Author: Admin
COVID-19 | The Case of Poland II
Poland in the FREE Network Covid-19 Project (May 26, 2020)
Current Health Situation in Poland
Poland noted its first coronavirus infection in early March 2020. After the initial rapid spread of the disease throughout the country and spike in the total number of registered infections, since early April the infection curve stabilized at a relatively low level (compared to other European countries) of 250-350 new daily cases. The flattening of the curve was a result of drastic health and social restrictions gradually imposed on society (more details below). Since the first reported case, the testing capacity has also been substantially improved, with the number of tests conducted daily increasing from 2K to 15-20K in late April, and holding steady since then.
Figure 1. Number of Covid infections per 100K inhabitants in districts in PL (as of May 25)
Even though Poland has not yet reached an apparent decrease in the number of new daily infections, since the end of April the government introduced a strategy of a slow, four-step re-opening of the economy (more details below). As of 26 May 2020, the total number of Covid infections in Poland approached 22K, with the number of fatalities as high as 1K, and cases reported in all but 7 districts of the country (out of over 300 – see Figure 1). At this point in time, Poland also found itself at the third phase of the lifting of restrictions on economic activity.
Government Health Policies
Lockdown Introduction
The Minister of Health announced a state of epidemic risk in the territory of Poland on March 14 [7], raising it further to a state of epidemic 6 days later [8]. Measures counteracting the epidemic were introduced centrally in Poland by the Minister of Health, and were gradually extended:
- Restriction on the size of public gatherings: since 14.03.2020 limited to 50 [7]; since 25.03.2020 – 2 people (except for families and funerals up to 5 people) [9],
- Ban on all non-essential mobility since 25.03.2020 [9]; since 01.04.2020 limitations on access to public spaces like parks, playgrounds and recreational areas; distance of 2 meters between people in public places; further restrictions for minors [10],
- Bars and restaurants closed and allowed only to provide take-away food since 14.03.2020 [7],
- Childcare institutions, all schools and higher education institutions closed on 12.03.2020, formally online education provided since 25.03.2020 [11, 12],
- Since 15.03.2020 foreigners banned from travelling into Poland (with exceptions), while all Poles arriving from abroad quarantined for 14 days after arrival [7],
- Shopping malls, sports and recreation centers, sports events, cinemas, theatres, etc. closed since 14.03.2020 [7]; since 01.04.2020 – hairdressers, beauty salons, physiotherapy, hotels etc. [10],
- Restrictions on the number of people using public transport since 25.03.2020 [9],
- Since 01.04.2020 restrictions on the number of people in shops and designated shopping hours for 65+ only [10], since 02.04.2020 obligation to wear disposable gloves [10],
- Restrictions in workplaces since 02.04.2020: distance between coworkers, access to protective equipment [10],
- Since 16.03.2020 certain hospitals devoted exclusively to patients with (suspicion of) Covid-19 [13],
- Since 16.04.2020 mandatory covering of mouth and nose in all public places, inside and outside [17].
Gradual Ease of Restrictions
On March 16, 2020, the Minister of Health announced a gradual strategy of lifting the restrictions imposed on social life and economic activity. The plan is divided into four steps. The first stage was implemented on 20.04.2020 [18]:
- increase in the limit of customers in shops,
- public spaces like parks and recreational areas (except playgrounds) open,
- mobility restrictions lifted for minors over 13 y.o.
The second stage was introduced on 04.05.2020 [19, 20, 21]:
- shopping malls open with restrictions on the number of customers, shopping hours for 65+ cancelled,
- museums, libraries, physiotherapy, hotels open,
- sports facilities open with restrictions on the number of users,
- 14-day quarantine for workers from neighbouring countries cancelled,
- since 06.05.2020 some nurseries and kindergartens open.
The third stage started on 18.05.2020 [22, 23]:
- mobility restrictions lifted for minors under 13 y.o.
- hairdressers, beauty salons, outdoor cinemas open, restaurants and bars – with restrictions on the number of customers,
- increase in the number of people using public transport,
- sport trainings allowed with restrictions,
- some classes (practical or individual) in post-secondary schools allowed,
- since 25.05.2020 classes for children from the 1st – 3rd grade in primary schools and final-year graduates allowed,
- since 01.06.2020 consultations with teachers at schools allowed.
The fourth stage is planned for the near future, without a specific date. It involves the opening of cinemas and sports centers.
Government Economic Policies
The government implemented several stages of the so called “Anti-crisis shield”, the first of which came into force on April 1. The overall package includes a number of broad measures to support enterprises and workers for a period of three months and covers both direct financial support as well as provisions regarding financial liquidity for companies [14, 15]. In March the National Bank of Poland decreased interest rates and announced that it will support access to credit through targeted longer-term refinancing operations and if necessary will provide monetary stimulus through large scale open market operations [16].
Short Summary of Measures
Labor market [14]:
- Increased flexibility of employee daily and weekly hours of work;
- Extension of childcare leave for parents with children aged 0-8;
- In case activities affected by revenue reduction (revenue fall by 15% year-to-year or 25% month-to-month):
- Self-employed or employees on non-standard contracts to receive a monthly benefit equivalent to 80% of minimum wage for up to three months;
- Companies to receive support equivalent to 50% of the minimum wage for inactive employees due to the stoppage, provided individual salaries are not reduced by more than 50%;
- Companies to receive support equivalent to up to 40% of average wage for employees whose hours are reduced by 20%;
- Alternative support to employment provided to SMEs (up to 249 employees) in case of revenue loss from the Labour Fund: depending on the level of revenue loss (>30%, >50%, >80%) support to employees expressed as ratio of the Minimum Wage (respectively: 50%, 70% and 90%);
- Relaxation of work and stay permits for foreigners.
Social transfers:
- No specific measures have been implemented but the government is considering:
- a tourism voucher of 1000 PLN paid to employees with a 90% contribution from the government (10% paid by employers); paid to employees on wages below the national average wage;
- additional support to housing benefit for those who become eligible to housing benefits due to the economic slowdown;
Tax breaks [14]:
- 100% of social security contributions to be paid by the government for self-employed and employees employed in micro enterprises (up to 9 employees) and 50% paid by the government in small enterprises (10-49) for three months;
- Tax payments and social security contributions on earnings and profits can be delayed till 01.06.2020;
- Losses from 2020 will be deductible from the 2021 tax base.
Emergency loans, guarantees and support [14]:
- Small-scale loans to small companies;
- Reduced administrative requirements and relaxation of numerous regulatory rules;
- Increased liquidity of firms through channels supported by the Polish Development Fund (PFR):
- extension of de minimis guarantees to SMEs;
- subsidies to SMEs which suffered revenue losses due to the pandemic;
- equities and bond issues to be financed by PFR;
- subsidies to commercial loan interest payments from BGK;
- commercial turnover insurance from Export Credit Insurance Corporation (KUKE);
- Relaxation of regulations related to contracts with public institutions (e.g. related to delays).
Monetary policy [16]:
- On 17.03.2020 NBP lowered the main reference interest rate by 0.5 pp and reduced the rate of obligatory reserves from 3.5% to 0.5%. The main reference rate was lowered further to 0.5% on 08.04.2020.
- NBP announced the readiness to engage in large scale open market operations;
- Targeted longer-term refinancing operations to allow credit refinancing by commercial banks.
References
[1] OECD Health Statistics, https://stats.oecd.org/viewhtml.aspx?datasetcode=HEALTH_REAC&lang=en.
[2] Central Statistical Office in Poland (GUS), bdl.stat.gov.pl.
[3] Supreme Medical Chamber (Naczelna Izba Lekarska), https://nil.org.pl/rejestry/centralny-rejestr-lekarzy/informacje-statystyczne.
[4] Ministry of Health, https://twitter.com/mz_gov_pl?lang=pl.
[5] Warsaw Stock Exchange (Giełda Papierów Wartościowych), https://www.gpw.pl/gpw-statistics.
[6] Central Bank of Poland (Narodowy Bank Polski), https://www.nbp.pl/home.aspx?f=/kursy/kursya.html.
[7] Ministry of Health, http://dziennikustaw.gov.pl/DU/2020/433.
[8] Ministry of Health, http://dziennikustaw.gov.pl/DU/2020/491.
[9] Ministry of Health, http://dziennikustaw.gov.pl/DU/2020/522.
[10] ministry of Health, http://dziennikustaw.gov.pl/DU/2020/566.
[11] Ministry of Science and Higher Education, http://dziennikustaw.gov.pl/DU/2020/405.
[12] Ministry of National Education, http://dziennikustaw.gov.pl/DU/2020/410.
[13] https://www.gov.pl/web/koronawirus/lista-szpitali.
[14] Polish Development Fund (Polski Fundusz Rozwoju Przewodnik Antykryzysowy dla Przedsiębiorców 02.04.2020), https://pfr.pl/tarcza.
[15] Polish Development Fund (Polski Fundusz Rozwoju Przewodnik Antykryzysowy dla Przedsiębiorców 05.05.2020), https://pfr.pl/tarcza.
[16] Central Bank of Poland (Narodowy Bank Polski), https://www.nbp.pl/home.aspx?f=/polityka_pieniezna/dokumenty/komunikaty_rpp.html.
[17] Ministry of Health, http://dziennikustaw.gov.pl/DU/2020/673.
[18] http://dziennikustaw.gov.pl/DU/rok/2020/pozycja/697.
[19] http://dziennikustaw.gov.pl/DU/rok/2020/pozycja/792.
[20] http://dziennikustaw.gov.pl/DU/rok/2020/pozycja/780.
[21] http://dziennikustaw.gov.pl/DU/rok/2020/pozycja/779.
[22] http://dziennikustaw.gov.pl/DU/rok/2020/pozycja/878.
[23] http://dziennikustaw.gov.pl/DU/rok/2020/pozycja/871.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Supporting Measures for Belarusian SMEs: the Context of the Covid-19 Pandemic
In the context of the evolving global economic crisis, governments are “competing” with each other in the complexity and scale of measures to support the economy and, in particular, small and medium-sized enterprise (hereafter SMEs). The main goal of these measures is, on the one hand, to prevent a significant increase in unemployment and a consequent social strain, and, on the other hand, to ensure economic recovery driven by the most efficient enterprises.
Belarusian SMEs, which currently employ more than 1.3 million people, usually respond faster and more extensively than the state companies to the downturn in the economy by laying off employees. At the same time, they are also expected to be more sensitive reacting to governmental support policies. In this regard, the policy brief discusses the role and response of SMEs in the period of crises and delineates short- and medium-term measures.
Why are SMEs in the Focus During Economic Downturns?
SMEs often become the focus of state policy in a period of adverse and unstable economic situations and the recent pandemic is not an exception. This special attention can be motivated by the following basic assumptions:
1) SMEs are more flexible and respond faster to both negative and positive trends in the economy (Muller at al., 2018);
2) the activity of SMEs is more labor-intensive compared to large enterprises (Beck et al., 2005; Cravo et al., 2012);
3) a period of economic uncertainty creates new opportunities (new niches, exits of competitors from the market) that can be used by the most proactive SMEs (Cowling et al., 2015).
Based on these assumptions, a large share of SMEs on the one hand makes the economy more resilient in crises and, on the other hand, contributes to the volatility of unemployment. As a result, governments try to support SMEs to prevent a rapid increase in unemployment due to staff cuts and bankruptcy and, simultaneously, to maintain a competitive environment that creates incentives for innovation.
Typically, governments have substantial experience and proven tools to uphold large public and too-big-to-fail private enterprises, while supporting a heterogeneous population of SMEs requires additional study and field tests.
At the same time, the design, the scope, and the coverage of support policies should be introduced having in mind the possible reactions of various types of SMEs to the economic hardship. Indeed, during an economic decline even in the worst hit sectors, businesses and SMEs in particular may react by implementing three basic strategies:
1) reducing costs by firing employees, cutting wages and by increasing productivity;
2) increasing revenue by introducing innovations (product, process, organizational, marketing), diversification, and entering new markets;
3) suspension of activities or liquidation of an enterprise (OECD, 2009).
Definitely, any government aims for the largest possible share of enterprises that pursue the second strategy leading to job creation and significant added value.
Policy Responses in the Period of the Pandemic
Due to the urgency of adoption and the weak predictability of the epidemiological situation, most of the proposed SME-support packages around the world are designed for the short term and are poorly targeted. Based on the study of already announced measures, the OECD (2020) has developed a comprehensive classification and sequence of SME-support measures undertaken by governments:
1. Health measures, and information for SMEs on how to adhere to them;
2. Measures to address liquidity by deferring payments (taxes, social security & pension contribution, rental, utilities);
3. Measures to provide extra and more easily available credit to strengthen SME resilience;
4. Measures to mitigate the consequences of lay-offs by extending possibilities for temporary redundancies and wage subsidies;
5. Structural policies (digitalization, training and education for SMEs, support in finding and entering new markets etc.).
Unfortunately, the government of Belarus has started discussing and implementing some of these measures only partially and in a rather non-specific way. Instead of this, we argue that all the measures should be targeted and adjusted to different sectors. To further expand and analyze our point, BEROC developed and commissioned an express random-sample survey of 100 Belarusian SMEs on April 13-27 in order to elaborate and justify relevant support measures (BEROC, 2020).
Belarusian SMEs in the Pandemic
The financial situation of Belarusian SMEs by sector and their response to the crisis manifested in implementing innovative approaches and new business models are illustrated in Figure 1.
Figure 1. Decrease of revenues and response of SMEs
SMEs operating in hotels, restaurants, catering (HoReCa), education, sport & leisure as well as transportation (the right lower rectangle) are characterized by a substantial decrease of revenues and low adaptability. At the same time SMEs in the communication and IT sector and scientific, technological and consulting sectors demonstrate a high degree of adaptability that may be related to some extend to managerial competencies and human capital in general which is concentrated in these sectors.
As an implication for policy makers and SMEs’ leaders, possible support measures (based on OECD classification) and business strategies are summed up in Table 1.
Table 1. Support measures and business strategies for Belarusian SMEs
Group | Sectors | Recommended strategy | Relevant Measure (number in the OECD classification) |
A. Decrease of revenues + slow adaptation | Construction,
wholesale trade & retail manufacturing |
Re-configuring supply chains, entering new niches, business process optimization | 2,3,5 |
B. Decrease of revenues + active adaptation | Communication & IT
Scientific, technological, consulting services |
Focusing on development of anti-crisis solutions in B2B and B2C segments | 2,4 |
C. Substantial decrease of revenues + slow adaptation | Transportation
HoReCa Education Leisure, beauty & sport |
«Conservation» or liquidation of a business | 2,3,5 |
D. Substantial decrease of revenues + active adaptation | Not identified in the survey | Diversification to adjacent market segments | 2,4,5 |
E. No changes or growth of revenue | Agriculture & Forestry
E-commerce, pharmacy, online services, online games… |
Expansion to new markets while competitors are on quarantine. | 5 |
Source: Own elaboration based on the survey.
The main measure to support SMEs in the short term (items 2-4 in the OECD classification) can be:
- Deferral, reduction or suspension of contributions to the social security fund (groups B, C) – this will save jobs in the short term;
- Wage subsidies that will allow paying minimum wages and keeping staff (groups A, C)
- Rent and utility deferrals or at least payment in arrears – for groups A, C – combined with the support of building owners. This will significantly reduce costs in the face of falling revenues instead of reducing labor costs;
- Loan holidays and preferential conditions for SMEs (group D). This will provide liquidity for enterprises that according to banks’estimates will be able to develop in the medium term;
- Temporary repeal of fines for late payment of taxes and contribution to the social security fund (groups A-D).
As for the medium-term measures, the most relevant ones are as follows:
- Expanding the coverage and improving the quality of business education (including digitalization of business) by means of providing vouchers and/or grants;
- Subsidies to unemployed people for starting up a business combined with basic training on entrepreneurship;
- Export support by developing infrastructure for certification and international marketing as well as providing export loans (Marozau et. al., 2020).
Conclusion
The Belarusian government is substantially restricted in terms of financial resources, fiscal and external debt opportunities to extensively support businesses suffering from the economic crisis. Therefore, formal and economically justified criteria for selecting sectors, as well as individual businesses and individual entrepreneurs should be developed. Meanwhile, the beneficiaries of the state support should not be the most affected businesses, but rather the most forward-looking ones. This so-called “picking winners” approach (Gonzalez-Pernia et al., 2018) would conduce to faster economic recovery and job creation driven by the private sector and, particularly, by SMEs. This is probably the main argument in favor of supporting small and medium-sized businesses in the crisis.
References
- Beck, T., Demirguc-Kunt, A., Levine, R. (2005). “SMEs, Growth and Poverty: Cross- country evidence.” Journal of Economic Growth, 10(3), 199-229.
- BEROC. (2020). “SME Survey Results”, Access mode http://covideconomy.by/business. Access date: May 19, 2020).
- Cowling, M., Liu, W., Ledger, A., & Zhang, N. (2015). “What really happens to small and medium-sized enterprises in a global economic recession? UK evidence on sales and job dynamics.” International Small Business Journal, 33(5), 488-513.
- Cravo, T.A., Gourlay, A., Becker, B. (2012). “SMEs and Regional Economic Growth in Brazil.” Small Business Economics, 38 (2), 217-230.
- González-Pernía, J. L., Guerrero, M., Jung, A., & Pena-Legazkue. (2018). “Economic recession shake-out and entrepreneurship: Evidence from Spain.” BRQ Business Research Quarterly, 21(3), 153-167.
- Marozau, R., Akulava, M., Aginskaya, H., (2020). “Measures to support small and medium-sized businesses in Belarus in the context of the pandemic and global recession.” BEROC Policy Paper Series, PP no.89.
- Muller, P., Mattes, A., Klitou, D., Lonkeu, O., Ramada, P., Ruiz, F.A., Devnani, S., Farrenkopf, J., Makowska, A., Mankovska, N., Robonn, N., Steigertahl, I. (2018). Annual report on European SMEs 2017/2018. The 10th Anniversary of the Small Business Act. European Commission.
- OECD. (2020). “COVID-19: SME Policy Responses.” OECD Centre for Entrepreneurship, SMEs, Regions and Cities (CFE). Access mode https://read.oecd-ilibrary.org/view/?ref=119_119680-di6h3qgi4x&title=Covid-19_SME_Policy_Responses. Access date: May 19, 2020.
- OECD. (2009). “The Impact of the Global Crisis on SME and Entrepreneurship Financing and Policy Responses.” OECD – Centre for Entrepreneurship, SMEs and Local Development, Paris.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
COVID-19 | The Case of Georgia
Introduction
Georgia has close to 4 million inhabitants. It borders Russia, Azerbaijan, Armenia and Turkey, which are also its main trading partners. The capital and largest city is Tbilisi with about 1,5 million inhabitants. Agriculture and the tourism sector dominate the local economy.
Georgia reported its first case of Covid-19 on February 27, 2020 and its first deaths on April 6, 2020. The government reacted quickly, banning direct flights from China in late January 2020 and imposing severe travel restrictions even within the country in March 2020. Schools and universities were closed on March 11, 2020. The government banned all larger public gatherings on March 21, 2020, the same day when the country declared the state of emergency. The four major cities of Georgia – Tbilisi, Batumi, Kutaisi and Rustavi – were put under lockdown on April 15, 2020.
As of May 8, 2020, Georgia reported a total of 9 fatalities, suggesting that the virus has quite successfully been contained so far. A breakdown of the healthcare system seems unlikely at the moment. Economically, the situation is more heterogenous. Georgia’s public finances are in a tolerable enough shape to handle a crisis. The public debt to GDP ratio is not very high (44.9% in 2018), and the government budget deficit is also below 3% of GDP. Georgia’s financial system has been praised as one of the strongest among in the ECA region. However, annual inflation in January-February was 6.4%, which is significantly higher than the target level of 3%. Georgia is facing uncertainties in terms of inflationary expectations, and this limits the National Bank of Georgia’s (NBG) ability to stimulate the economy under the current circumstances. Most probably, NBG will not cut the policy rate to avoid provoking further currency depreciation and stoking inflationary expectation even further. Moreover, a major weakness in the Georgian economic system lies in its lack of a broad social safety net infrastructure, which could help support afflicted groups during downturns. Finally, another risk is the substantial informal sector: workers in these sectors are hard to reach via conventional policy measures.
Below, we outline how the Georgian economy has been affected by Covid-19 and what the policy responses have been so far. We will also discuss several economic scenarios and explain which further policy options are thinkable.
How Does the Covid-19 Crisis Affect the Georgian Economy?
Demand Side Effects
- A decline in domestic consumption resulting from behavioural and policy changes is to be expected on the demand side – i.e. people staying home as a precaution or because they are required to. In addition, currency depreciation and possible price spikes (due to herding behaviours and potential disruptions in supply chains) are also expected to have a negative effect on consumption and investment.
Household consumption accounts for 66.7% of the Georgian GDP (Geostat, 2018). A significant reduction in household consumption (e.g. spending on transportation, clothing, electronics, and domestic services) would therefore result in an overall slowdown of GDP growth. A slowing of internal demand would hit people working in the informal sector particularly hard; namely, those without a regular salary (e.g. temporary workers, taxi drivers, and other self-employed service sector workers) and small and micro business-owners. Their situation is worsened still because the government’s fiscal stimulus and assistance is unlikely to reach them directly. They are also not expected to benefit from the extra liquidity injected into the financial system, as they will not qualify for bank loans to cover temporary income losses. Another vulnerable group are the formal sector workers employed in companies that face a dramatic decline in their usual economic activities (restaurants, hotels, the entertainment industry, transport, etc.). These companies are likely to put their workers on unpaid leave or simply fire them. Moreover, the slump in household demand will also be made worse by the fact that most families are likely to have limited savings and, therefore, their capacity to smooth consumption is limited. Hence, the crisis may cause a significant drop in well-being and, possibly, further deterioration in individuals’ physical and mental health, alongside the direct impacts of Covid-19
- A decline in domestic investment because uncertainty and deteriorating business sentiments will stall business investment decisions. Expectations of a global recession could become self-fulfilling if ‘business-as-usual’ does not resume in the next few months. If companies expect a slowdown in demand, they will also delay investment, and GDP will decline further. Investment (gross fixed capital formation) accounts for approximately 28% of Georgia’s GDP. Thus, the Georgian government has announced capital spending to combat the expected drop in private investment.
- A decline in tourism and related business seems inevitable as tourism arrivals and receipts are expected to decrease sharply as a result of the numerous travel bans, and due to precautionary behavior. According to our preliminary calculations, the Georgian economy lost between 3-9% of potential tourism revenue in February. Since the tourism sector accounts for 6% of Georgia’s GDP (GNTA 2018), a direct hit to the industry will substantially impact GDP. In table 1, we work out GDP losses associated with the following scenarios:
Table 1: Net effect of the coronavirus crisis on tourism in Georgia
- The spillover effect on other sectors: a drop in demand for goods and services in the region, in China, the EU, and the US – will affect the overall economy via trade and production linkages.
While it is difficult to predict how Georgia’s economy will react to a global shock of such magnitude, some preliminary estimations may already be made. Georgia’s growth rate over the last 20 years correlates notably to several neighboring economies. One of the greatest correlations is, unsurprisingly, with Russian economic growth. Russia’s growth is also highly correlated with other countries, reflecting global economic linkages. These correlations are reported in table 2 below:
Table 2: Correlations of growth rates
Table 2 | Georgia | Russia | Armenia | Turkey | China | Kazakhstan | Italy | Germany | France | US | Israel | Ukraine |
Georgia | 1.00 | 0.87 | 0.88 | 0.66 | 0.58 | 0.81 | 0.67 | 0.74 | 0.85 | 0.69 | 0.77 | 0.73 |
Russia | 1.00 | 0.90 | 0.60 | 0.73 | 0.83 | 0.64 | 0.67 | 0.82 | 0.63 | 0.79 | 0.91 |
Source: World Bank, authors’ calculations.
In order to explore how a slowdown across major world economies will affect Georgia, we have followed three economic scenarios relating to major world economies, as reported by Orlik et al. (2020). The numbers reflect growth rate changes relative to the baseline (no virus outbreak).
Table 3: Coronavirus effect on growth rates.
Table 3. Coronavirus effect on growth rates | Real GDP annual growth change in 2020 compared to the baseline scenario, pp | Real GDP growth, % in 2020, assuming a 5% baseline | |||
Russia | Germany | US | Georgia | Georgia | |
Scenario A: Outbreak causes localized disruption | -0.9 | -1.2 | -0.2 | -1.09 | 3.91 |
Scenario B: Widespread contagion | -3 | -2.8 | -1.3 | -3.09 | 1.91 |
Scenario C: Global pandemic | -4.8 | -3.6 | -2.4 | -4.55 | 0.45 |
Source: Orlik et al. (2020); authors’ calculations.
- A decline in trade is likely and it is possible to find certain similarities between the current situation and the economic slowdown in the Eastern Europe and Central (EECA) region in 2014-2017, caused by a drop in oil prices and global appreciation of the US dollar. The latter resulted in a sharp decline of external demand, falling commodity prices and regional currency crises, which equally affected the Georgian economy. The country’s goods exports fell by 23%, while imports contracted by 15% in 2015. Trade was only restored to the 2014 level by 2018. While, the forthcoming crisis is expected to not only have stronger negative impacts on external demand, but also disruptions in the production value chains, affecting Georgia’s trade in more severe ways. Trade of all commodities, except food and medicine, is projected to decline, depending on the duration of the shock.
- A decline in Foreign Direct Investment (FDI) is to be expected since foreign investors prefer to invest in safe assets. Additionally, currency depreciation expectations will negatively affect FDI. The FDI in Georgia amounted to 1,267.7 mln. USD in 2019 (7.1% of GDP).
- A decline in remittance inflows seems likely: since all countries will suffer economically in the aftermath of the health and oil price crises, we expect significant slowdown in remittance inflows from the rest of the word. The remittances decline will hit Georgia particularly hard as it is among the top receiver countries of foreign transfers. For instance, in 2019, money transfer inflows accounted for 9.8% of GDP. Various scenarios for just how much Georgia is set to lose in monetary inflows is presented in table 4 below:
Table 4. Net change in money transfers inflow in 2020 due to coronavirus (Mln. USD) | ||
Scenario 1: 10% decrease of net money transfers in the remaining months of the year (March-December) | Scenario 2: 30% decrease of net money transfers in the remaining months of the year (March-December) | Scenario 3: 50% decrease of net money transfers in the remaining months of the year (March-December) |
-114 | -372 | -629 |
Net change in consumption spending due to money transfers decline* | ||
-570 | -1,857 | – 3,146 |
Net change as a share of household total real consumption spending** | ||
+0.3% | -2.6% | -5.5% |
* $1 of transfers is assumed to become $0.8 equivalent of consumption spending.
** USD/GEL exchange rate is assumed to equal to the official exchange rate as for March 20th (3.1818) in the remaining months of the year (March-December). Inflation is assumed to be 6% in 2020.
Source: Geostat, NBG, authors’ calculations.
Supply Side Effects
- Production disruptions may occur on the supply side. Domestic production suffers as a result of forced business closures and the inability of workers to get to work, as well as disruptions to trade and business as a result of border closures, travel bans, and other restrictions on the movement of goods, people, and capital (in the PRC as a whole fell to 50%–60% of normal levels but is now normalizing, after the introduction of extremely restrictive measures that – so far – no country in the West has been able/willing to mimic. However, in the absence of such restrictions, the crisis may be prolonged, and production might be hard to restart quickly). The overall impact on production may be mitigated by the fact that in some sectors (particularly in manufacturing) production can be ramped up in later periods to compensate for lower production (providing closures do not last too long).
- Long-term economic effects need to be taken into account. Covid-19 will impact health via mortality and morbidity, and through changes in (and the diversion of) healthcare expenditure.
Currency Depreciation
The expected decline of tourist inflows, remittances, and exports as a result of reduced foreign demand from Georgia’s trading partners and low world oil prices have already affected the lari exchange rate (mostly through expectation channels). On the other hand, due to restrictions on air travel, the outflow of currency from Georgia to foreign countries will be reduced (the import of tourism services will be lower), which will have a positive effect on the exchange rate. Another positive factor may be that Georgia’s reliance on remittances from oil-exporting countries (like the Russian Federation) has been significantly reduced in recent years.
What Has Been Done to Address the Covid-19 Crisis?
The Government of Georgia timely started applying measures to address dramatic impacts on various market participants:
Businesses
- Restructuring loans for businesses affected by the crisis;
- Companies that operate in the tourism industry: hotels and restaurants, travel agencies, passenger transportation companies, site-seeing companies, arts and sports event organizers, etc., will have their property and personal income taxes deferred by the Georgian government for four months;
- Doubling the volume of VAT refunds to companies, with the aim of supplying them with working capital;
- Designing a state program to co-finance interest payments on bank loans by hotels with 4-50 rooms, throughout the country, for the next six months.
Workers
- Loan payment deferrals for three months;
- Personal income taxes deferred for employees in the tourism industry.
The Health Care System
- No new measures are planned at this point.
The Financial System
- Easing lending restrictions for commercial banks;
- NBG has not cut policy rates and is unlikely to do so given the risks of inflation.
Other Measures
- Boosting capital expenditure (CapEx) projects with the aim of providing additional economic incentives;
- Governmental price fixing for specific products (rice, pasta, sunflower oil, flour, sugar, wheat, buckwheat, beans, milk powder and its products) by subsidizing corresponding businesses.
Will the Current Measures Be Sufficient?
Given the rapidly changing scope of the crisis, the short answer is simple – probably not. As the forecast seems pessimistic, it is the role of the fiscal stimulus and, where possible, the monetary policy to help soften the economic shock.
It is evident that the measures adopted by the government as well as private commercial banks in Georgia will not be able to directly reach a sizeable group of the population affected by the shock – i.e. those unemployed due to Covid-19; those working in the informal sector; people with low income; or households that are very reliant on remittances transfers. It is important for the government to connect with these groups quickly, not only for humanitarian reasons, but also in the interest of a broader development agenda. In case of relatively prolonged quarantine sizable part of the population will no longer be able to support themselves and their families in coming months.
What More Can Be Done?
We broadly outline the additional monetary and fiscal policy measures that may be considered:
More Forceful Fiscal Intervention:
As previously mentioned, Georgia’s systemic weakness lies in its lack of a broad social safety net infrastructure, which could help target and support afflicted groups during downturns. An unemployment benefits system, which in other countries acts as an “automatic stabilizer” and reduces and mitigates the effect of economic downturns, simply does not exist in Georgia. Yet even with an unemployment benefits system in place, the sizeable informal economy would prevent such a system from effectively easing labor market tensions. In the current situation, the government should attempt to provide cash relief for workers in the informal sector, for the low-income self-employed, and for independent contractors. These groups of workers are the most vulnerable to income flow reduction during the crisis, furthermore, they are unlikely to have access to sick leave benefits or to take advantage from cheaper bank credit.
Based on the experience of other countries, the government perhaps should consider the following measures in addition to current measures:
- Providing low interest emergency loan/cash advances to affected adults, or direct cash payments to affected households, in particular households with the elderly and children. These measures are valuable as they can quickly reach afflicted groups. Unfortunately, this solution is not well-targeted and risks wasting government funds on those who are not disadvantaged.
- Simply providing “helicopter money”, or cash transfers to households below a certain income threshold (similar measures are being considered in the US) may be an option, but this measure is subject to the same concerns as above. However, the advantage is that cash transfers allow households to optimize their expenditure and do not distort consumption choices.
- Another form of wide-reaching support could be state subsidies to help support utility payments for a limited time. These measures, equally, are not well-targeted, nevertheless there may be methods to direct them towards the households which need them the most.
- Measures to encourage companies to not cut employment in the months following the crisis: following the example of other countries, Georgia may support salary payments for companies, on the condition that they do not reduce employment or force workers to take unpaid leave.
Naturally, none of the proposed measures are perfect as they cannot specifically target those most affected by the crisis, yet they may act as a short-term second-best solution. As these examples show, Georgia should consider to develop a targeted social safety net system in the future. Such a system can make the country more resilient in the face of future crises and unexpected emergencies.
Monetary Policy
While other countries push for fiscal stimulus and monetary expansion, Georgia is facing uncertainties in terms of inflationary expectations. As discussed, this limits NBG’s ability to stimulate the economy under the current circumstances. Annual inflation in January-February was at 6.4%, significantly higher than the 3% target. Going forward, a sharp decline in aggregate demand would reduce the pressure on inflation, while a depreciating nominal effective exchange rate will exert upward pressure. Therefore, the possibility to reduce the monetary policy rate depends on which effect will dominate in the future. In the meantime, NBG has approached the IMF to increase access to funding under its Extended Fund Facility program (NBG). Alongside the additional funds from other international donors, this will positively affect the economy, strengthen the nominal effective exchange rate and, consequently, curb inflation.
In addition to the measures already announced, NBG has the option of decreasing the minimum reserve requirements for deposits attracted in a foreign currency. This will stimulate FX lending and economic activity, without creating depreciation or inflationary expectations.
Overall, the Georgian government responded very timely and efficiently to contain the virus outbreak, earning well-deserved plaudits from the international community and approval from the general public. However, as the scope of the crisis continues to change rapidly, additional measures might soon be needed. As the economic landscape becomes more uncertain, the government needs to ensure that emergency economic stimulus measures directly reach the people most affected by the crisis.
Disclaimer
This policy brief was first published as an ISET policy note on March 25, 2020 under the title “The Economic Response to COVID-19: How is Georgia Handling the Challenge?“. This brief is an adaption of the original note and is published with the consent of the authors.
References
CIA World Fact Book, 2020. “Georgia”.
The Guardian, 2020. “How UK government could support people as coronavirus spreads”.
Imeson, Michael, 2019. “Georgian banks gather rewards for resilience”. The Banker.
Lomsadze, Giorgi, 2020. “Georgia gets rare plaudits for coronavirus response“. Eurasianet.
Migration Policy Institute, 2020. “Global Remittances Guide”.
Orlik, Tom; Jamie Rush; Maeva Cousin and Jinshan Hong, 2020. “Coronavirus Could Cost the Global Economy $2.7 Trillion. Here’s How”. Bloomberg.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Safety of Older People During the Covid-19 Pandemic: Co-Residence of People Aged 65+ in Poland Compared to Other European Countries
Bearing in mind that the estimated fatality rates related to Covid-19 infections are substantially higher among older people, in this Policy Paper we focus on the demographic composition of households of people aged 65+ as one of the social risk factors that influence the consequences of the pandemic. In light of plans of easing isolation restrictions and a gradual return to higher economic activity, a key challenge for the coming weeks is to ensure the safety of those most at risk. Although lifting the lockdown mainly affects the lives of the working population and children, attention should be paid to the channels that could enhance transmission of the coronavirus among older people. This includes the prevalence of co-residence with those who will get back to their workplaces or schools once they are open again. Compared to other European countries, Poland has the highest rates of people aged 65+ sharing their households with younger adults and children with nearly 40% living together with people aged up to 50 years old (excluding partners). On the other hand, Nordic countries, the Netherlands, Belgium and Germany report far lower rates of co-residence among the older population. In these countries however, older people commonly reside in formal care facilities, which, in turn, have proved vulnerable to outbreaks of infections. This emphasizes that each country has to carefully determine its own strategy on the way to recovery. Among other factors, the pace at which restrictions on social distancing are lifted should take into account the prevalence of co-residence among the older population.
Introduction
According to the WHO, at the early stage of the Covid-19 epidemic, the fatality rate among coronavirus-infected people was estimated at about 3-4% (WHO 2020a), although estimates based on the data from European countries suggest that the rate is lower and is closer to 1.5% (ECDC 2020). The rate is quite varied from country to country; it also fluctuates over time. To a large extent, the figure depends on the number of tests conducted and, consequently, the reliability of information on the number of people infected (Roser et al. 2020). Nevertheless, both the risk of experiencing serious symptoms of the coronavirus infection and the risk of death from complications arising from the disease increase significantly with the age of the infected person. Furthermore, the risk is definitely higher for the patients with underlying conditions, in particular cardiovascular diseases, diabetes, or hypertension (Emami et al. 2020). The highest risk is observed among older persons, with the fatality rate of people infected fluctuating from 1.8%-3.5% in the 60-69 cohort, to 13.0%-20.2% in the 80+ cohort (Roser et al. 2020). Therefore, a major challenge in the area of health and socio-economic policy measures in the coming months is to keep the older population safe and contain the spread of coronavirus in that population.
This Policy Paper presents an analysis of the housing situation of people aged 65+ in Europe. Co-residence may be one of the relevant social risk factors that determine the probability of being infected with viruses which, like SARS-Cov-2, are spread through droplet transmission. As shown by research on intra-household transmission at the early stages of the epidemic in China, the majority (75%-85%) of clusters (group illnesses) were observed within households (WHO 2020b). Depending on the data, the coronavirus secondary attack rate within households is estimated at 7.6%-15.0% (Bi et al. 2020; KCDC 2020b), and from this perspective it is important to note that the incidence rate is the highest in the 20-29 age group, with most of them showing no symptoms of the disease while being able to infect others (KCDC 2020a).
Given the limited scope of labor market activity in the 65+ population, compliance with the self-isolation regime by this group will not interfere much with the gradual easing of socio-economic restrictions. Things look different among younger people due to their work or study, and among the youngest members of the population due to their school or pre-school attendance. In line with the regulations introducing the state of epidemic in Poland, since March 23rd, 2020, many workplaces have been operating on a remote basis, with their labor force doing work from home, and many companies and organizations having been closed. Similarly, the nurseries, kindergartens, schools and universities have been closed since the 16th of March this year. However, the government has already announced a plan to ease some of the restrictions to pave the way for a phased return to more intensive social contacts and economic activity (Council of Ministers 2020). Because of the shortcomings of distance learning and serious inequalities in access to education in this system (Myck et al. 2020), and considering the adverse impact of closed schools and kindergartens on the working parents, it seems imperative to resume the operation of these facilities as soon as possible.
A key challenge for the coming weeks will therefore be to reconcile the socio-economic benefits of lifting the lockdown with the risk of health implications arising from less stringent social distancing restrictions. Those implications may be particularly severe for older people. Thus, this Policy Paper discusses structural determinants of the well-being of older people, with a focus on the housing situation in European societies and the rate of co-residence with the younger population. The analyses outline the status in Poland in comparison to other European countries, pointing to a great diversity of health risks for older people. One factor is the difference in the prevalence of co-residence between the older and younger populace, and another is the prevalence of formalized care facilities. Next to disease statistics, these differences should be taken into account in any decisions on lockdown easing or a detailed design of policy measures.
In Poland, the percentage of people aged 65+ in co-residence with other members of the household aged 50 or below (excluding a spouse or partner) is 37.4% for the female population and 38.6% for the male population, i.e. the highest in Europe. In Poland, 12.0% of people aged 65+ share a household with school-age children (aged 7-18), and 7.7% live together with children aged 0-6. Co-residence with minors usually means, for obvious reasons, that the adult parents of the minors live under the same roof as well. However, Poland also reports one of the highest percentages of co-residence with other adults without minors. For example, 7.6% of people aged 65+ live in one household with people aged 19-30, and 17.3% share a household with adults aged 31-50 who are not their spouses or partners. It is worth noting, however, that in the European countries considered here a high percentage of co-residence is negatively correlated with the prevalence of collective dwelling facilities that deliver formalized care for older persons. In Poland, the supply of such institutions – whether public or private – has been very limited, with only 1.6% of people aged 80+ living in those facilities. In contrast, in Belgium, almost every fourth person of that age is a resident of such a facility. When it comes to the pandemic, it must be underscored that although in such institutions the interactions with younger people can be quite easily limited, the experience of many countries has shown that they have been quite vulnerable to coronavirus clusters and epidemic outbreaks.
Considering that Poland reports the highest percentage of co-residence among people aged 65+, particular attention should be paid to the challenges for health and socio-economic policy measures introduced in Poland to manage the intensity of social contacts during the pandemic. This, in particular, applies to the regulations on students returning to schools and the easing of social distancing rules for students and working adults. Therefore, in countries such as Poland, the restoration of frequent social contacts, which is necessary, inter alia, to put the economy back on track, will have to be accompanied with adequate safeguards for those who are most heavily exposed to negative health effects of Covid-19.
The first section of this Policy Paper reviews co-residence percentage data for the 65+ population, based on data for Europe (the European Union member states and Norway, Switzerland and the United Kingdom, for the remaining European countries the data is not available), from the 2017 European Union Statistics on Income and Living Conditions study (EU-SILC.) The second section presents data on older people living in long-term care facilities in a number of European countries, collected in recent years by the OECD.
1. Older People in Co-Residence With Other Members of the Household
In the analytical discussions below, the terms “co-residence” or “shared household” refer to a situation where persons aged 65+ live in one household with adults who are not their spouse or a partner, or with children under 19 years of age. In Poland, the percentage of households shared by people aged 65+ and children aged 18 or younger is one of the highest in Europe. Of all the older people in Poland that live in a household setting on a permanent basis (i.e. excluding those living in formalized care facilities), as many as 16.9% of women and 16.6% of men aged 65+ share a household with persons under 19 years of age (cf. Figure 1). With the exception of Slovakia and Romania, other countries report a much lower rate. In countries such as Norway, Sweden, Denmark, or the Netherlands, the rate is between 0.1% and 0.6% for women, and between 0.5% and 1.2% for men (65+ population).
Figure 1. Population aged 65+ in co-residence with persons other than their spouse/partner, by the age of the youngest member of the household
a) Male
b) Female
In Poland, approximately 12% of women and men aged 65+ share a household with students aged 7-18. In other words, more than 460k women and 280k men aged 65+ in Poland have direct, daily interactions with students attending schools (Table 1). In addition, 13.9% of women and 14.7% of men aged 65+ (530k and 360k, respectively) share a household with persons aged 19-30, who – according to research findings from other countries – demonstrate the highest incidence of coronavirus disease (KCDC 2020a). On top of that, these proportions are significantly higher in rural areas, and over 40% of the 65+ population in Poland live in rural areas. Compared to other countries in Europe, it is especially in the rural areas that Poland reports a significantly higher percentage of older people in co-residence with younger people (Figure 2). For example, while in Poland 19.0% share a household with children aged 7-18, and 21.1% with people aged 19-30, in Sweden in the 65+ population in rural areas those percentages are 0.4% and 1.0%, respectively, and in Belgium 1.9% and 1.5%. In urban areas the disparities in the demographic structure of households between Poland and other European countries are less pronounced, but still the share of the 65+ population in co-residence with younger people is among the highest in Europe; with 7.2% sharing a household with school children and 9.5% with adults aged 19-30. In Sweden these percentages are 0.7% and 1.7%, respectively, and in Belgium 1.2% and 3.8%.
Table 1: Population aged 65+ in Poland in co-residence with other members of the household (other than a partner/spouse).
Urban | Rural | Total | |||||
Male | Female | Male | Female | Male | Female | Total | |
Population aged 65+ (in thousands) | 1 435 | 2 268 | 1 007 | 1 508 | 2 441 | 3 776 | 6 218 |
People in co-residence with a person aged (in thousands): | |||||||
– 0-6 | 82 | 107 | 117 | 175 | 199 | 282 | 481 |
– 7-18 | 91 | 174 | 190 | 288 | 281 | 462 | 743 |
– 19-30 | 142 | 210 | 216 | 315 | 359 | 525 | 883 |
– 31-50 | 353 | 546 | 446 | 681 | 799 | 1227 | 2026 |
People in co-residence with a person aged (in %): | |||||||
– 0-6 | 5.7% | 4.7% | 11.6% | 11.6% | 8.1% | 7.5% | 7.7% |
– 7-18 | 6.4% | 7.7% | 18.9% | 19.1% | 11.5% | 12.2% | 12.0% |
– 19-30 | 9.9% | 9.2% | 21.5% | 20.9% | 14.7% | 13.9% | 14.2% |
Source: Authors’ compilation based on the 2017 EU-SILC data.
Nota Bene: Share of 65+ population not living in formalized care facilities.
Figure 2. Population aged 65+ in co-residence with other members of the household (other than a partner/spouse), by age of the other members of the household.
- Urban
Rural
2. Residents of Formalized Care Facilities for Older Persons
Households where people aged 65+ live under one roof with younger people (usually they are all family members) reflect the financial status of the family on the one hand, but on the other they offer care to those who might need it to due to their age or health status. In that respect, unlike many other countries in Europe, Poland has a very low share of older people who, due to barriers to independent living, decide to relocate to a formalized care facility or a similar setting. In 2017, less than 1% of the 65+ population in Poland lived in formalized care facilities; and for the 80+ population the share was only slightly higher and reached 1.6% (Figure 3). One reason is the low number of vacancies in such facilities: in 2017 in Poland there were, statistically, 12 beds per 1000 inhabitants aged 65+. For comparison, in Nordic countries (Denmark, Finland, Norway, Sweden) more than 12% of the 80+ population live in formalized care facilities for older people; in Luxemburg and Switzerland the rate is close to 16%, and in Belgium it is 24%. These countries also report a much higher availability: from 50 beds per 1000 people aged 65+ in Denmark to over 80 beds in Luxembourg. The share of older people living in formalized care facilities is also relatively high in countries such as Slovenia (12.6% for the 80+ population) or Estonia (9.9%).
Figure 3. Long-term care facilities – resources and utilization.
The isolation regime introduced to restrict the frequency of visits, side by side with a system of appropriate checks and controls for the staff, are relatively simple ways to reduce the risk of external coronavirus infection in formalized care facilities. Yet, as we have learnt from numerous examples in Poland and internationally, infection transmission between the residents or between the residents and the staff has been a frequent source of infection clusters and outbreaks. For example, in South Korea, even more than 30% of new coronavirus cases could be the result of transmission between hospital patients or nursing home residents (KCDC 2020a). In connection with a coronavirus outbreak in a formalized care facility in the USA, more than half of the residents had to be hospitalized and, eventually, 33.4% died (McMichael 2020). It seems that keeping the residents of formalized care facilities safe from the infection should be a priority in an epidemic control policy. However, the pace at which social distancing restrictions are lifted so that students can get back to schools and the lockdown in public spaces can be removed, should not have a vital impact on the safety of those living in the facilities, in contrast to the situation of older persons who share a household with younger persons.
Summary
The well-being of the groups with the biggest exposure to the grave outcomes of coronavirus infection deserves special attention when lifting the lockdown introduced in connection with COVID-19 pandemic. In this context, the housing situation of older people and the nature of the underlying social contacts are among important aspects to take into account in developing detailed regulations. As outlined in this Policy Paper, different countries in Europe report different status in that respect. Of all the countries in Europe, Poland has the highest share of the 65+ population co-residing with younger people. On the other hand, less than 1% of the 65+ population live in formalized care facilities. In Europe, the lowest share of co-residence is reported in the Nordic countries, the Netherlands, Germany and Belgium. At the same time, the share of the 65+ population residing in formalized care facilities in those countries fluctuates from 4% to 8%, reaching over 10% in the 80+ population.
In formalized care facilities, lockdown lifting will not have material impact on the safety of the residents or the risk of coronavirus transmission. In contrast, the households where older people live side by side with the younger populace may actually represent a significant risk factor in terms of the spread of the epidemic and infection transmission to those who are most heavily exposed to the grave complications of Covid-19.
In general in Poland, 37.4% of women and 38.6% of men aged 65+ share a household with people under 50 other than their spouse or partner. This is the highest rate of co-residence with younger people for this age cohort in Europe. In Denmark, this percentage is 1.3% for women and 3.3% for men. Even in Spain it is much less common for people aged 65+ to share a household with younger family members (the rates being 28.0% for women and 26.6% for men, respectively). Additionally, in Poland, especially in rural areas, many people aged 65+ live under one roof with school-age children (7-18 years of age: 19.1% of women and 18.9% of men in this age group, respectively); and even more (20.9% of women and 21.5% of men) share a household with adults aged 19-30, which is the age group where coronavirus infection is the most prevalent (KCDC 2020a).
In view of major discrepancies in the demographic structure of households between countries, it seems necessary to differentiate the social distancing rules and the pace with which these rules are to be eased, if one of the objectives is to protect the people exposed to the most serious consequences of coronavirus infection. Especially in such countries as Poland, the policy of gradual opening of schools and other institutions and phased recovery of economic activity should be accompanied by a broad-based communication campaign on how to protect the most vulnerable household members. It seems advisable that the campaign be conducted both in the mass media and in schools, workplaces, and public spaces.
References
- Bi, Q., Y., Wu, S., Mei, Ch,., Ye, X., Zou, Z., Zhang, X., Liu, L.,Wei, S., Truelove, T., Zhang, W., Gao, C., Cheng, X., Tang, X., Wu, Y., Wu, B., Sun, S., Huang, Y., Sun, J., Zhang, T., Ma, J., Lessler, T., Feng (2020). “Epidemiology and Transmission of COVID-19 in Shenzhen China: Analysis of 391 cases and 1,286 of their close contacts.” medRxiv 2020.03.03.20028423
- ECDC – European Centre for Disease Prevention and Control (2020). “Coronavirus disease 2019 (COVID-19) in the EU/EEA and the UK – eighth update.”
- Emami, A., Javanmardi, F., Pirbonyeh, N., Akbari, A. (2020).”Prevalence of Underlying Diseases in Hospitalized Patients with COVID-19: a Systematic Review and Meta-Analysis.” Arch Acad Emerg Med. 8(1): e35.
- KCDC – Korea Centers for Disease Control & Prevention (2020a). “The updates on COVID-19 in Korea.”
- KCDC (2020b). “Coronavirus Disease-19: Summary of 2,370 Contact Investigations of the First 30 Cases in the Republic of Korea.” Osong Public Health Res Perspect. 2020 Apr; 11(2): 81–84.
- McMichael T., Currie D., Clark S., Pogosjans S., Kay M., Schwartz N., Lewis J., Baer A., Kawakami V., Lukoff M., Ferro J., Brostrom-Smith C., Rea T., Sayre M., Riedo F., Russell D., Hiatt B., Montgomery P., Rao A., Chow E., Tobolowsky F., Hughes M., Bardossy A., Oakley L., Jacobs J., Stone N., Reddy S., Jernigan J., Honein M., Clark T., Duchin J. (2020). “Epidemiology of Covid-19 in a Long-Term Care Facility in King County”, Washington. N Engl J Med. 2020 Mar 27.
- Myck, M., Oczkowska, M, Trzciński, K. (2020). “School lockdown: distance learning environment during the COVID-19 outbreak.” CenEA Commentary Paper.
- Oke, J., Heneghan, C. (2020). “Global Covid-19 Case Fatality Rates“.
- Rada Ministrów (2020). “Rozporządzenie Rady Ministrów z dnia 10 kwietnia 2020 r. w sprawie ustanowienia określonych ograniczeń, nakazów i zakazów w związku z wystąpieniem stanu epidemii” [Regulation of the Council of Ministers of 10 April 2020 on establishing certain restrictions, orders and prohibitions in connection with the introduction of the state of the epidemic].
- Roser, M., Ritchie, H., Ortiz-Ospina, E. (2020). “Coronavirus Disease (COVID-19) – Statistics and Research“.
- WHO (2020a). “Coronavirus disease 2019 (COVID-19)“. Situation Report – 46.
- WHO (2020b). “Report of the WHO-China Joint Mission on Coronavirus Disease 2019 (COVID-19)“.
Disclaimer
This Policy Paper was originally published as a CenEA Commentary Paper of 21st April 2020 on www.cenea.org.pl. The analyses outlined in this Policy Paper make part of the microsimulation research program pursued by CenEA. The analyses are based on EU-SILC 2017 data as part of microsimulation research using the EUROMOD model and have been provided by EUROSTAT, and on publicly available OECD data. EUROSTAT, the European Commission, the National Statistical Institutes in each country, or the OECD have no liability for the results presented in the Policy Paper or its conclusions.
This Policy Paper was prepared under the FROGEE project, with financial support from the Swedish International Development Cooperation Agency (Sida). FROGEE papers contribute to the discussion of inequalities in the Central and Eastern Europe. For more information, please visit www.freepolicybriefs.com. The views presented in the Policy Paper reflect the opinions of the Authors and do not necessarily overlap with the position of the FREE Network or Sida.
Covid-19 and Gender Inequality in Russia
Gender inequality is a complex phenomenon characterized by significant and persistent differences in social and economic indicators for women and men. In connection with the Covid-19 pandemic and unprecedented quarantine measures around the world, economists are thinking not only about the obvious global consequences for the global economy but also about the indirect effects, including those through gender-related changes in the labor market. What will the consequences of this crisis on the labor market be in the long run, especially on its gender and family-related components? In this brief, we look at the potential effects of the Covid-19 epidemic and the associated quarantine on gender inequality in Russia.
Introduction
Gender inequality is a complex phenomenon characterized by significant and persistent differences in social and economic indicators for women and men. These may be differences in access to education and medicine, labor market participation, wages, entrepreneurship, participation in politics and public administration, and the distribution of domestic unpaid labor within the family. Reducing gender inequality (like any other form of inequality) correlates with increases in GDP.
The prevalence and scale of gender inequality is, on average, lower in developed countries than in developing countries, and although there is a general tendency for gender gaps to narrow over time, this does not happen simultaneously and equally in all countries. According to the Global Gender Gap Index (2020), which ranks more than 150 countries, the five countries with the best indicators include Iceland, Norway, Finland, Sweden, and Nicaragua, while Congo, Syria, Pakistan, Iraq, and Yemen are in the very bottom. As of 2020, Russia is located approximately in the middle, being the 81st, right between El Salvador and Ethiopia.
In connection with the Covid-19 pandemic and unprecedented quarantine measures around the world, economists are thinking not only about the obvious global consequences for the global economy but also about the indirect effects, including those through gender-related changes in the labor market. A study of World War II, for example, shows that even short-term gender differences in the labor market can have long-term consequences (Goldin and Olivetti, 2013). What will the consequences of this crisis on the labor market be in the long run, especially on its gender and family-related components? In this brief, we look at the potential effects of the Covid-19 epidemic and the associated quarantine on gender inequality in Russia.
Heterogeneous Cross-Sectoral Effects
Economists are now discussing two main channels that can influence gender inequality (Alon et al., 2020). The first one works through differential risk of losing jobs and salaries for women and men due to the disproportionate impact of the epidemic and quarantine on sectors which predominantly employ each gender. The direction of this effect is not easy to predict. On the one hand, the current crisis differs from ordinary recessions in that the service sector, where more women are traditionally employed, is now suffering more than usual. However, it is very important to emphasize what kind of services we are talking about: restaurants and salons are not the whole of the Russian economy. According to the Russian Statistical Agency (Rosstat) 49% of all employed women in 2019 worked in three sectors – trade, healthcare, and education. At the same time, hotels, restaurants, and other services (which include hair and beauty salons) provided less than 8% of women’s employment.
Therefore, from the point of view of assessing the risk of job loss, it makes sense to consider state-financed sectors, where employees are likely to be retained, separately. Among the private businesses, two (non-mutually exclusive) types of sectors are likely to suffer the least. First, the critical ones that do not stop their activity during quarantine (for example, food retail, private medical centers). And second, those that are characterized both by a high ability to work “remotely” and continue to have sufficient demand for their goods and services – either directly or through value chains (see e.g. Volchkova, 2020). For example, agriculture, manufacturing and hotels are worse off in this combination than the financial sector, science, administration, and some types of online education. At the level of the individual characteristics of the employee, even when comparing the same occupations, the possibility of remote work positively correlates with the level of education, wealth, working for a company (rather than self-employment), and being female (according to Saltiel, 2020, for developing countries).
According to the same data from Rosstat, it turns out that about 49% of all women and 40% of all men worked in the “state-financed” and “remote-work” sectors (or 69% against 52%, if we add the trade sector). This is of course an overestimate, since not every job within a sector is characterized by state-financing or remoteness, but it likely represents the relative propensity across genders, which is of our interest. This relative propensity is mostly due to the much higher employment of women compared to men in health and education (approximately 4 to 1 in both sectors). In general, this may mean that the risk of job loss is now higher for men, and not for women as was predicted using US data by Alon et al. (2020), given the gender structure of employment by industry in the US. This rough assessment does not account for different opportunities for women and men to quickly find a new job, especially in the areas of high demand. For example, if the need for delivery workers has increased, and men are more likely to take this job, then it may be easier for them to quickly find a new job. This adaptive effect would unlikely overturn the original difference, because the number of such jobs is also limited.
The Effect of Childcare Facilities Closure
The second channel, likely having a multiplicative effect on the first, operates through the unexpected closure of children’s educational institutions (kindergartens and schools). These effects may be different depending on family composition. While before the pandemic, working parents could send their children to kindergarten and school, this opportunity is now completely unavailable. In the case of online education, not all children are independent enough to learn at home, especially primary school students. At the same time, other childcare support (e.g. from nannies, grandparents and other relatives, etc.) can also be significantly limited due to social distancing and self-isolation, although Russia is in a better position in this regard compared to many developed countries because grandparents traditionally help more in raising children. (It is interesting that in developed countries, the possibility of outsourcing household chores – childcare, cleaning, etc. – is one of the important explanatory factors for higher fertility among more educated women, compared with less educated ones, (see Hazan and Zoabi, 2015)).
Naturally, the situation with closed childcare and educational institutions will not affect the productivity of people without young children. According to the latest census in 2010, about 88 million people, which is as much as 75% of the total adult population of the country, do not live together with children under 18 years old. Also, most likely there will not be a big negative effect on families with children where one of the parents (most often the mother) or another individual in the household (a grandparent) took care of the child at home before the quarantine.
For all other families, the critical problem is juggling childcare with work. The most vulnerable categories of the population here are single mothers and single fathers (and there are about 5 and 0.6 million in Russia, respectively), especially those who do not have any outside help.
Among families with small children where both parents work, several important factors can be identified. On the one hand, according to developed countries, even in families where both parents work, women spend more time on household chores and childcare than men (Doepke and Kindermann, 2019). If one believes that the initial factors that affected this distribution of domestic work (such as traditional norms and role models or the relative income of spouses) have not disappeared, then the sharply increased burden of household chores will disproportionately fall on women. This can lead to a decrease in the relative productivity of women compared to men in the labor market and a greater risk of dismissal. In the long run, this can also negatively affect gender inequality, as even a temporary exit from the labor market may be accompanied by human capital losses and a worse career path in the future.
The Interaction of Both Effects
On the other hand, the opposite situation is also possible. If, due to the disproportionate effect of quarantine on various sectors of the economy, which has been discussed above, women have a lower risk of losing their jobs, then it is possible that at least temporarily, a significant part of the childcare will fall on men. This situation can also happen in families where the woman works in critical sectors of the economy (especially in healthcare) and the man works remotely from home.
Economists have suggested several mechanisms for the effect of short-term additional interaction between fathers and children on long-term participation in their upbringing: there is more information about children’s needs, learning-by-doing, and greater attachment to children. For example, the data from Canada shows that the introduction of 5 weeks of parental leave for fathers led to a more even distribution of domestic labor in households and a greater likelihood of the mother’s participation in the labor market, even 1-3 years after the fact (Patnaik, 2019). Moreover, even if there are not many families like this in the country, the new social norms can gradually spread in society through so-called “peer effects”. Dahl et al. (2014), for example, show using Norwegian data that the brothers and colleagues of men who took parental leave were 11-15% more likely to take it in the future, relative to brothers and colleagues of men who did not take such leave.
Other Hypotheses
Another major consequence of the epidemic and quarantine is the potential upsurge in domestic violence. Several European countries have already noticed an increase in such crimes (European Parliament, 2020), and some crisis centers in Russia have also reported an increase in calls to helplines. Economists identify different triggers for this behavior (Peterman et al., 2020). This may be a direct consequence of quarantine, which increases the time spent by the potential victim and abuser in a closed space, and the inability to seek immediate help, both psychological and medical. Indirect effects can also work through an increased risk of depression and post-traumatic stress syndrome, which were well documented for previous epidemics such as SARS and swine flu. and that may happen due to job loss, reduced income, general economic uncertainty, or a direct fear of getting sick.
These effects disproportionately affect women (and children); therefore, additional resources should be dedicated to identifying such crimes, strengthening support structures for women, and increasing the availability of reporting options without attracting the attention of an abuser (for example, such a warning system may be installed in pharmacies – a place where a woman can go to alone).
Economists have yet to accurately measure and test all these mechanisms, which interact with each other in complex combinations, but it is now clear that very different scenarios are possible, including the positive ones – of a long-run decrease in gender inequality.
References
- Alon T., Doepke M., Olmstead-Rumsey J., and Tertilt M. “The impact of Covid-19 on gender equality”, Covid Economics, Issue 4, 14 April 2020.
- Dahl G.B., Løken K.V., Mogstad M. “Peer Effects in Program Participation”, American Economic Review 104(7): 2049–2074 (2014).
- Doepke M. and Kindermann F. “Bargaining over Babies: Theory, Evidence, and Policy Implications”, American Economic Review, 109(9): 3264–3306 (2019).
- Goldin C. and Olivetti C. “Shocking Labor Supply: A Reassessment of the Role of World War II on Women’s Labor Supply”, American Economic Review, 103(3): 257-262 (2013).
- Hazan M. and Zoabi H. “Do highly educated women choose smaller families?” Economic Journal, 125(587): 1191-1226 (2015).
- Patnaik A. “Reserving Time for Daddy: The Consequences of Fathers’ Quotas”, Journal of Labor Economics, 37(4): 1009-1059 (2019).
- Peterman A., Potts A., O’Donnell M., Thompson K., Shah N., Oertelt-Prigione S., and van Gelder N. “Pandemics and Violence Against Women and Children”, Center for Global Development working paper, 1 April 2020.
- Saltiel F. “Who can work from home in developing countries?” Covid Economics, Issue 6, 17 April 2020.
- Volchkova N. “Who should receive government support during Covid-19 crisis”, in “Economic Policy during Covid-19”, April 2020.
- European Parliament. “COVID-19: Stopping the rise in domestic violence during lockdown”, Press Release 7 April 2020.
- Rosstat, “Russian census 2010”.
- Rosstat, “Russian labor force survey 2019”.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Covid-19 in LDCs: Assessing Resilience and Understanding How to Help
Poor and developing countries are now starting to be affected by the Covid-19 pandemic. Important differences in the setting need to be considered when thinking about their prospects, and the role richer countries may play in helping them face the challenge.
Introduction
Most of the focus in current analyses of the policy response to the Covid-19 crisis center on Western and East Asian countries that were hit first and hardest. Some initiatives are tracking the situation in transition countries of Eastern Europe (e.g., the FREE Network initiative and the Vienna Institute for International Economic Studies tracker).
However, poor and developing countries start also being affected by the pandemic, and richer countries have an important role in helping them face the challenge. Besides the moral obligation, in the presence of a global externality it would be extremely myopic not to do so. When thinking about this, it is important to reflect on the differences that will be relevant in these settings.
What is Happening? The Spread of the Virus
Currently, the spread of the contagion is still at substantially lower levels in low income countries (LIC) as compared to high income countries (HIC). There is not enough evidence yet to either support or reject the hypothesis that a lower spread could be due to differences in climatic zones (warmer temperatures and humidity). Younger populations might account for both a lower (observed) spread and lower mortality, but on the other hand the denser and multigenerational living arrangements with poorer hygienic conditions should be pushing in the opposite direction. Observing lower spread and lower mortality could also be put down to lower testing (and more generally, data availability and quality of information systems). Finally, we can’t exclude that this is simply a matter of timing. Many LIC are relatively less connected to global routes, and moreover were fast to close their borders: many opted for early lockdown. If this is the case, they are merely postponing the sharp increases in infections and fatalities observed in other countries. (At the time of writing, worrisome reports of a severe outbreak in Somalia are emerging.)
Figure 1: Total confirmed Covid-19 deaths.
Figure 2: Total Covid-19 tests per 1,000 vs. GDP per capita.
A number of factors related to the demographic structure as well as the public health systems are relevant as a base for our expectations on how the situation is going to evolve in these countries. Since age plays an important role on how severely Covid-19 patients are affected by symptoms, the demographic structure of the population has consequences for the demands that will be placed on the health care system by an outbreak. This plays in favor of LICs, where only 3% of the population is above 65 years of age on average. The corresponding share is 18% in OECD countries. The state of the health care system is intuitively crucial once there is an outbreak. In Table 1, the Global Health Security Index (GHS) “Health Security Score” paints a dismal picture in terms of overall capacity “to treat the sick and protect health”, where the group of LICs (as defined by the World Bank) scores an average of 14,5 out of 100 (HIC average is 51,9).
Table 1: Public health.
This is clearly related to how wealthy a country is. The wealthier countries have better health care systems in general, and will do better if they experience an outbreak, while the poorer countries will do worse. Even if the average 6% of GDP devoted to health care spending in LICs looks comparable to the HIC average share (8,8%), these translate into very different figures in terms of per capita dollar spending: 40 USD per capita in the first group, to be compared to over 4,000 USD in the second. Even if costs do differ as well, a ventilator is unlikely to be two orders of magnitudes cheaper in Liberia than in Italy. Nevertheless, the “Health security – response capability” index, which includes things as emergency response plans and existing links between health and security authorities, averages 30,9 in LICs against 45,8 for HICs. The difference across income levels is much smaller in this case, reflecting both the more general lack of preparedness in this particular domain, but also the familiarity and experience of poorer countries with infectious diseases outbreaks, which might give an edge in an emergency. The World Health Organization reports over one hundred “public health events of varying magnitude and socio-economic effects” annually in Africa, for example. After the 2014-15 Ebola outbreak, an Africa Centre for Disease Control and Prevention was set up in 2017, which might have contributed to an upgrade in the index. The Centre has been quick to react in the present case, as discussed later in the policy response section.
What is Happening? Economic Impacts
It is hard for HIC to put numbers on forecasts of economic activity. For LIC, the challenge of forecasting is further compounded by the normally poor array of statistical systems and the larger informal sectors. Better indicators of economic activity and income distribution normally rely on surveys, and while surveys are still being conducted these days (see for example the relentless work of IPA affiliates the focus at the moment is naturally on the health emergency and related behavior, rather than incomes and investments.
Even without exact numbers, we can nevertheless expect that LICs’ economies are going to be hit harder, for two main reasons:
- They are more sensitive to the global shock(s), through commodity prices and exports, and also because of the limited access to international financial markets
- They start from worse structural conditions, in terms of fiscal capacity and governance capacity, which makes them less resilient.
Again, a number of fiscal and macro factors are relevant for our expectations on how the situation is going to evolve, such as the trade and fiscal balance, and the composition of exports. Besides concerns for long-term growth prospects, the most immediate threat is that to people’s livelihoods, in particular poor people’s, due to the slowdown of economic activity. While this can’t be fully avoided due to the dependence on international linkages, it is made radically worse in case of domestic lockdown. The combination of large populations living below or at the margin of the poverty threshold and the slim fiscal capacity for compensation and redistribution results in much sharper trade-offs associated to different policy measures.
Some of these countries, heavily dependent on external trade and in particular on commodity exports, are at the moment facing a double shock, due to the collapse of commodity prices and the disruptions to global value chains, on top of the epidemic itself. This is dramatically reducing the fiscal space for response, which was already limited to start with. Therefore, even though a number of LICs have formulated response plans, as will be discussed in the next section, the question remains how to finance them.
Table 2: Macro factors.
What is Happening? Policy Response
With few exceptions, most countries in this group were quick to react in at least two dimensions: closing borders and closing schools. While the first was probably a very wise choice and might have delayed significantly the entry of the virus in the countries, not enough thought has been given to the consequences of school closures. Less than one in four countries is providing some form of distance learning; and even where this is available, access will be very unequal, for a number of reasons: access to internet and suitable devices, need to compensate for parent’s lost income, responsibility for younger siblings are just some of the factors, in addition to the inequality in parental socioeconomic and educational background which is common also to HICs. Based on experiences from the Ebola epidemic in 2014-15 in West Africa, the protracted lack of schooling is liable to leave deep long-lasting consequences.
A quarter of the countries (8 out of 31) entered lockdown or very strict social distancing. Few of them, with help from the international community, support the enforcement of a lockdown with food distribution (for example Liberia and Uganda). This is not possible everywhere, due to financing and logistic issues, and in its absence, livelihoods are put at risk. Because of this, in many areas people defy the rules, in some cases notwithstanding enforcement by the military. Another quarter of countries opted for curfews rather than lockdown, to limit the frequency of interactions without halting completely economic activity. Very few countries explicitly chose much more limited interventions in terms of social distancing (Burundi, Mozambique, Tanzania), while most of the rest do not have the governance capacity for intervention, in some cases due to other preexisting crises (Yemen, Mali, Guinea-Bissau).
The quality of the country’s health care system and the resources that can be invested in testing will determine for how long containment measures will be needed. Two thirds of the countries have already enacted emergency interventions in the health sector, meant to strengthen the general capacity for care and in particular the infrastructure for testing. All in all, though, half of the countries have opted for either strict public order measures or fiscal interventions. Most of the remaining half have neither, while very few have both. In most cases, the health-related emergency measures are financed by small reallocations of current spending that amount to few per-mille points of GDP. With fewer resources to cure and test, countries will need to maintain longer containment measures to avoid the spread, once the contagion reaches them. However, as mentioned above, the cost of lockdown is very different in these countries, where almost half of the population (48% on average) lives below the international poverty line. Stricter and longer lockdowns will call for broader fiscal interventions in support of households’ (food) consumption and SMEs. The few countries that planned such interventions, and/or to increase health sector spending by more than 1% of GDP, are counting on donor financing. At the same time, all are suffering contractions in their fiscal space, as noticed above, and the same can be said of most donor countries too. The question of how to finance this gap looms therefore large.
A Role for Rich Countries
In normal times, the relative importance of different financial flows entering developing countries could be phrased as follows: foreign aid is small, remittances bigger, trade and investments biggest. ODA receipt accounts for 12% of GDP in the average LIC. While almost all donor countries fall short of the pledge to give 0,7% of their annual GDP, even if they did, thus trebling the current aid bill (152,8 billion USD in 2019), this would still not reach the level of remittances flows, estimated at 551 billion USD in 2019. The FDI flows, estimated at 671 billion USD (in 2018) are more important in the aggregate, although their distributional implications are very different. The importance of trade is also substantial, as shown in Table 2.
Given the situation, though, with a global recession looming, we can expect substantial contractions in trade and FDIs at least in the short run, but more likely for a protracted period. The limitations to international mobility will also imply severe reductions in remittances flows, as migrant workers have either returned to their countries, or are more likely to lose employment in the host countries even if they stay. Clearly this implies a continued role for international support.
Without going in the merit of an optimal policy mix recommendation to developing country governments, which others have done (for example, the International Growth Centre COVID-19 guidance note), rich countries that want to play a role in this should keep in mind a few points. Aid budgets should at the very minimum not be reduced, notwithstanding the domestic fiscal squeezes. More than ever, the same amount of money has a much larger life-saving potential in a poor country than domestically. Besides quantity, the type of support will be important. During the health crisis, the priority needs to be to finance emergency expansion of health care spending, but for this to be sustainable it needs to be paired with a strong effort to limit the spread. This includes two elements: i) testing and tracing, or in absence of tests at least keeping track of the geographic spread of symptomatic outbreaks; and ii) supporting livelihoods to enable social distance or lockdown. The first includes, besides the medical material and infrastructure for the testing itself, which might not be the most cost-effective way of using resources, enabling safe and reliable public communication, which needs to go two-ways: from authorities to citizens, avoiding fake news and potential stigma attached to the contagion, and from citizens to the authorities to collect policy relevant data. Since internet is not widespread enough, and the radio only allows for one-way communication, the best shot at this is leveraging mobile telephone networks. Technical assistance in this could be valuable, as well as analytical capacity for the processing of the data.
It goes without saying that all the progress happening in rich countries, in terms of understanding of the virus spread, efficacy of different policies and behaviors, development of treatments and in due time vaccine should be promptly shared.
When it comes to consumption support, it is debatable whether cash transfers or in-kind distributions should be the preferred option. This will of course vary depending on the situation: cash is logistically easier and more flexible – but it will not help if and where the markets shut down.
In the aftermath, it is important to keep in mind that poor countries will not be able to borrow (in particular, issue domestic public debt) to finance fiscal stimuli and other recovery measures. There will be again an important role for international lenders. At the same time, a swift recovery of global economic activity must be considered as the all-over superior solution.
References
- GHS Index, 2020. “Global Health Security Index, 2019”.
- Our World in Data, 2020. “Total confirmed Covid-19 cases by country”.
- The World Bank, 2020. “World Bank Open Data”.
- UNCTAD, 2020. “Commodity exports (as a share of total merchandise exports) in 2017”.
- WHO, 2017. “Acute Public Health Events Assessed by WHO Regional Offices for Africa, the Americas, and Europe under the International Health Regulations (2005) – 2017 Report”.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Covid-19: News for Europe’s Energy Security
While there has been a lot of attention on the effect of Covid-19-related developments in the oil market, the effect on the natural gas market has almost evaded media attention. For the EU, however, the gas market and especially the impact of the pandemic on the gas relationship with its largest gas supplier, Russia, is of high relevance. This brief discusses the potential implications of Covid-19 on this relationship both under the pandemic and during the expected slow economic recovery. We argue that, while in the short run the security of Russian gas supply is likely to improve, this is unlikely to be the case in the aftermath of the pandemic. To ensure gas supply security in post-pandemic markets, the EU may need to finally implement the long-awaited “speaking with one-voice” energy policy.
Introduction
The ongoing coronavirus pandemic will not only affect human lives, but also bring new economic and political challenges. The energy sector, and in particular the dramatic decrease of oil prices, has been in the news since the beginning of the Covid-19 crisis. But discussions have so far rarely touched the natural gas market, despite the pandemic taking its toll also on this market. As for oil, the demand and price have been negatively affected by the economic slowdown. While not as drastic as for oil, the price of natural gas in the EU has declined by approximately 40% since the beginning of 2020 (World Bank, 2020). However, the impact of the pandemic is likely to be quite different in oil and gas markets. There are multiple reasons for that; for example, oil and oil products are predominantly consumed by the transport sector while natural gas is mostly used in the power sector, the industry and households, and these sectors were differently affected by the Covid-19 pandemic.
Understanding the impact of the pandemic on the gas market is especially interesting from the European point of view, given that natural gas accounts for 25% of total energy consumption and two thirds of this gas is imported. The imports are also very concentrated, with the main supplier Russia providing around 40% of the gas, compared to 25% of the crude oil. This dependency, as well as a long history of tensions with third parties (Ukraine and Belarus) on the Russian gas transit routes, has made the EU’s concerns about the security of Russian gas supply much more pronounced than for oil (see Le Coq and Paltseva, 2012). The combination of these factors – i.e. the importance of natural gas for the EU and the long-standing concern about gas supply security warrant an analysis of the short and mid-term effect of the Covid-19 pandemic on the gas market, and, specifically, on the EU-Russia gas relationship. This brief discusses how the pandemic-driven decline in gas demand, and the potential shift in the balance of power between the parties may affect both the dependency on, and the transit of, Russian gas.
EU Dependency on Russian Gas Under the Covid-19 Pandemic
As is well known, Covid-19 and the associated lockdowns imposed by many EU Member States, have caused a slowdown in most economies and a decline in energy demand. However, for natural gas, the effect is likely to be significantly smaller than for oil. While we do not yet have statistics for the EU’s gas demand in recent months, the Norwegian energy consultancy Rystad Energy has predicted the decline of gas demand to be around 4% for March and April 2020. This forecast was given quite early in the course of the pandemic, and is very likely an underestimation; still, it is very different from the one for oil, with the demand drop estimated to be a whopping 34% in April.
One reason why we do not observe a sizable decrease in gas demand is that the natural gas is used in electricity generation, especially as a base-load fuel to compensate for the intermittency of green energy sources, such as sun and wind. With the reduced electricity demand, renewable power generation has become relatively more important in the electricity supply in many countries. Since mid-March 2020, the share of renewable power generation across the EU is 46%, nine percent higher than during the same period last year (Energy Transition Lab, 2020). Interestingly, in France, Germany, Belgium, the Netherlands, the Czech Republic, Poland and Hungary, the absolute volume of electricity generation by renewable sources even increased relative to the same period in 2019, despite declining energy demand. One potential channel, anecdotally recorded for Germany could be higher solar generation due to cleaner skies resulting from the decline in emissions because of lower fossil energy consumption. A higher volume of a renewable generation often requires more back-up power to maintain grid stability. While natural gas is not the only back-up source, this need might still limit the decline in gas demand (or even increase it like e.g. in the Czech Republic). Of course, cheaper gas prices may also play a role: for example, Slovakia and Romania experienced an increase in gas-based generation, but a drop in the renewable generation since mid-March 2020 relative to the same period in 2019. Finally, another reason for the moderate gas demand decline is its residential use – which is likely to be sustained due to the lockdown regime introduced by many countries.
When it comes to Russian gas imports, the official statistics since mid-March – roughly the beginning of lockdown policies across the EU – are not available yet. However, we can with some reservation look at the evolution of the volume of gas sales to the EU disclosed by Gazprom (2020). There was a very sizable decrease in Russian gas imports by the EU – of more than 21% – as compared to the same period last year but it started before the lockdown: January 2020 recorded a drop of 34% and February of 20%). This suggests that the current decrease in Russian gas imports is only marginally related to the pandemic, and more related to the overall gas market situation (such as relatively full gas storage in the EU in 2020, a warm winter, an increase in LNG imports, etc.).
It is, however, likely that the negative effect of the pandemic on Russian gas imports by the EU will be noticeably higher than it currently appears in the Gazprom data, thereby further decreasing the EU’s dependency on Russian gas. Moreover, since demand and prices decrease, substituting for Russian gas, were there a supply interruption, should be relatively easy and cheap with the current excess capacity of the natural gas market and the substantial storage in the EU.
Another reason for the improvement in the security of Russian gas supply to the EU is the observation that Russia’s dependency on oil and gas exports in combination with pandemic-associated factors may lead to a substantial economic downturn in Russia (Becker, 2020). In these dire circumstances, Russia is unlikely to further risk its gas export revenues by pursuing geopolitical goals through the means of gas supply and gas transit. For all these reasons, one may expect the security of Russian gas supply to the EU to improve during the pandemic.
However, the EU dependency on Russian gas may still be a concern due to medium-run effects of Covid-19. First of all, while the gas prices have been in decline for roughly a year now, the recent decrease in natural gas prices has accelerated the negative impact on the unconventional natural gas industry. For example, the US natural gas rig count has declined by 20% since mid-March 2020, which accounts for more than a third of the 54% year-to-year decline (Ycharts.com, 2020). Similarly, nearly 42% of Australian gas resources could be uneconomic under the current gas prices, according to Rystad Energy. While gas prices are unlikely to stay low forever, the industry will need time to recover even if/when the natural gas demand rises again. Moreover, the East-Asian markets are likely to be served first, as they are expected to recover from the pandemic shock before Europe. This dynamic, coupled with historically higher LNG prices in Asia may delay the LNG flows to Europe. A shortage of LNG in Europe, in turn, is likely to hinder any diversification strategy from Russian gas, weakening the EU’s bargaining power. The new Russia-China gas pipeline, “Power of Siberia”, operational since the end of 2019, will also be used to satisfy the post-Covid-19 Chinese gas demand which is likely to recover before demand picks up in the EU. Its use will then allow Russia to be less reliant on exporting gas to the EU, further contributing to the EU’s gas security concerns.
Transit of Russian Gas to the EU: Covid-19 Effect
The EU’s energy security also depends on the reliability of Russian gas transit to the EU. There are currently 5 transit routes connecting Russia to the EU (plus the routes that are serving the Baltic states and Finland without further transit), see Figure 1. Three onshore routes connect Russia to the EU via Ukraine and Belarus. There has been a history of gas transit disputes associated with these routes, at times threatening the Russian gas supply to the EU. Two newer offshore pipelines, Nord Stream 1 (in operation since 2011) and TurkStream (in operation since 2020) connect Russia directly to Germany, and to the South-East of Europe via Turkey. Further, one more offshore route to Germany, Nord Stream 2, is currently underway, with the operations announced to start in the first quarter of 2021. All three offshore projects are expected to not suffer from geopolitical transit issues.
In relation to the Covid-19 pandemic, there are likely to be two major effects on Russian gas transit. First, the inauguration of Nord Stream 2 is likely to be further delayed. Nord Stream 2 is 50% financed by Gazprom, and this financing scheme may be difficult to sustain after the fall in oil and gas prices and a significant decrease of Gazprom’s export revenues. Indeed, while the statistics for March and April 2020 are not yet available, the Russian customs statistics suggests that the USD value of gas exports from Russia in January-February 2020 has decreased by 45% relative to the same period last year. Because Nord Stream 2 could facilitate gas delivery to the EU in case of a transit conflicts, its expected delay may negatively impact the EU’s gas security.
Additionally, the Covid-19 related demand drop may impact the utilization of Russia-EU gas routes, driven by the current agreements between Russia and the transit countries. Russia and Ukraine have just signed a transit agreement for the next 5 years. This agreement was widely perceived as a diplomatic success of the EU (that facilitated the deal), given the historically difficult geopolitical relation between Ukraine and Russia. One of the new features of this agreement is of particular interest within the Covid-19 context. Unlike for previous deals, Russia agreed to prepay a fixed volume of gas transit, 178.1 mcm/day for 2020, and 110 mcm/day units for 2021-24 (Pirani et al., 2020). So, underutilization of this route is costly for Russia.
Figure 1. Gas supply Routes to the EU.
With decreased demand due to Covid-19, warmer weather in the coming months and almost full gas storages in the EU, this contractual feature may affect how Russia allocates its gas exports across the routes. At least, in the short term, it may undermine Russian gas transit via the Belarus-Poland route. The concern about the utilization of this route in relation to the new Russia-Ukraine transit agreement has already been raised by Pirani et al. (2020). The Covid-19-associated decrease in gas demand is likely to make this concern much more real. Russia may use the Belarus-Poland pipeline sporadically, e.g. to adjust for the seasonal spikes in demand, without long-term capacity booking. Recent gas tensions between Russia and Poland (e.g. Poland winning in the arbitration court against Gazprom (RFE/RL, 2020), and Poland repeatedly expressing opinions and exercising legislative effort restricting the usage of Nord Stream 1 and construction of Nord Stream 2) may further exacerbate the issue.
In the medium term, however, when the EU gas demand has recovered but Nord Stream 2 is not yet in place, the Belarus-Poland route is likely to prove useful for Russia, at least starting from 2021 (when prepaid volumes of Russian gas transit via Ukraine will decline according to their agreement).
The transit contract between Russia and Poland is to be renewed in mid-May 2020, and as of now, it is unclear if, and how it will be written and whether the Belarus-Poland transit route will be used to a substantial degree or only marginally. If transit through the Belarus-Poland route is limited, it will imply poorer route diversification for a major part of European consumers of Russian gas, thereby lowering their security of Russian gas supply. This may also put another strain on the bargaining power allocation within the EU and the EU’s intended common energy policy of “speaking with one voice” with external energy suppliers like Russia.
Conclusion
Summing up, the decrease in demand of natural gas, as well as other factors associated with the ongoing Covid-19 pandemic, such as economic recession and turbulence in stock markets, are likely to have noticeable implications for the security of Russian gas supplies to the EU in the short term. On the one hand, even if the current pandemic-associated decrease in demand of gas from Russia seems rather moderate, the ultimate negative effect on Russian gas imports by the EU is likely to be larger. Lower imports from Russia are likely to improve the security of supply, both through lower import dependency of the EU, and through improved market opportunities due to the current market’s overcapacity. On the other hand, in the medium run, lower demand also negatively affects the non-conventional gas industry, undermining the diversification opportunities to LNG, and, consequently, natural gas energy security. Further, a fall in the gas demand by the EU coupled with the newly signed transit agreement between Russia and Ukraine may potentially cause underusage of the Belarus-Poland transit route, thereby putting a strain on the diversification of Russian gas import routes to the EU and on the power balance within the EU.
Energy security might be even more of a concern in the post coronavirus period when the economy is slowly recovering, and cheap and guaranteed energy supply is crucial. To ensure this supply, national efforts combined with an EU-wide policy coordination would be required. The long-discussed “speaking with one voice” common energy policy may finally need to materialize in order to facilitate reliable access to natural gas.
References
- Becker, Torbjörn, 2020. “Russia Economic Update — Brace for the Covid-19 Impact!”, FREE Policy Brief.
- Energy Transition Lab, Wärtsilä, 2020, retrieved April 27, 2020
- Gazprom, 2020. REMIT RSS, retrieved April 26, 2020.
- Le Coq, Chloé and Elena Paltseva, 2012. “Buyer Power as a Tool for EU Energy Security”, FREE Policy Brief.
- Pirani, Simon; Jack Sharples, Katja Yafimava, Vitaly Yermakov, 2020. “Implications of the Russia-Ukraine gas transit deal for alternative pipeline routes and the Ukrainian and European markets”, Oxford Institute for Energy Studies.
- World Bank, 2020. “Commodity Price Data (The Pink Sheet)”, retrieved April 26, 2020.
- Ycharts.com, 2020. “US Natural Gas Rig Count: 85.00 for Wk of Apr 24 2020”, retrieved April 27, 2020.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Quota or not Quota? On Increasing Women’s Representation in Politics
All over the world, politics remains one of the most male-dominated spheres in society, in spite of the substantial progress made in achieving more gender balance in the last decades. A large number of countries worldwide have adopted some form of electoral gender quotas to accelerate this progress, but the empirical evidence on the effectiveness of such policy tools is mixed.
In this policy brief, we first discuss the potential impacts of gender quotas. Quotas may (a) increase women’s representation in political positions, or decrease it, if there are backlash effects; (b) improve or worsen the quality of selected politicians; and (c) bring about important policy changes, given the wealth of empirical evidence of gender differences in policy preferences, with, for instance, women appearing more concerned about health and the health system than men. We then provide an overview of the empirical evidence on quota impacts in the economics literature, and contextualize these findings with a special focus on the countries of the FREE (Forum for Eastern Europe and Emerging Economies) network. We end with policy advice on the design of gender quotas in the domain of politics.
Quotas in the World and in the FREE Network Region
According to the International Institute for Democracy and Electoral Assistance (IDEA), 127 countries worldwide currently use quotas with the goal of increasing the presence of women in governmental institutions. Broadly speaking electoral gender quotas can be classified into seat reservation and candidate lists quotas. The former limit the competition for a governmental seat to women, whereas the latter prescribe a minimum representation of women in electoral lists. Candidate quotas can be legislated, i.e. they constitute a legal requirement, or voluntary, whereby parties adopt quotas in their internal statute.
Table 1: Share of women in national parliaments (in %) FREE Network countries
The popularity of gender quotas is, however, not uniformly distributed across the globe. For example, while political gender representation is far from equal in most countries of FREE network region (see e.g. table 1), out of these countries only Armenia, Poland and Sweden dispose of electoral gender quotas (see figure 1).
Figure 1: Gender quotas in the FREE Network region
Since 2011, Armenia has had a legislated candidate quota of 40% for its National Assembly. This quota replaced a previous quota of 15%, passed in 2005 – one of the requirements to enter the Council of Europe (Itano 2007). Poland has also had a legislated candidate quota of 35% for the Lower House (the Sejm) as well as for subnational elections since 2011 (IDEA 2020; World Bank 2019). Sweden, the fourth most gender equal country worldwide according to the 2020 ranking of the World Economic Forum, and ninth in the women’s political empowerment sub-index, does not have legislated quotas. However, political parties themselves have decided to adopt voluntary quotas: the ruling Social Democrats use a zipper system in which the two sexes alternate on party lists; the Left Party has a minimum 50% quota for women, while the Green Party has a 50% gender quota (IDEA 2020). The Swedish Moderates, Liberals, Center parties and the extreme-right Swedish Democrats currently do not have gender quotas. The Swedish Democrats entered the parliamentary elections in 2018 with the highest share of male candidates observed among the Swedish parties – 70% (SVT 2020; SVT 2018).
In spite of their popularity among policy-makers worldwide, the merits of quotas are still largely debated. Opponents of gender quotas are often concerned about their effects on the meritocratic selection of politicians. Another common criticism is that nominating more female candidates may not automatically translate into more women in powerful positions. For instance, the shares of women in the Armenian and the Polish Parliament are 24 and 29% respectively (World Bank 2019), well below the national legislated candidate quota (it bears noting, however, that these shares have been growing over the last ten years, as shown in Figure 3). The respective shares of female ministers are 7% and 23% (Government of the Republic of Armenia 2020; OECD 2020,).
Figure 2: Share of women in national parliaments (in %)
Why is increasing women’s political participation considered a policy objective of utmost importance in many countries worldwide, and how can gender quotas help achieving it? In this brief we contribute to the ongoing debate on the merits of gender quotas, by offering an overview of their potential effects and by critically reviewing the empirical evidence from the most recent academic literature.
Which Effects Can We Expect From Quotas?
The primary objective of electoral quotas is to reduce gender gaps in representation in electoral lists and in the targeted representative institutions. Quotas can also activate trickle-up mechanisms, whereby gender gaps decrease in positions that are not directly targeted by the quota. The trickle up effect occurs, for instance, if women’s networks within parties or in governmental organizations help the promotion of female leaders. Furthermore, gender quotas may help to improve the quality of politicians. As noted by, among others, Bertrand (2018), a society likely improves the quality of its leaders when it enlarges the pool where those leaders are chosen from. A critical underlying assumption in this line of argument is that there are no major differences in the distribution of “political talent” between women and men. However, even with equal distribution of political talent, if the supply of women willing to enter politics is very limited and there are not enough qualified women to fill the quota positions, the average quality of a “quota” politician may end up being lower than that of her colleagues – and quotas may have the unintended consequence of reinforcing stereotypes against female politicians. This, in turn, may ultimately imply lower promotion rates of women to key positions and/or worse electoral support of female politicians, thereby undermining women’s political empowerment at various levels.
One of the most popular arguments in favor of the adoption of gender quotas is that women’s political preferences may not be adequately represented by male-dominated political bodies. Gender quotas, by increasing female representation among politicians (and possibly among voters), can thus help closing a potential gap in substantial representation. A large body of literature has documented gender differences in policy preferences, by considering, e.g. the size and composition of government spending after the expansion of suffrage to women (Kenny and Lott 1999), voting records in referenda (Funk and Gathmann 2015), survey data (see, e.g. Bagues and Campa 2020), or women’s contributions to legislative amendments (Lippmann 2020). In this historical moment when the world is plagued by a pandemic, the most important gender difference to emphasize seems to be in the area of health. Exploiting the federal referenda held between 1981 and 2001 in Switzerland, Funk and Gathmann (2015) show that Swiss women are more likely to be in favor of health, unemployment and social security spending than men, and less likely to be in favor of military spending. Similarly, based on survey data from a sample of nearly 60,000 Spanish residents, Bagues and Campa (2020) find that women are significantly more likely than men to report that the health system is one of the problems that affects them the most. Likewise, Lippmann (2020) analyzes the contribution of French legislators to amendments and finds that women are 25% more likely than men to initiate at least one amendment related to health issues. This gender difference regarding health policy is also visible in the European Social Survey (ESS), which covers a representative sample of the population of 19 European countries. When asked to give a general opinion on the current state of health services in their country, female respondents turn out to be significantly less satisfied than male respondents on average. The difference is statistically significant, albeit not particularly large (12% of a standard deviation) and holds in most of the countries included in the ESS. One potential reason behind this noticeable difference in satisfaction with health services is that women also report lower health status than men (10% of a standard deviation and statistically significant).
Figure 3: Self-reported satisfaction with the current state of national health services
A natural question to ask in spring 2020 is whether a world with more women among political leaders would have had health systems better equipped to face a pandemic. While we will never have a definite answer to this question, studies of the impacts of gender quotas can help assessing whether the gender of political leaders matters for policy decisions.
What is the Empirical Evidence on the Effects of Quotas?
Quotas increase women’s representation in electoral lists, but only when they are binding and appropriately enforced (i.e. the cost for parties of not complying with the quota must be high enough). Yet, when quotas are limited to the composition of electoral lists, the strategic positioning of female candidates in “not-winning” positions tends to undermine the quota effect on the election of women (see Esteve-Volart and Bagues, 2012, and Bagues and Campa, 2020). This seems to be the case of Poland: According to Gwiazda (2017), the lack of a placement mandate obliging parties to put women in the top positions of a party list, is indeed one reason why the Polish quota has not translated into a higher share of female representatives.
The evidence on the spill-over of quotas to higher positions is mixed. Two studies find that candidate quotas in Italy and Sweden increased the probability that women reach leadership positions, above and beyond the quota mandate (De Paola et al. 2010, O’Brien and Rickne, 2016). Bagues and Campa (2020), however, fail to establish similar evidence in Spain.
In studies of developing countries, Beaman et al. (2009) find that seat reservation in India improved male voters’ perception of female leaders, as well as women’s probability of being elected once the reservation was removed. Conversely, experimental evidence from Lesotho suggests that, if anything, a quota-mandated female representative reduces women’s self-reported engagement with local politics (see Clayton, 2015).
An increasing number of studies also examine the quota impact on the quality of the elected politicians, proxied by different measures. Baltrunaite et al. (2014) find that a gender quota improved the average education of elected politicians in Italy, and Besley et al. (2017) provide similar evidence looking at a measure of labor market performance in Sweden. Bagues and Campa (2020), studying candidate quotas in Spain, fail to find an improvement in the quality of politicians, measured by their education and electoral performance; however, their assessment is that the quota did not decrease quality either, contrary to the expectation of many quota opponents. However, Chattopadhyay and Duflo (2004) find that, in the context of seat reservations in rural India, quota candidates are less educated.
Finally, the evidence on whether gender quotas bring about policy change is scarce. Chattopadhyay and Duflo (2004) show that the reservation of the most important seat in Indian villages brought policy choices closer to women’s preferences. In Spanish municipalities, Bagues and Campa (2020) fail to find significant increases in the share of “female expenditures” (issues women have been found to care more about than men, based on surveys) over two legislatures when candidate quotas were used.
Conclusion
Gender quotas are a popular policy tool used to close existing gender gaps in political empowerment, which are large in many countries in the FREE Network. A growing economics literature on the impacts of gender quotas helps assessing what objectives policy-makers may be pursuing when they adopt them, and under which conditions these objectives can be achieved. There is a number of lessons to be learned from this literature.
First, the design of the quota is crucial for it to achieve its primary objective, which is to increase women’s presence in the targeted political positions. Placement mandates, for instance, are particularly important in the design of candidate quotas to avoid that women are strategically placed at the end of the ballot. Second, policy-makers need to take the local context into account. Whether a candidate quota can generate spill-overs to higher-level positions likely depends on the degree of centralization of political parties for instance; where party leaders are very powerful, we may be less likely to see an increase in the share of female leaders following the adoption of a candidate quota. Third, the question when gender quotas successfully bring about policy change needs additional investigation. Different factors likely play a role, such as: the type of position targeted by the quota (legislative or executive, local or national, etc.); the extent of the increase in representation achieved; the magnitude of the gender difference in preferences; the type of decision-making process prevailing (majority voting or unanimity); how the selection of politicians is affected by the quota; and how women’s influence on policy is measured. Studies that systematically vary some of these factors will improve our understanding of this area of research. Fourth, there is no overwhelming evidence of negative effects of gender quotas in a number of dimensions, at least over a medium-term horizon.
The case for adopting and testing different forms of gender quotas, perhaps in combination with additional measures, is therefore relatively strong. Overall, our assessment is that quotas will have to remain in policy-makers’ toolbox for some time if the worldwide effort to close the persisting gender gaps in political empowerment is to continue.
References
- Bagues, Manuel; and Pamela Campa, 2020. “Can Gender Quotas in Candidate Lists Empower Women? Evidence from a Regression Discontinuity Design.” CEPR Discussion Paper No. 12149.
- Bagues, Manuel; Mauro Sylos-Labini; and Natalia Zinovyeva, 2017. “Does the Gender Composition of Scientific Committees Matter?”. American Economic Review, 107(4), pp. 1207–1238.
- Baltrunaite, Audinga; Piera Bello, Alessandra Casarico; and Paola Profeta, 2014. “Gender Quotas and the Quality of Politicians”, Journal of Public Economics, 118, pp. 62-74.
- Beaman, Lori; Raghabendra Chattopadhyay; Esther Duflo; Rohini Pande; and Petia Topalova, 2009. “Powerful Women: Does Exposure Reduce Bias?”. Quarterly Journal of Economics, 124(4), pp. 1497–1540.
- Besley, Timothy; Olle Folke; Torsten Persson; and Johanna Rickne, 2017. “Gender Quotas and the Crisis of the Mediocre Man: Theory and Evidence from Sweden”, American Economic Association, 107(8), pp. 2204-2242.
- Bertrand, Marianne, 2018. “Coase Lecture – The Glass Ceiling”. Econometrica 85, pp. 205-231.
- Chattopadhyay, Raghabendra and Esther Duflo, 2004. “Women as Policy Makers: Evidence from a Randomized Experiment in India”. Econometrica, 72, pp. 1409-1443.
- Clayton, Amanda, 2015. “Women’s Political Engagement Under Quota-Mandated Female Representation: Evidence From a Randomized Policy Experiment“. Comparative Political Studies, 48(3), pp.333 –369.
- Dahlerup, Drude (Ed.), 2006. “Women, Quotas and Politics”. Routledge, Taylor & Francis Group.
- De Paola, Maria; Vincenzo Scoppa; and Rosetta Lombardo, 2010. “Can gender quotas break down negative stereotypes? Evidence from changes in electoral rules”. Journal of Public Economics 94 (5), pp.344-353.
- Esteve-Volart, Berta; and Manuel Bagues, 2015. “Politicians’ Luck of the Draw: Evidence from the Spanish Christmas Lottery”, Journal of Political Economy, 124(5), pp. 1269-1294.
- Funk, Patricia; and Christina Gathmann, 2015. “Gender gaps in policy making: evidence from direct democracy in Switzerland”. Economic Policy, 30 (81), pp. 141–181.
- Government of the Republic of Armenia, 2020. Structure.
- Gwiazda, Anna, 2017. “Women in parliament: assessing the effectiveness of gender quotas in Poland”. Journal of Legislative Studies, 23(3), pp. 326-347.
- IDEA (Institute for Democracy and Electoral Assistance), 2020. Gender Quota Database.
- Itano, Nicole, 2007. “Quota Law Puts More Women in Armenia’s Election“. Women’s eNews.
- Kenny, Lawrence W. and John R. Lott, 1999. “Did Women’s Suffrage Change the Size and Scope of Government?”. Journal of Political Economy, 207, pp. 1163- 1198.
- Lippmann, Quentin, 2020. “Gender and Lawmaking in Times of Quotas.”
- O’Brien, Diana and Johanna Rickne, 2016. “Gender Quotas and Women’s Political Leadership”. American Political Science Review. 110(1), pp. 112-126.
- OECD (2020), Women in politics (indicator).
- SVT, 2018. “Här är partierna som har högst och lägst andel kvinnor bland kandidaterna”.
- SVT, 2020. “Ny mätning: SD Sveriges största parti“.
- World Bank Data, 2019. “Proportion of seats held by women in national parliaments (%)”.
- World Economic Forum, 2019. “Global Gender Gap Report 2020”. ISBN-13: 978-2-940631-03-2.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
The Swedish Exceptions: Early Lessons From Sweden’s Different Approach to COVID-19 – Insights From a SITE-LSE Webinar
Sweden’s policy in the Corona crisis has been subject to a lot of discussion in international media recently. Some point to the country portraying “the Swedish way” as a valid policy alternative to the forced lock-down of society, others criticize the Swedish government for being imprudent. Given the pace with which the virus spreads and considering the volatility of current events, it is pre-mature to draw any definite conclusions. But it is certainly time to start an informed policy discussion. The webinar “The Swedish Exceptions: Early Lessons from Sweden’s different approach to COVID-19, jointly organized by the Stockholm Institute of Transition Economics (SITE) and the London School of Economics (LSE) on April 22, 2020” brought together academics from different relevant disciplines from Scandinavia, the UK and the US . The webinar allowed to discern a few of the motivations behind the Swedish policy choices as well as a number of criteria which will serve to measure the success of governments’ responses to the Covid-19 pandemic in the future.
Understanding the Swedish Approach to Covid-19
Much has been written and said about the Swedish reluctance to impose a strict lock-down on the country: the Swedish government has so far relied mostly on expert recommendations, avoiding from more stringent policies such as the strict lock-downs imposed by for instance Sweden’s neighboring countries Norway and Denmark (more on Sweden in the Covid-19 crisis here). The majority of the speakers in the webinar agree that the Swedish policy in the Corona crisis has been an outlier, even with respect to traditional Swedish policy: Peter Baldwin, historian and professor at the University of New York and the University of California, Los Angeles, argued that Sweden has had an interventionist tradition with respect to social and health policy in the past. “Native policy traditions” therefore do not explain why Sweden has chosen this policy course in his view.
While it seems difficult to pin down historical or ideological reasons behind the Swedish policy stance with respect to Covid-19, Lars Trägårdh, professor of social history at Ersta Sköndal Bräcke University College in Stockholm, pointed out that even though the legal differences may seem stark, the difference in the policy impact may be smaller than expected, the crucial factor being the degree of compliance with a certain measure or recommendation and not its legal force. Trägårdh further argued that, since it may take many months to develop a vaccine, the sustainability of a given policy strategy is essential. According to him, a policy relying on voluntary compliance as the Swedish one rather than legal obligation, may therefore yield comparable effects in the short and medium run and could even turn out to be more successful in the long run.
Trägårdh argued that the true exceptionality of the Swedish response to the global pandemic has been the choice to not close elementary schools. This policy choice can be explained above all by the concern for children’s rights: for smaller children, digital learning simply is not a valid option. As declared by the government on several occasions, another reason is that parents working in professions such as healthcare may be induced to stay at home if schools are closed. Finally, Trägårdh cited a recent study from Iceland which suggests that the effect of closing schools on limiting the spread of the virus may be relatively small.
Later in the discussion, another potential argument in favor of the Swedish strategy emerged: Professor Sara Hagemann from the LSE School of Public Policy described the difficulty of leaving a lock-down, which Denmark is currently experiencing. The question which measures are to be lifted and which sectors of the economy are to be opened first has caused considerably more controversy than imposing the initial lock-down. In contrast, the public debate in Sweden can immediately focus on dealing with the long-term consequences of the crisis according to Trägårdh.
The significance of the concept of “herd immunity” (meaning the protection from disease arising from large percentage of the population having developed immunity) for the Swedish strategy is unclear. Baldwin pointed out that even though Swedish authorities have declared not targeting herd immunity, many measures implicitly seem to be aiming for this outcome.
Results of the Swedish Approach Until Today
Tom Britton, professor of mathematics at Stockholm University, agreed that the Swedish response to the Covid-19 crisis came late and that there has been too little testing. However, he argued that the government’s policy has been consistent, focusing on reducing the spread of the virus and protecting risk groups and especially the elderly. Whether Sweden has achieved the latter goal is still up to discussion, though. As of April 2020, reported infections and deaths in nursing homes had increased, which according to Trägårdh has been the major failure of the Swedish policy response up until today. Yet, the speakers agreed that the Swedish government’s measures have received a lot of public support within Sweden so far, which is a non-negligible factor for the long-term success of the strategy.
General Policy Conclusions
Professor Ole Petter Ottersen, president of the Karolinska Institute in Stockholm, Sweden’s largest centre of medical research, stressed the speed with which the virus has been spreading: the rapid development forces policymakers to quickly take decisions based on limited information. Given the lack of data, Ottersen called for politicians to practice humility and acknowledge the uncertainty surrounding policy choices. According to him, it will take years to evaluate whether the Swedish model or the Norwegian model of a quick and strict lock-down is better suited to fight the pandemic.
Policymakers around the globe face a dilemma: for sustainable crisis management and given countries’ interdependency, measures meant to fight the spread of Covid-19 should be aligned internationally and taken cooperatively. Yet, as Hagemann pointed out, it is clear that one policy cannot fit all: countries differ for instance with respect to their socio-economic structure, health care quality and availability, demographics, and with respect to the point in time when they were hit by the virus. This is not only the case between countries, but even within countries, which could justify a differentiated approach between rural and urban areas in some instances. In other words, all models and policy recommendations have to be adapted to the specific local setting. A strategy which allows for making local adjustments while maintaining a global perspective will be a major challenge for policymakers in the coming months and, likely, years.
Britton stressed the importance of understanding the limits of the models being used. Their predictions depend on a lot of assumptions regarding for instance how individuals behave and to what extent rules and regulations are being respected. Anti-body tests will soon provide more data on the actual spread of the virus, but even then, major questions, such as how to treat a potential trade-off between preventing deaths from Covid-19 vs. the socio-economic and health costs caused by a lock-down, will remain unanswered. This trade-off is country specific as well: Hagemann argued that Sweden and the other Nordic countries have quite successfully implemented remote working and learning options. This, however, will not be feasible in most developing countries, for instance, which necessarily affects the cost-benefit analysis of the available policy options.
Further, data collection and availability undoubtedly need to improve. As long as no better instruments of analysis are available, both scientists and politicians should be transparent about the simplifying assumptions and models they base their policy recommendations and decisions on.
Finally, despite their different academic backgrounds, all experts agreed on the need to take into account the indirect consequences of both the spread of the virus and the policy measures implemented to fight it. Covid-19 is likely to reinforce social inequities. For instance, it has been shown that in Stockholm, immigrant communities have been hit the hardest. As soon as the imminent health crisis is under control, the policy focus, therefore, has to shift towards the socio-economic consequences of the crisis.
Acknowledgements
The Stockholm Institute of Transition Economics wishes to express its appreciation to the speakers for their contributions to the policy debate, to the London School of Economics for the successful cooperation in organizing the event, and to the audience for its engaging questions and interest in the topic.
List of Speakers:
- Peter Baldwin, New York University and University of California, Los Angeles
- Tom Britton, Stockholm University
- Sara Hagemann, London School of Economics
- Ole Petter Ottersen, Karolinska Institute, Stockholm
- Lars Trägårdh, Ersta Sköndal Bräcke University College, Stockholm
- Erik Berglöf, London School of Economics (moderator)
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Money as an Economic Category and Its Relationship With Crypto Assets
This brief discusses money in its general definition and describes new types of money arising in the modern era of digitalization, such as electronic money, cryptocurrencies, Central Bank Digital Currencies (CBDC), etc. It provides an overview of some of the legislative approaches trying to deal with new types of money and outlines the benefits and shortcomings arising from allowing for financial operations with digital currency. It also stresses the necessity of a new integrated approach in national and international regulation of cryptocurrencies.
Introduction
Cryptocurrencies have existed for more than 10 years. During this period the interest towards this type of digital money has seen its ups and downs. However, by now, they have become part of modern financial markets. Today, more and more central banks consider the possibility of introducing national digital cash and try to create easy-to-understand and clear regulation for new payment methods. We can observe the rapid transformation of the traditional monetary system. At the same time, there is no clear understanding of how the new monetary system should look like. An essential step towards this understanding is developing a clearer systematization and definition of money, financial funds, cryptocurrencies, fiat money in the traditional and the modern sense. Explaining these concepts is necessary to facilitate effective regulation, the development and supervision of financial markets. Indeed, during rapid financial markets transformation, well-developed regulation is necessary to avoid excessive financial risks and speed up financial sector development.
The Place of Money in the Modern Financial System
Financial resources play an extremely important role in the economy: Monetary systems are like the blood circulation for the body. While there is a common understanding of what money is in the traditional sense, this concept does not take into account the recent development of the financial sector, the penetration of IT technologies, the entry of new non-financial institutions into the financial sector as well as the creation of new products at the intersection of finance and IT. As argued above, a clear and encompassing definition of money, reflecting these developments, is necessary for regulatory purposes both at the national and international level.
Typically, money is defined through its functions, such as a measure of value, means of circulation, means of payment and savings. For example, the Large Economic Dictionary suggests that “Money is the universal equivalent, a special product, used to form expressions of the value of all other goods. Money functions as a medium of exchange and of payments, as a measurement of value, wealth accumulation and world money” (Borisov, 2003). As can be seen, one of the most important characteristics of money is its universality. Money can be exchanged against different goods and services almost without any limitations. At the same time, Tarasov mentioned that money is “legal payment funds, usually consisting of banknotes and coins that are constantly circulating as a medium of exchange in accordance with government rule” (Tarasov, 2012). There are other definitions of money, but they usually describe traditional money.
Along with traditional fiat money, there are other payment methods and electronic money is the most common of them. According to the Belarusian legislation, electronic money is “units of value stored in electronic form, issued in exchange against cash and monetary funds and accepted as a means of payment […]”
Electronic money cannot be described as traditional cash or money on bank accounts. It is not included in the money supply and can be issued only by commercial banks. At the same time, electronic money can perform the same functions as traditional fiat money. Whether or not electronic money can be considered full-fledged money is essentially a legal issue.
Another very important question is dedicated to cryptocurrencies. Cryptocurrencies are usually issued based on blockchain technology (distributed ledger) and can be created (“mined”) by anybody. Hence, electronic money is representative of traditional money, but cryptocurrencies are not.
Taking into account the penetration of information technologies into finance as well as the appearance of electronic money and cryptocurrencies, we can define money as the universal equivalent (measure) of value constituting a legal means of circulation, payment and savings on certain territories within a particular jurisdiction, with a legal status guaranteed by the government (Luzgina, 2018). In this definition, the emphasis is placed on the legitimacy of money because in some countries, operations with digital currencies can be legally interpreted as operations with securities, equity etc., rather than money in the legal sense.
Belarus was one of the first countries that legalized operations with crypto assets. But this does not mean that cryptocurrencies have become the equivalent of national or foreign currencies. According to the Belarusian legislation, people can mine cryptocurrencies, exchange them against Belarusian rubles, foreign currencies, buy, sell and exchange against other tokens (Decree #8, 2018). There is no official permission to use crypto money as a measure of value, means of circulation or payment method. In other words, people cannot use bitcoins for purchasing goods and services. At the same time, cryptocurrencies can be used as traditional financial assets.
It is necessary to emphasize here that the digitalization of the financial sector is an ongoing process. It is very hard to be the leader in the sphere. Despite Belarus being an early mover in the legalization of crypto assets and notwithstanding the existence of a strong IT sector and attractive crypto assets regulation, Belarus is only the 59th among 65 countries in the Fintech Index 2020. Based on the experience of other countries, sustained progress in this area can be achieved by government support, the existence of a well-developed ecosystem and access to financing (Global FinTech Index 2020).
Belarus is not the only country in the world that has limitations on cryptocurrencies’ circulation as fiat money; restrictions differ depending on the jurisdiction. Many central banks consider cryptocurrencies as disruptive technologies with high risks. Regulatory bodies usually cannot control operations with crypto money. That is why cryptocurrencies can be attractive for payments in the grey economy. Moreover, exchange rate fluctuations of cryptocurrencies are very unpredictable. Owners of cryptocurrencies can become very rich as well as very poor within a short period of time.
Central banks can implement limitations to avoid or decrease risks. For example, operations with cryptocurrencies are prohibited in Bangladesh and strongly restricted in India. There are central banks (including the central banks of Malaysia and Austria) that take a neutral position with regards to crypto operations but inform the society about possible risks, including risks of high fluctuations (Luzgina, 2018). At the same time, Japan permits the circulation of cryptocurrencies as a means of payment within its current regulation. That is, the Japanese authorities legalized these digital assets and, supposedly, can keep risks under control.
It is important to understand that these, and other, differences in the approach to crypto assets regulation create barriers for international payments and investment transactions. At the same time, a unification of regulation would contribute to transparency and mitigate the risk of cybercrimes.
Central Bank Digital Currencies: Main Aspects
There is an intense political and academic debate about the future of crypto markets. At the same time, more and more countries begin to think about the introduction of Central Bank Digital Currency (CBDC). Countries like Ukraine, China, Sweden, Canada, Thailand and some others have announced their plans of issuing CBDC. CBDC can be compared with digital cash; it can reduce operational costs and make all money transactions more transparent. But there are some uncertainties: The technology is new and may cause confusion and even disapproval among the population who prefers to use only cash.
One of the most interesting examples of the introduction of CBDC is the case of Uruguay. In 2017-2018, this country realized a pilot project of CBDC (the e-peso). A limited amount of digital currency was issued and only 10,000 citizens joined the project. There was a limited list of stores and businesses that were allowed to work with digital currency and all transactions on the base of mobile phones were done only between registered users. This project has demonstrated several advantages of e-peso circulation. First, the system could work without Internet and provided anonymity but at the same time controllability of all operations. Second, security was the main concern: The person could get access to his/her digital resources even if he/she forgot the password of the digital wallet or lost the mobile phone, but non-authorized access was effectively avoided. Finally, the last but not the least advantage of the system was the exclusion of double charge or falsification during payment transactions. The project lasted half a year and finished successfully. However, transition to the digital currency did not follow.
As of now, many countries only consider or are going to realize pilot studies in this area. The only country that is going to implement CBDC in the foreseeable future is China. The cautious position of many central banks is understandable because CBDC is an analogue of digital cash. The population distrusts such forms of money. Another challenge is that senior citizens often prefer cash for payments and other financial transactions.
Tokens vs. Cryptocurrencies
Bitcoin and other cryptocurrencies present only one kind of digital tokens. According to the Belarussian legislation, a token is an entry in the register of transaction blocks (blockchain), or another distributed information system certified that the owner of a digital sign (token) has rights to civil law objects and (or) presents cryptocurrency. All cryptocurrencies are tokens but not all tokens can be defined as cryptocurrencies. Tokens are issued for multiple purposes. Governments in many countries try to identify all types of operations with tokens for the creation of clear regulation. For example, the Central Bank of Lithuania highlights the differences between issuing tokens in the framework of ICO (Initial Coin Offering) and STO (Security Token Offering). According to the Lithuanian regulation, ICO usually provides for presenting discount programs or using tokens as payment instruments. At the same time, STO includes the issuance of tokens that have features of bonds or other traditional financial instruments and is subject to regulation. In other countries, central banks do not highlight STO and operations regulation with tokens depends on the characteristics and specifics of each project.
Many countries have developed unique principles and rules of tokens regulation. But there are no unified approaches at the international level which makes it difficult for conscientious market participants to work with financial crypto assets over different jurisdictions. Moreover, there are uncertainties and risks that have to be investigated more in detail. Authorities in many countries are afraid of cybercrimes and increasing money laundering operations.
At the same time, many advantages are apparent. For example, in Belarus, crypto platforms get more popular, because they offer attractive financial instruments for the population and companies. On such platforms, companies can attract necessary resources and citizens invest in financial tools with regulated risks.
Figure 1 – Structure of digital, electronic money, tokens and financial means (Luzgina, 2018)
Comment: Fiat electronic money is an electronic analogue of fiat currency. In this case, if we put 100 euros in an electronic wallet, we should see 100 electronic euros after the transaction. At the same time, non-fiat electronic money differs from fiat currency. For example, we can exchange Belarusian ruble against electronic money – V-coin, which is issued by Belgazprombank in cooperation with the mobile operator – A1.
The above discussion results in a number of policy-relevant implications:
- The legal definition of money, financial funds and electronic money should be updated taking into account innovative forms of financial instruments development and the appearance of new financial market participants.
- Old rules and regulatory approaches hinder market development and unregulated space can create additional risks and uncertainties.
- The transition from cash to CBDC is possible but has limitations.
- A unified regulation for cryptocurrencies and other tokens should be developed at the international level for decreasing risks and further developing financial markets.
Conclusion
Financial market transformation is happening very rapidly. The penetration of information technologies in the financial sector created a huge number of new innovative products and simplified financial operations. All these changes have affected the payment system. The creation of electronic and digital currencies makes it necessary to reconsider the future of the traditional monetary system. But even the current regulation has to become more flexible and take into account the rapid growth of new types of financial market participants and products. The development of financial technologies creates additional risks, such as money laundering, money theft or uncontrolled financial operations which go beyond the borders drawn by national jurisdictions very often. Many central banks treat payments with cryptocurrencies and ICO with caution. At the same time, the process cannot be stopped because alternative methods of financial transactions are often more attractive compared with traditional financial services. But the low level of financial and digital literacy among the population combined with outdated legislation can slow down innovative processes in the financial sphere and augment the risks.
References
- “Money: meaning and functions of money – discussed!” (2007). Economics Discussion. Accessed September 12, 2017.
- Tarasov V.I. (2012), “Money, credit, banks”, Minsk: BSU. p. 375.
- “On Digital Economy Development”. Decree No.8 dated December 21, 2017.
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