Love is blind: partisan alignment and political corruption in Spain

Ever since the spectacular boom and bust cycle of the Spanish real estate industry, endemic corruption at the local level has become a widely recognized problem in the national public discourse. In an effort to expose an under-explored political determinant, this paper investigates the effect of local and regional alignment in fomenting corruption at the Spanish municipal level. To do so, we construct an ample panel dataset on the prevalence of corrupt practices by local politicians, which is employed to test the possible impact of partisan alignment in three consecutive joint municipal and regional elections. Findings show aligned municipalities to be more corrupt than non-aligned ones, an effect that is further associated with absolute majorities at both levels of government and higher capital transfers. By contrast, we also show that “throwing the rascals out” could be an effective strategy for curbing the corrupt practices of aligned municipalities. This indicates that the democratic political process may be effective in corruption control if agreements can be reached to remove corrupt politicians or parties from power.

Intraprocedural Artificial Intelligence for Colorectal Cancer Detection and Characterisation in Endoscopy and Laparoscopy

In this article, we provide an evidence-based primer of current tools and evolving concepts in the area of intraprocedural artificial intelligence (AI) methods in colonoscopy and laparoscopy as a ‘procedure companion’, with specific focus on colorectal cancer recognition and characterisation. These interventions are both likely beneficiaries from an impending rapid phase in technical and technological evolution. The domains where AI is most likely to impact are explored as well as the methodological pitfalls pertaining to AI methods. Such issues include the need for large volumes of data to train AI systems, questions surrounding false positive rates, explainability and interpretability as well as recent concerns surrounding instabilities in current deep learning (DL) models. The area of biophysics-inspired models, a potential remedy to some of these pitfalls, is explored as it could allow our understanding of the fundamental physiological differences between tissue types to be exploited in real time with the help of computer-assisted interpretation. Right now, such models can include data collected from dynamic fluorescence imaging in surgery to characterise lesions by their biology reducing the number of cases needed to build a reliable and interpretable classification system. Furthermore, instead of focussing on image-by-image analysis, such systems could analyse in a continuous fashion, more akin to how we view procedures in real life and make decisions in a manner more comparable to human decision-making. Synergistical approaches can ensure AI methods usefully embed within practice thus safeguarding against collapse of this exciting field of investigation as another ‘boom and bust’ cycle of AI endeavour.

Sustainable Policy Dynamics—A Study on the Recent “Bust” of Foreign Residential Real Estate Investment in Sydney

We undertook an autopsy of the drivers of individual foreign real estate investment ‘bust’ in Australia through a new theoretical lens of ‘habitus’. Our autopsy data drew contours around the individual foreign real estate capital ‘boom and bust’ cycle, as well as the long-term commitment of professionals in the real estate sector to Australia’s real estate market. More specifically, we showed that the foreign capital ‘boom and bust’ cycle began in earnest in about 2010 (starting at A$8.7 billion), grew to A$72.4 billion in 2016–2017, and then declined to A$12.5 billion in 2017–2018. This decline in foreign capital into Australian real estate occurred within a domestic real estate market in Sydney that also started to slow in 2017. Based on 20 semi-structured interviews with real estate professionals in Sydney and public material culture data, we found out that the off-the-plan apartment sales and global policy landscape changes contributed to the decline of foreign real estate investment in Australia. The three possible implications for Sydney’s future residential real estate development: (1) The loss of investors, (2) the evolution of the labor force, and (3) the diversification of housing products, have been raised as part of a future research road map.

Expected Lifetime in Different Employment Statuses: Evidence From the Economic Boom-and-Bust Cycle in Spain

This article analyses the impact of the recent economic crisis on the expected time spent in different employment statuses in Spain. Using data from the Economically Active Population Survey and life tables, we estimate the expected time in work, unemployment, retirement, and other types of economic inactivity during the economic boom-and-bust cycle. Differences in expected years of life spent in different employment statuses are decomposed into effects of mortality and employment behavior. Our results show that men’s working life expectancy is much more exposed to economic fluctuations. The impact of the ebbs and flows of the business cycle among women is mitigated by the long-term female trend of growing participation in the labor market associated with the increasing educational attainment of women. In addition, the improvement in mortality only partially contributes to gains in time spent in each status, while the main effects correspond to changes in labor market participation.