Another contraction in European household credit markets: Key findings from the ECRI Statistical Package
Bibliographic record
Abstract
The ECRI Statistical Package 2014 Lending to Households reveals that the total amount of outstanding household real debt at end-2013 contracted for the third consecutive year in both the EU member states (EU27) and the euro area (EA17). All in all, indicators point to less divergent growth patterns across member states in 2013, as the standard deviation of the sample in domestic currency recorded its lowest value in more than 15 years. Still, pronounced corrections continued in a few countries, especially in Slovenia, Portugal, Spain, Hungary and Latvia. The successive yearly contractions in the EU27 occurred despite significant easing in interest rates in many markets over the last few years. Gross disposable income of households, which is one of the main drivers behind households’ demand, and housing prices, which can affect both demand and supply of loans, have had strong effects on the dynamics of household debt since 2007. Considering household debt-to-GDP ratios, long-term comparisons between the different groups of countries composing the EU27 show that no convergence was observed across these groups and across EU27 countries in the years preceding the financial crisis. However, partly as a result of the 2008-09 financial crisis and its long-lasting effects, strong convergence was registered across EU27 countries between 2007 and 2013. Regarding non-financial corporation (NFC), the outstanding debt decreased again in 2013 in both the EU27 and the euro area. In 2013, the correction intensified in nominal terms in both the EU27 and the EA17, but slowed down in real terms in comparison with 2012. The Key Findings relate to the more detailed ECRI 2014 Statistical Package covering 38 countries: the 27 EU member states, three EU candidate countries (Croatia, Turkey and the Former Yugoslav Republic of Macedonia), the EFTA countries (Iceland, Liechtenstein, Norway and Switzerland) and four key global economies (the United States, Australia, Canada and Japan). The purpose of the package is to provide reliable statistical information that allows users to make meaningful comparisons in time and between these countries.
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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 | 0.001 | 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) | 0.001 | 0.002 |
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; both teacher heads agree on what is shown here.
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".