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The COVID19 crisis has thrown wide open the debate on Europe’s Economic and Monetary Union’s (EMU) future. Next Generation EU (NGEU) has broken the stalemate over a central fiscal capacity. The open question is whether NGEU is a one-off or a first step. The suspension of the Stability and Growth Pact has given new urgency to the debate on reforming EMU’s fiscal rules.

There is no debate as yet about how these two prospects relate to each other. This paper argues that a permanent fiscal capacity and revised rules should be seen as alternatives.

This study makes two claims: first, a fiscal capacity renders a reformed pact unnecessary and second, that is an optimal solution politically. A fiscal capacity would provide an efficient asymmetric shock absorber and therefore reduce the need for pre-emptive action against negative cross-border externalities. It would also provide an abundant supply of an EU-wide safe asset around which to structure the EU’s financial system, thus rendering unnecessary the backstopping of member states' debts.

This would restore democratic accountability while eliminating moral hazard and enforcement problems.

This study proposes a novel method utilising a speech-word pair bipartite network to examine the correlation structure between members of parliament (MPs) in the context of the UK- China relationship.

We construct MP-word pair bipartite networks based on the co-occurrence relationship between MPs and words in their speech content. These networks are then mapped into monopartite MPs correlation networks. Additionally, the study calculates correlation network indicators and identifies MP communities and factions to determine the characteristics of MPs and their interrelation in the UK-China relationship. This includes insights into the distribution of key MPs, their correlation structure and the evolution and development trends of MP factions.

Analysis of the parliamentary speeches on China-related affairs in the British Parliament from 2011 to 2020 reveals that the distribution and interrelationship of MPs engaged in UK-China affairs are centralised and discrete, with a few core MPs playing an integral role in the UK-China relationship. Among them, MPs such as Lord Ahmad of Wimbledon, David Cameron, Lord Hunt of Chesterton and Lord Howell of Guildford formed factions with significant differences; however, the continuity of their evolution exhibits unstableness. The core MP factions, such as those led by Lord Ahmad of Wimbledon and David Cameron, have achieved a level of maturity and exert significant influence.

The research has several limitations that warrant acknowledgement. First, we mapped the MP-word pair bipartite network into the MP correlation network for analysis without directly analysing the structure of MPs based on the bipartite network. In future studies, we aim to explore various types of analysis based on the proposed bipartite networks to provide more comprehensive and accurate references for studying UK-China relations. In addition, we seek to incorporate semantic-level analyses, such as sentiment analysis of MPs, into the MP-word -pair bipartite networks for in-depth analysis. Second, the interpretations of MP structures in the UK-China relationship in this study are limited. Consequently, expertise in UK-China relations should be incorporated to enhance the study and provide more practical recommendations.

Firstly, the findings can contribute to an objective understanding of the characteristics and connotations of UK-China relations, thereby informing adjustments of focus accordingly. The identification of the main factions in the UK-China relationship emphasises the imperative for governments to pay greater attention to these MPs’ speeches and social relationships. Secondly, examining the evolution and development of MP factions aids in identifying a country’s diplomatic focus during different periods. This can assist governments in responding promptly to relevant issues and contribute to the formulation of effective foreign policies.

First, this study expands the research methodology of parliamentary debates analysis in previous studies. To the best of our knowledge, we are the first to study the UK-China relationship through the MP-word-pair bipartite network. This outcome inspires future researchers to apply various knowledge networks in the LIS field to elucidate deeper characteristics and connotations of UK-China relations. Second, this study provides a novel perspective for UK-China relationship analysis, which deepens the research object from keywords to MPs. This finding may offer important implications for researchers to further study the role of MPs in the UK-China relationship.

This study proposes a novel scheme for analysing the correlation structure between MPs based on bipartite networks. This approach offers insights into the development and evolving dynamics of MPs.

Using a mixed methodology comprising interviews, case file analysis and descriptive statistics, this study aims to examine the experiences of all 43 young people in Wales subject to secure accommodation orders between 1st April 2016 and 31st March 2018.

Children in the UK aged 10–17 years who are deemed to be at a significant level of risk to themselves or others may be subject to a secure accommodation order, leading to time spent in a secure children’s home (SCH) on welfare grounds. Following a rise in the number of children in Wales referred to SCHs for welfare reasons, this paper describes these young people’s journeys into, through and out of SCHs, giving insight into their experiences and highlighting areas for policy and practice improvements.

Findings indicate that improvements in mental health support and placement availability are key in improving the experiences of this particularly vulnerable group of young people throughout their childhood.

Other practical implications of the study’s findings, such as improvements in secure transport arrangements, are also discussed.

While the findings are limited by the reliance on self-report methods and the size of the study, namely, the small number of young people with experience of SCHs who were able to participate, the findings build on the existing knowledge base around children’s residential accommodation and provide new insights into how best to support these children.

Climate change has a direct impact on companies. Therefore, the scenario analysis is used to provide companies and stakeholders in this specific sector with forward-looking measures and narratives of the world's future state. This work aims to provide an independent, wide and rigorous literature review on the topics of scenario analysis and climate change, analyzing a large set of referred papers included in economic journals on the Web of Science Clarivate Analytics data source. This review, by means of a mixed approach, can help address new policy strategies and business models.

The work employs 416 abstracts and relative titles in the field of economics, employing data mining for qualitative variables and performing descriptive statistics and lexicometric measures, similarity analysis and clustering with Reinert's hierarchical method in order to extract knowledge. Furthermore, qualitative content analysis allows for the return of a comprehensive and complete universe of meaning, as well as the analysis of co-occurences.

Content analysis reveals three main classification clusters and four unknown patterns: model area, risks, emissions and energy and carbon pricing, indicating research directions and limitations through an overview with an extensive reference bibliography. In the research, the prevalent use of quantitative instruments and their limitations emerge, while qualitative instruments are residual for climate change assessment; they also highlight the centrality of transition risk over adaptation measures and the combination of different types of instruments with reference to carbon pricing.

Scenario analysis is a relatively new topic in economics and finance research, and it is under-investigated by the academy. The analysis combines quantitative and qualitative research using text analytics.