Around the Bloc: Eurovision Infuriates Russian Pols
Top Russian politicians cry foul after Ukrainian singer takes home top prize at Eurovision.
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Top Russian politicians cry foul after Ukrainian singer takes home top prize at Eurovision.
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Atmosphere heating up again as anti-abortion groups march across country for more restrictive legislation.
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Missile interceptors are ‘1,000 percent’ aimed at Russia, Duma defense committee head fumes.
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A team of Hungarian chefs buoyed by a partisan crowd in Budapest took first place in one of Europe’s most prestigious cooking competitions, the Bocuse d’Or Europe.
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Some analysts see rejection of bill modeled on Russia’s 'foreign agent law' as another sign of cooling relations with Moscow.
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World’s biggest aircraft makes a rare appearance in the Czech capital.
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New Justice Ministry report says illegal for foreign-funded NGOs even to criticize the country’s leaders or discredit government policies.
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Russian company halts production after international outrage.
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Trend of attacks and killings by nationalists continues, rights groups say.
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In Moldova, U.S. military hardware removed from Chisinau square ahead of 9 May celebrations.
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Belgrade unwilling to accept conditions set by former enemy for accession talks to go ahead.Missile interceptors are ‘1,000 percent’ aimed at Russia, Duma defense committee head fumes.
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Demand for luxury housing units from the upper and upper-middle income groups in Hong Kong has been increasing over the last few years. as the market cannot satisfy demand, some prospective buyers have turned their attention to “special” housing units. this research paper attempts to investigate buyers’ preferences for two types of “special” units, namely duplex units and adjoining flats. the study investigates the price premiums paid by the buyers, and examines the effects of these special units on property price. the study employs two hedonic price models: one measuring the buy- ers’ preference on duplex units and the other one measuring buyers’ preference on adjoining flats. The results show that buyers are willing to pay a larger premium for special residential units: HK$588/ft2 more for a duplex unit and HK$934/ft2 more for an adjoining property unit, respectively. furthermore, a relatively larger premium is found for adjoining flats compared to duplex units. This implies that a property unit, purchased as an adjoining flat can add more value to the property price (in terms of $s per sq. ft.) compared with being a duplex unit.
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This paper compares the effectiveness of different property portfolio diversification strat- egies using five methods; (1) correlation matrices, (2) efficient frontiers, (3) Sharpe ratios, using three different sub methods, (4) coefficients in equations explaining total returns and (5) R-square values in equations explaining total returns. The evaluation methods are applied to both value weighted and equally weighted indices based on Swedish real estate return data. All methods show that, if any, diversifying over property types is a better strategy on the Swedish market than diversifying over re- gions. No test yields significant support for regional diversification. The support for the property type strategy is stronger when using equally weighted indices.
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Because of global urbanization and sustainable development trends, reusing vacant buildings is a crucial strategy employed in urban development and management. Reusing and adjusting the future service values of unused buildings to extend building life cycles is a sustainable approach that benefits society, the economy, and the environment. However, repurposed spaces are easily re-discarded because a comprehensive system and operational plan for assessing the effects of building reuse remains unestablished. The research framework adopted in this study was based on the seven factors of the AdaptSTAR model; assessment criteria for building reuse were then created. In addition, 62 types of reused building cases in Taiwan were investigated and a decision model for reuse type prediction and business strategy was constructed on the basis of artificial neural networks. The results indicated that the proposed decision model yielded a reuse type accuracy of 89% and a business strategy accuracy of 78%. This systematic approach can be adjusted according to local conditions and applied as an effective decision support tool.
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Due to the severe restrictions on access to credit resulting from the current economic climate, credit risk analysis of mortgage loans has been considered paramount for banking institutions and is currently accompanied by higher credit underwriting standards. In this paper, we present an empirical comparison of three decision support tools (i.e. Analytic Hierarchy Process (AHP), Delphi, and Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH)) in the specific context of trade-off readjustments in credit risk analysis of mortgage loans. We conducted a panel study with credit analysts and focused on five lines of comparison: ease of use; time-consumption; ease of applicability; accuracy; and overall evaluation. Results indicate that Delphi surpasses AHP and MACBETH in terms of ease of use, time-consumption and ease of applicability. As for accuracy, the differences obtained between AHP and MACBETH are not significant, and both methods perform better than Delphi. Most of the decision makers considered AHP the “overall best” approach.
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In real estate studies, arguably the most important topic revolves around what actually affect the price of properties. In addition to various macroeconomic factors, the mortgage industry is also believed to play a major role. Nonetheless, despite its profound implications on the banking sector, the property market, and the economy as a whole, there is no consensus as to the relationship between property price and bank mortgage lending. In light of this, this paper aims to investigate the relationship between property price and mortgage lending, along with other macroeconomic variables, in two housing sub-markets of Hong Kong (i.e. the mass housing market and the luxury housing market). The findings illustrate that one-way directional relationships are discovered 1) from mass housing price to mortgage lending; 2) from luxury housing price to mortgage lending; and 3) from mass housing price to luxury housing price. Macroeconomic factors such as GDP, inflation rate, and interest rate are also found to play a major role in influencing the prices of both property markets and the amount of outstanding mortgage loans. Implications based upon these findings are also discussed.
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Mass appraisal, or the automatic valuation of a large number of real estate assets, has attracted the attention of many researchers, who have mainly approached this issue employing traditional econometric models such as Ordinary Least Squares (OLS). However, this method does not consider the hierarchical structure of the data and therefore assumes the unrealistic hypothesis of the independence of the individuals in the sample. This paper proposes the use of the Hierarchical Linear Model (HLM) to overcome this limitation. The HLM also gives valuable information on the percentage of the variance error caused by each level in the hierarchical model. In this study HLM was applied to a large dataset of 2,149 apartments, which included 17 variables belonging to two hierarchical levels: apartment and neighbourhood. The model obtained high goodness of fit and all the estimated variances of the parameters in HLM were lower than those calculated by OLS. It can be concluded as well that no further neighbourhood variables need be added to the model to improve the goodness of fit, since almost all the residual variance can be attributed to the first hierarchical level of the model, the apartment level.
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Decision making takes into account a myriad of factors about the future topics, which often prove challenging and quite complicated. Multiple Attribute Decision-Making (MADM) methods still have not become powerful enough to help decision makers to adopt the best solutions regarding future issues. Different scenarios are suitable for developing an appropriate outlook toward different probable futures. Scenarios are not inherently quantitative, but recently different integrated quantitative methods have been incorporated with the processes in various studies. Previously, different types of scenario-based MADM methods have been presented in different studies, but they just considered each case separately. In those studies, MADM methods were only applied to evaluate the situation in scenario-based MADM. This research concentrates on another paradigm in applying scenarios to upcoming events, MADM methods in the new area are explored, and the concept, which is called MADM based scenarios, is presented. In different situations and scenarios, different MADM models will happen. New concepts about most useful criterion and applicable alternatives are introduced in this new approach for decision-making about the future. In addition, a general framework is proposed for applying MADM-based scenarios for unpredictable scenarios and situations, which can be almost controlled future in practice.
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Applying the GARCH or ARCH model, this paper finds that Poland's stock market index is positively associated with industrial production or real GDP and the German stock market index, negatively affected by the government borrowing/GDP ratio, the real interest rate, the nominal effective exchange rate, the expected inflation rate, and the government bond yield in the euro area, and exhibits a quadratic relationship with the M2/GDP ratio. It suggests that the stock market index and the M2/GDP ratio show a positive (negative) relationship if the M2/GDP ratio is less (greater) than the critical value of 43.68%. Hence, to maintain a healthy stock market, the Polish authorities are expected to pursue economic growth, reduce government borrowing, avoid currency appreciation, and keep a relatively low interest rate or a relatively low expected inflation rate. Although currency appreciation has a negative impact on the stock market index, it is possible that the negative relationship might change if a certain threshold value is reached in the future.
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Many regions and their representatives decide on the amount of support they will provide to industrial clusters, their births, and their existing phase based on the public budget. Nowadays the efficiency of public spending must be provided. There are many examples showing situations where industrial clusters were cancelled when public support was limited or no longer available. Through the use of a special diagnostic method, one can find out if the industrial cluster is able to rise and also be viable without massive public budget support. The suggestion of a new method for industrial cluster identification is the aim of this paper. The Porter's diamond model of the cluster's competitiveness environment is the substance of the novel method.
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