The 1998 Canadian Bank Merger Decision and the 2008 Financial Crisis: Factual and Counterfactual Investigations
Bibliographic record
Abstract
The observed stability of large Canadian banks during the 2008 financial crisis, in contrast with several American and European counterparts, poses a puzzle.This puzzle is explored through three essays, each pursuing a question with a different method.Yet all three are linked to the historic interlude marked by the 1998 government rejection of proposed mergers of four large Canadian banks and by the 2008 crisis when the banks remained stable.Essay One is a The genesis of this dissertation reaches back to the completion of my bachelor's degree at Dalhousie University in 1996, when outstanding questions about economics led me to later study the methodology of economics at the University of Ottawa through a master's degree between 2000 and 2003.Along the way, I recall the announcement of proposed bank mergers in 1998.While a prominent question at the time was whether consolidation would lead to the greater concentration in the Canadian banking industry, there was less thought to the consequences for bank stability.The years at Ottawa involved not only the study of methodology and heterodox economics under the supervision of Dr. Mario Seccareccia but also working with Mario as his teaching assistant for Canadian economic history.It was there where we began a discussion about the merits of the counterfactual method.It was also during these years when I decided that I would only undertake a doctorate if a question of sufficient interest revealed itself to me.The fall 2007 was pivotal: I married Brenna MacNeil and began working at the federal Department of Finance, all the while an international financial crisis began to gather.The Department was a good vantage point from which to observe the unfolding crisis and the public responses to it.It was here where I became interested in the puzzle of Canadian bank stability and wondered about the role of the 1998 bank merger decision.With our second daughter having just been born, Brenna supported me taking a leave of absence from the public service to begin this doctorate in September 2011.This set of three essays took time to shape, but ultimately came together through the committed supervision of my three-person committee.Early in the journey, Dr. Saul Schwartz expressed intrigue (rather than fear) with the challenge of a counterfactual exercise.Saul offered to be part of committee, and ultimately became my project's overall coordinator as well as supervisor for Essay Two and coach in matters academic and intellectual.One of my regrets of finishing this doctorate is that I will no longer benefit from our regular meetings.Dr. Seccareccia accepted my invitation to extend our early discussions about Canadian economic history and the counterfactual method by acting as supervisor of Essay Three.I am fortunate to have had Mario as a teacher for close to twenty years.Finally, it was a chance glance at Dr. Randall Germain's 2010 book on financial governance that led me to his office in Carleton's political science department.Through supervising Essay One, Randall introduced me to the thought of Robert Cox, notably his "method of historical structures".In hindsight, this introduction was a watershed moment in the evolution of my dissertation's overall framework, and more generally my intellectual orientation, given the links between Cox's framework and my early exploration of economic methodology.I have been blessed to have had these three scholars provide the necessary guidance and nudges to move me along my journey.
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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 | 0.041 | 0.158 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".