The Impact of COVID-19 Income Supports on Earnings

[Disclaimer: This blog represents my personal views and not those of the Central Bank of Ireland or the European System of Central Banks.]

Last week, the CSO released the latest in its Insights from Real Time Administrative Sources series on the “Impact of COVID-19 Income Supports on Employees”.  Using administrative data on employee earnings and COVID-19 support scheme payments (PUP and T/EWSS), it tracks the individual gross weekly earnings of matched cohorts to Q4 2020 (‘matched cohort’ means the CSO is comparing the (median) earnings of same group of individuals year-on-year).* 

For policy makers deliberating the future of COVID supports (PUP and WSS), the information in the release provides several useful insights.** I highlight three aspects in this post: (i) the strong earnings growth of non-recipients of supports throughout 2020; (ii) the diverse earnings experience of different demographic and income groups; and (iii) the different earnings growth experienced by PUP versus T/EWSS recipients, which, for the first time, is shown separately in this release.  Some more details on each below.

For non-recipients, earnings grew strongly throughout 2020
One of the most striking observations is the strong growth in earnings for non-recipients of either PUP or T/EWSS, as shown in Chart 1 below.

Note: A recipient is defined as an employee who received at least one payment of either PUP or WSS during the quarter. All the comparisons are of growth in the median. The median is the mid-point in the distribution of the level of earnings, i.e. half of earners in a given group earn more, half earn less.

The fourth quarter, with year-on-year earnings growth of 7.1%, is particularly strong for non-recipients (as we already knew from the previous release to Q3, the group of all recipients experienced large falls in earnings in 2020). Year-on-year growth for the bottom 20% per cent of (non-recipient) earners was over 21% in Q4 (see Figure 1.5 in the release). The release notes that this increase is mainly among younger age groups, and workers in the wholesale & retail and health sectors. Some of this likely reflects the steep slope of the age-earnings profile for younger workers, and also perhaps longer hours worked during the pandemic. However, the CSO also notes that it reflects individuals changing jobs during the pandemic, which could point to more permanent effects on the level of earnings.

But it is not just at the bottom where we see earnings growth for non-recipients. We see growth right across the distribution. For example, the top-20% of (non-recipient) earners registered growth of 4.7% in Q4 2020. In fact, the combination of strong growth with the size of the non-recipient group (75% of employees in Q4), puts growth for the median of all workers (i.e. non-recipients plus recipients) in positive territory in Q4 (+4.6%). This is a remarkable outturn for the year that was in it. As highlighted in this piece with Tara McIndoe-Calder in March, the fact that average household incomes actually grew during 2020 is one of the reasons for the large jump in savings we saw during the year.

The earnings growth of recipients differs significantly across demographic groups
Reflecting the concentration of shut-downs in face-to-face services and some retail sectors, we know that the pandemic has affected the employment of some groups more than others, notably females, lower paid and younger workers (see, for example, this recent speech by Deputy Governor Sharon Donnery).  However, when we look at earnings growth, and including supports, the same groups tend to be the least affected during 2020 (see Table 1 below, which is based on Table 1.2 in the release).  The fact that some groups fare less badly reflects, in part, the level of supports relative to pre-pandemic earnings. We know, for example, that younger and female workers generally work fewer hours during the week (i.e. part-time), and tend to work in lower-paying sectors.  So, these are almost like ‘reference effects’. Note that the CSO analysis is of gross earnings, i.e. before income tax, and there may be future tax liabilities for some recipients where supports were not taxed at source.

One thing we do not see in the Q4 data – at least for growth at the median – is much evidence of an impact from the change in payment rates from mid-October onwards, when payments were more closely aligned to pre-COVID gross earnings. In my paper with Brian Cahill (CSO) from February, when we only had data to Q3 2020, we thought this could change income for some groups. But we do not see it in this release. As the payment could have both risen for some (the top rate increased to €350) and fallen for others, it could be washed out in the median, and we would need to dig down to the individual data to see it.  The Christmas Bonus, when there was additional PUP payment in December, could also be a factor.

Very different earnings growth by type of support and demographic group
The release provides, for the first time, a breakout of earnings growth (plus supports) for the two different types of supports, PUP and T/EWSS***. Whilst I focus on earnings here, the update on numbers receiving various supports released last week is also relevant.  

In Q2 and Q3, earnings for PUP (only) recipients fell by around 5% (for the median), less than half of the fall for T/EWSS recipients (Chart 2, below). So, even with employer top-ups, the gross earnings of (all) wage subsidy recipients fall a lot during this period (at the median). The one positive is that by Q4 both groups’ earnings were back at around Q4 2019 levels.   

Focusing on all recipients misses some of the variation within demographic or regional groups (Charts 3-5). For some workers – like males, older workers and workers in Dublin – wage subsidy recipients fare ‘better’ in terms of earnings growth, than PUP recipients in these groups. I say ‘better’, but in all quarters, earnings plus wage subsidies are still significantly lower than pre-COVID earnings for these sub-groups.

In contrast – for females, younger workers and workers outside of Dublin – PUP recipients fare better than wage subsidy recipients, and, in almost all quarters, earnings plus PUP are higher than pre-COVID earnings (although this is less so the case for the non-Dublin group).  For wage subsidy recipients in these sub-groups, earnings in Q2 and Q3 are below pre-COVID levels (except for under-25s), before recovering somewhat in Q4.

The timing of different health restrictions, and specifically which sectors were closed and when, likely explains some of the differences we observe between certain groups. For example, the closure of construction, with higher earnings on average and more male workers, could explain some of the gender differences we observe (this is also related to the ‘reference effect’ I mentioned above).  Related to this, we also need to be careful about comparing medians across individual quarters, as the composition of matched cohorts varies from quarter-to-quarter, as shown in Table 1.9 in the release.

Conclusions
With the above caveats in mind – plus the fact that this is aggregate data, albeit medians for specific groups – these patterns point to at least two important considerations when considering the future for these supports as the economy re-opens.

First, and most obviously, not all workers will be affected equally by changes to PUP or wage subsidies.  Taking PUP as an example, changes to the scheme as different sectors reopen could impact younger, female and, to a lesser extent, workers outside Dublin more.

Second, and related to the first point, for some recipient groups median earnings increase during 2020, notably PUP recipients. Therefore, whatever changes are made, and at what speed, could have a bearing on work incentives and labour supply.  I am not saying that workers on PUP do not want to return to work, but rather we should pay close attention to the literature and evidence on how unemployment benefits affect unemployment (see, for example, this recent paper on youth unemployment duration and unemployment benefits by Maynooth economists Aedin Doris, Donal O’Neill and Olive Sweetman). Furthermore, labour supply is a multi-dimensional issue, of which pay is just one. In the current context, other factors like the spread of the virus, migration (and how the pandemic affects cross-border flow of workers), caring responsibilities and health concerns also play a role.

Notes: (*) Average weekly earnings are estimated by summing all earnings during the quarter and dividing by weeks worked in the quarter. (**) Revenue pays the wage subsidy (T/EWSS) directly to qualifying employers who then pay employee wages. So, formally, it is a support for employers. For convenience, I refer to it broadly as an ‘income support’ in this post. (***) The release also provides data on the earnings growth of a third group: employees who receive both PUP and T/EWSS during a quarter (but not necessarily at the same time). This group accounts for around one-in-five recipients in Q4. For a clear comparison between the experience of recipients on the two types of supports, I omit this third group here.

I thank, without implicating, Brian Cahill (CSO) for answering my many queries about the data in the release.

2021 Economic Letters from the Central Bank

Volume 2021 of the Central Bank’s Economic Letters series has seen a set of interesting contributions across a range of topics so far this year. The Economic Letters published to date are:

The effects of the 1ST COVID 19 lockdown and re-opening on sales in Irish customer-facing businesses.

Guest post by Eoin O’Leary, Emeritus Professor of Economics, Cork University Business School, UCC.

Introduction

There has been vast media coverage on the effects of the COVID 19 pandemic on the Irish economy, most of which has been speculative as the struggles of workers, businesses and government has been ongoing. Yet the recent publication of the monthly Retail Sales Index (https://www.cso.ie/en/statistics/services/retailsalesindex/) and the Monthly Services Index (https://www.cso.ie/en/statistics/services/monthlyservicesindex/) for October provides a fascinating insight into how sales in customer-facing businesses in 21 retail and market services sectors have been affected by the pandemic since the beginning of 2020.

These sectors, which employed 1.1 million workers in the Republic of Ireland in 2019, have been directly affected by the sudden onset of the first lockdown of many shops and services enterprises in March, followed by graduated re-openings with social distancing measures and increasing reliance on remote access for customers.

The period January to October 2020 is ideal for investigating the 1st wave of the pandemic, as it covers the first lockdown in March and the subsequent re-opening during the summer before the 2nd lockdown on 19th October 2020. The sectors being investigated are major contributors to the Irish economy. Together they employed over 1.1 million workers in 2019, which represents 49% of total employment in the state.

The first key date in the timing of the response to the pandemic was the government-imposed lockdown starting on 27th March. Apart from retail enterprises involved in food, fuel and pharmacy (ie Food, Beverages and Tobacco in Supermarkets; Food, Beverages & Tobacco in Specialized Stores; Fuel and Pharmaceuticals, Medical & Cosmetic Articles) which remained open throughout 2020, all other retail sectors closed from this date with some providing remote access for customers. This was followed by a graduated re-opening (with social distancing measures continued) from June to mid-October. There was variation, with for example Bars (not selling food) being closed until September 21st, while mainstream non-food retailing (ie the remaining 8 retail sectors) re-opened from June 8th.

In market services, food and accommodation services (ie Accommodation and Food Services Activities) were closed from 27th March and re-opened on June 28th. There were differences within the remaining sectors. For Wholesale Trade those businesses involved in food, fuel and pharmaceutical distribution would not have been significantly affected during the 1st lockdown, while non-food retailers would have experienced a downturn. For Transport and Storage, passenger transport was severely curtailed while, anecdotally, there is evidence that courier services prospered. The other 4 sectors (ie Information and Communication; Professional Scientific and Technical Activities; Administrative and Support Services Activities and Other Business Services) were influenced by having to serve customers almost exclusively via remote access.

The Data and Method

Table 1 shows detailed descriptions of the sectors covered and their 2019 employment levels. For the Retail Sales Index, sales from a sample of 1,700 enterprises of varying sizes are collected each month across 13 sectors and indices generated. In addition to sales, in relevant sectors, data are collected on the % of sales from online sales of enterprises with a presence in Ireland. This source provides very detailed and comprehensive coverage of businesses of all sizes in retailing, accounting for 253 thousand persons engaged in 2019 (22% of the 1.1 million covered in the paper). One exclusion is that the index does not cover the retail trade of food and non-food via stalls and markets.

For the Monthly Services Index, sales from a sample of 2,250 enterprises with more than €20 million sales and more than 100 persons engaged is collected.  In addition to the index only covering these larger enterprises, the 8 sectors are more broadly defined than retail (see Table 1).  These sectors covered 876 thousand persons engaged or 78% of the total in 2019.  Notable exclusions from this series are financial and insurance activities; public administration; education; human health; creative arts, music and entertainment activities.  Together, both indices provide interesting insights into a substantial portion of the Irish economy that has been most affected by the pandemic.                      

In order to estimate the effect of the pandemic on each of these 21 sectors from January to October 2020, the actual monthly value index is compared to what the index would have been if no pandemic occurred.  The latter is estimated using a simple model which first estimates the trend of the value index for each sector, calculated over the previous 5 years, for the 9 months starting in February 2020.   This month is taken as the beginning of the pandemic because there is evidence, especially in food retailing, that customer behaviour shifted during that month when it became clear that a lockdown was imminent. 

The trend is computed using the average annual percentage change in the seasonally adjusted value index from January 2015 to January 2020 which is applied to the February to October 2020 indices.  It then adjusts the resultant series for each sector by monthly seasonal factors.  These are derived by dividing the seasonally adjusted index by the unadjusted value index for February 2015 to October 2019 and calculating the average seasonal factor for each of the 9 months over these 5 years (see https://www.cso.ie/en/statistics/services/).  The resultant seasonal factors are then applied to the estimated trend from February to October 2020. 

The effect of the pandemic is assumed to be the difference between the estimated trend with seasonal variation and the actual unadjusted value index for each of the 9 months being analysed.  It is assumed that the pandemic is the chief irregular component effecting the sales indices in these 21 sectors.  There can be little doubt that it was by far the most significant abnormality that prevailed during 2020.

The Findings

Overall, of the 21 sectors investigated, actual monthly sales are estimated to have been down in 16 sectors, with 5 either unchanged or doing better than they would have if there was no pandemic.

  • By far the most negatively affected were Accommodation Services, which relates to hotels and other kinds of accommodation, down a massive 72%, and Bars down 58%.
  • Other very large declines were in Transport and Storage (-37%); Books, Newspapers and Stationery (-32%); Clothing Footwear and Textiles (-30%); Fuel (-25%); Food Services, which includes restaurants and cafes (-24%) and Department Stores (-23%).
  • 7 sectors were down between 3 and 18%, namely: Furniture and Lighting (-18%); Motor Trades (-12%); Administrative and Support Services (-11%); Professional, Scientific and Technical Services (-10%); Wholesale Trade (-8%); Other Retail (-7%) and Electrical Goods (-3%).
  • 2 sectors were unaffected, namely Information and Communication and Pharmacies.
  • Notably, 3 sectors experienced higher sales than they would have experienced without the pandemic.  These were predictably Specialized Food Stores (+11%), and Supermarkets (+7%) and, perhaps less predictably, Hardware, Paints & Glass stores (+9%).

Figures 1–21 present detailed graphs of the actual value index for each sector from January to September 2020 and the estimated trend and seasonal variation, using the simple model described above.  The base is January 2020 = 100 to facilitate comparison between sectors. The average monthly difference in percentage terms between the estimated and the actual is presented under the heading of each graph, to signify the magnitude of the effect of the pandemic.  This magnitude is used to determine the order in which sectors are presented, beginning with those whose sales are down the most due to the pandemic and ending with 3 sectors whose sales improved in the pandemic.  The commentaries beside each Figure bring out the highlights with suggestions of possible explanations. Where available the trends in the % of sales from online sales are included in the commentaries for retail sectors.

Concluding Comments

These findings provide fascinating insights on the effect of the COVID 19 pandemic on the sales performance of Irish customer-facing businesses in 21 sectors during the 1st lockdown and subsequent re-opening in 2020.  Three points are worth making in conclusion: 

Contact email: eoin.oleary@ucc.ie.  The author would like to thank Eleanor Doyle and Owen O’Brien for discussions that inspired this work. 

The Fiscal Response to COVID-19

Here’s a useful paper from the Department of Finance summarising the fiscal response to date to the pandemic: https://www.gov.ie/en/publication/84a0c-taking-stock-the-fiscal-response-to-covid-19/

There’s lots of interesting material in it. One such piece is this comparison of deficits for 2020 and 2021 in the euro area.

https://www.gov.ie/en/publication/84a0c-taking-stock-the-fiscal-response-to-covid-19/