Bibliographic record
Abstract
In Australia, exchange rate volatility has significantly increased after the floating of the exchange rate in 1983. On an international basis, there have been concerns about the possible detrimental effects exchange rate volatility could have on trade volumes and productivity levels. Since productivity growth and trade have been regarded as crucial factors in the promotion of sustainable economic growth and improving the material living standards for Australians, further research into the relationship between exchange rate volatility and trade/productivity will prove to be useful to policy makers. The objective of this study is twofold. Firstly, in light of the Australia-United States (US) productivity gap, this thesis will investigate whether there is reverse causality flowing from the real exchange rate movements/volatility to labour productivity in Australia. The importance of significant exchange rate depreciation/volatility having a negative impact on productivity has been highlighted by Harris (2002) for the case of Canada. Secondly, the impact of exchange rate volatility on Australian export volumes to US and Japan will be analysed. Although extensive theoretical and empirical research on this relationship has been conducted, this issue has remained highly ambiguous. To date, no empirical study has taken into consideration the threshold effects of exchange rate volatility on export volumes. Therefore, this thesis examines the relationship between exchange rate volatility and trade/productivity via linear and non linear threshold estimations of the trade and productivity models. The non linear threshold models estimation in this thesis is based on Hansen (2000)'s methodology. To ensure that sound economic interpretations of the models can be made, cointegration tests will be conducted and Vector Error Correction Models (VECMs) will be estimated. The econometric results obtained from this thesis indicate that long run equilibrium relationships between exchange rate volatility and trade/productivity exist. However, Granger Causality tests employed could not find evidences supporting the reverse causality link for the case of productivity. Finally, significant threshold effects of exchange rate volatility on trade/productivity have been tested for, suggesting that standard trade/productivity models involving exchange rate volatility have understated their true underlying relationships.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".