Three Essays in Macroeconomics with a Focus on Economic Growth, Monetary Policy and Knowlege Dissemination
Bibliographic record
Abstract
This thesis includes three essays on empirical macroeconomics.The first chapter applies modern ideas-oriented growth accounting, based on the semi-endogenous growth theory of Jones (2002), to compare the sources of Canadian and U.S. economic growth between 1981-2014.Two features stand out in comparison to the U.S. growth experience over the same period.First, over a full percentage point of the average U.S. growth of 1.64 percent is due to excess ideas growth.Second, the constant growth view' that reconciles large sources of transitional growth with relatively stable average growth is not supported in Canada.The second chapter of this thesis examines the empirical link between movements in interest rates and capacity utilization, using 2SLS fixed effects estimations in a panel setting of 21 U.S. manufacturing industries between 1975-2011.The study arrives at three main findings: (a) In most industries a cut in the interest rate does not simultaneously stimulate capacity utilization; (b) in contrast to previous studies, the results do not show evidence that durable-goods industries are more sensitive to interest rate changes than other industries are; and (c) in many industries, the interest rate and capacity utilization move in the same direction.This suggests that First and foremost, I would like to express my special appreciation and gratitude to my advisor, Professor Hashmat Khan, who has been a tremendous mentor for me.He has supported and encouraged
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.007 |
| 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".