The Eurasian Economic Union: Development Prospects and Possible Obstacles

This article analyzes the development prospects and problems for the Eurasian Economic Union (EAEU). It examines issues of integration within the EAEU, as well as interactions with other countries, both CIS (Commonwealth of Independent States) and non-CIS. The main problem of integration within the EAEU is the dominance of redistributive motives over productive ones. This article assesses the extent of Russian oil and gas transfers to EAEU partners and the impact of tax maneuvers on their size. It shows that the creation of mechanisms for redistributing profits within the EAEU will allow a positive economic effect to materialize from free trade agreements with non-CIS countries. The article assesses the risks for the EAEU related to Russia’s introduction of a unilateral ban on food imports from countries on the sanctions list and to the possible establishment of tariffs on trade with Ukraine.     

Inequality Assessment by Probabilistic Development Indices

Social Indicators Research - This paper analyses the Human Development Index (HDI) time series from 2010 to 2017. An alternative index is studied, which combines the same components of the HDI by...     

The changing character of industrial relations: Comment

Readers wishing to correspond with Mr. O’Connell may do so through the editorial office of the Journal.     

Making ends meet: perceptions of poverty in Sweden

During the era after the Second World War, Sweden has built a welfare system based on labor market participation and income maintenance. Low unemployment and decent wages are supposed to guarantee people a labor market income or income maintenance, which in turn should provide a proper standard for everyone. However, a rapid increase in unemployment and economic problems have made the future of the Swedish welfare state more uncertain than ever. These circumstances have, among other things, led to the suggestion that Sweden should abandon the income maintenance policy and create a social policy system with the more limited ambition of guaranteeing everyone a minimum income. In that case, one central question must be answered: what constitutes a decent minimum income in today's Sweden? Where should we draw the poverty line under which people will not be forced to live? These questions are central in the current debate. The consensual poverty line method is used in this article to derive a poverty line relevant for today's Sweden. The results shows that more than every fifth household has an income below the consensual poverty line. That is, they have an income that most Swedes would argue is too low to make ends meet. The level of the consensual poverty line was compared with the National Board of Health and Welfare's guidelines for social assistance. The consensual poverty line was shown to be more generous to small households and the norm for social assistance was more generous to larger households. Finally, the expenditure for guaranteeing all Swedish household a minimum income equal to the consensual poverty line was estimated: more than SEK 25 billion per year. The results in the article casts serious doubt on the ability of the Swedish welfare state to secure a decent income to all citizens.     

Understanding manager resistance to blockchain systems

Blockchain technology has received much attention in the media and there is an increasing interest amongst organizations within financial services due to the potential benefits. As blockchain-based systems are a nascent technology, the requirements of the technology need to be understood, to allow blockchain systems to be successfully integrated within financial service organizations. There are gaps in academic research in understanding how managers evaluate the value of a blockchain-based system. This study develops a model to explain manager resistance to implementing blockchain-based systems in financial services organizations. This research advances the theoretical understanding of managers’ perspectives on blockchain-based systems and models their resistance to blockchain technology.     

Uniform asymptotic linearity of a process based on a signed rank statistic

Consider the process with, cf. (1.2) on page 265 in B1, X₁, …, X_N a sample from a distribution F and, for i = 1, …, N, R${}_{\text{|x}{}_{\text{1}}\text{, - q}{}_{\text{1}}\text{ø|}}$ , the rank of |X₁ - q₁ø| among |X₁ - q₁ø|, …, |X_N - q_Nø|. It is shown that, under certain regularity conditions on F and on the constants p_i and q_i, T^ø_N(t) is asymptotically approximately a linear function of ø uniformly in t and in ø for |ø| ≤ C. The special case where the p_i and the q_i, are independent of i is considered.     

CEO Reciprocal Interlocks in French Corporations

In France the chairperson of the board is mostoften the firm's CEO. This position strengthensthe insiders' hold on the board of directors.Moreover, a large fraction of outside directorsis composed of CEOs of other firms. Thereciprocal interlocking of CEOs creates the possibility of mutual interdependence of CEOs.We investigate factors explaining reciprocalinterlocking directorates of CEOs in Frenchcorporations. Our results indicate that CEOs oflarger firms hold more reciprocal CEOinterlocks and when CEOs have more outsidedirectorships, CEOs hold more reciprocalrelationships. We also find a positiverelationship between the number of CEOsreciprocal interlocks and their firms'performance measured by ROA. We find evidencethat CEOs hold more reciprocal interlocks whena blockholder is present on the CEO's board.     

On Combining Wavelets Expansion and Sparse Linear Models for Regression on Metabolomic Data and Biomarker Selection

Wavelet thresholding of spectra has to be handled with care when the spectra are the predictors of a regression problem. Indeed, a blind thresholding of the signal followed by a regression method often leads to deteriorated predictions. The scope of this article is to show that sparse regression methods, applied in the wavelet domain, perform an automatic thresholding: the most relevant wavelet coefficients are selected to optimize the prediction of a given target of interest. This approach can be seen as a joint thresholding designed for a predictive purpose. The method is illustrated on a real world problem where metabolomic data are linked to poison ingestion. This example proves the usefulness of wavelet expansion and the good behavior of sparse and regularized methods. A comparison study is performed between the two-steps approach (wavelet thresholding and regression) and the one-step approach (selection of wavelet coefficients with a sparse regression). The comparison includes two types of wavelet bases, various thresholding methods, and various regression methods and is evaluated by calculating prediction performances. Information about the location of the most important features on the spectra was also obtained and used to identify the most relevant metabolites involved in the mice poisoning.