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. 

Some recent and historical developments in Corporation Tax

Two pieces for the Irish Examiner this week that look at some developments in Corporation Tax.

First, on changes in royalty flows as a result of the practical ending of “double-irish” type structures and second, on Apple’s 40-year presence in Cork and the taxation of its profits.

Changes in earnings during COVID-19

Disclaimer: this post represents my own views and not those of the Central Bank of Ireland

Two recent CSO releases shed light on the evolution of earnings in the first three quarters of 2020.  Alongside employment and hours, understanding the impact of COVID-19 on earnings tells us how household incomes are affected by the shock.

In previous work, using data from the Financial Crisis, we found that earnings in Ireland were sensitive to economic conditions, notably changes in the unemployment rate. The workers most exposed to lower pay when labour demand falls are those with weaker bargaining power.  For example, in our paper we focused on the lower wages of new hires during the last crisis.

When looking at changes in average earnings, such as from the CSO’s Earnings and Labour Costs release, it is important to take account of changes in the composition of employment. For example, if changes in employment are concentrated amongst lower paid workers, average earnings could rise when there is a negative aggregate demand shock. In a SSISI paper in 2012, Kieran Walsh showed that these compositional effects can be large. The CSO also noted the potential for compositional effects in the context of COVID-19 average earnings changes.

Tracking the earnings of the same workers in the same jobs can remove some of these composition effects, giving a clearer picture of underlying wage developments.  The CSO does something close to this in its Labour Market Insight Bulletin 4/2020, showing changes in average gross weekly earnings conditional on workers being in employment in Q1 and Q3 2020. Earnings includes wage subsidies, where applicable, but exclude PUP payments.

The chart below, from the data in the CSO Bulletin, shows that for all sectors earnings fell by almost 4 per cent for workers in employment in Q1 and Q3. In some sectors, like Administrative & Support Services and Financial, insurance & real estate the changes are double-digit. In others, like Construction and Accommodation & food, earnings are up.

Source: CSO (2020, Figure 5).
Notes: Gross weekly earnings, percentage change (nominal)

For comparison, during the financial crisis, and controlling for composition effects, average weekly nominal pay also fell by around 4 per cent, most of it between 2008 and 2009 (Lydon & Lozej, Table 2). At that time, the declines were largest in sectors connected to property market, like construction and real estate.  The emphasis on nominal pay is important. Between 2008 and 2010, prices (CPI) also fell sharply, by over 5 per cent.  This helped offset the fall in nominal earnings, cushioning the impact on households’ purchasing power.  Price levels have fallen in 2020, by around 1.5 per cent, which suggests a fall in real earnings in the first three quarters of the year of around 2.5 per cent.

… changes in earnings positively correlated with labour demand, but important to control for hours

The changes in earnings between Q1 and Q3 are generally positively correlated with changes in labour demand, such as changes in employment or job postings.  There are some notable exceptions like Accommodation & food – where employment fell by over a fifth, but average earnings rose marginally, by 0.4 percent; or Industry, where employment grew by 2.4 per cent, but average earnings fell by 6.4%. 

Despite conditioning on workers in employment in Q1 and Q3, there are likely still many factors affecting earnings dynamics that are not picked up in the conditional averages. One example is hours-worked. As weekly earnings are the product of hours worked and hourly pay, higher or lower earnings could be due to higher or lower hours. This could matter in sectors with seasonal hours, like Accommodation & Food services.

To get at the the change in hours worked, and for a sample broadly aligned to the administrative earnings data, the CSO provided me with average actual hours worked by sector for employed persons interviewed in Q1 and Q3, from the LFS. I use this data to back out change in average hourly pay as the change in weekly earnings minus change in weekly hours worked.  Readers should note that earnings data is from administrative sources (including wage subsidies), whereas the hours data is from a survey.  Furthermore, the two matched LFS samples are six months apart and may not be exactly representative.

The chart below shows the data. The line in the chart is the change in average gross weekly earnings, corresponding to the bars in Chart 1. Whilst there are offsetting increases in hours in several cases, they are usually small. Furthermore, the direction of the change in hourly pay and earnings is roughly the same for most sectors, with the notable exception of Accommodation and food services. In fact, the increase in hours worked (10.5%, an increase from 32.1 to 35.5 hours per week) offsets a large fall in hourly pay (minus 10.1%).  This fall in hourly pay is more closely alinged with the fall in demand (employment and job postings) that we have seen during COVID-19.  Looking at the historic LFS data, it is clear that this hours increase in Q3 is not unusual. In fact, it is entirely predictable: the historic Q1 to Q3 change in hours is almost exactly the same as the 2020 figure, at 10.3 per cent.

Source: CSO (2020, Figure 5) and LFS actual hours worked by sector

The third chart below shows the correlation between the estimated change in hourly pay (conditional on working in Q1 and Q3) and the change in job postings by sector from Indeed.  Job postings are generally a good indicator of labour demand, and, whilst postings are down across the board, we find that sectors where postings have declined the most have generally see larger falls in hourly pay.

Source: Own calculations using CSO data. Job postings data from Indeed.

It should be said that three quarters of data is a relatively short time period. Added to this is the fact that the COVID-19 shock has generated a very high degree of uncertainty. For firms in some sectors – such as exporters, industry or multinationals – the demand shock may may turn out to be less bad than initially feared. This might help explain negative earnings growth for workers in Industry, but positive employment growth.  It is quite possible that in Q4 or Q1 2021 we may see a strong earnings growth for some sectors as employers unwind pay freezes that were put in place early-on the crisis.

looking ahead

By combining administrative and survey data in novel ways, the CSO provides timely and granular insights on the COVID-19 labour market. This is crucial information for understanding the impact of the shock, and how policy might help mitigate it.

The decline in earnings in 2020 for employees working in both Q1 and Q3 is similar to falls seen during the last recession, albeit with a different sectoral pattern. There are other differences this time around. The most significant difference is the large and decisive policy response to COVID-19 – both fiscal and monetary. In November, over a quarter of workers were supported by Pandemic Unemployment Payments or Wage Subsidies. Furthermore, the government has committed to these supports remaining in place while restrictions remain in in place. Another important difference is healthier state of household balance sheets going into 2020, a factor which dragged on domestic demand during the last recession.

If the spread of the virus can be brought under control in 2021, this points to a potentially shorter duration shock than before. However, the longer restrictions continue, the greater the potential for behaviour to change – like less business travel or less bricks-and-mortar retail, for example – and the harder it becomes for some businesses to reopen. This would lead to permanent job losses, even after restrictions are lifted. Furthermore, if employment and (real) earnings shocks persist, there is greater potential for precautionary savings, with negative feedback loops for domestic demand. The fact most people who have experienced reduced employment or been laid off due to COVID-19 said they expected to return to the same job suggests a widespread perception of this as a short-term or temporary shock – albeit this was in Q3, before the most recent Level 5 restrictions.

Related to this, in services – the sector most affected by the shock – turnover picked up sharply during the summer easing of restrictions. Although some sub-sectors, like travel and accommodation remained far below pre-COVID levels. Job postings in services track tend to track turnover very closely, rising in the summer, before declining again in the move to Level 5.  This suggests that permanent relaxation of restrictions, leading to increased demand, could undo some, but not all, of the labour market damage we have seen in 2020.

On the decline in inequality: a question of emphasis

Robert Sweeney of TASC writes on the decline of inequality in Ireland.

In sum, income inequality, according to the best evidence, has fallen; Ireland, by conventional measures, has the most progressive tax system in the EU; and Ireland has a very high share of low-work intensity households. It is also the case that in historical terms our inequality is high, and differences in living standards have likely increased. Lower income households basically work as much as the rest of society, and the poorest pay almost the same share of their income in tax as the rich. Facts are facts and needn’t be quarrelled with. But there are many ways to present them.

Fiscal Council Webinar Wednesday 2nd December

The Fiscal Council is hosting a webinar on the December 2020 Fiscal Assessment Report, “Sustaining the Economy through Covid-19″.

This is the Council’s 19th Fiscal Assessment Report and comes as the Covid-19 pandemic continues to have a major impact on the Irish economy and public finances. The Report assesses the economic and fiscal consequences and explores a range of possible scenarios to 2025 along with an assessment of the policy consequences.

The twice-yearly Fiscal Assessment Report is the Council’s main publication. It assesses the Government’s budgetary stance, macroeconomic and fiscal forecasts, and compliance with fiscal rules.

The webinar will take place at 2pm Irish time on Wednesday 2nd December 2020.

Those interested in attending are invited to register at: https://zoom.us/webinar/register/WN_H2MmvtM-SYuOY4OPdt4ckQ.