Outlook for the world economy and central bank implications
Bibliographic record
Abstract
We have upgraded our views for global economic growth to 6.8% in 2021 and 4.2% in 2022. In this podcast with Kim Mundy, Senior Economist & Currency Strategist and Belinda Allen, Senior Economist discuss the upgrade and themes behind it including the vaccine roll out and a lift in the size of the government sector in driving the recovery. Financial markets have drawn a straight line from economic recovery to inflation and higher interest rates. Kim runs through the outlook for the major economies of US, Canada, China, Japan, Eurozone and the UK and what it means for the central bank in each country. ------ DISCLAIMER ------Before listening to this report, you are advised to read the full Global Markets Research disclaimers which can be found at www.commbankresearch.com.au. Information in this podcast is of a general nature only. It does not take into account your objectives, financial situation or needs and does not constitute personal financial advice. This report provides general market-related information, and is not intended to be an investment research report. The information contained in this report is approved and distributed by Global Markets Research, a business division of the Commonwealth Bank of Australia ABN 48 123 123 124 AFSL 234945 (\\"the Bank\\"). The information is solely for informational purposes and is not to be construed as a solicitation or an offer to buy or sell any securities or other financial instruments. It does not constitute a personal recommendation or take into account the particular investment objectives, financial situations, or needs of individual clients. Where 'CBA data' is cited, this refers to the Bank proprietary data that is sourced from the Bank's internal systems and may include, but not be limited to, credit card transaction data, merchant facility transaction data and applications for credit. As the statistics take into account only the Bank's data it may not reflect all trends in the market. All customer data used, or represented, in this report is anonymised and aggregated before analysis and is used, and disclosed, in accordance with the Group's Privacy Policy Statement. The Bank believes that the information in this presentation is correct and any opinions, conclusions or recommendations are reasonably held based on the information available at the time of its compilation but no representation or warranty, either expressed or implied, is made or provided as to accuracy, reliability or completeness of any statement made.
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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) | 0.311 | 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".