Vol 14, No 2 (2020)

Global shifts in perspectives on environmental concerns and the growing significance of large-scale sustainability programs have brought the issue of green financing to the fore of financial research. In terms of volume, this area has demonstrated high growth rates in various types of capital markets. Unfortunately, few studies exist which explore the yields on green bonds in emerging markets in comparison to developed ones. As such, in this paper, we contribute new evidence to the field of green financing and outline several
major differences between green issues in these types of capital markets. We study yield premiums of green bonds on a sample of 2,450 green issues and comparable traditional bonds over the period from 2008 to March 2020. We contribute to the literature by new empirical evidence on green financing. Our results provide evidence of small but statistically significant negative premiums on green bonds of 23,4%1 compared to the expected yields for standard issues. We also show that the negative premium on green bonds is more pronounced in developed markets (- 27%2) than in emerging ones (18%3). Moreover, we provide new evidence on the negative premium-liquidity relationship. Our research concludes that negative premiums are related to a higher level of liquidity:
green bonds have lower bid-ask spreads and a higher level of liquidity than traditional ones. These conclusions can assist investors, potential issuing companies, and public authorities in achieving a better understanding of the current situation of the green bond market in global terms.

Although business groups occupy strong positions in Russia, existing studies on Russian group-affiliated companies are insufficient yet to provide a thorough understanding of how the internal capital markets of business groups operate and influence corporate activities. The purpose of this paper is to assess the impact of the internal capital markets on the investments of Russian group-affiliated companies.

What motivates the use of internal capital markets? Does the reallocation of intragroup funds help mitigate financing constraints of group members and facilitate their investments? To find relevant answers we apply the generalized method of moments (GMM) to estimate investments models based on data for 514 Russian companies affiliated with 48 business groups over the period from 2014 to 2018. Following the existing studies based on both Q model of investment and the Euler equation model, we analyze the relationship between subsidiaries’ investments and such factors as lagged investments, sales, leverage, asset profitability and liquidity as well as the size of both subsidiaries and their groups.

The results reveal that leverage and profitability of business groups positively influence the investment activity of subsidiaries. These findings support our hypotheses that the internal capital markets of Russian business groups are active and help mitigate the financial constraints of affiliated companies. Meanwhile, we find that subsidiaries’ investment activity is negatively related to their asset profitability which is typical for tunneling or propping practices followed by controlling shareholders. The results also show some evidence of the positive relationship between subsidiaries’ cash flows and investments, demonstrating that the internal capital markets in Russia do not eliminate the financial constraints of group-affiliated companies. The findings on the internal capital markets of Russian business groups described in this paper may be useful for managers seeking for mechanisms to increase the financial resource availability for large and medium companies in the context of sanctions, macroeconomic instability and yet not sufficiently developed financial markets in Russia.

Various aspects of credit risk have been studied by many researchers. Scientists and practitioners consider different credit risk assessment methods depending on its application, e.g. to determine capital adequacy, to make loss loan provisions, or to estimate its influence on the interest rate. At the same time, there are almost no studies that consider the relationship between loan loss provisioning framework and loan decisions. The study seeks to 1) understand how the practices and procedures of loan loss provisioning impact total gross loans of Russian banks, and 2) identify constraints for insufficient levels of lending and factors that can foster lending.
With the use of an econometric model we estimate a quantitative effect of credit portfolio on the growth of loan loss provisions. We base our model on data derived from financial statements of 400 Russian credit institutions between 2014 and 2019. In addition to our empirical model, we analyze statistical data on the development of the Russian banking system and compare the loan loss provisions in Russian and foreign financial organizations. The estimates are based on Russian official statistics and financial statements of banks within and outside Russia. The study reveals that the existing credit risk assessment method that rests on the regulations provided by the Bank of Russia is responsible for excessive loan loss provisions accumulated by Russian banks. This, in turn, affects the volumes of bank loans.
In our research we have arrived at the conclusion that the existing loan loss provisioning is excessive. Current loan loss provisions do not correspond to real lending losses. They negatively affect the financial results of credit institutions, resulting in ungrounded refusals to lend, which in turn limits economic growth. These results support the rationale for reinventing the existing framework of loan loss provisioning.