RETRACTED ARTICLE: Analyzing of innovations influence on economic growth by fuzzy system

Economic growth may be developed on the basis on combination of different factors. In this investigation was analyzed the economic growth prediction based on the innovations by field of technology. Gross domestic product (GDP) was used as economic growth indicator. The method of adaptive neuro fuzzy inference system (ANFIS) was applied to the data in order to detect the influential parameters for the GDP prediction. Five inputs are considered: number of granted patents in electrical engineering, number of granted patents as instruments, number of granted patents in chemistry, number of granted patents in mechanical engineering and the number of granted patents in other fields. Results shown that the innovations in electrical engineering has the highest influence on the GDP prediction.

     

Prediction of bank financial strength ratings: The case of Turkey

Bank financial strength ratings have gained widespread popularity especially after the recent financial turmoil. Rating agencies were criticized because of their ratings and failure to predict the bankruptcy of the banks. Based on this observation, we investigate whether the forecast of the rating of bank's financial strength using publicly available data is consistent with those of the credit rating agency. We use the data of Turkish banks for this investigation. We take a country-specific approach because previous studies found that proxies used for environmental factors (political, economic, and financial risk of the country) did not have any explanatory power and it is hard to find international data for other important factors such as franchise value, concentration, and efficiency. We use two popular multivariate statistical techniques (multiple discriminant analysis and ordered logistic regression) to estimate a suitable model and we compare their performances with those of two mostly used data mining techniques (Support Vector Machine and Artificial Neural Network). Our results suggest that our predictions are consistent with those of Moody's financial strength rating in general.. The important factors in rating are found to be profitability (measured by return on equity), efficient use of resources, and funding the businesses and the households instead of the government that shows efficient placement of the funds.     

Spatio-temporal determinants of the structural and productive transformation of regions in Central and East European countries

This paper investigates the determinants of the structural (between-sectoral) and productive (within-sectoral) transformation of 56 NUTS2 regions in Central and East European (CEE) countries over the 2008–2014 period. Over the analysed period, a transformation of the analysed regions has taken place towards the tertiary sector and high value-added activities. The results from a spatial panel Durbin analysis reveal the existence of product-space linkages and point to a productive transformation towards high technology-intensive activities as an important driver of industrial development. Equal access to digital infrastructure in urban and rural areas and transfer of skills, knowledge and resources through the inflow of foreign investment and imports of production inputs increase the contribution of manufacturing to regional employment. The effect of profit tax reductions on the share of manufacturing employment is about five times larger than the effect of government subsidies to production.     

Macro‐Fiscal Volatility and the Composition of Public Spending*

Earlier empirical literature has examined some long‐ and medium‐term aspects of macro‐fiscal volatility while leaving its short‐term fiscal impact unexplored. To help fill that gap, we examine the impact of macro‐fiscal volatility on the composition of public spending. To that end, we analyse a panel of 10 EU countries during 1991–2007. Our results suggest that increases in the volatility of regularly‐collected and cyclical revenues such as the VAT and income taxes tend to tilt the expenditure composition in favour of public investment. In contrast, increases in the volatility of ad hoc taxes such as capital taxes tend to favour public consumption spending, albeit only a little. We interpret such volatility innovations as conveying news to the fiscal policymaker about the underlying economic conditions, with especially regularly‐collected and cyclical taxes prompting short‐term cyclical fine‐tuning.     

Does competition influence bank failures?

There has been a notable debate in the banking literature on the impact of bank competition on financial stability. The aim of this article is to provide the first investigation of the role of bank competition on the occurrence of bank failures. We analyse this issue on a large sample of Russian banks for the period 2001–2007, as the Russian banking industry is a unique example of an emerging market which has undergone a large number of bank failures during the last decade. Our findings support the view that tighter bank competition enhances the occurrence of bank failures. Thus, measures that increase bank competition could undermine financial stability.     

Examining macroeconomic models through the lens of asset pricing

We develop new methods for representing the asset-pricing implications of stochastic general equilibrium models. We provide asset-pricing counterparts to impulse response functions and the resulting dynamic value decompositions (DVDs). These methods quantify the exposures of macroeconomic cash flows to shocks over alternative investment horizons and the corresponding prices or investors’ compensations. We extend the continuous-time methods developed in Hansen and Scheinkman (2012) and Borovi?ka et al. (2011) by constructing discrete-time, state-dependent, shock-exposure and shock-price elasticities as functions of the investment horizon. Our methods are applicable to economic models that are nonlinear, including models with stochastic volatility.     

Person-level assessment of measurement invariance

Quality & Quantity - Existing procedures for testing measurement invariance focus mainly on group-level comparisons rather than individual comparisons (i.e., the main conclusion typically...     

Will AI ever sit at the C-suite table? The future of senior leadership

As the sophistication of artificial intelligence (AI) systems develop and AI becomes a key element of organizational strategy across a wide spectrum of industries, new demands are being placed on senior leaders. To understand the growing challenges leaders will face in the age of AI, we conducted interviews with 33 senior leaders in several countries across a wide range of industries. Our research highlights key capabilities and skills that leaders will require. Underlying these capabilities is a mindset oriented toward continuous learning and self-development, which will enable ongoing and rapid adaptation to change. Our findings identified the following key capabilities: digital know-how, data-driven focus, networking, ethics, and agility. To successfully navigate the coming era, senior leaders will need to focus on reskilling the workforce, recruiting and retaining highly skilled talent, building an intrapreneurial culture, and managing unprecedented changes in technologies and the nature of work.