Has the Financial Crisis Changed the Business Cycle Characteristics of the GIIPS Countries?
Bibliographic record
Abstract
Since the financial crisis erupted in 2008, the governments of Portugal, Ireland, Italy Greece and Spain (GIIPS) find themselves in a position where financing their debts has become increasingly difficult. As a result, these governments reduced government expenditure and/or increased taxes in order to reduce their deficits. Hence, whilst other countries in the Eurozone – notably Germany - enjoyed a recovery from the financial crisis, the GIIPS countries only just started to recover. It is therefore no surprise that the business cycles of the northern and southern European countries diverged, and there was and still is a real fear of deflation. This poses a risk for the Eurozone, as it makes the common monetary policy less effective. In this paper we analyse these business cycles in detail. We ask whether the financial crisis has changed the characteristics of the business cycles of the GIIPS countries. For example, the austerity measures in Greece may lead to a convergence of government spending between Germany and Greece and to greater convergence of business cycles in both countries. If it does, then there is some hope that the common monetary policy will return to being effective in the future. But it may not. The austerity measures could also lead to greater divergence between Greece and Germany, in which case leaving the monetary Union would not only be beneficial for Greece. It might be unavoidable.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".