1997) as a means of determining the changes associated with EI reform. Using four pre-EI reform quarters and four post-EI reform quarters, it becomes possible to control for changes that would have been associated with seasonality alone. No analysis was done during the first phase of EI reform (third and fourth quarters of 1996) as the implementation of EI reform was not complete and any resulting analysis may be inconclusive.

The first section of this paper focuses on the exhaustion of benefits by UI/EI claimants and summarizes claim exhaustion rates (CERs) before and after EI reform for specific demographic, industry and occupation groups. Then, probit regression analysis is used to test the significance of the observed change in the probability of exhausting EI claims while controlling for various characteristics.

The second part of the analysis deals with social assistance take-up. A comparison of SA use by claimants, both exhaustees and non-exhaustees, and by non-claimants is completed using wave one and wave two data. Wave two refers to the second interview of COEP, and, therefore, gives more indication about activities by individuals who were unemployed for a longer period of time.

Claim Exhaustion At First Interview

Claim exhaustion refers to the situation in which individuals who claimed EI benefits used up all entitled weeks of benefits. The number of weeks payable varies depending on each individual's number of weeks of insurable employment and the unemployment rate of their area. To measure the exhaustion rate, the share of individuals who received insurance claims and had their claims terminated within a year of their ROE job loss date is calculated. These include claimants whose entitlement weeks were used up completely and not those whose claims were terminated for other reasons.

Claim Exhaustion Rates Before and After EI Reform: Descriptive Results

Figure 1 and Table 1 reports exhaustion rates for each quarter of interviews. Both show an overall decrease in the CER. The CER seems correlated with the quarters and might be affected by seasonality. The average CER for the last four quarters is smaller than the average for the first four quarters, indicating a downward shift in the CER, in the years following EI reform.

The numbers shown in Table 1 are somewhat lower than those in a recent study² that found the CER to be in the 40 per cent range. In this report, the definition was narrowed so that only people whose claims were entirely terminated/exhausted within a year of their job loss were included.

Table 2 examines the CER by various characteristics. The results indicate that the CER is:

• higher among older workers;
• higher in the Atlantic Provinces and Quebec;
• higher for seasonal and temporary workers than for workers in other types of employment; and
• higher for workers who have a permanent layoff when compared to workers with other reasons for job loss.

Table 2 also compares the CER for various groups before and after EI reform.

• The most marked drops in the exhaustion rate were for women, seasonal and temporary workers, and residents of the Atlantic, Ontario and Prairies regions.
• Permanent workers experience almost no change in their EI exhaustion rate , neither did single individuals with no children at their care.
• Workers who lost their job because they quit voluntarily or had a temporary layoff experienced a decline in their CER.

Consistent with the expectation that the longer the employment period prior to a job loss, the more weeks of entitlement an individual will obtain, Table 3 confirms a decrease in CER as the number of months of tenure at last job increases.

Claim Exhaustion Rate: Regression Results

A probit regression is estimated to assess the significance of changes in CER. The dependent variable is the probability of exhausting an EI claim. The sample was restricted to only individuals who had a claim.

The probability of exhausting one's EI claim is estimated by assessing the infinitesimal change to the probability of exhaustion after controlling for a unit change in each of the personal and employment-related characteristics. These characteristics include age, gender, education, household composition, region of residency, employment type, industry, occupation, and race.

The potential impact of EI reform is examined by creating an interaction dummy variable which takes on the value of 1 when the independent variable occurs within the post-EI period, and 0 otherwise. For example, the female variable (itself a binary variable) is multiplied with the variable (EI reform) to allow for the slope coefficient of changes in probability of exhaustion for women in the post-EI period to be different than that of men. Moreover, it is generally believed that women have different labour-market behaviour than men.

The multivariate regression results presented in Table 4 confirm trends observed in the descriptive analysis section. Table 4 presents the direction and magnitude of the impact of each characteristic on the probability of exhausting EI claims. For the most part, the direction of change, as indicated by the sign of the coefficient, is the same as observed earlier in Table 2.

It is worthwhile to note that by employment type, workers in seasonal employment were less likely to exhaust their claim after EI reform. Temporary workers also experience a decrease in the probability of exhausting their claims.

Although the results presented here provide an overall picture, the exact causes of these changes is not clear as more evaluation work is needed to assess other aspects not covered in this paper, such as the impact of the improving economy, new entrants/re-entrants, etc. Therefore, it must be recognized that the exact impacts related to EI reform changes, such as the change to the hours-based system or the decrease in the number of insurable weeks, is not entirely clear in this context.

Footnotes

1	For more information on the COEP, see the report entitled “COEP as a Tool for Legislative Oversight, Monitoring and Evaluation”, HRDC.
2	See Strategic Evaluation and Monitoring, 1999. “Evaluation of Long-Term Unemployment in Canada: Outlook and Policy Implications.” Ottawa, Human Resources Development Canada.