Geography, Factors and Consequences of COVID-19 Diffusion in Russia

The chapter describes the spread of the COVID-19 in the Russian regions and its consequences. Two COVID-19 waves could be distinguished, the beginning of the third was recorded. Each wave began in the largest metropolitan areas, where there is a high density of population and interaction, then spread to the periphery. The epidemic affected Russia more than the world average but less than most East-European countries;Moscow was among the most affected areas worldwide. However, the current (real-time) statistics of confirmed cases and deaths may underestimate their real extent due to a number of discussed distortions. Excess mortality in Russia in 2020 corresponded to Latin American countries. It was higher in the least developed Russian regions with high poverty and insufficient health care infrastructure, in the largest agglomerations with an elderly population and in mining regions with a large number of temporary labor migrants. As a result of the epidemic, a special healthcare infrastructure was created and numerous electronic services were developed. However, it also sharpened the debate about restrictive measures. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

INTERNET DIFFUSION AND INTERREGIONAL DIGITAL DIVIDE IN RUSSIA: TRENDS, FACTORS, AND THE INFLUENCE OF THE PANDEMIC

The demand for digital technologies has been growing due to a shift in the technological and economic paradigm. The need for online services has increased since the beginning of the COVID pandemic. There are significant disparities between Russian regions in the digital technology accessibility and the development of computer skills. In 2020, the Internet diffused rapidly in most regions, although previously, there had been a slowdown. As markets got saturated with digital services, the digital divide between Russian regions narrowed. Overall, the Internet use patterns are consistent with those of the spatial diffusion of innovations. Amongst the leaders, there are regions home to the largest agglomerations and northern territories of Russia, whereas those having a high proportion of rural population lag behind. Coastal and border regions (St. Petersburg, the Kaliningrad region, Karelia, Primorsky Krai, etc.) have better access to the Internet due to their proximity to the centres of technological innovations as well as the high intensity of external relations. Leading regions have an impact on their neighbours through spatial diffusion. Econometrically, access to the Internet depends on income, the average age and level of education, and its use depends on the business climate and Internet accessibility factors. Regional markets are gradually getting more saturated with digital services and technologies. The difference between regions in terms of access to the Internet is twofold, whereas, in terms of digital technology use, the gap is manifold. In many regions, the share of online commerce, which became the driver of economic development during the lockdown, is minimal. Based on the results of the study, several recommendations have been formulated © Zemtsov, S. P., Demidova, K. V., Kichaev, D. Yu., 2022

Entrepreneurship Policy and SME Development during Pandemic Crisis in Russia

: Small and medium-sized enterprises (SMEs) suffered from government restrictions and a drop in consumer demand in 2020–2021 and therefore became one of the main targets of anti-crisis support worldwide. We aimed to identify trends and factors influencing the SMEs' dynamics in the Russian regions during the coronacrisis, including the impact of entrepreneurship policy. We have verified with the econometric analysis that the SMEs' number reduction was more serious in regions with a large SME sector, with a high proportion of industries potentially affected by the crisis, with stricter anti-pandemic measures. The latter factor had an impact not only on the domestic market, but also on SMEs in neighboring regions, which proves the existence of close ties between enterprises of different regions. However, there are some factors that influenced the SMEs development positively: relatively higher income level, more favourable business climate and larger consumer market. The previously undertaken efforts of the regional authorities to improve the business climate had a positive effect on the SMEs survival during the crisis. Business digitalization turned out to be an effective way to adapt (online services and sales), and state support policies could be more efficient (targeted and accessible) in digitally advanced regions. The agrarian regions due to continued demand for food got through the crisis more easily, while the border regions, focused on foreign trade relations, suffered more. In general, the business performance reduction was smaller in the regions that significantly intensified support. In a group of proactive regions (Tyumen, Belgorod, Ulyanovsk oblast, Crimea,1 etc.), where both general and specific support were increased above the national average, SMEs decrease rate was 1.6% lower. According to our calculations, during crises special attention should be paid to supporting business digitalization, improving regional business climate and increasing the accessibility of markets for SMEs (transport development, import substitution, etc.). These measures can become a significant factor in business development after the events of 2022. © 2022, Pleiades Publishing, Ltd.

Pandemic Challenges for the Technological Startups in the Russian Regions

Technological startups help to adapt economies to the global risks and allow one to track future trends. This paper identifies the main trends and birth factors of new high-tech companies in the Russian regions during 2013-2020. In 2020, fewer than 10,000 startups were created, this number has been steadily declining (by 40% since 2015), especially during the pandemic (-21%). Most of the startups are concentrated in Moscow, the Moscow region, St Petersburg, and the largest metropolitan areas. The share of the Leningrad, Belgorod, Kaliningrad, Lipetsk, Ulyanovsk, and Kaluga regions is growing due to the proactive policies of local authorities. Most startups are associated with knowledge-intensive services for business (B2B) and digital technologies. In 2020, their number increased in pharmaceuticals (about 100%) and in the production of medical devices (by about 30%). Based on the results of econometric analysis, start-up activity in Russia, analogous to countries with an established market economy, depends upon human capital concentration, market access, and a favorable business climate. Universities, through attracting students, especially those in STEM specialties, stimulate startup creation;although the share of university startups does not exceed one third of a percent. Budgetary and university expenditures on R&D are ineffective in terms of creating new companies. The influence of development institutions on start-up activity was not found, while clusters and technology parks have a weak effect. The growth of startups is lower in regions with a predominance of large organizations, as well as in resource centers. The latter may be one of the manifestations of the "resource curse". Startup activity is stable over time and depends on the situation in neighboring regions, which limits the chances to change the situation by means of entrepreneurship support policy. During the pandemic, start-up activity decreased minimally in regions with large metropolitan areas and a high level of education. Recommendations include tools for establishing a more balanced cross-regional situation by implementing the model of an entrepreneurial university, an expansion of start-ups' access to capital and markets, and the regionalization of entrepreneurship policies.

COVID-19: Spatial Dynamics and Diffusion Factors across Russian Regions

Confirmed cases of coronavirus infection, at first approximation, corresponds to models of diffusion of innovations. We applied models to analyze spatial patterns in Russia. The article describes in detail statistical and other restrictions that reduce the possibility of predicting such phenomena and affect decision-making by the authorities. Keeping current trends according to our estimates, as of May 12, the dynamics of confirmed cases will begin to decline in the second half of May, and the end of the active phase of the epidemic, at least in Moscow, can be expected by the end of July. The dynamics of confirmed cases are a reduced and delayed reflection of real processes. Thus, the introduction of a self-isolation regime in Moscow and many other regions has affected the decrease in the number of new confirmed cases in two weeks. In accordance with the model, carriers infected abroad (innovators) were concentrated at the first stage in regions with large agglomerations, in coastal and border regions with a high intensity of internal and external relations. Unfortunately, the infection could not be contained;the stage of exponential growth across the country began. By mid-April 2020, cases of the disease were recorded in all Russian regions;several cases were in the most remote and least connected regions. Among the econometrically identified factors that determine the spread of the disease, one can note a high population density in cities, proximity to the largest metropolitan areas, an increased share of the most active and often traveling part of the population (innovators, migrants), intensive ties within the community and with other countries and regions. The spread rate is higher in regions with a high population exposure to diseases, which confirms the theses on the importance of the region s health capital. Moreover, the combination of factors and their influence changed in accordance with the stages of diffusion, and at the initial stage, random factors prevailed. In conclusion, some directions for further research are given. © 2021 Russian Academy of Sciences. All rights reserved.

COVID-19: Spatial Dynamics and Diffusion Factors across Russian Regions

The observed spread of coronavirus infection across Russian regions, as a first approximation, obeys the classic laws of diffusion of innovations. The article describes in detail theoretical approaches to the analysis of the spread of social diseases and discusses methodological limitations that reduce the possibility of predicting such phenomena and affect decision-making by the authorities. At the same time, we believe that for most regions, including Moscow, until May 12, 2020, the dynamics of confirmed cases are a reduced and delayed reflection of actual processes. Thus, the introduced self-isolation regime in Moscow and other agglomerations affected the decrease in the number of newly confirmed cases two weeks after its introduction. In accordance with our model, at the first stage, carriers infected abroad were concentrated in regions with large agglomerations and in coastal and border areas with a high intensity of internal and external links. Unfortunately, the infection could not be contained, and it started growing exponentially across the country. By mid-April 2020, cases of the disease were observed in all Russian regions;however, the remotest regions least connected with other parts of Russia and other countries had only isolated cases. By mid-May, at least in Moscow, the number of new cases began to decline, which created the prerequisites for reducing restrictions on the movement of residents. However, the decrease in the number of new cases after passing the peak of the epidemic in May is slower than the increase at the beginning. These facts contradict the diffusion model;thus, the model is not applicable for epidemiological forecasts based on empirical data. Using econometric methods, it is shown that for different periods of diffusion, various characteristics of the regions affect the spread of the disease. Among these features we note the high population density in cities, proximity to the largest metropolitan areas, higher proportion of the most active and frequently traveling part of the population (innovators, migrants), and intensive ties within the community, as well as with other regions and countries. The virus has spread faster in regions where the population has a higher susceptibility to diseases, which confirms the importance of the region’s health capital. The initial stage was dominated by random factors. We conclude this paper with directions for further research.

Institutions, entrepreneurship,and regional development in Russia

The role of small and medium-sized enterprises (SMEs) in the Russian economy remains modest and declined in 2019. In 2020, due to the crisis and anti-covid-19 measures, the share of SMEs in GDP and employment will significantly decrease. Why is this happening, and is it worth supporting a seemingly insignificant sphere of the economy? The article describes the factors and patterns of entrepreneurship development in Russia and their relations with the regional development. The development of SMEs is negatively affected by uncertainty of the economic situation and decline in demand. High investment risks and a low level of trust narrow the possibilities for productive and opportunity entrepreneurship development. As a result, the share of informal employment and necessity entrepreneurship is high and will grow in Russia, especially in the least developed regions. Although in the pre-crisis years, there was a tendency toward an improvement in formal institutions, an increase in the availability of financing, but not in all regions. Informal institutions and norms change more slowly, they determine low involvement in entrepreneurial activity. A crisis can lead to a reduction in the number of entrepreneurs, which will have a negative long-term effect on sustainable regional development. The sectoral structure of the SME has diversified, and the share of internet services has grown. These processes because of forced digitalization during the epidemic may accelerate, especially in large agglomerations. Direct state support previously had little effect on the SME development due to the lack of awareness and distrust, small scale, so there is doubt that it will be able to radically change the situation in the current period. If the crisis and anti-epidemic measures continue in the summer, the worst negative consequences should be expected in the southern regions, where more than 50% are employed in the entrepreneurial sector, but entrepreneurial ecosystems and digitalization are poorly developed. Our calculations show a potential reduction in the number of small and medium-sized enterprises by 50-60%, which could lead to a decrease in gross regional product by an average of 3-10%. Роль малого и среднего предпринимательства (МСП) в экономике России остается скромной и снижалась в 2019 г. В 2020 г. в связи с кризисными явлениями и мерами по борьбе с эпидемией covid-19 доля МСП в ВВП и занятости существенно сократится. Почему так происходит, и стоит ли поддерживать незначимую на первый взгляд сферу экономики? В статье описаны факторы и закономерности развития предпринимательства в России в их взаимосвязи с развитием регионов. На развитие МСП негативно влияет неопределенность экономической ситуации и сокращение спроса. Высокие инвестиционные риски и низкий уровень доверия сужают возможности развития наиболее значимой части предпринимательства - производительного и добровольного. В результате в России высока и вырастет доля неформальной занятости и вынужденного предпринимательства, особенно в наименее развитых регионах. Хотя в предкризисные годы наблюдались тенденции улучшения формальных институтов, повышение доступности финансирования, но далеко не во всех регионах. Неформальные институты и нормы изменяются медленнее, а именно они определяют низкую вовлеченность в предпринимательскую деятельность. Кризис может привести к сокращению и так малого числа предпринимателей, что окажет негативный долгосрочный эффект на устойчивое региональное развитие. Отраслевая структура сектора МСП диверсифицировалась, росла доля интернет-сервисов и наукоемких услуг. Эти процессы в результате вынужденной цифровизации во время эпидемии могут ускориться, особенно в крупных агломерациях. Прямая государственная поддержка ранее слабо влияла на развитие сектора МСП из-за неосведомленности и недоверия предпринимателей, малых масштабов, поэтому есть сомнения, что она сможет кардинально изменить ситуацию в текущий период. Если кризис и противоэпидемические мероприятия продолжатся и летом, то наибольшие негативные последствия следует ожидать в южных регионах, где более 50% заняты в предпринимательском секторе, но слабо развиты предпринимательские экосистемы и низкий уровень цифровизации. Наши расчеты показывают потенциальное сокращение числа малых и средних предприятий на 50-60%, что может привести к снижению валового регионального продукта в среднем на 3-10%.

VULNERABILITY OF THE POPULATION OF MOSCOW DISTRICTS TO NATURAL HAZARDS

The frequency of natural hazards, such as heat waves, epidemics, floods, hurricanes etc. tends to increase both in Russia and abroad. Under the climate change, population aging and accelerating mobi lity, increased urban density and environment degradation the residents of large cities are becoming more vulnerable to the consequences of such events. According to experts, more than 11 thousand people be came victims of 2010 extreme summer temperatures in Moscow. The effects of the coronavirus epidemic are y et to be assessed, and it is important to study the socio-economic differences of Moscow districts in t he context of crisis and expanding pandemic, considering the negative consequences for health and life of residents. The authors propose a natural hazard vulnerability index for Moscow districts. The index accounts for the proportion of the most susceptible part of the population, as well as the possibility of ada ptation of residents. Such social strata as pensioners, disabled persons, residents of poorer areas and migr ants are the most vulnerable, i.e. incapable of self-protection or leaving a disaster area because of physica l or financial restrictions. It was found that since 2010 the vulnerability of population has increased i n 104 of 125 Moscow districts, as a result of increasing numbers of elderly and disabled people, and decreasi ng incomes in the depressed areas. Priority territories for implementing the policy of adaptation to ha zardous events are in Zelenograd (Matushkino, Savelki, Staroe Kryukovo, Kryukovo, Silino), in the southeast (Nekrasovka, Veshnyaki) and the northeast (Northern Izmailovo, Metrogorodok, Golyanovo) parts of the capital. The adaptability in central districts, subjected to gentrification, is increasing due to th e growing proportion of wealthy citizens. As a result of the 2020 crisis, associated with the pandemic and the fall in oil prices, a decrease in household incomes could further aggravate the vulnerability of residents of the majority of Moscow districts;the most negative consequences are expected in more vulnerable areas. The results allow m ore precise application of natural hazards monitoring, warning and adaptation tools. For example, the ab ove- mentioned vulnerable areas are in need of providing the timely ambulance access and raising awarenes s of the elderly locals and migrants. В России и за рубежом наблюдается рост повторяемости опасных природных явлений, в том числе пиковых термических условий, эпидемий, наводнений, ураганов и др. В результате изменений климата, старения и роста мобильности населения, увеличения плотности застройки, ухудшения экологической ситуации, жители крупных городов становятся более уязвимы к последствиям подобных событий. Так, по оценкам экспертов в Москве более 11 тыс. человек стали жертвами экстремальных летних температур 2010 г. Последствия эпидемии коронавируса только предстоит оценить, но изучение социально-экономических различий районов Москвы актуально в условиях начавшегося кризиса и развернувшейся пандемии с учетом негативных последствий для здоровья и жизни жителей. Авторами предложен индекс уязвимости населения районов столицы к опасным природным явлениям. Индекс учитывает долю наиболее восприимчивой части населения, а также возможности адаптации жителей. Наиболее уязвимы пенсионеры, инвалиды, жители более бедных районов и мигранты - все те слои общества, которые не могут защитить себя или покинуть зону бедствия из-за физических или финансовых ограничений. Нами установлено, что с 2010 г. в 104 из 125 районах Москвы уязвимость населения выросла за счет роста числа пожилых и маломобильных граждан, сокращения доходов населения в депрессивных районах. Приоритетные территории для проведения политики адаптации к опасным явлениям расположены в Зеленограде (Матушкино, Савёлки, Старое Крюково, Крюково, Силино), на юго-востоке (Некрасовка, Вешняки) и северо-востоке (Северное Измайлово, Метрогородок, Гольяново) столицы. В центральных районах, подверженных процессам джентрификации, благодаря увеличению доли состоятельных граждан и благоустройству адаптивность росла. В результате кризиса 2020 г., связанного с пандемией и падением цен на нефть, сокращение доходов населения может привести к дальнейшему росту уязвимости жителей большинства районов Москвы, а наибольшие негативные последствия ожидаются в более уязвимых районах. Результаты позволяют более точечно применять инструменты мониторинга, предупреждения и адаптации к опасным явлениям, в частности в упомянутых районах потребуется обеспечение своевременного доступа скорой помощи и проведение разъяснительной работы с пожилыми жителями и мигрантами.