Russian Metropolitan Areas: Crisis Resilience in 2020

The economic turmoil of 2020 is hammering real estate and construction, but its degree is not the same across Russia. We saw this happening during the 2008 and 2014 crises, and we are watching it right now. Tracking the situation on the real estate markets of large Russian cities, we see that the dynamics of market indicators in crisis periods have always been different in various cities under the same external conditions, and different regional real estate markets react to macroeconomic shocks in different ways.

Written by Ilya Volodko and Andrey Vakulenko – MACON Realty Group, EECFA Russia

Moscow city – Source of picture

The 2020 crisis and regionality in Russia

While the past crises were mostly of macroeconomic nature, the crisis in 2020, in addition to the macro component such as falling oil prices and the ruble’s volatility, has a strong local component: different regimes and periods of lockdown measures due to the pandemic and the variety and unequal effectiveness of regional measures to support businesses and the population. Because of this, the current crisis affects local real estate markets even more asymmetrically.

One of the main influences on the degree of penetration of the crisis into the largest cities of Russia will be exerted by the structure of their economies because the degree of damage caused by lockdown and other measures to combat the pandemic on different sectors is mixed. To analyse these differences, we have used data from the Institute for Urban Economics Foundation on the structure of the economy of Russian cities and the volume of the Gross Urban Product (GUP).

To understand how strongly a metropolitan economy reacts to the crisis, MACON consultants have assigned a stability coefficient to each metropolitan economic sector (classification according to the Brookings Institution methodology), depending on its vulnerability, recovery rate and predicted consequences. Coefficient 1 means the greatest stability/no influence, 0 means the least stability/complete or partial temporary liquidation of the industry:

  • Local/non-market services. Stability coefficient 1. The most stable sector, including state and municipal services, education, health care, social support, culture and art, recreation, etc. Its volume is set to remain or increase due to additional indexation or one-time/permanent support measures.
  • Manufacturing. Stability coefficient 0.8. Despite a possible decline in output and employment, the sector is sufficiently stable as severe lockdown measures do not apply. Since these are large businesses, they receive the greatest support both directly (financially) and through government orders, tax incentives, subsidized interest rates and easier access to debt financing.
  • Utilities. Stability coefficient 0.8. They remain fundamentally resilient to the crisis. They are negatively affected by shrinkage in business activity, which is offset by the rise in consumption by individuals, many of whom still work remotely. Yet, the difference in tariffs for individuals and businesses is hurting earnings.
  • Commodities. Stability coefficient 0.7. It includes mining, agriculture, forestry, hunting and fishing. The impact is more significant, the dynamics of commodity prices has a negative trend. But given the large volume of employment, the traditional volatility in these markets, and the non-stop nature of many extractive industries, the sector is most likely to continue working and maintain basic employment in mid-term.
  • Construction. Stability coefficient 0.5. A major negative impact due to the industry’s high dependence on any macroeconomic fluctuations, as well as with the multiplier effect, due to which even a slight decrease in construction volumes causes great changes in related industries. But the nature of the industry guarantees a considerable degree of state support and hence stability.
  • Transportation. Stability coefficient 0.5. The sector contracted due to both direct factors during the lockdown (almost complete elimination of air traffic, reduction of railway transportation, prohibition of movement within cities, between municipalities and regions), and indirect factors during the lockdown (reduction of wholesale and retail trade turnover). Yet, the need to ensure commodity logistics preserves industry volumes at an acceptable level.
  • Business/Finance. Stability coefficient 0.4. One of the most vulnerable sectors of the metropolitan economy, including financial services, insurance, real estate and new technologies (science and technology). It is characterized by a great drop in business activity and a decrease in physical access to such services.
  • Trade and tourism. Stability coefficient 0.1. The segment of retail and wholesale trade, catering, hotel and conference services is the most affected in the current crisis due to the impossibility of carrying out such activities during the lockdown. It is aggravated by the low ability of the sector to recover fast, the simplicity of liquidation procedures, the lack of access to credit and inadequate state support.

Based on data on the structure of metropolitan economies, as well as the above estimates and stability coefficients, it is possible to compile a ranking of the largest Russian metropolitan areas in terms of the degree of resistance to the crisis, where the first place/highest value means a higher degree of stability.

The findings

The metropolitan areas of Perm, Chelyabinsk and Saratov demonstrate the greatest stability. In these cities, on average, more than 60% of the economy is accounted for by the 3 basic sectors: local/non-market services, manufacturing, utilities. These are either fully controlled by the state/municipality or have a major systemic/city-forming character allowing them to receive benefits that contribute to the preservation of employment and production.

The metropolitan areas of Moscow, St. Petersburg, Krasnodar and Yekaterinburg turned out to be the least resistant to the crisis. The share of the 3 basic sectors (local/non-market services, manufacturing, utilities), in contrast to the leaders, is much lower here: on average 45% versus 63%. However, the share of Business/Finance and Trade and tourism sectors, which are the most vulnerable in the current situation, is much higher (42% versus 23%). But while Moscow and St. Petersburg, due to broader financial opportunities, can offset these factors with active financial, tax and other support of the population and businesses, non-capital cities do not have such a resource.

We have found that the poorer the city, the more stable it is in the current crisis. The paradox is that Russian metropolitan areas that actively developed before the current crisis with a great deal of financial, business services, improved construction market and IT-technologies are in a much more difficult situation today than those with an economic structure from the pre-digital era and with industrial enterprises and non-market services.

For construction forecast on Russia, consult the latest EECFA Forecast Report Russia that can be purchased on eecfa.com

Construction and resilience

The different resilience to the crisis in various cities has a direct consequence on the segments of the construction market. Apart from the obviously severely affected office and retail, the most indicative is housing where demand reacts rather quickly to macroeconomic shocks and changes in the external environment. The number of housing transactions in Q2 2020 compared to Q1 2020 decreased in most Russian cities and regions owing to the dropping income of the population, the restrictions on movement, and the temporary impossibility of state registration of transactions. However, the most pronounced decline in demand was precisely in the cities with the least crisis-resistant economies which experienced a bigger increase in unemployment and a much bigger reduction in general business activity and a decrease in household income.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

This site uses Akismet to reduce spam. Learn how your comment data is processed.