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Record W7047219963

Essays on Disability and the Labour Market

2022· article· en· W7047219963 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSuperconducting and THz Device Technology
Canadian institutionsnot available
Fundersnot available
KeywordsEarningsWageCognitive disabilitiesVariation (astronomy)CognitionDisability insuranceCognitive skillDuration (music)
DOInot available

Abstract

fetched live from OpenAlex

My dissertation consists of three chapters about the effects of disability and disability policy.\nThe second chapter analyzes the variation in labour market outcomes across disabilities by representing disability as a bundle of characteristics. Rich with information on the characteristics of a disabling condition, I use the Participation and Activity Limitation Survey to compare the relative importance of each {characteristic} and their interactions on employment, wages, hours worked, and annual employment income. The disability {characteristics} include the type of activity limitation, number of limitations, timing of onset, severity, and persistence. I find substantial cross-sectional variation in labour supply, wages, and annual earnings across the activity limitations. Severity is most predictive of labour supply, while persistence/ duration of disability is predictive of all outcomes. Cognitive types of disabilities have more impact on wages than physical. Lastly, I find the timing of onset has important implications for wages and annual income. My results are consistent with disabilities that onset by age eighteen inflicting additional wage penalties through reduced skill accumulation.\nThe third chapter uses Canadian survey and administrative tax data to estimate the effect of disability types in the ten years after onset on the level and composition of personal income. I distinguish disability types based on reported limitations to daily activities and group them into physical, cognitive, or concurrent (both). I find substantial heterogeneity in the effect on personal income across types. Following onset, people with cognitive disabilities experience larger and more permanent declines in employment and market income than those with physical disabilities. Those with cognitive disabilities receive similar increases in total government transfers and fewer transfers from programs designed for disability. Instead, this group offsets some of the decline in market income with transfer programs that target families. Finally, the estimated effect of concurrent disabilities on market income and government transfers appears to be additive as it equals the sum of the effects of physical and cognitive disabilities.\nThe fourth chapter observes that individuals with an early-onset (before age 18) disability attain less education than their non-disabled counterparts. This equates to an eighteen percentage point gap in post-secondary attainment between these populations in Canada. This gap relates to how disability affects the cost and return to investing in education and the availability of additional income through social insurance. I build and estimate a structural life-cycle model of education and labour market choices to analyze the effect of social insurance on education investments for early-onset individuals. I focus on two social insurance policies in Canada: social assistance (SA) and disability insurance (DI). Using linked Canadian survey and administrative tax data to estimate the model, I reproduce the education gap, life-cycle employment rates, and attachment to SA and DI. I find the effect of disability on the accumulation of human capital accounts for two-thirds of the education gap. However, 18.6\\% of the gap is related to disincentives from social insurance policies, mainly from added benefits in SA available for beneficiaries with disabilities. Through counterfactual experiments, I find decreasing the value of SA poses an insurance-incentive trade-off for early-onset individuals. Instead, post-secondary grants for early-onset individuals increase their educational attainment, employment, and improves welfare. Moreover, this policy helps pay for itself through added tax revenues and reduced dependence on SA.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.733

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.046
GPT teacher head0.283
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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