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183–215
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The paper continues investigation of the logistic model of financial leverage. Analogies between collaterized loans with margin calls and macrofinancial leverage are studied. The gamma distribution for the global financial leverage was found and its parameters were estimated on the IMF data about development of the world financial system in 2003–2012. The model was applied in order to estimate the amount of global assets that would have been fully collaterized by the world GDP. In particular, it was found that about 6 per cent of world financial assets in 2012, or approximately $17tn could be defined as toxic ones. Stochastic logistic model that underlies the process did possess some qualities which significantly differs from its deterministic analogue. As appeared, noise was able to transform the stable deterministic model into unstable stochastic system. If existed, the stochastic attractor coincides with the mode of gamma distribution. It was much smaller than its deterministic analogue, though stochastic trajectories might converge towards zero. The Lyapunov exponent while being the standard measure of the stochastic model stability served as a signal of investors’ confidence in the global markets solvency. Correspondingly, a reduction of gamma distribution to the exponential one could be interpreted as a signal of the financial system destabilization. Hence the crisis might emerge either due to credit expansion and excessive borrowing or as an unintentional outcome of investors’ reluctance to refinance their indebtness because of unusually high volatility. The latter was modeled as a system’s behavior along the “Fisher trajectory” accompanied by decreasing value of the equity market. Such processes could have resulted in the increase of leverage (per unit of GDP) whereby undermining the validity and universality of the no-arbitrage mechanism under uncertainty.
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216–248
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We explore perceptions of inequality and attitudes toward redistribution exploiting ISSP and LiTS cross-country data sets. These perceptions vary across countries as well as across individuals within countries. We try to explain this variation using variation in opportunities for vertical social mobility available to individuals. The main research question is whether individual perceptions of income differentiation are driven by experience of past mobility and availability of channels leading upward. In other words, is more socially mobile society more tolerant to income inequality than less mobile and segmented? An intuitive answer seems obvious yes but empirical evidence is still scarce.
Our key hypothesis speculates that tolerance of individuals to a given inequality level is positively associated with previous experience of vertical mobility. This experience includes the scale of mobility as well as the perception of how legitimate and just are ways to success. In there search literature, this view is associated with “the tunnel effect” proposed by A. Hirschman. The paper explores this effect using three different cross-country data sets that cover different countries and use varying definitions and measures of social mobility. The estimates appear robust to various specifications in ordered probit regressions.
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249–284
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In this article we study the institutional reform of the German labour market during the period 2003–2005, the so-called Hartz reforms. The aim of this paper is threefold. First, we describe the economic and institutional context of the German labour market before the Hartz reforms in light of general trends in market economies. The falling competitiveness of the German economy, the need to increase the flexibility and dynamics of the labor market have made the ruling elite to proceed with institutional transformations. Second, we analyze the theoretical concepts that became the basis for the labour market reform and examine the changes in the main labour market institutions. Finally, we evaluate the outcomes of the institutional reforms for economic activity, employment, unemployment and labour costs. Of major interest is the question about the impact of the Hartz reforms on internal flexibility.
In this work we rely on the institutional analysis. Results of the study contribute to the understanding of the mechanism of labour market transformations. At the same time its main conclusions can be used for improving the economic and social policy in the Russian Federation.
We came to the following conclusions. We have found the positive impact of the changes in labour market institutions on labour market outcomes: especially on the dynamics of economic activity and employment. The Hartz reforms fundamentally modified the functioning of the German labor market and increased both flexibility and job creation capacities. However, the pattern of German de-regulatory reforms accesses mostly the margins of the labour market, i.e. ‘outsiders’, that contribute to a growing dualisation of the employment system. This dualisation trend was reinforced by dynamics in industrial relations and company employment practices where we can observe growing reliance on mechanisms of internal flexibility for the skilled core work force and increasing use of non-standard types of employment in less specifically skilled occupations.
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285–327
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Food industry plays a key role in each country. That is why the process of globalization makes the problem of ensuring safe production vary important, especially while attracting foreign capital. In this article the two mechanisms of the FDI distribution in Russian food industry companies are discussed. Special econometric tools for this analysis are also proposed. We investigate regional characteristics and the spatial lags (like factor of agglomeration, market potential and others) as determinants of the process. To test the influence of these determinants on the probability to have more than 10% of foreign capital in a company we estimate the hierarchicalbinary-choice models on a sample of Russian food industry companies (from RUSLANA database, on 2009). According to the results, the hierarchical diffusion of foreign investors is motivated by the seeking of local market and by seeking of the efficiency through lower transportation costs and better investment environment. The local resources in innovations are not significant on this level. When the investors develop new regions they take into account almost all the investigated regional characteristics. The logical complexification of a model allows not only to display the regional heterogeneity but also to determine the regions where the effect of some factors is irregular or more tangible. The development of transport infrastructure of the region and its spatial lag should be pointed out as one of the most substantial effects on the probability to have the FDI.
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328–344
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The data used in regression analysis may be inexact or uncertain. Uncertainty of data comes from randomness and from fuzziness. Statistical regression has many applications. But problems can occur, for instance, if the data set is too small, or there is difficulty verifying distribution assumptions. The standard econometric estimation is used when both the independent and dependent variables are given as real numbers. However, in many real-life situations only fuzzy data is available. The statistical techniques can be extended to include ambiguity of events. Fuzzy linear regression is a modelling techniques based on fuzzy set theory. It is applied to different areas such as finance, business administration and so on. The regression model with fuzzy data has been treated from diffferent points of view. Models where the variables are fuzzy or models where the relation of the variables is fuzzy may be considered.
Significant amount of research has been conducted on fuzzy regression models. One can consider models with fuzzy observations and crisp parameters, crisp observations and fuzzy parameters, fuzzy observations and fuzzy parameters.
In this paper, we apply calculus of variations methods in fuzzy regression analysis. The fuzzy regression model is considered to be fuzzy outputs, fuzzy inputs and crisp parameters. In order to include fuzzy constant term into regression model, we solve the calculus of variations problem. The results show that the regression model with fuzzy constant term has better performance than the regression model with crisp constant term.
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