Correlation between Violations of Environmental Legislation and Probable Distortion of Financial Reporting

ABSTRACT

This work seeks to statistically verify the hypothesis that there is a link between violations of environmental legislation and distortions in the financial reporting of economic entities. For this purpose, the authors studied the reporting documents of companies that are operating in Russia and have violated environmental legislation. The financial reporting of the latter was analyzed based on the authors’ methodology. In order to determine the probability of distortion, companies were typologized and a probit model was constructed. The results confirmed the working hypothesis that economic entities’ opportunistic behavior in the area of environmental protection is, as a rule, accompanied by distortions of financial information about their activities.

KEYWORDS:

• violation of environmental legislation
• distortion of reporting
• probit regression
• opportunistic behavior
• non-observed economy

Disclosure Statement

No potential conflict of interest was reported by the authors.

Notes

1. The national accounting methodology separates out the concepts of the shadow and non-observed economies. The non-observed economy is economic activity that is not observable by direct statistical methods. It includes the economy that is not observable for statistical and economic reasons. It also includes the informal sector, illegal activity, and other types of undercoverage [Shiriaeva, 2009]. The shadow economy, as a part of the non-observed economy, includes economic activity hidden from society and the government in order to evade taxes or, so much the worse, to walk away from the requirements of government laws and generally established rules.

2. “Mirovaia ekonomika okazalas’ v porochnom kruge” (available at https://utro.ru/articles/2014/10/03/1215219.shtml); “Mirovoi krizis - khronika i kommentarii” (http://worldcrisis.ru/crisis/3120673, date accessed: April 19, 2019).

3. For example, there is the problem of disappearing (turbulent, unstable) populations. This term is understood as a general population of entities, the size and structure of which are prone to large changes over time. In particular, small businesses, even with a consistent number of entities, have a characteristically high coefficient of renewal of these entities (some close; others move to a new category—medium-size business—or change sector orientation), so the sector’s structure is constantly changing. Therefore, with statistical observation of small business by means of sampling, conclusions are de facto extended to a population that no longer exists [Glinskii, 2008].

4. If Shiriaeva’s above classification is kept in mind, from the point of view of manipulation of information, producers in three groups (No. 1, No. 2, and No. 6) merit attention.

5. “Ekologicheskie pravonarusheniia v regionakh Rossiiskoi Federatsii. Materialy prakticheskoi chasti vserossiiskogo studencheskogo konkursa ‘Eko-iurist 2017’” (available at http://network.bellona.org/content/uploads/sites/4/2018/04/sb_site.pdf, date accessed: April 19, 2018).

6. “Baza dannykh po rossiiskim kompaniiam, otrasliam i regionam” (available at http://www.SKRIN.ru, date accessed: April 20, 2018).

7. The proposed typology makes it possible, among other things, to obtain a generalized assessment of the financial component of a studied entity’s investment climate.

8. Financial indicators were selected so that the quality of their reflection could be cross-checked in the informational space (showed maximum variation). The essence of the method is the comparison of data from different sources. One source is balance sheets and statements of financial performance, and the other is SCF. This comparison gives some idea of possible distortions when it is extended to sectoral corpora. The divergence of the indicators was assessed using the Mann–Whitney criteria.

9. Probit regression is a nonlinear econometric model in which the explanatory variable can take on only two values (0 or 1).

10. When assessing the probability that reliable reports are drafted by companies that violated environmental legislation, companies are excluded from consideration if there is insignificant statistical information for their type of economic activity. Accordingly, the probability of reliable reporting is assessed based on an analysis of the financial reporting of companies from four categories in the Russian Classification of Economic Activities (A, B, C, E). Together, these categories account for more than 80 percent of all companies that violated environmental legislation in 2016.