By Andrey Yushkov, O’Neill School of Public and Environmental Affairs
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Coronavirus continues spreading across the globe. As of July 2020, Russia ranks fourth in the world by the total number of COVID-19 cases with more than 765,000 confirmed cases, behind only the U.S., Brazil, and India. However, it ranks only 11th by the total number of deaths (12,200), and its fatality rate (about 1.6%) is surprisingly low compared to other countries. Although the primary reason is thought to be data manipulation by federal and regional governments which hides the actual number of coronavirus-related deaths, there may be other objective reasons that help explain this puzzle: a relatively younger population, less reliance on nursing homes (e.g., compared to the U.S.), and more testing per capita.
In this blog post, I will discuss the spread of COVID-19 across Russia’s regions as well as fiscal consequences of the pandemic for different territories, and contribute to the nascent scholarly discussion about the risks that Russian subnational governments currently face and various governance technologies used by the federal center to shift responsibility to regions.
The situation with the total number of COVID-19 cases and deaths, as well as with various restrictions imposed by regional governments, is extremely heterogeneous across Russia’s regions. While the initial outbreak in Moscow was by far the most severe, the spread of the virus had stabilized there by mid-May. As of July 18, Moscow and Moscow Oblast have about 233,000 and 61,500 cases respectively and account for nearly 40% of all cases in Russia. Almost 5,300 people have died in these two regions, bringing the the fatality rate to about 1.7%. St. Petersburg has much fewer cases (29,000) but the second highest number of deaths (1,750) and the highest fatality rate (6%). Other regions that have more than 10,000 cases include Nizhny Novgorod, Sverdlovsk, Rostov, Irkutsk Oblasts, Krasnoyarsk Krai (capitals of all these regions have a population of more than one million people), and Khanty-Mansi Autonomous Okrug, which is the largest oil-extracting region of Russia. One suspicious tendency is that some regions, despite having relatively large number of cases, report an extremely low fatality rate. Ryazan, Yaroslavl, Bryansk Oblasts as well as the Republics of Tatarstan and Bashkortostan all have more than 5,000 cases but a lower than 0.5% fatality rate. Five regions, including sparsely populated Jewish Autonomous Oblast and Chukotka and Nenets Autonomous Okrugs, have fewer than 1,000 total cases, while only two regions (Sakhalin Oblast and Nenets Autonomous Okrug) reported no deaths.
Figure 1 presents the map of COVID-19 cases in Russian regions per 100,000 residents. As of July 18, four regions officially have more than 1% of their residents infected (Moscow at 1.8%, Tyva Republic at 1.7%, Yamalo-Nenets Autonomous Okrug at 1.6%, and Murmansk Oblast at 1.1%). The effect of the proximity to Moscow can be seen in several regions of Central Russia, including Ryazan, Ivanovo, Lipetsk, Oryol, and Kaluga Oblasts, which have between 0.5% and 1% of their population infected with the COVID-19. Oil- and gas-extracting regions of Russia (particularly, Khanty-Mansi and Yamalo-Nenets Autonomous Okrugs) suffer relatively more on a per capita basis since they have a much higher share of fly-in fly-out workers than an average Russian region. Southern regions are relatively less affected, which represents an empirical puzzle that deserves further investigation. The disputed territories of Crimea and Sevastopol are the only two regions where the number of reported cases per 100,000 residents is less than 100.
The pandemic has been truly an exogenous shock for all Russian regions and their public finances. However, not all the regions share the same financial and fiscal risks associated with an increased pressure on their healthcare systems and economy. Some regions, as previous crises have shown, become more vulnerable than others. It depends not only on their own policies, but also on the actions of the federal center.
For instance, Alexeev and Chernyavskiy (2018) demonstrated that poor and transfer-dependent regions suffered relatively less than rich regions during the crisis of 2009 because of the targeted financial support from Moscow. At the same time, poor regions experienced tougher problems during the crisis of 2014-15 when the federal center was not willing to provide comparable amounts of anti-crisis support to regions. Thus, transfer-dependence can be one of the factors that is directly related to regional fiscal risks. Figure 2 shows the number of officially registered COVID-19 cases per 100,000 residents relative to the share of federal fiscal transfers in consolidated regional revenues. One important observation is that Tyva, being a traditionally transfer-dependent region, has one of the highest infection rates. Fiscal risks for this republic are high, especially if federal revenues continue falling during the pandemic (another reason for their decline is the negative oil price shock) and the federal center will not be able to provide sufficient support to this region. Other regions that are in the risk zone include Northern-Caucasian republics (Ingushetia, Karachay-Cherkessia, Kabardino-Balkaria) as well as Kamchatka Krai, Kalmykia, and Altai Republic. They all critically depend on intergovernmental transfers from Moscow, have vulnerable healthcare systems, and experience a continuing upsurge in the number of cases.
Another factor is regional indebtedness. In recent years, debt burden has significantly increased in many regions. Even though the share of cheap budget credits provided to regions by the Ministry of Finance has almost doubled since the global financial crisis, some regions still have high debt service costs since they have to repay relatively more expensive commercial loans or government securities. Figure 3 depicts the infection rate and regional per capita government debt. Fortunately for highly indebted regions, they do not currently experience extremely high infection rates. Several regions are still at risk, including Mordovia (which is a well-known case of improper debt management at the regional level), Magadan Oblast, Yakutia, and Khabarovsk Krai. If the pandemic persists in these regions, they will likely face problems with debt repayment or refinancing in the very near future. However, if the federal government steps in and starts replacing commercial loans with budget credits more aggressively, this risk could potentially be mitigated.
Yet another risk is related to the structure of regional economy and, in particular, to the share of corporate profit tax in regional government revenues. Usually, the higher this share, the more developed the region is. However, this tax is also more volatile than other major sources of revenue (e.g., relatively stable personal income tax) and tends to drop significantly in times of crises, which implies that relatively rich regions can suffer more from the lockdown and its consequences, especially in the short term. Figure 3 shows the infection rate and the share of corporate profit tax in consolidated regional revenues. As expected, the most developed regions (Moscow, Moscow Oblast, St. Petersburg, Sverdlovsk Oblast, etc.) have the highest share of this tax in their revenues. However, not all of them equally suffer from the pandemic. Apart from the capital region, territories that have relatively high revenue risks include Murmansk Oblast, Kaluga Oblast, Nizhny Novgorod Oblast, and Kamchatka Krai.
The most vulnerable regions according to these three risk factors are Magadan Oblast, Kamchatka Krai, Murmansk Oblast, North-Caucasian republics and Tyva. Most of these regions cannot fully reopen yet and still experience problems with the lack of beds in hospitals, high unemployment, and insufficient federal support, which complicates the situation even further. Moscow, despite having the largest number of COVID-19 cases and the highest share of corporate profit tax in revenues, have only moderate risks since the pandemic seems to have overcome its peak there, debt burden and transfer dependence are very low, and, more importantly, the Russian capital has always demonstrated its ability to recover relatively fast from economic downturns.
Future research should investigate more formally whether the actual number of COVID-19 cases and deaths in a region is significantly correlated with regional policies (e.g., restrictions, travel permits, requirements to wear masks, etc.) and increases economic and fiscal risks related to the severity of the pandemic. It is clear, however, that 1) regional heterogeneity in policies and their outcomes will remain high, and 2) a lot will depend on economic and fiscal actions of the federal center.