Conceptualising the right to data protection in an era of Big Data

In 2009, with the enactment of the Lisbon Treaty, the Charter of Fundamental Rights of the European Union entered into force. Under Article 8 of the Charter, for the first time, a stand-alone fundamental right to data protection was declared. The creation of this right, standing as a distinct right to the right to privacy, is undoubtedly significant, and it is unique to the European legal order, being absent from other international human rights instruments. This commentary examines the parameters of this new right to data protection, asking what are the principles underpinning the right. It argues that the right reflects some key values inherent in the European legal order, namely: privacy, transparency, autonomy and nondiscrimination. It also analyses some of the challenges in implementing this right in an era of ubiquitous veillance practices and Big Data

A spatial analysis of employment multipliers in the US

The actual effectiveness of employment promotion policies depends on the ability of the intervention at creating new jobs in the targeted sector, but also, to a large extent, on the impact they have on other parts of the local economy. Estimating the latter effect is therefore quite important for regional economic development policies. Along the lines of Moretti (Am Econ Rev Pap Proc 100: 373-377, 2010), we present an empirical analysis of local employment multipliers using data on 123 US Metropolitan Statistical Areas over the period 1980-2010. From the methodological point of view, in this work not only endogeneity (via instrumental variables estimates), but also spatial spillovers are taken into account. According to the results, the magnitude of the multiplier could be rather limited. On the other hand, there is clear indication that the impact of these interventions is not fully contained within the local economy and they have a positive effect on closely surrounding ones

Historical Research Approaches to the Analysis of Internationalisation

Historical research methods and approaches can improve understanding of the most appropriate techniques to confront data and test theories in internationalisation research. A critical analysis of all “texts” (sources), time series analyses, comparative methods across time periods and space, counterfactual analysis and the examination of outliers are shown to have the potential to improve research practices. Examples and applications are shown in these key areas of research with special reference to internationalisation processes. Examination of these methods allows us to see internationalisation processes as a sequenced set of decisions in time and space, path dependent to some extent but subject to managerial discretion. Internationalisation process research can benefit from the use of historical research methods in analysis of sources, production of time-lines, using comparative evidence across time and space and in the examination of feasible alternative choices

Threat and imposition of economic sanctions 1945–2005: Updating the TIES dataset

Recent research on economic sanctions has produced significant advances in our theoretical and empirical understanding of the causes and effects of these phenomena. Our theoretical understanding, which has been guided by empirical findings, has reached the point where existing datasets are no longer adequate to test important hypotheses. This article presents a recently updated version of the Threat and Imposition of Economic Sanctions dataset. This version of the data extends the temporal domain, corrects errors, updates cases that were ongoing as of the last release, and includes a few additional variables. We describe the dataset, paying special attention to the key differences in the new version, and we present descriptive statistics for some of the key variables, highlighting differences across versions. Since the major change in the dataset was to more than double the time period covered, we also present some simple statistics showing trends in sanctions use over time