Estimating Worker Information Gaps From A Stochastic Wage Frontier: A Study Of Canadian Labour Markets
Bibliographic record
Abstract
In the presence of imperfect information in labour markets, optimal job search entails accepting a wage offer if it exceeds a workers reservation wage. However, this generally means that a worker with a given skill, will not earn the maximum wage on offer, and the gap between the maximum wager and the wage earned could be viewed as an indicator of labour market inefficiency arising from worker information gaps. The inefficiency arises because information is costly, so workers do not search long enough to discover the maximum wage, which would otherwise be sought and earned if information were costless. The aim of this paper is to empirically investigate the extent of labour market inefficiency within and across a number of population strata in Canada. These strata include individuals grouped according to various socio-economic and demographic characteristics such as gender, geographical location, education, and immigration status. The econometric model adopted is the stochastic frontier function used initially extensively in studies of production and cost efficiency of firms, and subsequently employed in studies of worker information gaps. The data we use are drawn from the 2001 Census of Canada.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".