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A systematic review and meta-analysis on the effects of ill health and health shocks on labour supply

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A systematic review and meta-analysis on the effects of ill health and health shocks on labour supply. / Shawa, Ken Chamuva; Hollingsworth, Bruce; Zucchelli, Eugenio.
In: BMC Systematic Reviews, Vol. 13, No. 1, 52, 03.02.2024.

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Shawa KC, Hollingsworth B, Zucchelli E. A systematic review and meta-analysis on the effects of ill health and health shocks on labour supply. BMC Systematic Reviews. 2024 Feb 3;13(1):52. doi: 10.1186/s13643-024-02454-y

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@article{79e25a08fd764ceba4744589207e7594,
title = "A systematic review and meta-analysis on the effects of ill health and health shocks on labour supply",
abstract = "Background: Several studies have explored the effects of ill health and health shocks on labour supply. However, there are very few systematic reviews and meta-analyses in this area. The current work aims to fill this gap by undertaking a systematic review and meta-analysis on the effects of ill health and health shocks on labour supply. Methods: We searched using EconLit and MEDLINE databases along with grey literature to identify relevant papers for the analysis. Necessary information was extracted from the papers using an extraction tool. We calculated partial correlations to determine effect sizes and estimated the overall effect sizes by using the random effects model. Sub-group analyses were conducted based on geography, publication year and model type to assess the sources of heterogeneity. Model type entailed distinguishing articles that used the standard ordinary least squares (OLS) technique from those that used other estimation techniques such as quasi-experimental methods, including propensity score matching and difference-in-differences methodologies. Multivariate and univariate meta-regressions were employed to further examine the sources of heterogeneity. Moreover, we tested for publication bias by using a funnel plot, Begg{\textquoteright}s test and the trim and fill methodology. Results: We found a negative and statistically significant pooled estimate of the effect of ill health and health shocks on labour supply (partial r = −0.05, p < .001). The studies exhibited substantial heterogeneity. Sample size, geography, model type and publication year were found to be significant sources of heterogeneity. The funnel plot, and the trim and fill methodology, when imputed on the left showed some level of publication bias, but this was contrasted by both the Begg{\textquoteright}s test, and the trim and fill methodology when imputed on the right. Conclusion: The study examined the effects of ill health and health shocks on labour supply. We found negative statistically significant pooled estimates pertaining to the overall effect of ill health and health shocks on labour supply including in sub-groups. Empirical studies on the effects of ill- health and health shocks on labour supply have oftentimes found a negative relationship. Our meta-analysis results, which used a large, combined sample size, seem to reliably confirm the finding.",
author = "Shawa, {Ken Chamuva} and Bruce Hollingsworth and Eugenio Zucchelli",
year = "2024",
month = feb,
day = "3",
doi = "10.1186/s13643-024-02454-y",
language = "English",
volume = "13",
journal = "BMC Systematic Reviews",
issn = "2046-4053",
publisher = "BioMed Central",
number = "1",

}

RIS

TY - JOUR

T1 - A systematic review and meta-analysis on the effects of ill health and health shocks on labour supply

AU - Shawa, Ken Chamuva

AU - Hollingsworth, Bruce

AU - Zucchelli, Eugenio

PY - 2024/2/3

Y1 - 2024/2/3

N2 - Background: Several studies have explored the effects of ill health and health shocks on labour supply. However, there are very few systematic reviews and meta-analyses in this area. The current work aims to fill this gap by undertaking a systematic review and meta-analysis on the effects of ill health and health shocks on labour supply. Methods: We searched using EconLit and MEDLINE databases along with grey literature to identify relevant papers for the analysis. Necessary information was extracted from the papers using an extraction tool. We calculated partial correlations to determine effect sizes and estimated the overall effect sizes by using the random effects model. Sub-group analyses were conducted based on geography, publication year and model type to assess the sources of heterogeneity. Model type entailed distinguishing articles that used the standard ordinary least squares (OLS) technique from those that used other estimation techniques such as quasi-experimental methods, including propensity score matching and difference-in-differences methodologies. Multivariate and univariate meta-regressions were employed to further examine the sources of heterogeneity. Moreover, we tested for publication bias by using a funnel plot, Begg’s test and the trim and fill methodology. Results: We found a negative and statistically significant pooled estimate of the effect of ill health and health shocks on labour supply (partial r = −0.05, p < .001). The studies exhibited substantial heterogeneity. Sample size, geography, model type and publication year were found to be significant sources of heterogeneity. The funnel plot, and the trim and fill methodology, when imputed on the left showed some level of publication bias, but this was contrasted by both the Begg’s test, and the trim and fill methodology when imputed on the right. Conclusion: The study examined the effects of ill health and health shocks on labour supply. We found negative statistically significant pooled estimates pertaining to the overall effect of ill health and health shocks on labour supply including in sub-groups. Empirical studies on the effects of ill- health and health shocks on labour supply have oftentimes found a negative relationship. Our meta-analysis results, which used a large, combined sample size, seem to reliably confirm the finding.

AB - Background: Several studies have explored the effects of ill health and health shocks on labour supply. However, there are very few systematic reviews and meta-analyses in this area. The current work aims to fill this gap by undertaking a systematic review and meta-analysis on the effects of ill health and health shocks on labour supply. Methods: We searched using EconLit and MEDLINE databases along with grey literature to identify relevant papers for the analysis. Necessary information was extracted from the papers using an extraction tool. We calculated partial correlations to determine effect sizes and estimated the overall effect sizes by using the random effects model. Sub-group analyses were conducted based on geography, publication year and model type to assess the sources of heterogeneity. Model type entailed distinguishing articles that used the standard ordinary least squares (OLS) technique from those that used other estimation techniques such as quasi-experimental methods, including propensity score matching and difference-in-differences methodologies. Multivariate and univariate meta-regressions were employed to further examine the sources of heterogeneity. Moreover, we tested for publication bias by using a funnel plot, Begg’s test and the trim and fill methodology. Results: We found a negative and statistically significant pooled estimate of the effect of ill health and health shocks on labour supply (partial r = −0.05, p < .001). The studies exhibited substantial heterogeneity. Sample size, geography, model type and publication year were found to be significant sources of heterogeneity. The funnel plot, and the trim and fill methodology, when imputed on the left showed some level of publication bias, but this was contrasted by both the Begg’s test, and the trim and fill methodology when imputed on the right. Conclusion: The study examined the effects of ill health and health shocks on labour supply. We found negative statistically significant pooled estimates pertaining to the overall effect of ill health and health shocks on labour supply including in sub-groups. Empirical studies on the effects of ill- health and health shocks on labour supply have oftentimes found a negative relationship. Our meta-analysis results, which used a large, combined sample size, seem to reliably confirm the finding.

U2 - 10.1186/s13643-024-02454-y

DO - 10.1186/s13643-024-02454-y

M3 - Journal article

VL - 13

JO - BMC Systematic Reviews

JF - BMC Systematic Reviews

SN - 2046-4053

IS - 1

M1 - 52

ER -