Three Essays on Fiscal Policy
Bibliographic record
Abstract
This dissertation examines the domestic and international effects of fiscal policy shocks on country risk, stock markets returns and trading partners. There are three essays in this study. First essay examines the relative impacts of macroeconomic, financial and political variables on country risk for five advanced economies; the US, the UK, Canada and Singapore for 1984:M1-2014:M12 and Germany for 1990:M9-2014:M12 time periods. To do so, I follow a two stage estimation procedure. In the first stage, a CAPM is used to estimate time-variant country betas which are used as a proxy for country risk by using a DCC-GARCH model. Then, at the second stage, time variant country betas are regressed on a set of macroeconomic, financial and political variables to distinguish the relative effects of each variable on country risk. Finally, a Kalman Filter approach is used to re-estimate time-variant country betas as a robustness check. The empirical findings of this study show that even though the significance and the direction of the impacts of risk factors differ from one country to another, among macroeconomic variables, budget surplus and current account surplus have significant effects on most country betas, whereas, generally, political risk does not have a significant effect on country risk in advanced economies. In the second essay, I characterize the effects of fiscal policy shocks on aggregate and sectoral stock market returns in the US for 1975-2013 period with a Structural Vector AutoRegressive (SVAR) Model. The results of this study show that in case of an expansionary (tight) fiscal policy, aggregate stock market returns decrease (increase). Unexpectedly, neither sectoral stock returns respond to policy shocks in the same direction, nor is there an observed co-movement between the reactions of stock returns of different sectors. As energy and utility sector returns move in the same direction with aggregate returns, financial sector returns move in the opposite direction. Moreover, both positive government spending and positive government revenue shocks decrease industrial sector returns whereas increase healthcare sector returns. Finally, the third essay characterizes the results of US government spending shocks on domestic and foreign economies. To do so, I analyze the dynamic effects of a positive US government spending shock on real output and real household consumption of Canada and the US, as well as, the real exchange rate from 1957 to 2013 by employing a SVAR model. The findings of the study state empirical evidence in favor of a positive international transmission of domestic fiscal expansion. A positive US government spending shock increases not only US output and consumption but also Canadian output, as the real exchange rate appreciates.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 0.005 |
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".