Russian business under economic sanctions: is there evidence of regional heterogeneity?

ABSTRACT

Sanctions against Russia, beginning in early 2014, provide us with a unique opportunity to study whether, and how, sanctions affect a territorially-vast global power. This study empirically examines the economic impact of these sanctions, paying particular attention to the existence or nonexistence of its regional heterogeneity. For these purposes, this study utilises survey data that asked the executive managers of Russian regional companies to assess the impact of sanctions on their management activities in late 2015. There are several key findings. First, approximately half of those interviewed perceived the economic sanctions as having a negative impact. Second, no regional variation in the impact of the sanctions could be found. It follows that financial sanctions, aimed at an entire nation, exert a significant and geographically uniform impact. Moreover, even regional businesses near the Asia-Pacific region, holding strong connections with Asian countries, were unable to avoid the impact of sanctions.

KEYWORDS:

• Economic sanctions
• enterprise survey
• Far East
• Russian economy

Acknowledgments

This study is financially supported by the ERINA’s research project on “Market Quality in the Far East: from the Viewpoint of Company Management.” The early draft was presented at several places including the 57th JACES annual conference at Kansai University (Osaka, Japan), and the 2nd World Congress of Comparative Economics at Higher School of Economics (St. Petersburg, Russia). I am grateful for the valuable comments and advice from the participants, especially from Professors Andrey Yakovlev, Shinichiro Tabata, Ichiro Iwasaki, and Hirofumi Arai.

Disclosure statement

No potential conflict of interest was reported by the author.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Notes

1. Public Law 115-44 ‘Countering America’s Adversaries Through Sanctions Act’ (CAATSA) is targeting Iran, Russia, and North Korea.

2. GfK Russia, market research company based in Moscow, conducted the interview survey.

3. Listed targets of sanctions were initially 114 individuals and 24 entities, then increased to 237 individuals, 457 entities, and 2 vessels as of March 2019. See the list: https://sanctionssearch.ofac.treas.gov/.

4. 170 persons and 44 entities are subject to the restriction measures in March 2019 while they were initially only 21 individuals. See the list: http://www.consilium.europa.eu/en/policies/sanctions/ukraine-crisis/.

5. The EU’s sanctions are moderate because the member countries are afraid of its counter-effects although the impact varies among member countries (Hasselbach, 2014; Veebel & Markus, 2016).

6. Zakirova and Zakirova (2018) confirmed that banks on the list of sanctions returned to domestic capital market for debt financing, causing increased demands and costs for domestic financing, which then resulted in deteriorating financial conditions of all companies including those not on the list.

7. The eastern region includes Primorsky krai, Khabarovsk krai, Zabaykalsky krai, Jewish A.O., Amur oblast, Irkutsk oblast, Republic of Sakha, and Republic of Buryatia. The western region includes Republic of Karelia, Arkhangelsk oblast, Vologda oblast, Leningrad oblast, Murmansk oblast, Novgorod oblast, Pskov oblast, Smolensk oblast, and Tver oblast.

8. The sectoral classification with 13 sub-industries is possible. We do not use this because this neither changes the estimation results, nor produce a statistically significant coefficient for each industry.

9. The estimation using individual variables separately identifying Sberbank and capital banks shows that the company financed by capital banks statistically significantly and negatively assess the impact.

10. Inclusion of dummy variables for individual Asian countries (China, Japan, South Korea, and India) in the estimations do not produce statistically significant coefficient nor change the result, thus we omitted them from estimations.

11. Country dummy variable for trade partners are not included in the estimations as the inclusion of these variables do not change nor produce any statistically significant results.

12. Milov (2017) pointed out that the size of the Chinese financial system cannot make up for western loan because its size is too small and it only prefer to finance domestic demand and projects related to the One Belt, One Road strategic initiative.