Small and medium-sized enterprises (SMEs) are essential drivers of economic growth and development in both developed and developing economies. In Europe, those are defined as “enterprises which employ fewer than 250 persons and which have an annual turnover not exceeding EUR 50 million and/or an annual balance sheet total not exceeding EUR 43 million” (European Commission, 2003). In the United States, SMEs are firms that have fewer than 500 employees in manufacturing sectors and less than USD 7.5 million annual receipts in most non-manufacturing sectors (US Small Business Administration, 2020). Despite differences in conceptualization, SMEs represent over 95% of all businesses across the world, generating around half of the private-sector employment and 40% to 60% of value added (European Commision, 2019; OECD, 2019; World Bank, 2020).

SMEs are often characterized by informality, flat (horizontal), as opposed to hierarchical internal structures, and open and fluid communications between the owners and employees (Rothwell & Dodgson, 1991). Flexibility and adaptability to changing circumstances, as well as creativity and innovativeness are also among their defining features (Antony et al., 2005). Despite their inherent strengths, SMEs face a range of size-related challenges in attracting and retaining qualified workforce and accessing finance (Beck & Demirguc-Kunt, 2006; Dundon & Wilkinson, 2018; Harvie et al., 2013). National and cross-country data also suggest that as compared with large companies, SMEs have lower productivity and wage levels, being more vulnerable to supply and demand shocks (OECD, 2019, 2020). Thus, improvements in SME governance, aimed at reducing regulatory complexities and leveling the playing field, have been high on the policy agenda of many governments (OECD, 2019).

The RA Law on Small and Medium Entrepreneurship (National Assembly of the Republic of Armenia, 2000) was harmonized with the EU legislation in 2010 and defines SMEs as enterprises having up to 250 employees, with an annual turnover not exceeding AMD 1500 million and/or an annual balance sheet total not exceeding AMD 1000 million. According to this definition, there are around 70000 SMEs in the country, accounting for 99.8% of all businesses (Statistical Committee of the Republic of Armenia, 2019). SMEs are represented in all sectors of the economy, with a significant share in wholesale and retail trade (64% of all businesses), and account for 23.6% of gross value added in GDP (Ibid.). Their highest contribution in absolute terms (gross value added as % of GDP) is in wholesale and retail trade (7.4%), followed by manufacturing (4.4%), and construction (3.3%); the relative contribution (as compared with large companies) is the highest in real estate and repair of household goods (other services) (100% both), professional, scientific and technical services (99.2%), accommodation and food services (95.4%), and construction (93.3%).

The third edition of the Eastern Partner countries’ SME Policy Index (OECD et al., 2020) states that “despite the lack of a comprehensive medium-term SME strategy,” the institutional and regulatory framework for SME policy has improved in Armenia over the past years. The Midterm Strategy for the Development of Small and Medium Entrepreneurship (years 2020-2024) was discussed by the Government in October 2019 but is still under review (Government of the Republic of Armenia, 2019). As stated in the draft decision, the Government aims to “facilitate entrepreneurship in Armenia, support the increase in productivity among SMEs, their competitiveness in local and international markets, as well as the introduction of productive technologies and innovative ideas.”

The coronavirus pandemic engendered a global crisis that, unlike most other crises in world history, entails both supply and demand shocks. Worldwide, more than twenty million people have been infected as of August 2020, and due to lockdown measures, around 300 million full-time employees have become unemployed or have had a reduction in work hours and pay (International Labour Organization, 2020; World Health Organization, 2020). The pandemic has affected employment, investment, and growth prospects, and may result in permanent changes in consumption and work patterns (Baldwin & Weder di Mauro, 2020; Barrero et al., 2020; Barua, 2020; Coibion et al., 2020; Reeves et al., 2020).

Although both large companies and SMEs have been affected by the crisis, recent reviews (Balla-Elliott et al., 2020; Bartik et al., 2020; Dua et al., 2020; Lindsay et al., 2020; OECD, 2020) acknowledge that its effects are greater on SMEs. The OECD summary of 40 surveys in member states and partner countries (OECD, 2020) reveals that more than half of SMEs have had substantial revenue loss and fear to be out of business within a quarter unless public assistance is available and extended over the duration of the crisis. There is evidence that SMEs are increasingly digitizing operations to adapt to changing circumstances, but temporary closures, employment and wage reductions, and bankruptcies have occurred. The most widely used policy instruments directed at mitigating the effects of the crisis are income and profit tax deferrals, loan guarantees and direct lending to SMEs, and wage subsidies (Ibid.).

A McKinsey analysis of several small business surveys in the United States (Dua et al., 2020) suggests that if government support is unaccounted for, 1.4-2.1 million (25-36%) small businesses “could close permanently as a result of the disruption from just the first four months of the COVID-19 pandemic.” According to this study, the most vulnerable are businesses which face both financial (liquidity) and COVID-related (revenue shock) challenges.

Some of the reasons why SMEs are more vulnerable to the crisis, as identified in the literature, are as follows: first, these businesses are overrepresented in sectors which were directly hit, e.g., tourism, retail trade, and transportation; second, as compared with large companies, SMEs in general have less cash in reserve, and thus, are more affected by human resource and capital underutilization; third, SMEs are more dependent on global and national supply chains, which were disrupted by the crisis (Bartik et al., 2020; Barua, 2020; Dua et al., 2020; OECD, 2020).

Based on the reviewed literature, we advance the following hypothesis on the impact of the crisis on businesses in Armenia:

H1 : SMEs in Armenia have been affected by the crisis to a greater extent than large companies.

As compared with large companies, SMEs generally offer lower-paying jobs but also account for most of the private-sector employment in a country (European Commision, 2019; OECD, 2019). This implies that SME employees are more likely to represent those in the middle of the income distribution, the middle class (Atkinson & Brandolini, 2014; Banerjee & Duflo, 2008). The latter, as some analysts argue, have been more affected by the crisis due to the lack of savings and wealth collateral (Reeves & Rothwell, 2020; Sawhill, 2020). Hence, we also hypothesize that

H2 : As compared with large-company employees, SME employees are more inclined to think that the crisis has equally affected them and most people.

Irrespective of firm size, the effects of the pandemic on employment have been greater in industries that assume proximity, e.g., transportation, trade, arts and entertainment, and food and hospitality. By contrast, employees in services that can be provided remotely (e.g., education, information and communications, finance and insurance) have been less affected (del Rio-Chanona et al., 2020; Fernandes, 2020; Saltiel, 2020). Many observers also emphasize that apart from engendering poverty, the pandemic will increase income inequality within nations. This is because most of the jobs that can be performed remotely are relatively high-paying positions occupied by professionals with medium to high qualifications (Elliot Major & Machin, 2020; Furceri et al., 2020; Palomino et al., 2020; Sumner et al., 2020). Thus, we hypothesize that

H3 : Employees of the sectors in which work can be carried out remotely (e.g., education and ICT services) have been less affected by the crisis, in both SMEs and large companies.

H4 : Employees with medium to high professional qualifications have been less affected by the crisis, in both SMEs and large companies.

The majority (77%) of respondents are employed by SMEs. Companies having less than ten employees (“micro” enterprises) account for more than half of the employment within the SME category, followed by those with 10-49 employees (see Figure 1). This finding is consistent with the national statistical data (Statistical Committee of the Republic of Armenia, 2019, p. 13), according to which SMEs account for the majority of wage employment (68%) in the Republic of Armenia.

Around half of the SME respondents (54%) are male, more than a third (39%) are from Yerevan, and a third (33%) are from urban areas other than Yerevan. Similarly, around half of the large-company employees (54%) are male, 65% are from Yerevan, and 23% are from urban areas other than Yerevan. The average age of SME employees is 34 (median=32), the youngest respondents being 18, while the oldest respondent aged 66. More than half of the respondents (60%, n=577 due to missing values) have tertiary education (bachelor’s, master’s, five-year specialization, and postgraduate degrees), and 15% have middle professional and vocational education. The average age of large-company employees is 34 (median=32), the youngest respondents being 19, and the oldest aged 69. The majority of respondents (79%) report having tertiary education.

Most (around 60%) of the SME respondents are wage employees, followed by those who own a business (are self-employed, 22%), and those who are in agriculture or horticulture (10%). Around 90% of the large-company respondents indicated that they work as wage employees. As of March 1, 2020, 51% of the SME employees were employed full-time, 10% were employed part-time, 13% report having daily pay, and 17% did not work. The majority (84%) of large-company employees for whom complete data are available (n=205) indicated that as of March 1, 2020, they worked full-time. Wage distribution data (see Figure 2, panels a and b) show that 26% of the SME employees had wages less than AMD 92 thousand, and about as many (27%) had wages in the range of AMD 92-120 thousand. Most (47%) of the large-company employees had monthly income in the range of AMD 180 to 500 thousand.

Table 1 provides summary descriptive statistics of the independent variables of the study, and Table 2 provides the matrix of pairwise correlations between the independent and the dependent variables. It can be observed from the pairwise correlation matrix that although weakly, SME employment is significantly positively correlated with both layoff and pay reduction (r=0.15 and 0.14, respectively, p=0.00 for both). The highest correlations of primary interest to this study are as follows: layoff is significantly negatively associated with full-time employment (r=-0.25) and income (r=-0.22), while pay reduction is significantly negatively associated with full-time employment (r=-0.17) and age (r=-.10). The two variables measuring employment changes due to the pandemic (layoff and pay reduction) are significantly positively correlated (r=0.42, p=0.00).

Logistic regression results (see Table 3) show that being an SME employee increases the likelihood of layoff and pay reduction. The odds ratios are 2.5 and 2, respectively. The regression models do not have a good fit, but the SME variable is significant at 1 to 5% levels in both cases, and accounts for more of the variance in the dependent variable (layoff or reduction in pay) than the other independent variables. Other variables that are significantly associated with layoff are gender, full-time employment, and monthly income; in the pay reduction equation, those are age, residence in the capital city, residence in an urban area, and full-time employment.