Bibliographic record
Abstract
This thesis consists of three empirical essays that study two independent topics: income under-reporting and immigrants’ portfolio allocations. The first essay forms Chapter 2 where we use data from the Survey of Financial Security and the Survey of Household Spending to estimate the incidence and extent of income underreporting in Canada. We find that roughly 20% to 40% of households underreport income by, on average, roughly $6,000 in 1999. In contrast to the existing literature, we show that self-employment status is a poor indicator of income under-reporting. We find that roughly 26% of non self-employed households under-report income, regardless of how self-employment status for households is determined. We profile income under-reporters and find that income underreporting is pervasive. We propose a simple ratio method of identifying income-under-reporting households for our second essay, Chapter 3. Our method is a straight-forward application of the Permanent Income Hypothesis; that is, households make consumption decisions based on their expected lifetime income not their reported lifetime income implying that consumption-to-income ratios should be higher for under-reporting households. We argue for using housing costs as the consumption measure in our approach. Our results confirm that households that under-report their income have mortgage-to-income ratios (MIR) or rent-to-income ratios (RIR) well in excess of those households that do not under-report. Using this finding, we propose using a Receiver Operating Characteristic (ROC) curve to determine the optimum cutoff threshold for MIR/RIR to detect under-reporters. Our third essay, Chapter 4, uses data from the 1999 and 2005 Survey of Financial Security to investigate the differences in portfolio allocations and values between immigrants and Canadian-born households. In general, we find that immigrants hold more real estate and less pension assets relative to Canadian-born households. Limited cohort analysis suggests that settled immigrants’ portfolio allocations are similar to that of Canadian-born households in contrast to recent immigrants’ portfolios. We also find evidence that the length of time living in Canada has a positive effect on ownership rate, share and value of both real estate and pension assets.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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 source (direct Gemma or distilled Codex), 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".