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Record W2811323347 · doi:10.1111/aepr.12224

Comment on “Instability in Europe and Its Impact on Asia”

2018· article· en· W2811323347 on OpenAlexaboutno aff
Soko Tanaka

Bibliographic record

VenueAsian Economic Policy Review · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsnot available
Fundersnot available
KeywordsWelfare stateBrexitEuropean unionPolitical economyState (computer science)PopulismWelfare capitalismGlobalizationEuropean social modelEuropean integrationWelfarePolitical scienceEconomicsDevelopment economicsEconomic policyMarket economyLawPolitics

Abstract

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Kaji (2018) explains in her introduction that three unintended consequences of European integration became renewed sources of instability and crises. While the European Union (EU) succeeded in economic integration, it has given rise to the following three unintended consequences: (i) growing anti-integrationist movements and Brexit; (ii) skepticism about the benefits of the free movements; and (iii) the burden of the welfare state, which brought social exclusion and populism movements of unemployed workers. The welfare state does not belong to European integration, but rather to each member state of the EU. So, problems of the welfare state should be checked up not at the EU but at the member state level. We saw in 2016 that the Brexit campaign led by populist politicians was victorious and Mr. Trump was chosen as the president of the USA. Although developed continental countries have guarded their welfare states, the UK departed from its postwar welfare system from the Margaret Thatcher government era in the 1980s and went step by step to a laissez-faire system of the Anglo-Saxon type similar to the USA. So, it was not the burden of the welfare state, but rather the weakness of the welfare state that strengthened populism and social exclusion. Kaji (2018) grasps postwar European integration as a continuous unity. There were qualitative changes at least twice. When the USA and the UK switched to neoliberal capitalism and financial globalization in the 1980s, the continental European Community countries had to follow up with the single market integration which began in 1985. The single market had to be followed up by monetary integration in the 1990s to avoid a possible breakup, which might have happened with attacks by hedge funds and investment banks (mainly Anglo-Saxon institutions) under the free movement of capital. The second change happened when the neoliberal global capitalist system broke down in the Lehman crisis. The crisis dramatically worsened budget deficits in almost all capitalist countries. The southern European countries fell into government debt crises, which developed into the euro crisis from 2010 onwards. After the Lehman crisis, Europe has been living in the era of the post-Lehman crisis. As Kaji (2018) explains in detail, Greece, Ireland, Italy, Portugal, and Spain, the GIIPS countries, have endured tough times. In the era of the post-Lehman crisis, income gaps, social exclusion, and populism prevail. They are problems of modern capitalism rather than those of the European integration per se, though populists peg the blame on Brussels. Kaji (2018) expects that a new Franco-German leadership will move Europe forward to tackle the three unintended consequences. The economic scene in Europe changed in 2017. Every EU country recorded positive economic growth, and higher economic growth is expected to continue in 2018 and 2019. But how will the EU be able to fight successfully against the serious problems mentioned earlier? Kaji (2018) does not appear to be so confident, since she refers to the possible defeat of President Macron in 5 years’ time. Kaji (2018) explains what happened from 1970s to the Brexit referendum and how the UK has fallen into chaos in the face of the Brexits negotiation with the EU. But, it is not so clear what made the UK exit from the EU. Kaji points out two “problems”: dissatisfaction of the voters with the present regime and the divide between the integrationists and the anti-integrationists. Her reasoning appears to be a kind of tautology and does not explain why the UK chose to exit. In her final section, Kaji (2018) discusses the impacts of possible instability in the EU on Asia and the global trading system through trade, financial, and free trade agreement (FTA) channels. Kaji (2018) says the EU is the largest guardian of free trade and explains the FTA networks of the EU with Japan, Canada, and other many countries. But, she also points out that the EU will turn protectionist. Why will the guardian of free trade turn protectionist? The answer is: there has been instability in the EU such as the North–South and the East–West divides and/or a possible government change in France or other happenings in the future. If the EU turns protectionist, Asia will receive a direct hit in trade in goods and the USA will be hit hardest in services trade. This story seems confusing. First of all, it turns everything upside down. The game changer for the global trading system is the USA under the Trump administration. It is protectionist and wants to change the global trade rules. The EU has been resisting the protectionist president in several ways. Second, is not a more careful analysis indispensable before Kaji says that the EU will turn protectionist? It seems unclear why the divides or other elements that Kaji (2018) points out will turn the EU to become protectionist. The EU maintained its multilateral free trade system during the euro crisis and even in the economic stagnation after the crisis. France will not be able to turn protectionist even under a populist government, because its economy will die. Its very high percentage export share in gross domestic product (GDP) (46%) will also exert a big impact on the EU to remain a multilateral free trader in the future. The future is unknown, but Kaji’s last section is not persuasive enough because she says that the EU will be neither a free trader nor a protectionist.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.916
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.004

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.

Opus teacher head0.043
GPT teacher head0.304
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2018
Admission routes1
Has abstractyes

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