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This study examines the impact of influential shareholders, namely, state and influential businessmen, on the dividend policies of firms. A special focus is made on the causal effect of exogenous changes: general and personal economic sanctions leading to toughened state policies concerning dividends.

Russian firms included into the Moscow Stock Exchange Broad Market Index were examined for a period from 2009 to 2019 using a generalized method of moments and a tobit model. The effect of personal sanctions was elucidated with the use of difference-in-differences method with multiple time periods.

The analysis showed that government or businessmen's ownership does not affect dividend payments. However, after 2014, state-owned companies began to increase their payments. At the same time, owing to a series of changes triggered by general economic sanctions, businessmen-owned companies decrease their dividends payout ratio. Personal sanctions imposed do not have long-term effect on Russian companies' dividends.

This study estimates the effect of ownership structure on dividend payouts after an exogenous change. The results show that there is heterogeneity in influential owners' decisions regarding dividends and changes strengthening it.

This paper aims to study the impact of CEOs’ personality and social connections on corporate risk-taking in the Russian market.

Using a sample of 93 large listed Russian corporations between 2008 and 2016, this study tests a range of personal traits, including the classical personal characteristics like age and tenure, some country-specific traits such as connections and military experience, as well as other human and social capital characteristics.

This study finds non-linear relationships between corporate risk-taking and CEO age and tenure. This study also finds that firms run by CEOs with military experience take more corporate risk. On the CEOs’ social capital side, this study’s results suggest that both political and educational connections are positively related to corporate risk-taking.

This study also tests some traits that have usually been ignored by the literature, such as marital and family status.

This study examines whether CEO power influences the book-based and market-based performance of Russian companies when it is restricted by the presence of essential shareholders, namely, state and influential businessmen.

Managerial power is divided into structural, ownership, expert and prestige. The proposed power metrics include not only CEOs but also the board of directors' characteristics that may restrict or enhance CEO power. The empirical analysis is based on the sample of 90 large traded Russian firms, which shares are included in the Moscow Stock Exchange Broad Market Index (MICEX BMI), observed from 2012 to 2019.

Panel data analysis suggests that higher board ownership and tenure may restrict CEO power, which in turn would be beneficial for corporate performance. the authors also see that in companies owned by influential businessmen, CEO power influence on M/B value is more negative, while state ownership does not moderate it. CEO power metrics, based on political experience and tenure, affect corporate performance differently in companies affiliated with extractive industries.

First, the authors consider two channels through which a company in emerging markets may get additional resources: CEOs and influential owners. Second, the authors develop power metrics based on Finkelstein's managerial power classification (1992) and the idea of relative power proposed by Bebchuk et al. (2011). It allows identifying whether the board of directors' may constrain or enhance CEO power to raise corporate performance. Third, the authors analyze developing Russian markets that represent a good ground for testing the question, whereas empirical research on Russia is relatively scarce (Grosman and Leiponen, 2018). Fourth, the authors pay particular attention to the CEO power in the extractive industry, strategically important for the Russian economy.

本研究擬探討行政總裁的權力，若因有不可或缺的股東 - 即國家和具影響力的實業家 - 的存在而受到約束時，其權力會否影響俄羅斯公司以賬簿為基礎和以市場為基礎的表現

管理權分為結構性的、所有權的、專家的和聲望的。提出的權力指標不但包括行政總裁，也涵蓋或會限制或增加行政總裁權力的董事會特徵。本研究的實證分析法是基於90間股份被納入莫斯科股票交易廣泛市場指數的大型俄羅斯上市公司樣本，觀察期由2012年至2019年

面板數據分析顯示、較高的董事會所有權和較長的任期或會限制行政總裁的權力，這因此有利於提升企業績效。我們亦看到，在具影響力的企業家擁有的公司裡，行政總裁權力對市價淨值的影響是較負面的，而國有制沒有把它減低。就隸屬採掘業的公司而言，基於政治經驗和任期的行政總裁權力指標，會對企業績效帶來不同的影響

(一) 我們考慮在新興市場公司可取得額外資源的兩個途徑：行政總裁和具影響力的所有者。(二) 我們基於芬克爾斯坦 (Finkelstein, 1992) 的管理權分類，以及 Bebchuk et al. (2011) 所提出相對功率的學說，建立了權力指標。憑著這權力指標，我們可鑑定董事會會限制、抑或增強行政總裁提升企業績效的權力。(三) 我們分析發展中的俄羅斯市場，其為測試我們問題的良好地方，而探討俄羅斯的實證研究較為稀有 (Grosman and Leiponen, 2018) 。(四) 我們特別關注在採掘業的行政總裁權力，而採掘業對俄羅斯經濟來說、是具有重要戰略意義的

The purpose of this paper is to present a tool to categorize companies as potentially profitable on the basis of an intellectual capital (IC) analysis.

The paper distinguishes two crucial attributions for picking shares: IC and capitalization of IC-based growth potential. Using these two attributions, the author creates a portfolio from a sample of European companies and annually rebalances it. To test its attractiveness, the author then compares the portfolio with benchmarks and random portfolios during the period from 2006 to 2013 using a Sharpe coefficient.

The comparison of the constructed portfolio with the benchmarks demonstrates the importance of IC for market investors and the validity of the proposed tool. The Sharpe ratio of the portfolio is significantly higher than the mean and median Sharpe ratios of random portfolios. In addition, the importance of IC for choosing proper investment goal increases in crisis.

This investigation can be improved by analysing other IC such as the qualification of CEOs, participation of the company in business alliances, and a company’s innovation activity. In addition, the paper considers only European companies.

The proposed tool provides a method to construct investment-attractive portfolios on the basis of IC.

The paper contributes to the literature by identifying the underestimated shares on the basis of a company’s IC and by developing an algorithm to create an IC-based investment portfolio.

This paper aims to explore whether individual intellectual capital of a fund manager allows mutual fund to outperform market.

The sample includes 85 Russian equity funds for the period of 2013. First, Jensen’s alpha for each fund has been calculated, and then cross-sectional regression analysis has been used. While only a part of fund managers publish biographic sketches, the authors use the Heckman procedure to control for self-selection issues.

The results support the idea that the individual characteristics indicate the possibility to earn abnormal alpha. Managers with economic education and with Moscow education perform better than others. Relationship between both fund performance measures and manager’s experience has inverted U-shape. Jensen’s alpha reaches its highest level at the point of 9 years, whereas beta – at 10 years of manager’s experience.

Investigation can be improved by including more variables that influence the disclosure of managers’ personal information, for example, by conducting surveys. Additionally, cross-sectional data restrict the analysis.

The discovered characteristics of managers’ intellectual capital can be used as additional screening tool for the investor who is deciding on mutual fund choice in Russia. While individual intellectual capital is observable and more persistent in time in comparison with the past fund performance, such tool allows better decision-making.

This is the first paper that explores which characteristics of Russian fund managers are connected with higher abnormal return (measured by Jensen’s alpha) and risk (beta) of mutual funds.

Company intellectual capital (IC) is nowadays considered as a key resource that can transform a company’s value. For this reason, the efficiency of IC is crucial for all stakeholders. Evaluating efficiency is difficult, because IC is partly unobservable and its efficiency varies across time. The aim of this study is to suggest a methodology for estimating the dynamic efficiency of a company’s intellectual resources.

The panel data model suggested by Kneip et al. (2012) is used to estimate dynamic efficiency. The main feature of this model is that the unobservable component has a multi-dimensional factor structure. Taking advantage of the ability of this model to control for unobserved complex heterogeneity, the authors use the results in further stochastic frontier analysis. A data set containing information about Russian companies for the period from 2001 to 2010 is used.

In this paper, the dynamic efficiency of Russian companies is estimated. It is shown that, using the traditional efficiency estimate, companies can be overestimated.

The main limitation of the suggested methodology is that it is necessary to have a long panel data structure.

Taking advantage of time-varying efficiency, one can estimate the efficiency growth rate as a measure of performance, standard deviation as a measure of risk and autocorrelation as a measure of stability.

This is the first study to present clear evidence of the time-varying nature of IC efficiency. On the methodological side, the paper presents a fairly simple method capable of estimating various indicators of a company’s efficiency.