The effects of mega-events on perceived corruption

In recent decades, the media have covered many cases of corruption related to the celebration of mega-events around the globe. In most of these cases, politicians and other high officials are involved. This paper analyses the effect of hosting mega-events on the level of perceived corruption in 34 OECD countries, during 1996–2017. Summer and Winter Olympic Games, FIFA World Cups, and Universal Expositions are considered. Results show that, when we take the year of the celebration of the event as the turning point, there is no robust evidence in favour of a positive impact on perceived corruption. However, when we take the election date of the host country as the threshold, the magnitude of the effect is lasting, reaching its maximum value 1–2 years before the celebration itself, and increasing the perceived level of corruption by about 4%.     

General or central government? Empirical evidence on political cycles in budget composition using new data for OECD countries

Previous studies used general government data to examine whether national governments’ electoral motives and ideology influenced budget composition in OECD countries. General government data includes, however, the state and local level. Using new data for general and central government over the period 1995–2016, I reexamine political cycles in budget composition. The results suggest that, both at the general and central government level, leftwing governments spent more on education and less on public services than rightwing governments. Defense expenditure was somewhat lower under leftwing than rightwing governments and in election years; especially in federal states. Effects of government ideology on the individual expenditure categories are larger at the central than general government level. Scholars need to re-examine results on ideology-induced effects that have been derived from general government data where central government data should have been used.     

Economic forecasting with evolved confidence indicators

We present a machine-learning method for sentiment indicators construction that allows an automated variable selection procedure. By means of genetic programming, we generate country-specific business and consumer confidence indicators for thirteen European economies. The algorithm finds non-linear combinations of qualitative survey expectations that yield estimates of the expected rate of economic growth. Firms’ production expectations and consumers’ expectations to spend on home improvements are the most frequently selected variables – both lagged and contemporaneous. To assess the performance of the proposed approach, we have designed an out-of-sample iterative predictive experiment. We found that forecasts generated with the evolved indicators outperform those obtained with time series models. These results show the potential of the methodology as a predictive tool. Furthermore, the proposed indicators are easy to implement and help to monitor the evolution of the economy, both from demand and supply sides.     

Public acceptance of and heterogeneity in behavioral beach trip responses to offshore wind farm development in Catalonia (Spain)

A combined travel cost – contingent behaviour survey of residents and tourists in Catalonia is conducted on-site to examine the effects on beach recreational demand of developing an offshore wind farm (OWF) project. The survey considers four potential OWF scenarios with different degrees of visual impact. We allow for heterogeneity in trip preferences among individuals and control for on-site sampling through the use of a random parameters negative binomial (RPNB) model and a Multivariate Poisson log-normal (MPLN) model, respectively. The welfare measures derived from the RPNB model relate to the current beach users only, whereas those from the MPLN model refer to the general population of residents and tourists in Catalonia. The results show the importance of the specific place of location of the OWF project and how the installation of wind turbines would significantly decrease the demand for trips, depending on their degree of visual impacts, leading to a substantial welfare loss. However, the results also show that the project mainly would cause a displacement of trips to other beaches within Catalonia rather than outside Catalonia and that the welfare per trip measures generated by the RPNB and MPLN models substantially differ. Policy implications of these findings are discussed.     

How entrepreneurs recognise entrepreneurial opportunity and its gaps: a cognitive theory perspective

ABSTRACT

Previous studies have verified the relationship between entrepreneurial opportunity recognition and performance. However, the influences of a perceived gap between entrepreneurial opportunities before and after launching a new venture have been neglected. This study applied the partial least square method to analyse the entrepreneurial behaviours and performance of 214 Taiwanese new ventures, and adapted the bootstrap re-sampling method for estimating the variables. The empirical results showed that entrepreneurial resource and entrepreneurial alertness significantly influence the perceived opportunity, while the entrepreneurial resource significantly affects the actual opportunity. The results further demonstrated that both the perceived opportunity and actual opportunity considerably influence new venture performance. This study offered a research framework to better understand the cognition path of entrepreneurial opportunity, and suggested the factors affecting the recognition of perceived opportunity by longitudinal method can be further evaluated. To improve performance, entrepreneurs should enrich entrepreneurial resources and allocate them appropriately, and heighten and maintain their alertness to reduce the perceived gap arising from recognising entrepreneurial opportunities.     

Consumption,asset wealth,equity premium,term spread,and flight to quality

We link transitory deviations of consumption from its equilibrium relationship with aggregate wealth and labor income to equity returns on the one hand, and to two characteristics of bond investors—the premium demanded to hold long‐term assets, and “flight to quality” behavior—on the other hand. Using a panel of 10 euro area countries over the period 1984Q1–2017Q4, we show that a rise in the consumption–wealth ratio predicts both higher equity returns and the future term spread, while a fall in the consumption–wealth ratio explains a large fraction of the rise in the spread between the “risky” and the “safe‐haven” bond.     

The risk-based approach under the new EU data protection regulation: a critical perspective

Abstract

The first broad reform of personal data protection legislation in the European Union entered into force in May 2018 (Regulation (EU) 2016/679, the General Data Protection Regulation). Remarkably, with this reform a risk-based approach has been introduced as the core data protection enforcement model, while data protection authorities see their regulatory role significantly weakened. The risk-based approach is to be implemented by the data controllers (i.e. the operators) via data protection impact assessments (evoking the established environmental impact assessment procedure) and notification of breaches, among other procedures. Hence the scope of both the concepts of risk and risk regulation spread beyond conventional domains, namely the environment, public health or safety, i.e. physical risks, to encompass risks to intangible values, i.e. individual rights and freedoms, presumably harder to assess and manage. Strikingly, the reform has been accompanied by a confident discourse by EU institutions, and their avowed belief in the reform’s ability to safeguard the fundamental right to data protection in the face of evolving data processing techniques, specifically, big data, the Internet of Things, and related algorithmic decision-making. However, one may wonder whether there isn’t cause for concern in view of the way the risk-based approach has been designed in the data protection legislation. In this article, the risk-based approach to data protection is analysed in the light of the reform’s underlying rationality. Comparison with the risk regulatory experience in environmental law, particularly the environmental impact assessment procedure, is drawn upon to assist us in pondering the shortcomings, as well as the opportunities of the novel risk-based approach.     

Global uncertainties and portfolio flow dynamics of the BRICS countries

This paper investigates the dynamics of bond and stock market capital flows to BRICS countries under uncertainties such as global economic policy uncertainty and the US trade policy uncertainty. We use a time-varying Granger causality framework over the January 2008-November 2019 period to analyze the predictive power of uncertainties on capital flows in the form of bond and equity. The results show that the effects are heterogeneous across countries and stronger during the Global Financial Crisis period and post-2018 period while it lost its significance in the subsequent period. The negative influence of uncertainties on capital flows directed to BRICS countries is also evident in the results of non-parametric time-varying panel models. Overall, it is thought that the heterogeneous structure of the causality between uncertainty and portfolio flows into BRICS may present portfolio diversification benefits for global investors.     

The long-run reversal in the long run: Insights from two centuries of international equity returns

We perform the most comprehensive test of long-term reversal in national equity indices ever done. Having examined data from 71 countries for the years 1830 through 2019, we demonstrate a strong reversal pattern: the past long-term return negatively predicts future performance. The phenomenon is not subsumed by other established cross-sectional return patterns, including the value effect. The long-term reversal is robust to many considerations but highly unstable through time. Finally, our findings support the overreaction explanation of this anomaly.     

大数据对法院司法统计的积极功效及边界

最高人民法院于2016年应用人民法院大数据管理和服务平台以后,全国法院司法统计完全实现计算机自动采集。从发展脉络来看法院司法统计正处于智能化转型阶段,仍然存在一些问题。随着大数据及新技术的引入,司法统计“大数据”得以成为现实,包括了数据采集的全面化、统计分析的综合化、统计平台的社会化,进而提出了大数据助力司法统计精准化的具体路径,包括了提高基础数据的量与质、加强对司法统计数据的深度分析和可视化分析、推进基础设施建设。然而,二者并不具有正相关性。因此,推进司法统计大数据化需要注意有两个限度。