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All (4) ((4 results))

  • 1. Heterogeneous causal effects of labour market programs: A machine learning approach Archived
    Articles and reports: 11-522-X202200100017
    Description: In this paper, we look for presence of heterogeneity in conducting impact evaluations of the Skills Development intervention delivered under the Labour Market Development Agreements. We use linked longitudinal administrative data covering a sample of Skills Development participants from 2010 to 2017. We apply a causal machine-learning estimator as in Lechner (2019) to estimate the individualized program impacts at the finest aggregation level. These granular impacts reveal the distribution of net impacts facilitating further investigation as to what works for whom. The findings suggest statistically significant improvements in labour market outcomes for participants overall and for subgroups of policy interest.
    Release date: 2024-06-28
  • 2. A Case Study in Administrative Data Informing Policy Development Archived
    Articles and reports: 11-522-X201700014714
    Description:

    The Labour Market Development Agreements (LMDAs) between Canada and the provinces and territories fund labour market training and support services to Employment Insurance claimants. The objective of this paper is to discuss the improvements over the years in the impact assessment methodology. The paper describes the LMDAs and past evaluation work and discusses the drivers to make better use of large administrative data holdings. It then explains how the new approach made the evaluation less resource-intensive, while results are more relevant to policy development. The paper outlines the lessons learned from a methodological perspective and provides insight into ways for making this type of use of administrative data effective, especially in the context of large programs.

    Release date: 2016-03-24
  • 3. Estimating the effects related to the timing of participation in employment assistance services using rich administrative data Archived
    Articles and reports: 11-522-X201700014718
    Description:

    This study assessed whether starting participation in Employment Assistance Services (EAS) earlier after initiating an Employment Insurance (EI) claim leads to better impacts for unemployed individuals than participating later during the EI benefit period. As in Sianesi (2004) and Hujer and Thomsen (2010), the analysis relied on a stratified propensity score matching approach conditional on the discretized duration of unemployment until the program starts. The results showed that individuals who participated in EAS within the first four weeks after initiating an EI claim had the best impacts on earnings and incidence of employment while also experiencing reduced use of EI starting the second year post-program.

    Release date: 2016-03-24
  • 4. Estimating the Impact of Active Labour Market Programs using Administrative Data and Matching Methods Archived
    Articles and reports: 11-522-X201700014740
    Description:

    In this paper, we discuss the impacts of Employment Benefit and Support Measures delivered in Canada under the Labour Market Development Agreements. We use linked rich longitudinal administrative data covering all LMDA participants from 2002 to 2005. We Apply propensity score matching as in Blundell et al. (2002), Gerfin and Lechner (2002), and Sianesi (2004), and produced the national incremental impact estimates using difference-in-differences and Kernel Matching estimator (Heckman and Smith, 1999). The findings suggest that, both Employment Assistance Services and employment benefit such as Skills Development and Targeted Wage Subsidies had positive effects on earnings and employment.

    Release date: 2016-03-24
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Articles and reports (4)

Articles and reports (4) ((4 results))

  • 1. Heterogeneous causal effects of labour market programs: A machine learning approach Archived
    Articles and reports: 11-522-X202200100017
    Description: In this paper, we look for presence of heterogeneity in conducting impact evaluations of the Skills Development intervention delivered under the Labour Market Development Agreements. We use linked longitudinal administrative data covering a sample of Skills Development participants from 2010 to 2017. We apply a causal machine-learning estimator as in Lechner (2019) to estimate the individualized program impacts at the finest aggregation level. These granular impacts reveal the distribution of net impacts facilitating further investigation as to what works for whom. The findings suggest statistically significant improvements in labour market outcomes for participants overall and for subgroups of policy interest.
    Release date: 2024-06-28
  • 2. A Case Study in Administrative Data Informing Policy Development Archived
    Articles and reports: 11-522-X201700014714
    Description:

    The Labour Market Development Agreements (LMDAs) between Canada and the provinces and territories fund labour market training and support services to Employment Insurance claimants. The objective of this paper is to discuss the improvements over the years in the impact assessment methodology. The paper describes the LMDAs and past evaluation work and discusses the drivers to make better use of large administrative data holdings. It then explains how the new approach made the evaluation less resource-intensive, while results are more relevant to policy development. The paper outlines the lessons learned from a methodological perspective and provides insight into ways for making this type of use of administrative data effective, especially in the context of large programs.

    Release date: 2016-03-24
  • 3. Estimating the effects related to the timing of participation in employment assistance services using rich administrative data Archived
    Articles and reports: 11-522-X201700014718
    Description:

    This study assessed whether starting participation in Employment Assistance Services (EAS) earlier after initiating an Employment Insurance (EI) claim leads to better impacts for unemployed individuals than participating later during the EI benefit period. As in Sianesi (2004) and Hujer and Thomsen (2010), the analysis relied on a stratified propensity score matching approach conditional on the discretized duration of unemployment until the program starts. The results showed that individuals who participated in EAS within the first four weeks after initiating an EI claim had the best impacts on earnings and incidence of employment while also experiencing reduced use of EI starting the second year post-program.

    Release date: 2016-03-24
  • 4. Estimating the Impact of Active Labour Market Programs using Administrative Data and Matching Methods Archived
    Articles and reports: 11-522-X201700014740
    Description:

    In this paper, we discuss the impacts of Employment Benefit and Support Measures delivered in Canada under the Labour Market Development Agreements. We use linked rich longitudinal administrative data covering all LMDA participants from 2002 to 2005. We Apply propensity score matching as in Blundell et al. (2002), Gerfin and Lechner (2002), and Sianesi (2004), and produced the national incremental impact estimates using difference-in-differences and Kernel Matching estimator (Heckman and Smith, 1999). The findings suggest that, both Employment Assistance Services and employment benefit such as Skills Development and Targeted Wage Subsidies had positive effects on earnings and employment.

    Release date: 2016-03-24
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