Beyond its impact on the healthcare system, the Covid-19 pandemic has already reached labor markets throughout every economy via economic shocks. As of 1 April 2020, ILO estimates indicate a substantial rise in global unemployment, leading to a 6.7% decline in working hours in the second quarter of 2020, which is equivalent to 195 million full-time workers. In this policy note we will draw the reader’s attention to the potential scale of the impact on the labor market and the respective social consequences in Georgia. We will identify a wide variety of groups affected by the Covid-19 crisis, with a special emphasis on the labor market, and provide our judgement on the possible extent of the repercussions. The current crisis affects almost every segment of the population, including members of the following large social groups:
- Labor market participants face high risk of job loss. Fewer employment opportunities and broad scale layoffs force a large section of self-employed and salaried workers into challenging circumstances.
- Recipients of Targeted Social Assistance (TSA) are at great risk of slipping deeper into poverty. While members of this group mostly rely on social assistance layouts, the supplementary income that they receive, often from informal sources, could be cut. In addition, the increased prices on food and other essential goods could be particularly detrimental to this group of people.
- Senior citizens are extremely exposed to the danger of the virus and struggle with greater health risks.
Our analysis starts with an overview of the Georgian labor market and the short-term impacts of Covid-19 on workforce displacement throughout the various sectors. The impact is not gender neutral, as it affects men and women differently depending on the sector. Therefore, we will further provide the decomposition of the impacts on the labor market and propose gender-responsive solutions to the pandemic. To mitigate adverse effects across various vulnerable groups, we will review the existing theoretical and practical evidence on targeted and universal support schemes. An overview of international social support programs is moreover provided in this note. We will further analyze the relative merits and drawbacks of our pre-defined policy options based on a multi-criteria assessment in the context of the Covid-19 crisis and thereafter provide recommendations for policy implementation.
Covid-19 – Impact Across Sectors and an Overview of the Labor Market
Unemployment in Georgia is expected to experience a large-scale increase in the short-term, leading to massive social problems. Workers have been told to remain at home because of the broad virus containment measures taken during the outbreak. Those with the opportunity to work from home are relatively well-off, unlike the large variety of vulnerable groups affected by the lockdown. Low levels of economic activity impact almost all industries, and the most vulnerable sectors include accommodation and food services, most wholesale and retail trade and entertainment and recreation. These difficulties place hundreds of thousands at risk, either by downward adjustments to income or working hours, or by completely losing their jobs.
In order to evaluate Covid-19’s potential short-run effect on employment across various economic sectors, we have qualitatively assessed the strength of the impact at the sub-sectoral level, taking into account the following: (1) list and scale of economic activities prohibited during the ‘lockdown’; (2) restrictions imposed on transportation; (3) drop in consumer demand; (4) fall in intermediate input use.
In Table 1 we present our assessment of the Covid-19 impact across sectors, coupled with the corresponding labor market statistics.
Table 1: Covid-19 impact on possible workforce displacement across sectors.
The key findings from the labor market assessment include:
- Close to 30 percent of hired workers face a high risk of job displacement, mostly driven by an expected fall in economic activity in the trade, construction, manufacturing, and accommodation and food services sectors;
- The least impacted industries are projected to be education, public administration and defense, utilities, and health;
- The majority of self-employed are active in the agricultural sector, which faces a moderate impact for several reasons: the closedown of open food markets, restrictions on transportation, and a partial decline in demand (mostly from the food service sector). Although agriculture is not projected to be severely affected, a substantial number of the self-employed (mostly subsistence farmers) in this sector, considering their significantly lower than average baseline earnings, may require special policy emphasis within this group.
Finally, it should be emphasized that the severity of impacts across sectors will further depend on the longevity of the lockdown measures and the sequence in which they may be lifted for different economic activities.
In addition to the assessments in Table 1, Annex 1 presents a correlation between our estimates weighted by sub-sectors and the ILO’s assessment of the current global impact of the crisis on economic output across the sectors. It should be further noted that, in most cases, the scale of impacts coincide, and the remaining differences are due to: (1) our approach being based on more detailed sub-sectoral data; (2) the ILO looks at the global impact, whereas we focus solely on Georgia.
Short-term Workforce Displacement Risks in Vulnerable Sectors
To alleviate social problems stemming from the labor market shock during the strict, short-term quarantine measures, the clear need for safety net programs has raised the important questions of how they should be designed and who the recipients of support should be.
The discussion of social program designs requires a thorough analysis of the potential target groups. As mentioned in the previous section, after drastic quarantine and lockdown measures, many people in Georgia are at risk of finding themselves without jobs or with decreased salaries and earnings, which, in turn, is a main cause of social problems, like the inability to provide food and other necessities. The highly affected groups, as outlined in Table 1, can be clustered across the following sectors of economy:
- The accommodation and food service sector is currently the most directly and highly affected sector. Hotels and restaurants are completely closed for an uncertain period, except for the food delivery business. However, even this is constrained to certain periods of the day, since according to the state’s emergency rules after 21:00 all movement, including delivery, is forbidden.
Most people hired within accommodation businesses face temporary job loss. This group includes hotel administration staff, housekeeping staff, people working in hotel restaurants, etc. Similarly affected are employees in restaurants and cafés, faced with cutbacks in salaries, if not complete job loss.
Another significant group within this sector are the self-employed. Owners of small family hotels and restaurants, typically dependent on tourism expenditure, now find themselves without any cashflow.
- A significant portion of the wholesale and retail trade sector also faces major shutdowns. To begin with, employees of trade centers and individual stores are now out of work for an indefinite period. These include consultants in clothing stores, hardware stores, household appliance stores, etc. A very limited number of shops that continue to work via online sales have retained several employees on decreased salaries.
The reality is also harsh for the self-employed in retail trade. Open marketplaces, including construction materials shops and farmers’ markets have been shut, and such people are left without a vital income source. It should also be noted that most of these workers are members of a lower social strata and are less likely to have enough, if any, savings for the quarantine period.
- As for the relatively small, but equally affected, arts, entertainment and recreation sector, art galleries, museums, night clubs, theatres, movies, and sports and spa facilities, have all been closed down due to their ‘non-vital’ function. Salaried as well as self-employed workers in these sectors found themselves without employment soon after the state emergency was announced.
- Additional highly affected groups are those hired and self-employed in the transportation sub-sectors. The closing of public transportation has left hired bus, metro, and minibus drivers entirely without work.
Other than hired employees, self-employed drivers for intercity transportation are now left without work since intercity commuting is now forbidden under the state of emergency. Comparatively less affected are self-employed taxi drivers, who are still allowed to work, however only between 06:00-21:00. The fact that many drivers previously worked night shifts, combined with declined daytime demand, results in significant cutbacks in daily earnings for taxi drivers.
- Another significantly affected group are those workers employed in households. These include housemaids, nannies, private tutors, handymen, etc. Since everyone is being cautious and following social distancing instructions, many households have dismissed their hired help for an indeterminate period, and even those still employed have a hard time getting to work due to the suspension of public transport, and are therefore left without vital daily income.
- The agriculture, forestry, and fishing sector, the largest in terms of employment, remains less affected relatively, though it is facing restrictions since restaurants and cafés require fewer agricultural products than before. Moreover, as farmers’ markets have closed, their access to marketplaces has become significantly constrained. Farmers are now supplying only supermarket chains and restaurants with delivery services, a significant economic decrease compared to the normal environment. It should also be noted that self-employed small farmers are in the majority in the sector. Such workers are likely without strong links to supermarket chains or restaurants, and therefore, they will be more noticeably affected by the economic impact.
An important specificity of self-employed and domestic workers is that many are also informally employed, thus their identification by official sources (i.e. in tax returns or small business registers) is extremely problematic. Thus, the existence of a large variety of potentially affected groups, as well the inability to correctly estimate the severity of impacts across groups, highlights the need for a temporary social protection mechanism that will cover all affected parties, particularly since the people included in the groups above are not typically the main recipients of social assistance programs.
Decomposition of Labor Market Impacts by Gender
In this section, we present the gender decomposition of labor market impacts, and conclude that unemployment-driven assistance may benefit men considerably more than women.
Chart 1 summarizes the distribution of self-employed and salaried men and women across low, medium, and highly affected industries, based on the sub-sectoral assessments previously described and using gender-disaggregated employment data.
Figure 1: COVID-19 impact on possible workforce displacement, by gender
It is evident that the proportion of employed men is significantly higher in the most vulnerable sub-sectors. Such a picture is highlighted by the high male-employment ratios in construction, transportation, and parts of manufacturing, as well as the high female-employment in the minimally affected education and healthcare industries.
To summarize, during the current crisis men are more susceptible to job displacement, and if a social assistance policy is solely based on labor market outcomes, they will yield higher benefits. Such social support mechanisms will deepen existing gender inequalities in the country as women face disproportionate and increasing burden of care work (in situation of lockdown).
Social Assistance Policy Objectives in a Crisis
Considering the diversity of groups influenced by the lockdown, any assistance program should have several main policy objectives:
- Maximizing the reach of a policy to those in need and minimizing their risk of impoverishment – a large part of the population is affected by the lockdown, thus there is a substantial risk of increasing poverty directly from job loss and indirectly via job losses within families. Social assistance should, in a best-case scenario, reach the maximum number of disadvantaged people, while avoiding providing assistance to the affluent.
- Minimizing fiscal pressure – social assistance can create substantial pressure on the budget, especially in the current situation as revenues have decreased due to the lockdown. Furthermore, people who do not require support should not receive assistance, thus, decreasing unjustified pressure on the budget.
- Progressivity and gender responsiveness – an assistance program should provide proportionally larger support to those in greater need and aim to balance support by gender.
To mitigate the negative social impact of the economic lockdown, the government will have to provide significant and effective social assistance. And this is where all governments face a key dilemma, as they decide between providing targeted versus universal assistance.
An Overview of Targeted vs. Unconditional Universal Assistance
Targeted assistance is based on the methodology to define target groups, this could be under a points-based system (similar to current targeted social assistance available in Georgia) or a certain criterion defining affected groups. Under any targeting approach, two major challenges exist: (i) missing certain affected people (exclusion error), where defining an ideal criterion is impossible; and (ii) supporting those who do not require any assistance (inclusion error). Hanna and Olken (2018) show that targeted programs have the potential to maximize welfare, however, they require a substantial amount of data and effort to minimize errors in the inclusion and exclusion of recipients. They further illustrate that, under normal circumstances, to reach 80% of poor people, the inclusion error will be around 22-31%. Deciding on a targeting methodology can also be costly and time consuming. Klasen and Lange (2016) highlight that there is little difference between simple targets, such as demography or geography, and more complex asset-based measures, and both make poor proxies as they do not capture poverty effects in great enough detail.
In contrast, a universal support scheme can also be considered; defined as an unconditional transfer to every member of society. From the administrative perspective it is substantially easier to organize and administer, as it will not require the formation of targeting methodology or identification of target groups. Compared to targeted assistance, universal support will simply not have exclusion errors. However, the universality of the scheme would be associated with large inclusion errors. Nevertheless, considering the current situation in Georgia, with a large variety of affected groups, the inclusion error need not be as high as in normal circumstances. As previously noted, due to the lockdown, the number of vulnerable groups will have increased substantially.
Unlike targeted support schemes, there is limited practical evidence behind the implementation of universal programs (Banerjee et al., 2019). However, some of the impacts can be identified from existing pilot case studies, impact assessments of existing targeting schemes, and an analysis of theoretical knowledge. The key here is that the expected impacts depend substantially on the duration and type of the support scheme (i.e. direct cash transfers, provision of vouchers or coupons, tax credit).
For our purposes we assume that the duration of the support scheme will be relatively short-term (related to the length of the lockdown). Furthermore, there is nearly no practical evidence on the impact of the long-lasting universal support schemes (Banerjee et al. 2019). Theoretically, long-lasting universal support can have a negative impact on labor force participation. Moreover, Banerjee et al. (2017) finds no evidence that unconditional transfers discourage work. Considering the characteristics of the crisis, labor market participation is already limited because of the lockdown.
In addition, direct unconditional cash transfers could serve the progressivity purpose well, as households in greater need will receive a larger portion of their income, compared to those who require less assistance. Progressivity will depend on whether the recipient of a cash transfer is a household or an individual. Providing a cash transfer to households might have a disproportionate impact on larger households, requiring them to sustain themselves with less money per capita. Another important point to consider is whether money should be provided to everyone or only to the working age population (those above 15 years of age).
Coupons and Vouchers vs. Direct Cash Transfer
The type of support scheme can have a substantial influence on its impacts from the welfare and macroeconomic perspectives. One form of support scheme is the provision of vouchers or coupons to help households with utility payments or to purchase essential goods. Utility vouchers will disproportionally support more well-off households that use more appliances. The universality of such vouchers is also questionable, as some households are not connected to the utility networks (for instance the natural gas network), and thus will not benefit at all from vouchers. Considering the situation, the positive impact of vouchers is that during such a lockdown utility companies will not face liquidity problems that may otherwise arise from increased delinquency rates.
On the other hand, cash transfers allow recipients to rationalize between the consumption of different types of goods. As opposed to the provision of coupons and vouchers, transfers could further increase welfare by allowing individuals to self-rationalize (Ghatak & Maniquet, 2019).
A Review of Social Support Programs Internationally
In this section, we discuss various governments’ (Table 2) social protection measures during the Covid-19 crisis. The actions taken cover the different functions of social protection, such as unemployment benefits; special social assistance or direct cash transfers; wage subsidies; deferrals of tax payments; pensions and pension fund adjustments; sickness and childcare benefits; etc.
In order to promote income security and stimulate aggregate demand, several countries have introduced either universal or quasi-universal direct cash payments (e.g. Australia, Hong Kong, Singapore, Serbia, Greece, the US). In order to further ease liquidity constraints on individuals and enterprises, some countries have announced the deferral of certain tax payments, social security contributions, rent, and utility payments (e.g. Bulgaria, Estonia, Spain, Canada). In addition, several governments are providing grants and wage subsidies to SMEs, start-ups, and other hard-hit businesses to avoid the drop in revenues and safeguard employment. In most cases, these measures were supplemented by extended unemployment benefits.
Table 2: Covid-19 social protection measures, by country
|Central, South, and Eastern European Countries||Certain Social Protection Measures Taken
|Hong Kong, China||
|United States of America||
Source: Policy Responses to Covid-19, IMF policy tracker, April 2020; Social protection responses to the Covid-19 crisis, ILO, March 2020; Countries’ public announcements of Covid-19 economic responses.
Alternative Policy Options
Considering the existing social challenges, policy objectives, and possible alternatives implemented around the world, we propose the following five policy options:
Option 1 – Targeted Assistance
Considering the current situation in Georgia, the state’s capacity to implement a targeted exercise is extremely limited. This is largely due to the lockdown and the complexity of matching the current economic challenges and general characteristics of target groups. One way for the government to target different groups would be to use its administrative resources and revenue service databases to identify affected unemployed people no longer receiving salaries. However, using these resources, it will be hard to identify the majority of self-employed and informal workers who have also lost their income (fully or partially) and are facing hardships; examples of these individuals may include a small business owner working at the Eliava construction materials market, a self-employed tourism sector worker, a domestic worker – a nanny or cleaning lady, etc. Under normal circumstances, such individuals do not require any social assistance, however due to the lockdown they may not have enough cash inflow to sustain their families.
Furthermore, targeted assistance can create perverse incentives for some employees. Depending on the amount of the assistance, employees (that are still allowed to work) whose net salaries are close to the assistance threshold, might be discouraged from work. For example, if targeted assistance is 200 GEL, a grocery store worker with a gross salary of 300 GEL might prefer to leave their job temporarily (as unpaid leave for example).
Furthermore, the government could target following socially vulnerable groups that are easier to identify, such as:
- Receivers of targeted social assistance, adults – 297,094 individuals;
- Receivers of targeted social assistance, under 18 – 161,374 individuals;
- Pensioners – 765,911 individuals.
Providing additional support to these groups will mean indirectly covering some self-employed individuals and informal workers. Many of such socially vulnerable groups work informally or are self-employed. Furthermore, some individuals could potentially have family members that are either informally or self-employed.
To calculate the total number of people subject to the targeted scheme, we consider the above listed individuals and add the group of hired employees that may lose the job or may have to take unpaid leave. Based on our estimates, around 200,000 hired workers may lose their income. Adding this to the number of TSA recipients (458,468) and pensioners not receiving TSA payments (692,431) brings the total number of beneficiaries of a targeted assistance scheme to 1,350,899 individuals. Assuming, 150 GEL in assistance per adult, and 75 GEL for under 18s, this will bring the cost of targeted assistance to approximately 191 mln. GEL per month.
Option 2 – Income Tax Breaks
The second policy option to consider is a variation on a tax break (tax credit, lowering income, or other taxes). Such an assistance mechanism will not be universal and only benefit the taxpayers. Furthermore, it is not a fact that tax relief will be transferred from employers to employees. Thus, essential social assistance may not be provided to a large proportion of the population. In addition, due to the lockdown, opportunities for investments have shrunk and hence, most tax saving will not influence economic growth. Finally, a decrease in tax rates will create additional pressure on government revenues, already negatively influenced by the lockdown, which may potentially create fiscal problems.
Aside from the costs of tax breaks, one should also bear in mind that this policy option is only intended for income tax payers who managed to retain their jobs. In an optimistic scenario, about 200,000 of hired employees will be left jobless, thus, about 640 thousand people will be aided by tax breaks. If income tax for all these employees would be reimbursed, the cost of tax breaks would amount to approximately GEL 136 mln. (monthly). It should also be mentioned that if companies are not paying income tax to the government, they might fail to reimburse this money to their employees, leaving some people without any assistance.
Option 3 – Unconditional Universal Cash Transfers
The third policy option is unconditional universal cash transfers. In this case, the government would make an unconditional cash transfer to every member of society. From a practical perspective there are two important questions to be answered: (i) should cash transfers be provided to individuals or to households?; and, (ii) should cash transfers only be made to the working age population or to children as well?
To minimize the potential negative consequences stemming from the possible negative gender impacts, individual payments are the preferred system. This may be as men are more often than not considered to be heads of their households, and if assistance is household-based women may not be able to take full advantage of it.
Furthermore, to ensure the progressivity of a universal cash transfer, it should not be limited to the working age population. A common approach would be to give guardians of children a decreased amount of a standard Universal Basic Income (UBI) payment (Ghatak & Maniquet, 2019). The progressivity of such a scheme is an important advantage, as it ensures support to those people who are not participants of the labor market and dependents of employed family members. Thus, the universal system helps mitigate the substantial indirect impacts on poverty resulting from job losses.
A major drawback of the unconditional universal cash transfer is its expense. This is primarily due to the large inclusion error, which accompanies this system by its very definition. However, alternatively, in a targeted program the vast majority of the affected self-employed and domestic workers (in total, close to 50% of all employment) are nearly impossible to identify. Furthermore, due to the lockdown, the potential group under risk of impoverishment is greater than under normal conditions. Consequently, compared to a perfectly targeted system (without any inclusion or exclusion errors) an unconditional universal cash transfer would be only marginally costlier.
However, with imperfect targeting, an unconditional cash transfer would be substantially costlier compared to targeted assistance. Assuming 150 GEL assistance for all working age population (2,968,964 individuals) and 75 GEL for children (754,500 individuals), the total cost of unconditional universal cash transfers would be 502 mln. GEL per month.
Option 4 – An Opt-out/Opt-in Unconditional Universal Transfers
As previously mentioned, the significant cost of a universal support scheme is a notable challenge, particularly because budgetary fiscal pressure is already high due to decreased economic activity and tax revenues. Thus, implementing a potentially costly assistance program will be hard from a public finance perspective. To partially alleviate this problem and decrease the inclusion error of universal cash transfers, the government could implement it in the following ways:
- The government could offer unconditional transfers to all individuals whose income is impossible to identify, while providing an opt-out option in case they do not deem the assistance necessary (for example, individuals and their families with savings or those unaffected by non-labor income);
- The government may assist employed workers based on their income using the following two principles:
- Offer assistance using an opt-out option to everyone whose income is below a certain threshold (for example, 700 GEL gross salary for the month of March);
- Offer assistance using an opt-in option to everyone whose income is above the threshold.
Opt-out/opt-in universal cash transfers have the potential for governmental savings. To evaluate the expected cost of this option we assume that half of all employees (i.e. 430,000) with a salary of over 700 GEL gross would opt-in into the system. In this case, the total cost of opt-out/opt-in universal cash transfers would be up to GEL 470 mln. Furthermore, in the better-case scenario, where no employees with a gross salary over 700 GEL would opt-in into the system, the total cost of the cash transfer scheme would be up to GEL 437 mln. Thus, our expected cost of the opt-out/opt-in universal cash transfer will be an average of GEL 454 mln.
Option 5 – Conditional Cash Transfers
To decrease the fiscal pressure associated with unconditional universal cash transfers, the government could use relatively simpler methods to minimize inclusion errors in the system. In this case, the government could potentially exclude employees who may not face an urgent need for assistance. Firstly, the government could exclude individuals who received an income of over 40,000 GEL in 2019 from the program. Secondly, those workers with an average monthly income of 1,200 GEL in 2020 could also be left outside the assistance scheme. This will allow the government to limit the inclusion error of the cash transfer system, while keeping similar overall impacts.
We evaluate the expected cost of the conditional cash transfer assuming 30% of the hired workers (258,048) having monthly income above 1,200 GEL. Based on the same population data, as for calculation of the cost of the unconditional cash transfer, the expected cost for conditional cash transfer will be roughly GEL 463 mln.
Multi-Criteria Analysis of Policy Options
To summarize these options, we have created a multi-criteria assessment of the different possibilities for social assistance using our pre-defined policy objectives. We assess each policy option on a 5-point scale, with 1 representing the worst performance, while 5 showing perfect performance. The overall efficiency of the policy option is a simple average of points in each criterion.
Table 3: Multi-Criteria Assessment of different social assistance systems during Covid-19
|Assessment Criteria||Option 1 – Targeted Assistance||Option 2 – Income Tax Break||Option 3 – Unconditional Universal Cash Transfer||Option 4 – Opt-out/opt-in Unconditional Universal Cash Transfer||Option 5 – Conditional Cash Transfer
|Monthly Cost of the assistance Scheme (mil. GEL)||191||136||502||454||463|
|1. Minimization of Exclusion Error (minimization of impoverishment risk)||3||1||5||5||4|
|2. Minimization of Inclusion Error (minimization of fiscal cost)||4||2||2||3||3|
|3. Ease of implementation||2||5||5||4||4|
|5. Gender responsiveness||3||2||5||5||5|
Summary and Recommendations
In this policy note, we have summarized the potential social impacts of Covid-19 and the subsequent lockdown caused by the pandemic. Our assessment of the sub-categories of employment show that there is a large group of mid to highly affected individuals among the employed populace. Around 30% of hired employees will be significantly influenced, while 22% will suffer a medium impact. The impact on the self-employed will also be substantial, roughly 15% of the group will be highly affected, where 84% of self-employed individuals will feel a medium impact from the lockdown. The impacts are also disproportionate from a gender perspective, posing a risk of unemployment-driven assistance benefitting men more so than women.
Having reviewed international responses to the Covid-19 crisis from 17 selected countries, the evidence compiled has helped to form possible designs for a social assistance program. We believe that direct cash transfers to individuals are preferable to providing assistance for the purchase of specific goods or services, as individuals can self-rationalize.
Our multi-criteria assessment shows that an opt-out/opt-in unconditional universal cash transfer is marginally better compared to other universal cash transfer schemes. It has the best performance in minimizing the risk of impoverishment. Furthermore, our analysis shows that under the current conditions, the government’s ability to correctly design a targeted program that is able to reach all affected individuals is limited. This is primarily due to the relatively high percentage of self-employed on the Georgian labor market. Consequently, a targeted program would have a limited impact on minimizing the risk of impoverishment. This is even more true for possible tax breaks. The greatest merit of a targeted program is that it imposes less fiscal pressure and is thus substantially less costly compared to a universal support scheme.
Annex 1 – Comparison of Sectoral Impact Assessments by ILO (globally) and ISET-PI (for Georgia)
Annex 2 – Summary of the assumptions used for calculating costs of different support schemes
|A||Working Age Population (>15)||2,968,964|
|B||Population Below Working Age (<15)||754,500|
|D||Total Hired Workers||860,161|
|E||Hired Workers with salary above GEL 700||430,081|
|F||Share of hired workers with salary above GEL 1,200||30%|
|G||Total number of hired workers who lose labor income||200,000|
|H||TSA Recipients (>18)||297,094|
|J||TSA Recipients (<18)||161,374|
|K||Cash transfer per adult (GEL)||150|
|L||Cash transfer per child (GEL)||75|
-  ILO Monitor 2nd edition: COVID-19 and the world of work, April 2020.
-  NACE 2 classification system, 4-digit level
-  Based on the Labor Force Survey, Geostat (2018)
-  One has to note that the working environment for frontline health workers has changed and they are exposed to higher health risk and psychological stress, which regardless of relatively stable labor market positions makes them more vulnerable physically and psychologically.
-  For example, more women live in poverty as demonstrated by the fact that 55% of social assistance recipients are women.
-  Hanna, R. & Olken, B. (2018). Universal basic incomes vs. targeted transfers: anti-poverty programs in developing
- countries. J. Econ. Perspect. 32(4):201–26.
-  Klasen, S. & Lange, S. (2016). How narrowly should anti-poverty programs be targeted? Simulation evidence from Bolivia and Indonesia. Discuss. Pap. 213, Courant Res. Cent., Göttingen, Ger.
-  Banerjee, AV., Niehaus, P. & Suri T. (2019). Universal basic income in the developing world. Annu. Rev. Econ. 11:961–85.
-  Banerjee, AV., Hanna, R., Kreindler, G. & Olken B. (2017). Debunking the stereotype of the lazy welfare recipient: evidence from cash transfer programs. World Bank Res. Obs. 32:155–84
-  Ghatak M. & Maniquet F. (2019). Some theoretical aspects of a universal basic income proposal. Annu. Rev. Econ.11.
-  For the purposes of this policy option we will concentrate solely on income tax breaks.
-  These scenarios do not consider additional potential saving from individuals with an opt-out option utilizing this opportunity.
This policy brief was first published as an ISET policy note on April 17, 2020 under the title “The Social Impacts of COVID-19 – Case for a Universal Support Scheme?”.
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.