Quantitative Storytelling in the Making of a Composite Indicator

The reasons for and against composite indicators are briefly reviewed, as well as the available theories for their construction. After noting the strong normative dimension of these measures—which ultimately aim to ‘tell a story’, e.g. to promote the social discovery of a particular phenomenon, we inquire whether a less partisan use of a composite indicator can be proposed by allowing more latitude in the framing of its construction. We thus explore whether a composite indicator can be built to tell ‘more than one story’ and test this in practical contexts. These include measures used in convergence analysis in the field of cohesion policies and a recent case involving the World Bank’s Doing Business Index. Our experiments are built to imagine different constituencies and stakeholders who agree on the use of evidence and of statistical information while differing on the interpretation of what is relevant and vital.

     

Going concern modifications and related disclosures in the Italian stock market: do regulatory improvements help investors in capturing financial distress?

Journal of Management and Governance - This paper investigates the investor reaction to audit reports containing a going concern modification (GCM) in the Italian market following new amendments...     

Opting out of workers’ compensation: Non-subscription in Texas and its effects

Journal of Risk and Uncertainty - Texas is the only state that does not mandate that employers carry workers’ compensation (WC) insurance coverage. In place of traditional WC, companies can...     

Factor analysis for ranked data with application to a job selection attitude survey

Summary.  Factor analysis is a powerful tool to identify the common characteristics among a set of variables that are measured on a continuous scale. In the context of factor analysis for non-continuous-type data, most applications are restricted to item response data only. We extend the factor model to accommodate ranked data. The Monte Carlo expectation–maximization algorithm is used for parameter estimation at which the E-step is implemented via the Gibbs sampler. An analysis based on both complete and incomplete ranked data (e.g. rank the top q out of k items) is considered. Estimation of the factor scores is also discussed. The method proposed is applied to analyse a set of incomplete ranked data that were obtained from a survey that was carried out in GuangZhou, a major city in mainland China, to investigate the factors affecting people's attitude towards choosing jobs.     

Business Collaboration within the Nazi War Machine: Corporations and the State in the Austrian Semiperiphery

The military strength of German National Socialism was based on the collaboration of large corporations with the Nazi state. Business provided capital, loans, taxes, managerial expertise and production for war industries. I elaborate four ideal‐typical modes of business collaboration. Each mode is illustrated by a case study of a German corporation that acquires an Austrian firm: Krupp (traditional mode); the Reichswerke state conglomerate (coercive); Deutsche Bank (managerial nationalist); and IG Farben (competitive investment mode). The first and the last modes occurred when the state was highly dependent on large businesses for the economic requisites of war. The acquired firms in the Austrian semiperiphery contributed to Nazi war mobilization, as they exploited labor and resources from the peripheral regions of southeastern Europe. Patterns of the state's resource dependency on business led to bargaining interactions between state and business, over time shaping the mix between state and private ownership of war industry.     

Employment and Earnings Expectations of Jobless Young Skilled: Evidence from Italy

Quality of Life (QoL) is a multi-dimensional idea that includes various distinctive dimensions and its estimation is considered as an essential factor for policy assessment. The study estimates the inter-district variation in QoL in Pakistan by using a data set of Household Integrated Economic Survey of 2010–2011. Objective and subjective indices are constructed to measure QoL with 7 domains and 31 indicators within 89 districts of Pakistan by employing the principal component analysis. The leading result of the study reveals that top ranked district is Jhelum in term of QoL and Tharparkar is at the bottom. The analysis also reveals that the most of the top ranked districts are located in Punjab province. This reflects the better performance of the province in term objective and QoL indices. Whereas, the districts of Balochistan emerge at the lower end in terms of objective and QoL indices. Majority districts of Punjab shows a modest level of satisfaction regarding the facilities provided by the government and the least satisfied districts belong to KPK and Sindh. It is interesting to identify that disparity in the objective index and subjective perceptions are representing QoL differences.

     

M&A and diversification strategies: what effect on quality of inventive activity?

Journal of Management and Governance - The aim of this paper is to examine how an acquirer’s diversification strategy shapes the multiple dimensions of inventive activity. Differing from...     

Promoting sustainable development through civil society: A case study of the EU’s NSA/LA thematic programme in Kyrgyzstan

The article focuses on the contribution of the European Union (EU) in promoting sustainable development through the involvement of civil society in partner countries. More specifically, it analyses the main features and outcomes of the projects implemented by civil society organizations (CSOs) in Kyrgyzstan under the EU thematic programme Non‐State Actors and Local Authorities in Development (NSA/LA). Despite its importance—this is the only EU programme providing direct support to non‐state actors and local authorities engaged in poverty reduction—to date, there has been very little research on the functioning of this instrument on the ground. This article seeks to fill this gap in the literature by examining the EU’s contribution to sustainable development through a case study on Kyrgyzstan. The study is based on primary data: 10 semi‐structured interviews conducted with the EU‐funded organizations implementing the NSA/LA programme. The NSA/LA projects were analysed by considering two major fields of engagement of non‐state actors in the development process: as service providers and as advocates (Banks & Hulme, 2012). Overall, the organizations awarded EU support were not only focused on fulfilling short‐term needs but also sought to introduce new ways of dealing with poverty and inequality, positioning themselves between the “Big‐D” and the “little‐d” approaches to development (Bebbington, Hickey, & Mitlin, 2008). Nonetheless, the EU‐funded projects were too limited and fragmented to be able to sustain long‐term structural change. Therefore, the EU should place new emphasis on creating synergies between new and old structures at the grassroots level and establishing mechanisms and bodies that could merge and co‐ordinate their efforts. In addition, the calls for proposals could highlight the need to share the lessons learnt by “obliging” the beneficiaries to act as multipliers and to pass on their positive experience to neighbouring communities. Finally, the EU could stimulate the funded organizations to experiment with innovative mechanisms of involvement in the policy‐making process, by making this aspect a mandatory requirement of the projects implemented with its support.