Quantifying the Effect of GST on Inflation in Australia’s Capital Cities: An Intervention Analysis: Discussion Paper No 153
Bibliographic record
Abstract
This paper examines the magnitude and duration of the GST effect on inflation in Australia’s eight major capital cities using the Box and Tiao intervention analysis and quarterly data spanning from 1948:4 to 2003:1. We found that GST had a significant but transitory impact on inflation only in the September quarter of 2000 when this new tax system was implemented. In this quarter inflation showed an additional increase of 2.6 per cent in Sydney (minimum effect) and 2.8 per cent in Australia as a whole, the same figure for Hobart was 3.3 per cent (maximum effect). Based on the Wald test results, we have also found some evidence that there is no significant (or substantial) difference in the average price changes among major capital cities. We could not reject the null hypothesis that GST increased the CPI by 2.8 per cent across the board in various cities. These results are also consistent with previous studies/surveys.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".