Bibliographic record
Abstract
This dissertation consists of three empirical chapters. The first chapter examines the extent to which real-world agents are rational in making quantitative expectations, an issue over which there is much debate. In this chapter dynamic models for new plant-level survey data are estimated in order to test rationality for manufacturing plants that report expectations of capital expenditures. An advantage of such data is that rationality is tested in environments where agents may not have knowledge of each others' expectations, so strategic motives for biases or inefficiencies are minimized. Model estimates and tests suggest that weak implications of rational expectations are rejected, as are adaptive expectations. The second chapter examines expectations formation in the economists' laboratory as psychologists have documented several biases and heuristics that describe deviations from Bayesian updating-a standard assumption for economists. Indeed, Confirmation Bias predicts that individuals will exhibit systematic errors in updating their beliefs about the state of the world given a stream of information. This chapter examines this bias within a non-strategic environment that motivates experimental subjects financially to provide probability estimates that are close to those of a Bayesian. Subjects revise their estimates of the state of the world as they receive signals. Comparing their estimates to those of a Bayesian shows that subjects display conservatism by underweighting new information. In addition, subjects display confirmation bias by differentiating between confirming and disconfirming evidence. The third chapter seeks to determine, through reduced-form Phillips curves estimates and a structural model, whether the indicator relationship between capacity utilization and inflation has diminished as in recent years high levels of capacity utilization have not led to higher inflation. In Canada, the capacity utilization rate is benchmarked to survey data, thereby providing a unique opportunity to empirically analyze this macroeconomic relationship. Estimates of time-varying parameters and structural break models indicate that there have been breaks over time in the relationship. The timings of the breaks suggest that increasing competitiveness and a rules-based monetary policy may help account for the demise of the relationship. Estimates of a monopolistically competitive sticky-price model economy qualitatively lend credence to this conjecture.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".