International spillovers of US monetary and fiscal policies on small open economies
Bibliographic record
Abstract
This thesis focuses on the spillover effects of US monetary and fiscal policies on some of its main trading partners. The first chapter examines the cross-border macroeconomic effects of US monetary policy shocks on Canada and Mexico. To do this, we depart from the standard two-country VAR models routinely used in the literature by adopting a proxy VAR approach. In particular, we employ the first-stage model averaging method to construct an optimal instrument for US monetary policy shocks. The main finding of this chapter is that US monetary policy shocks have a significant impact on Canada’s macroeconomic variables, but not so for those of Mexico. The second chapter provides a theoretical model of the spillover effects of monetary policies based on various competing price regimes. It investigates the impact of the US monetary policy on its two neighbours, Canada and Mexico, under two different pricing regimes: Producer Currency Pricing (PCP); and Dominant Currency Pricing (DCP). We use a New Keynesian DSGE model to explain the transmission channels of monetary policy under various pricing systems. We find that in a Likelihood race, the model with DCP outperforms the model with PCP. Furthermore, by analysing the variance decomposition of business cycle fluctuations, the dominant role of foreign monetary shock in overall fluctuations is observed. The third chapter focuses on the second wing of the domestic policy which is fiscal policy. Since the recent financial crisis of 2007/08, the spillover effects of fiscal policies have become increasingly important in the wake of the zero interest rate lower bound. Using SVARs with external instruments and data on macroeconomics variables from the UK and Canada, we find that shocks to the US fiscal policy cause the trade balance in the UK to increase, while they cause the Canadian dollar to appreciate against the US dollar.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".