Price and cost competitiveness. Quarterly data on price and cost competitiveness of the European Union and its Member States. First quarter 2002. ECFIN/266/1-02-EN
Bibliographic record
Abstract
IThe format of the series "price and cost competitiveness of the euro area and the individual Member States of the European Union" has been modified.In order to improve our assessment of the competitiveness of the euro area and individual Member States, the database has been disentangled from the assessment part.This allows for a timely presentation of the Database on price and cost competitiveness for the euro area, for each Member State, as well as for five other industrial countries (United States, Japan, Norway, Australia, and Canada 1 ).The second component offers an analytical rather than a purely descriptive assessment of the main features of the euro area and the individual member States' price and cost competitiveness.This assessment will be made twice a year, while the quarterly update of the database is maintained.The nominal effective exchange rate (NEER) of a country (or currency area) aims to track changes in the value of that country's currency relative to the currencies of its principal trading partners.It is calculated as a weighted average of the bilateral exchange rates with those currencies.Changes in cost and price competitiveness depend not only on exchange rate movements but also on cost and price trends.The real effective exchange rate (REER) aims to assess a country (or currency area's) price or cost competitiveness relative to its principal competitors in international markets.It corresponds to the NEER deflated by selected relative price or cost deflators.Countries in the euro area share a single currency and there is no longer any exchange rate between them.For these countries, the terms "nominal effective exchange rate" and "real effective exchange rate" have been replaced by the terms "trade-weighted currency index" and "relative price and cost indicators" but the underlying concepts and their calculation remains the same.The tradeweighted currency indices for individual countries using the euro may diverge because they have different trading patterns.In addition, the relative price and cost indicators may evolve differently due to diverging price and cost trends.A comprehensive assessment of developments in cost and price competitiveness should ideally draw on various measures of the real effective exchange rate.Most international trade is in manufactured goods and some widely used measures focus on unit labour costs in the manufacturing industry (ULCM).However, in-house labour costs account for only a limited share of total costs jn the manufacturing industry.The sector purchases a growing amount of inputs from the rest of the economy, including financial services, marketing, accounting etc.In addition, an increasing amount of services are traded internationally.Therefore, some prefer to consider developments based on unit labour costs in the whole economy (ULCE).Moreover, capital costs account for a sizeable fraction of total costs.Price measures such as the GDP-deflator (PGDP) include the return on capital.On the other hand, the measures based on ULCE and PGDP cover many sectors whose output is neither directly nor indirectly traded.The report also displays real exchange rates based on the deflator of private consumption, and the deflator of exports of goods and services (PX).This series is also available on the Internet.Our Web sitel permits the downloading of standard statistics to your PC or Macintosh.Moreover, differently defined nominal and real exchange rates are available upon request.A technical annex provides further details.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.017 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.017 |
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".