Bibliographic record
Abstract
This thesis is comprised of three essays on international macroeconomics.The first chapter examines empirically both the long-run and short-run impacts of the exchange rate volatility on manufacturing sector and bilateral exports during the sample period of 1999-2010 in five major ASEAN countries.A set of autoregressive distributed lag bounds tests are applied to examine the long-run level relationships among the variables, and long-run impacts of exchange rate volatility on exports.Seemingly unrelated regressions models with error corrections are estimated to capture shortrun dynamics.Significant and negative impacts of exchange rate volatility on exports are widely observed, which suggests risk averse exporters shift resources away from exporting to reduce exposure to higher exchange rate risk.The second chapter employs the economic policy uncertainty index (EPU) developed by Baker et al. (2013) to empirically examine its effect on economic growth across both advanced and emerging countries over 1985-2006.In addition, this study aims to identify the channels through which the EPU affects economic growth.A series of Kiviet's estimators are utilized for this dynamic panel data analysis.The results confirm that higher economic policy uncertainty reduces economic growth and the three channels of economic growth, physical capital accumulation, human capital accumulation, and total factor productivity (TFP) for both country groups.The third chapter develops a set of two-country open economy dynamic stochastic general equilibrium models to explore cross-country correlations among real variables. First and foremost, my deepest gratitude goes to my thesis co-supervisors, ProfessorHashmat Khan and Professor Raúl Razo-Carcia, for their constant guidance, support and encouragement in this process.Without their help and patience, insight and knowledge, and advice and comments, I would have not been able to complete the dissertation.I learned numerous skills in programming econometric models, building up theoretical models and running simulations, all of which will be my invaluable assets eternally.They both have been my role models, and have taught me not only the commitment as an economist but also lessons on personal life and career development.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.015 | 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".