Corporate Transparency As An Investor Protection Tool: Evidence From Russia

Abstract

The paper looks into the problem of enhancing financial performance and efficiency of business processes of Russian companies through improved corporate transparency. For the purpose of empirical analysis of relation between corporate transparency and financial performance, we suggest an original corporate transparency rating (disclosure score) tailored specifically for the Russian market. The rating is comprised of 39 indicators reflecting the degree of information disclosure, relevant for all major stakeholder groups. The transparency index for the Russian listed companies is developed from analysis of the publicly available sources. 39 possible attributes are divided into the following categories: general information about the company, corporate strategy, corporate governance, financial information disclosure, corporate risk management, corporate social policy and investment activities. All attributes are assigned equal weights. Alongside the obtained aggregate index, some other indicators of corporate governance quality are included into the model, such as the board membership and the number of independent directors. Econometric modeling reveals positive relation between the level of corporate transparency and the market-to-book ratio for the publicly traded Russian companies. This suggests that improved corporate transparency can be considered as a value driver, controlling information asymmetry, reducing tunnelling, improving risk perception and thus contributing to the attractiveness of companies for investors in general. However, we are fully aware that for the opaque markets, empirical results are not always consistent and heavily depend on metrics and operationalization of variables as well as employed statistical techniques.

Keywords: Corporate transparencytransparency ratinginvestor protectionopaque marketempirical analysisRussian companies

Introduction

Against the backdrop of stagnating economy and sanctions regime, Russian companies have very few viable opportunities to attract funding. Among the most underutilized sources of long-term funding are the savings of residents. However, the rights of investors, especially the minority shareholders and bondholders have to be properly protected. The latter requires, among others, a sufficient level of corporate transparency. The study addresses the problem of measuring corporate transparency in the Russian market and estimating its influence on firm value.

Problem Statement

Corporate transparency is an integral part and an important characteristic of corporate governance due to its role in controlling information asymmetry and conflicts of interests thus contributing to investor protection. However, in the opaque markets, like the Russian one, the straightforward logic of better corporate transparency increasing the firm value due to less concern on the part of investors about tunnelling by insiders does not always work. The “opacity” of the emerging markets is not confined only to non-transparency and poor disclosure on the part of insiders; the outsiders themselves in many cases are poorly equipped with analytical tools and unwilling to make necessary efforts to obtain relevant information. Consequently, a thorough empirical investigation has to be carried out of relation between corporate transparency and financial performance as measured by shareholder value creation in an emerging market. Up until now, the accumulated empirical evidence in this respect has been rather controversial. Besides, due to problems with obtaining the required data for empirical analysis of Russian companies from the existing databases (like well-known Standard and Poor’s transparency rating), a corporate transparency rating (disclosure score) tailored specifically for the Russian market had to be developed.

The existing literature on relation between corporate transparency and firm value in emerging markets is not consistent. The accumulated empirical evidence is rather inconclusive and the results heavily depend on transparency and disclosure metrics and employed statistical techniques. For example, (Black, Black, Love, & Rachinsky, 2006; Black, Kim Woochan, Jang Hasung, & Park Kyung-Suh 2009; Cheung, et al., 2007) for Hong Kong provide some evidence in favour of positive disclosure-firm value relation for Russian, Korean and Hong Kong companies respectively. However, (Balasubramanian, Black, & Khanna, 2010) find no statistically significant relation between improved disclosure and firm value for Indian companies. (Aljifri, 2008) for United Arab Emirates and (Alsaeed, 2006) for Saudi Arabia fail to establish any relation between the transparency and value of companies.

Research Questions

The major research question is whether improved corporate transparency and disclosure is perceived by the opaque Russian market as an effective enough tool of the investor protection to influence the share prices?

Purpose of the Study

The purpose of the research is two-fold. First, we have to develop a specifically tailored for the Russian market transparency index (disclosure score) from analysis of the publicly available information from corporate sites, annual reports, financial and social policy statements, sustainable development reports, as well as other sources containing relevant data.

Second, we have to hypothesize the character of relation between corporate transparency and market valuation of the companies in the Russian market and present the rationale behind empirical results. Alongside the hypothesis about positive transparency-value relation, a number of other hypotheses have to be developed. The hypotheses will be statistically tested.

Research Methods

The transparency index (disclosure score) was developed from analysis of the publicly available data. 39 possible attributes were divided into the following categories: general information about the company, corporate strategy, corporate governance, financial information disclosure, corporate risk management, corporate social policy and investment activities. All attributes were assigned equal weights. In cases of formal presentation of data without substance (not infrequent in an opaque market), we had to make a judgment.

The aggregate transparency index Dscore (disclosure score) was calculated using simple formula:

$\mathbf{D}\mathbf{s}\mathbf{c}\mathbf{o}\mathbf{r}\mathbf{e}=\underset{\mathbf{j}=\mathbf{1}}{\sum }{\mathbf{d}}_{\mathbf{j}}$,(1)

where dj = 1 if information is disclosed; dj = 0 – otherwise.

Alongside the disclosure score, two other independent variables related to corporate governance quality were introduced into the model – the number of board members and the number of independent directors. A standard set of control variables were also included.

The sample comprised data covering the 2009-2015 period for 250 largest companies in the non-financial sector of the national economy. Detailed description of the sample, descriptive statistics and other technical information are not reported here. However, all the relevant data used in empirical analysis can be provided upon request. Besides, it should be noted that two variables related to corporate governance demonstrated little variation through the whole period under consideration: the average number of board members was 9 with 4 independent directors.

The firm value was measured by Market-to-book ratio. Alongside the disclosure score, a number of other independent variables were introduced including the number of board members, the number of independent directors, state ownership, strategic foreign shareholder, financial leverage, company age as well as time and sector of economy dummy variables.

The unbalanced panel data was analyzed using fixed effects model which was proved to be the most appropriate technique for the sample. Missing values is an inherent problem of large sets of panel data. However, estimates can still be consistent if missing data is of random character, which means that the probability of non-availability is independent of the value of missing variables.

The developing of a transparency index (disclosure score) involves subjected judgements and is influenced by a number of assumptions. The selection of items heavily depends on the country context: emerging economies can differ substantially from the developed countries in their disclosure requirements as well as market perceptions.

The issue of selecting the voluntary items of information and the method of scoring the disclosure index has been discussed in detail in the literature (see, for example, a review in (Hossein & Hammami, 2009). There are two distinctive approaches to developing a disclosure score: a weighted index and an unweighted index. Some researches use both. In a number of earlier studies (Wallace, 1987; Cooke, 1991, 1992; Ahmed & Nicholls, 1994; Hossain, Tan, & Adams, 1994; Hossain & Hammami, 2009) an unweighted approach is employed where the disclosed information scores 1 and undisclosed (insufficiently disclosed) – 0. The weighted disclosure approach was used by (Barrett, 1977; Marston, 1986). However, a number of studies show that the both weighted and unweighted scores produce generally the same results (Coombs & Tayib, 1998; Firth, 1979).

The transparency index (disclosure score) for the Russian listed companies was developed from analysis of the publicly available sources. 39 possible attributes were divided into the following categories: general information about the company, corporate strategy, corporate governance, financial information disclosure, corporate risk management, corporate social policy and investment activities. All attributes were assigned equal weights. In cases of formal presentation of data without substance (not infrequent in an opaque market), we had to make a judgment. Detailed description of the questionnaire is omitted for the sake of brevity; it can be provided upon request.

The aggregate transparency index Dscore (disclosure score) was calculated using simple formula:

$\mathbf{D}\mathbf{s}\mathbf{c}\mathbf{o}\mathbf{r}\mathbf{e}=\underset{\mathbf{j}=\mathbf{1}}{\sum }{\mathbf{d}}_{\mathbf{j}}$,(1)

where dj = 1 if information is disclosed; dj = 0 – otherwise.

Alongside the disclosure score, two other independent variables related to corporate governance quality were introduced into the model – the number of board members and the number of independent directors. A standard set of control variables were also included.

The sample comprised data covering 2009-2015 period for 256 largest companies in the non-financial sector of the national economy. The following multivariate regression equation was used to test the above-mentioned hypothesis

Market-to-book ratio = $\mathrm{}\mathrm{\alpha }+{\mathrm{\beta }}_{\mathrm{1}}\mathrm{D}\mathrm{s}\mathrm{c}\mathrm{o}\mathrm{r}\mathrm{e}+{\mathrm{\beta }}_{\mathrm{2}}\mathrm{A}\mathrm{g}\mathrm{e}+{\mathrm{\beta }}_{\mathrm{3}}\mathrm{I}\mathrm{n}\mathrm{d}\mathrm{D}\mathrm{i}\mathrm{r}+{\mathrm{\beta }}_{\mathrm{4}}\mathrm{L}\mathrm{e}\mathrm{v}{+\mathrm{\beta }}_{\mathrm{5}}\mathrm{F}\mathrm{o}\mathrm{r}\mathrm{S}++{\mathrm{\beta }}_{\mathrm{6}}\mathrm{G}\mathrm{o}\mathrm{v}+{\mathrm{\beta }}_{\mathrm{7}}\mathrm{D}\mathrm{i}\mathrm{r}+{\mathrm{p}}_{\mathrm{1}}\mathrm{D}\_\mathrm{I}\mathrm{n}\mathrm{d}\mathrm{u}\mathrm{s}\mathrm{t}\mathrm{r}\mathrm{y}+{\mathrm{p}}_{\mathrm{2}}\mathrm{D}\_\mathrm{t}\mathrm{i}\mathrm{m}\mathrm{e}+\mathrm{\epsilon }$,

where $\mathrm{D}\_\mathrm{t}\mathrm{i}\mathrm{m}\mathrm{e}$ – time dummy; $\mathrm{D}\_\mathrm{I}\mathrm{n}\mathrm{d}\mathrm{u}\mathrm{s}\mathrm{t}\mathrm{r}\mathrm{y}$ – sectoral dummy; $\mathrm{\epsilon }$ – random error.

The descriptive statistics and formulas for the variables are presented in Table 01 .

The regression analysis results are presented in Tables 02 and 03 .

The Hausman test (Prob. = 0.0041) shows that the revealed effects are strongly correlated with the regressors. Consequently, the fixed effects model is most appropriate for the analysis of the data under consideration. Table 04 contains the results of fixed effects model analysis.

Findings

The results of statistical analysis support the first hypothesis of positive relation between transparency and firm value of Russian companies with 10% significance using single-sided t-criterion. Financial leverage has strong positive impact on firm value (most recent results for Russian companies have reversed this relation) while the presence of foreign shareholder produces no statistically significant effect. Both the number of board members and the number of independent directors have failed to demonstrate positive influence on the share prices. However, while the number of independent directors is statistically irrelevant, the number of board members is negatively related to firm valuation. The latter result contradicts the findings of (Saravanan and Gandhi, 2012) for Indian companies. However, the negative relation between firm financial performance and the number of board members was confirmed by (Duc and Phan, 2012) for Vietnamese companies.

As for the transparency-value analysis for Russian companies, the obtained results are consistent with earlier findings by (Black, et al., 2006).

Summing up the results of transparency-value empirical analysis for emerging markets in general, the positive causal relation between corporate transparency and market valuation is yet to be proved unequivocally. The accumulated empirical evidence is inconclusive and the results heavily depend of transparency and disclosure metrics and employed statistical techniques. For Russia in particular the question of causality is still open. Further statistical tests have to be carried out to take into account an increasing emphasis on administrative regulation of businesses.

Conclusion

Our results indicate, though not conclusively prove, positive relation between firm value and corporate transparency. We by no means claim that improved corporate transparency would immediately attract the much needed funds of resident savers. However, without consistent policy of transparency and disclosure as part of investor protection policy as a whole, there definitely will be no long-term market-based financing. The companies would be forced to rely heavily on state funding and be subject to the arbitrary allocation of funds. In the long term, only proper investor protection policy, not only declared but taken for granted, would persuade Russian residents to invest their savings in national companies, thereby providing much needed stability in the event of possible financial crises.

Acknowledgements

This research is supported by the Russian Science Foundation under Grant No. 16-18-10432.

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