Bibliographic record
Abstract
My thesis, entitled Essays in Applied Monetary Economics, consists of two essays concerning issues of the monetary transmission mechanism in Canada. The first essay deals with the demand for money. Traditional studies estimating the long-run demand for real money in Canada assume that narrow money, or M1, bears zero interest. However if implicit interest has been paid, such interest should be taken into account in determining the opportunity cost of holding money. We present evidence showing that the banking industry in Canada moved from being characterized as oligopolistic over the 1960's and 1970's to more competitive over the 1980's and 1990's. Using quarterly data over the period 1961:1–2000:3 we construct a competitive own rate of return variable in a manner similar to Klein (1974) and include it in the demand for money. From three estimation methodologies, the central result is that over the period 1960:1–1980:3 where the degree of competition is low, the conventional money demand model which omits an own rate of return performs well. However, over the period 1982:2–2000:3, the own rate of return is correctly signed and statistically significant. Along with an improved money demand specification over the latter period, this provides independent evidence that the market for demand deposits became more competitive. The second essay examines whether the effects of monetary shocks have differential regional effects. We identify three possible sources of regional effects: differences in the importance of interest-sensitive industries, differences in the contribution of exports to output, and differences in the shares of small firms. Impulse responses are derived for provincial employment levels. The results show that Newfoundland and P.E.I. are strongly adversely affected by a monetary contraction. Manitoba, Saskatchewan and Alberta are also affected. Ontario is moderately affected, while Quebec is marginally unaffected. The responses New Brunswick, Nova Scotia, and British Columbia are statistically insignificant. The factors contributing to these results is the contribution of manufacturing and primary goods to GDP and to exports. The higher are each, the greater the response to monetary policy. Descriptive data show that the maritime and prairie provinces have relatively high contributions of primary based output to provincial GDP and exports, while Ontario and Quebec have relatively high contributions of manufacturing output to provincial GDP and to exports.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.016 | 0.006 |
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".