Covid 19 Pandemic Unemployment Payments in the Western Region

 

Continuing our analysis of the economic and social impacts of the Covid 19 pandemic on the Western Region it is useful to look at the number in Western Region counties in receipt of the Pandemic Unemployment Payment (PUP) today, 19th May.

The Department of Employment Affairs and Social Protection has provided a county breakdown for the (PUP) payments , valued at €201.8m, just issued to 585,000 people (of which 252,800 are female and 331,800 are male).  The Covid-19 Pandemic Unemployment Payment (PUP) is an emergency payment for employees and the self-employed who have lost their income and are fully unemployed due to the pandemic. It is paid at a rate of €350 per week into a recipient’s bank account.

While the PUP is the most significant payment, there are also over 54,000 employers who have registered with the Revenue Commissioners for the Temporary Covid-19 Wage Subsidy Scheme (TWSS) with at least one subsidy being paid in respect of over 464,000 people under that scheme (there is no county breakdown available for this).  These payments are in addition to the 214,700 people who were reported on the Live Register as of the end of April[1][2].

 

The Pandemic Unemployment Payment (PUP) in the Western Region

Of the 585,000 in receipt of the payment, 102,800 are in the Western Region.  This accounts for 17.6% of the national total while the Western Region accounted for 16.8% of the Labour Force in 2016 (the most recent data at this level).  The number in receipt of the PUP has fallen slightly (2.2%)  from 598,000 on 5th May (104,900 in the Western Region) as some recipients have begun to return to work and some employers have entered the TWSS.

Figure 1 shows the number of people in receipt of the PUP in the Western Region counties and in Kerry and Limerick, which, along with the Western Region counties, make up the Atlantic Economic Corridor (AEC).  In the Region, Galway (31,800) and Donegal (22,200) have the most people in receipt of the payment, with more than 20,000 people also receiving the payment in Kerry and Limerick.  Leitrim (4,000), Roscommon, (6,900) and Sligo (7,500), the smaller counties, have the lowest number of recipients (and the smallest numbers nationally, along with Longford (4,500) and Carlow (7,500)).

 

Figure 1: Number of people in receipt of Pandemic Unemployment Payment on 19th May in Western Region and AEC counties

Source: https://www.gov.ie/en/news/7fc9de-update-on-payments-awarded-for-covid-19-pandemic-unemployment-paymen/  Appendix 2

 

Clearly the most populous counties have the highest numbers of recipients so it is more useful to consider the percentage of the Labour Force in receipt of the payment.  The most recent available county data on the size of the Labour Force is from Census 2016, and although the national labour force has increased since then, the Census data is used here[3] to allow for a comparison of rates by county (Fig 2).

Nationally (using the 2016 denominator), 25% of the labour force were in receipt of the PUP, but 27% of those in the Western Region labour force were receiving it.  There is very significant variation among Western Region counties, with 31% of the labour force in Donegal in receipt of PUP but only 23% of those in Roscommon (the only Western Region county to be below the state average).  Looking at the other AEC counties, Limerick (24%) is also lower than the State but Kerry, like Donegal, is very high (31%).

 

Figure 2: Percentage of County Labour Force (2016) in receipt of Pandemic Unemployment Payment

Source: https://www.gov.ie/en/news/7fc9de-update-on-payments-awarded-for-covid-19-pandemic-unemployment-paymen/  Appendix 2 and  CSO, Census 2016 Summary Results – Part 2. Table EZ011

 

There is no county breakdown available for the Temporary Covid-19 Wage Subsidy Scheme (TWSS) which some unemployed workers receive instead of the PUP and so it is not clear what influence this would have on these figures.  The importance of different sectors for employment discussed in a previous blog, and in turn the different impact of Covid 19 public health measures on various sectors, all affect the level of PUP payments in each county.

 

Reliance on key sectors

The job losses have been largest in sectors where economic activity is difficult or impossible because of public health measures and social distancing guidelines (the recent Working Paper from the DEASP discusses sectors in more detail)   Three sectors, Accommodation and Food Services  (21.3%), Wholesale and Retail (15.0%) and Construction (13.1%) together account for almost half (49.4%) of all those in receipt of the PUP (Figure 3).

 

Figure 3: Pandemic Unemployment Payments – Sector Breakdown, Payment 19th May.

Source: https://www.gov.ie/en/news/7fc9de-update-on-payments-awarded-for-covid-19-pandemic-unemployment-paymen/  Appendix 2

 

This is in line with the most recent CSO Business Impact of COVID-19 Survey 20 April to 3 May 2020 (published 18th May) which shows that 69.1% of enterprises in Accommodation and Food services ceased trading, either temporarily or permanently while two thirds (66.7%) of responding enterprises in the Construction sector had ceased trading either temporarily or permanently as of 3 May 2020.

The Western Region is particularly reliant on these sectors (as shown in Census 2016) with 12.7% of total employment in 2016 in Wholesale and Retail and higher dependency on Accommodation and  Food Services in the Western Region (6.9%) and Construction (5.4%) than the rest of the state (5.6% in Accommodation and Food; 5.0% in Construction).

While the county data for the sectoral breakdown of the PUP is not available, Figure 4[4] is taken from the recent DEASP Working Paper (PDF 1.7MB) which shows the breakdown of the payments in each county for the week ending 17th April[5].  The importance of the Accommodation and Food Services sector in the Region, and along the Atlantic Economic Corridor, is clear.

 

Figure 4: Pandemic Unemployment Payment- Sectoral Breakdown by County

Source: DEASP Working Paper , May 2020 Figure 6 . Apologies for the poor quality. The key sector of Accom & Food is at the bottom (dark blue), Construction is large blue section in the middle and Wholesale & Retail is at the top (orange).

 

The Accommodation and Food sector is most important along the Western Seaboard , this takes in the five counties (Kerry, Sligo, Clare, Mayo and Galway) with the greatest proportion of those claiming the PUP in this sector. In Kerry almost 30% of those claiming the PUP were employed in Accommodation and Food services, along with more than a quarter of those claiming PUP in Sligo, Clare and Galway, and more than 20% in Donegal, Leitrim and Limerick.  Of the Western Region counties, only Roscommon had fewer than 20% of PUP claimants in that sector.  This is in line with its relatively low percentage in receipt of the PUP (Fig 2 above).

 

Conclusion

While there is variation in the impact of the Covid 19 among Western Region counties, the consequences for the Region as a whole are clearly significant.  As discussed previously  the pattern of employment in the Western Region compared to the rest of the state has both positive and negative aspects in this current crisis.  Higher dependence on Accommodation and Food services means more vulnerability but, in the short term, the greater reliance on public service employment can provide more stability and resilience.

As the ESRI noted, there was an almost total decline in certain types of economic activity from mid-March onwards.    With some working in Wholesale and Retail able to return to work this week (18th May), and more expected form the 8th June, we can expect some decrease in the numbers receiving the PUP in the next payment round but Accommodation and Food services such as cafes, restaurants and pubs will main closed longer.  As many outlets, particularly in the retail, food and hospitality sectors, simply stopped trading and in these key sectors remote working was generally not an option, it is not clear how many of these will be in a position to resume trading when the shutdown period ends.

This series of posts brings together new data and previous WDC analyses and examines them from the perspective of the possible impacts of the Covid 19 pandemic on the regional economy.  The posts aim to develop our understanding of what may be happening at a regional level and what will need to be done in the later phases of the public health emergency and beyond, but they are early interpretations and should be viewed as a work in progress rather than a definitive commentary.

 

Helen McHenry

 

The views expressed here are those of the author and do not necessarily represent or reflect the views of the WDC

 

[1] Department of Employment Affairs and Social Protection  Update on Payments Awarded for Covid-19 Pandemic Unemployment Payment and Enhanced Illness Benefit

[2] Covid-19 Enhanced Illness Benefit is also payable and of the 44,600 people medically certified for receipt 6,900 (15.5%) are in Western Region counties. This payment predominantly relates to applications in respect of people who have been advised by their GP to self-isolate together with a smaller number in respect of people who have been diagnosed with Covid-19.

[3] The Labour Force in the State in Census 2016 was 2, 304,037, while the most recent estimates of the labour force, in Q4 2019 from the Labour Force Survey, was 2,471,700, an increase of 167,663 or 7.3%.

[4] Figure 6 in the DEASP Working Paper

[5] Data on county sectors provisional and subject to revision

Remote Working in Ireland During Covid-19 – Initial Findings from WDC/NUIG Survey

Introduction

The WDC in partnership with Whitaker Institute NUIG has just published initial findings of its survey Remote Working in Ireland During COVID-19, see here. These are the summary results from the national survey of 7,241 individuals across a wide range of industries and occupations over a one-week week period in April-May 2020. This is a very high response, well in excess of the number surveyed for the CSO Quarterly Labour Force Survey. The survey was led by Tomás Ó Síocháin and Deirdre Frost at WDC and Professor Alma McCarthy, Professor Alan Ahearne and Dr Katerina Bohle-Carbonell at NUI Galway.

The survey results show that 87% of respondents are now working remotely because of Covid-19. Over half of those surveyed (51%) had never worked remotely before the Covid-19 pandemic. Of those who had never worked remotely, 78% would like to work remotely for some or all of the time after the crisis is over.

Advantages to Remote Working

  • The top three advantages of working remotely were: no traffic and no commute (76%);
  • Reduced costs of going to work and commuting (55%);
  • Greater flexibility as to how to manage the working day (48%).

Over two thirds say their productivity is the same or higher working from home. 37% of respondents indicated that their productivity working remotely during COVID-19 is about the same as normal and 30% report that their productivity is higher than normal.  25% report that their productivity is lower than normal and 9% of respondents indicate that it is impossible to compare productivity as the demand for products/services/business has changed.

Close to half (48%) say it is easy or somewhat easy to work from home while 37% find that it is difficult or somewhat difficult to work from home.

Challenges to Remote Working

The top three challenges of working remotely included:

  • Not being able to switch off from work (37%);
  • Harder to communicate and collaborate with colleagues and co-workers (36%);
  • Poor physical workspace (28%).
  • Internet connectivity is a challenge to working remotely with close to 1/5 (19%) reporting this as an issue, which highlights the importance of the speedy rollout of the National Broadband Plan.

The challenge of juggling childcare with work commitments was cited as a key issue in the open-ended comments received. The provision of better ergonomic equipment is one of the key changes suggested by employees to help with their well-being and productivity while working remotely.

Remote Working in the Future

The majority (83%) indicated that they would like to work remotely after the crisis is over.  Of these:

  • 12% indicated they would like to work remotely on a daily basis
  • 42% indicated they would like to work remotely several times a week
  • 29% indicated they would like to work remotely several times a month
  • 16% indicated they do not want to continue working remotely.

Those with dependent children aged between 6 and 12 years are most likely to want to continue working remotely following Covid-19.

In a recent WDC blogpost, I noted regional patterns in working from home, pre Covid-19, see here. In this survey while a significant majority of workers across all regions want to continue some type of remote working (83%), even more workers in the West (85.7%) and Midlands (86.8%) want to continue the practice.

Just over half (51%) would like to work from their home, with the balance seeking a mix of home, a hub/work-sharing space and the office. The practice of remote work will be important in sustaining regional and rural communities as well as reducing congestion on key routes.

Of the 16% who do not want to continue any type of remote working, there is a higher share of women (17%) compared to 13% of men. There is also a higher share among those without dependent children, indicating that one of the benefits of remote working is that it helps those juggling work and family life.

Further Analysis of Survey Findings

The results presented in the initial report, publicly available here are just the summary findings. Must more extensive analysis is to be undertaken and this will help inform the future policy direction of remote work generally and how remote work can help as we emerge from the Covid-19 restrictions. The following themes will be explored.

  • Geographic analysis of the 19% who indicate internet connectivity as a challenge.
  • Geographic profile of other challenges, advantages and preferences for remote working post Covid-19.
  • Given the extent to which ‘no traffic and no commute’ was expressed as an advantage, analysis of the data on commute times/distances will be useful.
  • Further analysis of the profile of companies where respondents indicate their organisation or line manager would not support future remote working arrangements.
  • Preference to continue remote working by organisational size, age profile, gender, with dependent children or not.
  • Profile of those who do not want to continue remote working post covid-19.

In addition, the WDC would welcome any suggestions for further analysis.

Future Outlook for Remote Working

In a recent blogpost in relation to remote working, I asked What will be the New Normal? see here. I examined trends in the numbers working from home and how the numbers have changed with changing economic circumstances with an indication that there is a correlation between economic growth and employment levels.

One of the trends seems to be that with a tight labour market, and high employment levels, there are greater levels of working from home. More employees seek the opportunity of working from home especially given the longer journey times associated with full employment and congested transport networks. It is also argued that employers are more receptive to the practice, in part related to the need to retain skilled workers.

However, following the crisis, the unemployment rate is likely to be much higher than pre-crisis levels. How will this impact on the demand for remote working? The results from the WDC/NUIG survey indicate that the demand for continued remote work will continue.

Furthermore, in the short to medium term there will be physical/social distance requirements that will likely impact on the numbers who can return to their workplace. So, it is likely that for a transition period at least, there will be much higher levels of working from home than pre Covid-19.

In future blogposts the WDC will highlight findings from more detailed analyses of the WDC/NUIG survey.

 

Deirdre Frost

May 2020

 

The views expressed here are those of the author and do not necessarily represent or reflect the views of the WDC.

Exploring some potential impacts of the Covid 19 shock on the Western Region – revisiting sectoral employment patterns

The Corona virus pandemic and consequent shutdown is bringing, and will bring, a massive economic shock globally, nationally and regionally, but the detail and scale of the consequences are not yet clear.  There are many unknowns including in relation to its duration, and the speed and extent to which jobs will return once restrictions are lifted.  Nonetheless, it is useful to consider, using available data, how the Western Region may be impacted.

In this short series of blog posts I look at some of our previous analyses of our regional economy and society from the perspective of the potential impacts of Covid 19, so that we can begin to consider areas of priority for support and for stimulation when opportunities once again become available.

Please note that this post was originally published on 30th March, and is being republished now but has not been updated.  The data remains the most recent available and there will be discussion of more recently published analyses of the potential economic, employment and sectoral impacts of Covid 19 in future posts.

An overview of potential national impacts

The Quarterly Economic Commentary  (QEC) recently published by the ESRI (26.03.20) notes that authorities response to the spread of the virus, while absolutely necessary from a general health perspective, will result in millions of jobs being lost globally in the coming weeks and months and a sharp contraction in global economic activity.  They highlight that the swiftness of the economic deterioration is unprecedented in modern times and in many respects exceeds that of the financial crisis[1] (pg 1).

The ESRI examined the impact of the current restrictions on economic life with the assumption that the restrictions are in place over a period of 12 weeks. Under such a scenario the domestic economy would contract by 7.1 per cent and national unemployment increase significantly from 4.8 per cent in February to 18 per cent in Q2 2020 before falling back to just under 11 per cent by the end of the year (pg 2).

In this post I revisit some of the sectoral employment analysis carried out by the WDC insights team in the last few years from the perspective of the current economic shock, highlighting key areas of employment in the region and some potential implications of the crisis.  The data is from Census 2016, collected almost four years ago and while there will have been changes since, it still gives a good picture of sectoral employment patterns in the Western Region.

 

Employment in high level sectors

Differences between the Western Region counties and the Rest of the State[2] in sectoral employment is shown in Figure 1.  In order to make the chart easier to read, some sectors have been grouped together to create these ‘high level sectors’ which give a useful overview of employment characteristics (see foot note for detail of what is included in each high level sector.[3]).

 

Figure 1: Percentage in total employment by high level sector in seven western counties, Western Region and the Rest of State

CSO, Census 2016 Summary Results – Part 2. Table EZ011.  A table is also provided at the end of the post.

Public Services is the largest source of employment in all western counties. It ranges from 32.6% of all jobs in Sligo to 24.6% in Clare.  Public Services includes Health, Education, and Public Administration.[4]  Counties Sligo, Leitrim, Roscommon and Donegal are the four counties in the State with the highest shares of their population employed in Public Services.  In the short term these public sector jobs will provide some employment stability, though employment in the childcare sector, which is included here, has been devastated.

The next largest employment sector in all western counties is Locally Traded Services which includes the three sectors Wholesale & Retail, Accommodation & Food Service, and Transport & Storage.  These sectors are being very significantly affected by the shutdown and may face particular difficulties recovering.

The Western Region is weaker in Knowledge Intensive Services than the rest of the state.  While there will be significant variation, many Knowledge Intensive services (Financial, Insurance & Real Estate, Information & Communications, and Professional, Scientific & Technical activities ) lend themselves to remote working and so employment may be able to continue in this sector during the shutdown.

Industry (largely manufacturing) is the third largest employment sector (see more discussion below).  15.8% of all jobs in Galway are in Industry, with Donegal having the second lowest share (9.2%) nationally.

The relative importance of different sectors varies in the seven western counties, though Public and Locally Traded services are the two largest employers in all.  The dominant role of Public Services in the counties of the northwest shows the relative weakness of private sector activity in the area.  Worryingly, five of the six worst performing counties in terms of employment growth between 2011 and 2016 (the period of recovery from the financial crash), are located in the Western Region.  This vividly illustrates the job creation challenge still faced by the region and the importance of maintaining as many jobs as possible in the next few months.

In terms of the more immediate consequences of the Covid 19 shutdown, the high dependency on public service employment should provide more stable employment in the region in the short term but the lower level of employment in Knowledge Intensive services may make a return to economic growth more difficult.  Some manufacturing, particularly in the medical device sector, may be well placed to benefit from the crisis.

There is more detailed discussion on sectoral employment pattern in Western Region counties in this WDC Insights post.

 

Detailed sectors Western Region and Rest of State

Combining sectors allowed us to see consider the county data more easily.  However, it is important to look at employment in more detailed sectors and their importance in the Western Region to get a better understanding of potential employment consequences.  The two long established patterns of greater concentration of employment (with more employment in fewer sectors) and more reliance on traditional and public service sectors in the Western Region are still evident in 2016 (Fig. 2).

 

Figure 2: Percentage of total employment in each broad sector in the Western Region and Rest of State, 2016

CSO, Census 2016 Summary Results – Part 2. Table EZ011

 

The Western Region’s jobs profile relies more on traditional sectors and public services.  Industry’s share of total employment in the Western Region (13.7%) is considerably higher than in the rest of the state (11%). Manufacturing has consistently played a greater role in the Western Region’s jobs market and this intensified between 2011 and 2016.   The region’s Industry sector has performed very strongly. The high-tech medical devices cluster is a major influence, employing 28% of everyone working in Industry in the region and growing by 30% since 2011.  While many of the jobs in this medical devices sector may be maintained throughout the shutdown, and indeed there is some expansion in response to the crisis, other industrial jobs are more vulnerable.

Agriculture, Health, Education are other sectors that are more important in the region than elsewhere and are ones which are, in the short term at least, less likely to be affected by the shutdown (with the exception of childcare, which is included here).  In contrast, Accommodation & Food service which accounted for almost 7% of employment in the region is likely to lose almost all employment in the short term.

The Knowledge Intensive Services sectors of Financial, Insurance & Real Estate, Information & Communications, and Professional, Scientific & Technical activities are all considerably larger employers elsewhere. Combined, they employ 9.7% of workers in the Western Region, but 16.2% in the rest of the state.

Conclusion

As the ESRI noted (Pg 10), there has been an almost total decline in certain types of economic activity from mid-March onwards. Many outlets particularly in the retail, food and hospitality sectors have simply stopped trading. This will inevitably result in a dramatic increase in the numbers of workers in these sectors being made unemployed. In particular, the wholesale and retail trade and the accommodation and food service activities, which together employed over 65,548 people in the Western Region in 2016 (almost 20% of the 333,919 in employment then), look set to lose a substantial number of workers over a very short period of time.  Supermarkets, some food retailers and pharmacists are, however, increasing employment.

The pattern of employment in the Western Region compared to the Rest of the state has both positive and negative aspects in this current crisis.  Higher dependence on Accommodation and Food services means more vulnerability but in the short term the greater reliance on public service employment will provide more stability and resilience.

Yet the dominant role of public service employment in the region is also an indication of the relative weakness of private sector activity and opportunities.  The region’s slower recovery from the financial crash many mean it is more vulnerable in this crisis

If you are interested in reading more about the economic impacts of Covid 19 and government responses the ESRI scenario for the rest of the year is here.  The OECD has updated their report Covid-19: SME Policy Responses.  Potential business impacts and the pattern of business demography in the Region will be discussed the next post.

 

This series of posts brings together previous WDC analyses and examines them from the perspective of the possible impacts of the Covid 19 pandemic on the economy.  The posts aim to develop our understanding of what may be happening at a regional level and what will need to be done after the public health emergency, but they are early interpretations and should be viewed as a work in progress rather than a definitive commentary.

 

 

Helen McHenry

 

The views expressed here are those of the author and do not necessarily represent or reflect the views of the WDC.

 

 

[1] Quarterly Economic Commentary Spring 2020

[2] Rest of state refers to all counties in the Republic of Ireland except for the seven counties of the Western Region (Counties Donegal, Sligo, Roscommon, Leitrim, Mayo, Galway and Clare.)

[3] Locally Traded Services includes Wholesale & Retail, Accommodation & Food Service, and Transport & Storage; Knowledge Intensive Services includes Financial, Insurance & Real Estate, Information & Communications, and Professional, Scientific & Technical activities;  Public Services includes Health, Education, and Public Administration; Administrative and other services includes a wide variety of services including personal services, sporting activities, creative and other services.

[4] The Health and Education sectors also include substantial private sector employment e.g. private nursing homes, childcare, training providers.  It is not possible to separate this out however.

 

Table of Data from Fig. 1.

How are we doing? Changes and Trends in County Incomes in the Western Region

The CSO released data on County Incomes and Regional GDP for 2017 last month (along with preliminary figures for 2018).  In this post changes in disposable incomes per person in Western Region counties incomes in the Western Region are examined with a particular focus on the differences among counties and the changes over time.  Regional GDP will be considered in a forthcoming post.

It should be remembered that the ‘Household Disposable Income per person’ discussed in this post is calculated at a macro level and the county data is most useful for comparison among counties and over time.  Indeed the CSO notes that “While the county figures involve uncertainty, they do provide a useful indication of the degree of variability at county level.”

The map from the CSO below gives a quick overview of Household Disposable Income per person in 2017.  It shows, unsurprisingly, that the highest disposable incomes are in the east and south, while counties in the west and north have the lowest disposable incomes. The highest disposable income per person is in Dublin which, along with Kildare, Limerick, Wicklow and Meath, had per capita disposable income greater than the state average in 2017 while Cork, Tipperary, and Westmeath were just below (see Figure 1 below for more detail).

Source:  CSO, 2019, County Incomes and Regional GDP 2017

 

A summary of key data for Western Region counties is provided in Table 1 below.  The data for 2017 can be regarded as more robust than the 2018 estimates and so it is used for most of the comparisons in this post.  In 2017, disposable income per person in the Western Region was €17,856 in 2017 and in 2018 it is estimated to have increased to €18,007 (the Western Region figures were calculated using inferred populations).

Table 1: Disposable income data for Western Region counties

*CSO Preliminary Estimate for 2018.  ^Own calculations

Source:  CSO, 2020, County Incomes and Regional GDP 2017  and CSO Statbank Table CIA02

 

Disposable income per person in Donegal has been consistently the lowest in the region (and nationally) and estimates for 2018 show a small decline in incomes in Donegal (-0.7%)  and Leitrim (0.3%) between the two years.  Disposable Incomes in Donegal in 2017 were only 76% of the state average.  Only two Western Region counties (Galway and Clare) had disposable incomes of more than 90% of the state average, while Sligo had a disposable income of 89% of the state average. Incomes were 84% of the state average in Mayo and Roscommon. The Western Region as a whole had a disposable income per person of 86% of the state average in 2017.

The most significant growth between 2017 and the 2018 estimate was in Clare (1.9%) with income in Galway growing by 1.8%.  For the Western Region as a whole, per capita disposable incomes showed a growth of 0.8%.  Disposable income per person in the state was €20,714 in 2017 and is estimated to have grown by 3.8% to €21,495 in 2018.  As noted, however, the 2018 data is estimated[1]. Household Disposable Income per Person in Dublin is estimated to have grown by 6.8% and by 8% in Laois, 7% in Westmeath, 6% in Offaly and 5.3% in Kildare.  It is estimated to have fallen in Wexford, Leitrim, Cavan, Monaghan and Donegal.  The differing growth rates among counties are giving rise to increasing regional imbalance.

Disposable income per person for all Irish counties is shown in Figure 1 below.  As mentioned, disposable income per person in Donegal lowest in the state while Roscommon and Mayo have the next lowest.  In contrast, Galway had the twelfth highest disposable income per person, with Clare in fourteenth place.  The highest disposable incomes nationally are in Dublin, Kildare and Limerick.  These, along with Wicklow, Meath and Cork, all had Disposable Income per person of more than €20,000 per annum.  No Western Region county had a disposable income of more than more €19,000 per annum.

Figure 1: Disposable Income per Person for all Counties, Western Region and State, 2017.

Source:  CSO, 2020, County Incomes and Regional GDP 2017

 

Trends over Time

It is also interesting to look at changes in disposable incomes over time.  Figure 2 shows trends in disposable incomes in the Western Region between 2008 and 2018.  All of the counties show the rapid decline from the 2008 peak followed by varying rates of recovery.  There was a small peak in 2012 followed by a fall in 2013 which related to a decline in social transfers as discussed here.  Galway consistently had the highest income in the region (with the exception of 2011 when Leitrim was highest).  In contrast, disposable incomes in Clare had fallen to the 3rd lowest in the region in 2011 but have shown steady recovery since then and currently disposable incomes are second highest in the region.

Nationally, by 2017 seven counties [2] had returned to the income levels of 2008, but none of these was in the Western Region where no county had a higher Disposable Income per Person in 2017 than it did in 2008.  The estimates for 2018 suggest that 11 counties will have disposable incomes above the 2008 peak, but again, none of these is in the Western Region.

 

Figure 2: Disposable Income per Person for Western Region Counties 2008-2018 (€)

Source:  CSO, 2020, County Incomes and Regional GDP 2017

 

Disposable Incomes in the Western Region compared to the State

When considering how counties are doing it is interesting to look back over a longer period, with data comparing counties to the state average available back to 2000 (Fig 3).  While Figure 2 shows the Disposable Incomes per person, when considering the trends among counties it is helpful to use indices, so that county figures can be examined relative to the state (State=100).  Thus Figure 3 provides a contrast to the more positive trends indicated above in Figure 2 which showed growth in disposable incomes in Western Region counties, particularly between 2014 and 2016.  Growth rates in the Western Region were lower than for the state as a whole and so Figure 3 shows that Disposable Incomes in Western Region counties are declining relative to the state average.

The gap between counties in the Western Region and the rest for the most part narrowed (i.e. they got closer to the state average) during the boom period and into the slowdown.  In fact, regional divergence was least in 2010 when all parts of the country were significantly affected by recession.  Galway and Leitrim were the only Western Region counties to have a disposable incomes of higher than the state average during the period 2000-2017 (Galway in 2009 and 2010 and Leitrim in 2010) .  Since then, it is of concern that all Western Region counties, except Sligo, have declined relative to the state index of disposable income per person.

 

Figure 3: Index of Disposable Incomes per person in Western Region counties 2000-2017, State=100

Source:  CSO, 2020, Statbank Table CIA02

 

Although disposable incomes in most Western Region counties was lower relative to the state in 2017 than in 2000, the pattern of change has varied among counties.  Perhaps most significantly, the index for Clare was 96.5 relative to the state (100) in 2000 but by 2017 it had fallen to 90.5, though this was showing significant recovery on a low point of 88.9 of the state average in in 2015.

Roscommon (92.0) and Mayo (92.2) were in a similar position relative to the state in 2000, and both have declined significantly since then (Roscommon, 84.0, Mayo 84.2) though the pattern for both over time was different.

Sligo is the only Western Region county to have improved relative to the state between 2000 (88.9) and 2017 (89.1) though the difference is small, down from a peak of 95.5 in 2012.  Similarly, Leitrim had only a very small change between 2000 and 2017 (87.9 to 87.5) but it had peaked at 100.6 in 2010.

Galway, which is often considered to be the engine of the region, also declined relative to the state, despite good performance to 2010, and having started in 2000 with an index of 94.2 relative the state, by 2017 it had fallen to 91.7, though this was the highest in the Western Region. Finally, the index of disposable income per person in Donegal, having started from a low base (81.4) continued to decline over the period to 75.6 in 2017 and has remained the lowest in the state during that period.

 

Ranking of counties

Another way to look at how the Western Region counties are doing is to compare them to other counties and rank the relative positions.  In Figure 4, the rank of the Western Region counties is shown for four years (2000, 2006, 2011 and 2017).

Figure 4: Rank of Disposable Income per Person in Western Region among all counties

Source:  CSO, 2020, Statbank Table CIA02

 

Between 2000 and 2017, in the Western Region only Sligo (from 19 to 18) and Leitrim (from 21 to 20) improved their position relative to other counties, though Leitrim had experienced greater improvement in 2006 (ranked 11) and 2011 (ranked 8).  There was significant variation in Sligo, falling as low as 22nd in 2006 and rising to 13th in 2011.

Galway did not vary significantly across the period (from position 11 in 2000 to 12 in 2017) while incomes in Clare, according to this measure, fell from 8th place in 2000 to 14 in 2017, having been as low as 17th in 2011.

The most significant changes were in Roscommon and Mayo which started in 13th (Mayo) and 14th (Roscommon) positions, but have fallen to the bottom three with disposable income per person in Mayo ranked 24th, Roscommon ranked 25th in 2017.  Donegal has had the lowest disposable income of all counties for the whole period.

 

Conclusion

The relative declines in disposable incomes in Western Region counties is of concern.  While incomes in the Western Region have grown, they are not increasing at the same rate as other counties.

Last year the CSO released Geographical Profiles of Income in Ireland 2016, a new, very comprehensive report on incomes in Ireland which provides data at both county and Electoral Division (ED) level (discussed in a WDC Insights blog here).  In addition, new data Earnings Analysis Using Administrative Data Sources (EAADS) provides statistics on earnings at county level (findings for the Western Region are discussed here).  This data, along with the Geographical Profiles of Income and the County Incomes data) gives us an opportunity to triangulate different data sources and gain a better understanding of patterns in earnings and some of the factors contributing to income differences in the region.

Having this data at county level will allow for a more nuanced understanding of the income situation and trends in the Western Region.  I hope to have the opportunity to explore these further in the near future.

 

This post has provided a brief overview of the key County Income figures for the Western Region based on the recent CSO release.  The growth and change in the regional economies as shown by the Regional GVA data will be examined in the next post.

 

 

Helen McHenry

 

[1] There can be quite significant variation between the preliminary and final figures.

[2] Limerick, Wicklow, Dublin, Kildare, Kerry, Westmeath and Tipperary

Why do we travel? Distance to rural services and the need for rural journeys

Understanding the reasons rural dwellers travel is essential to ensuring we can take focused, effective, and fair climate action and aid a transition to low carbon rural regions. In this the second blog post examining data on travel and journeys in Western Region counties and rural areas, the need to travel to services, the distance many rural dwellers live from everyday services, and the reasons why some journeys are not made are all considered.  This post forms part of a series examining data and issues on rural travel and journeys as part of WDC work (some of which falls under Action 160[1] in the Climate Action Plan) on how we transform the Western Region to a low carbon region.  A post on the rural emissions is available here and the first in this series covering issues of rurality and transport and the reasons for travel is here.

 

Distance to services

In the previous post on transport, the importance of travel for work and education were outlined along with the other reasons we make journeys.  Travelling for work and business are clearly important, but most journeys are made to reach services of varying kinds.  People living in rural areas tend to be at a greater distance from services than their urban counterparts and so the journeys made tend to be longer and more car based (both of which will be discussed in future blogs).  Greater distance to services tends to reduce options for travel and in particular, given the lack of public transport and the distance to public transport services, increases reliance on car travel in rural areas.

This is highlighted in Figure 1 below, which compares the proportion living within 15 minutes’ walk of key services in rural areas compared with the national picture.  Indeed the National Household Travel Survey also found that 40% of all rural respondents did not live within 15 minutes of any of these services.

Figure 1: Percentage living within 15 minute walk of services, National Household Travel Survey, 2017

Source: https://www.nationaltransport.ie/wp-content/uploads/2019/01/National_Household_Travel_Survey_2017_Report_-_December_2018.pdf

 

This can be seen more specifically at a county level (Figure 2) which shows the average distance (km) of residential dwellings to everyday services.  This higher average distance to services for rural people  means that rural dwellers are travelling further and for longer periods (discussed more in a future post) are more likely to need a car, which is the only way to access most of these services.

Figure 2: Average km distance to key everyday services for Western Region counties

Source: CSO, 2019 https://www.cso.ie/en/releasesandpublications/ep/p-mdsi/measuringdistancetoeverydayservicesinireland/  Statbank Table MDS02

 

The services shown in Figure 2 above are ones that may need every day access, other services such as banking, libraries and leisure services like swimming pools may be sued less often but have much higher average distances, again increasing the need for motorised transport (most likely a car).  These are shown in Figure 3.  The distance to hospital is greatest, and while some outreach services are provided, many people will need to attend appointments and on going treatment services in these hospitals.  Some transport services are available but many will, where possible or necessary, use private transport of their own or with a friend, relative or volunteer.

Figure 3: Average distance (km) to other services which may be used regularly for Western Region counties

Source: Source: CSO, 2019 https://www.cso.ie/en/releasesandpublications/ep/p-mdsi/measuringdistancetoeverydayservicesinireland/  Statbank Table MDS02

 

The need for car travel is partly a function of the distances to be travelled but it also relates to difficulty accessing public transport.  The average distance to a train station and a public bus stop (which in all Western Region counties is less than the average distance to a train) is shown in Figure 4 below.  For most of these counties, these distances are greater than most people are likely to be able or wish to walk, especially given the hazards of walking on many rural roads, and the probability that many of the journeys in winter would not be in daylight.

Figure 4: Average distance to a bus stop and train station in Western Region counties (km)

Source: CSO, 2019 https://www.cso.ie/en/releasesandpublications/ep/p-mdsi/measuringdistancetoeverydayservicesinireland/  Statbank Table MDS02 Note: Average distance to a train station is not shown for Donegal as there is no station in that county and the distance is too large for the chart (113km).

 

Even if people are to walk this distance (active travel modes in rural areas will be considered in a future post) many of these bus stops have very few services.  All counties have even greater average distances to train stations and in certain situations (e.g. for work or business and hospital appointments) travelling by train may be a preferred option.

Of course levels of service are very important. Figure 5 below shows the percentage of the population whose nearest Public Transport stop has a low service frequency.  This gives a clear indication of why so few rural journeys are by public transport (again to be discussed in a later post).

 

Figure 5: Percentage of the Population in Western Region counties whose nearest Public Transport stop has a frequency of fewer than 10 services per day.

CSO Ireland, 2019, Measuring distance to everyday services 2019 Table 2.3 (XLS 14KB)

 

People not travelling

Finally, having discussed the reason people are making journeys and some of the issues for them in rural areas, it is also interesting to examine, in as far as the data allows, the journeys not made.  The CSO’s National Travel Survey briefly examines the distribution of persons travelling and not travelling by degree of urbanisation  and found that over 77% of persons residing in rural (thinly populated) areas took a journey on the travel reference day.  This was an increase of over eight percentage points on 2014. By comparison, nearly two thirds (65.9%) of persons living in intermediate density areas and 71.1% of residents of urban (densely populated) areas made journeys on the travel reference day.  At a regional level the survey shows that in the Border region 58.4% travelled on the reference day (which was the lowest regionally) and in the West 74.1% travelled. Nationally 71.3% travelled on the reference day.

The most common reason why people did not travel on the reference day was that they had no wish or need to travel or were fully occupied with home duties – nearly two thirds of persons (62.8%) gave this as their main reason for not taking a journey. Understanding more about why people don’t travel could be important in helping us consider how we reduce people’s need to travel on some occasions as a part of the ‘Avoid, Shift, Improve’ approach to developing more sustainable transport.

 

Conclusion

This post, the second in a series on transport data and issues for rural areas and the Western Region, examines some of distance to services, access to public transport and highlights some information on journeys not made.  The next posts in this series will look at the length of journeys, travel time and the mode of transport.  The collation and analysis of the available data will allow us better understand the reasons for, and nature of, rural journeys, This is essential to design policies to reduce emissions and help us to meet our transport targets as well as developing develop more sustainable rural transport options.

 

 

Helen McHenry

 

[1] There are eleven pieces of research and studies which are counted as ‘Steps Necessary for Delivery’ of Action 160, including the one to be carried out by the WDC “Study of transition to a low carbon economy: impacts for the rural western region”.

Does a Rising tide lift all Boats? A look at the latest CSO data on Poverty and access to Services

The CSO released the latest data on Income and Living Conditions (Survey on Income and Living Conditions SILC) last week, see here. The headline figures indicate a continued rise in incomes between 2017 and 2018 which in turn was higher than the figures five years earlier, in 2012 (see earlier post on this here). This is in line with other national economic indicators such as continuing economic growth, employment growth and decreasing unemployment. To what extent is a rise in incomes reflected in a decline in poverty rates and how is this distributed at a spatial level within Ireland? This post highlights some recent data and asks does a rising tide lift all boats?

Poverty Rates

The CSO produce data on three different poverty measures and here we will examine the different rates as they apply to rural and urban areas.[1]

At Risk of Poverty rate[2]

The at risk of poverty rate nationally decreased from 15.7% in 2017 to 14.0% in 2018.The at risk of poverty rate in rural areas in 2018 is 14.7% compared to 13.6% in urban areas. In both rural and urban areas, the trend is downward – in rural areas (down from 17.2% in 2017), and in urban areas 13.6% (down from 15.1% in 2017). This is illustrated in Chart 1 below.

Deprivation Rate

The CSO also measure the deprivation rate, which is a broader measure than poverty and is defined as follows: Households that are excluded and marginalised from consuming goods and services which are considered the norm for other people in society, due to an inability to afford them, are considered to be deprived.  The set of eleven basic deprivation indicators are detailed below[3]. Individuals who experience two or more of the eleven listed items are considered to be experiencing enforced deprivation.

Nationally, the deprivation rate has decreased over the last few years. In 2016 it was 21% and it has since decreased from 18.8% in 2017 to 15.1% in 2018. At a spatial level it appears that there is a higher rate of deprivation in urban areas than in rural, in 2018 the urban deprivation rate was 16.0% while in rural areas it was 13.4%. Both of these rates have also shown a decrease from one year earlier, in 2017 the rates were 20.2% and 15.9%. This is also shown in Chart 1 below.

Consistent Poverty

Finally, the other commonly used measure of poverty, is the consistent poverty rate. An individual is defined as being in ‘consistent poverty’ if they are

  • Identified as being at risk of poverty and
  • Living in a household deprived of two or more of the eleven basic deprivation items discussed above

Nationally the rate went from 8.2% in 2016 to 6.7% in 2017 to 5.6% in 2018. In urban areas the consistent poverty rate declined from 7.4% in 2017 to 5.5% in 2018. In contrast the consistent poverty rate in rural areas increased slightly; from 5.3% in 2017 to 5.8% in 2018.

Regional Difference

The CSO also publish produce data at NUTS 2 regional level for the different poverty measures.

At Risk of Poverty rate

The regional data indicates that the at risk of poverty rate is higher in the more rural regions (Northern and Western) with 20.1% or a fifth of the population there at risk of poverty in 2018. There was a slight decline on a year earlier (21.8%). This consistent poverty rate in the Southern region is considerably lower 15%, down from 16.8% a year earlier. The Eastern and Midland region has the lowest rate 11.1%, down from 12.8% in 2017.

Deprivation Rate

The deprivation rates are more similar across regions (compared to the at risk of poverty rate), as chart 2 shows, though both the Southern and Eastern and Midland regions recorded more significant declines than that experienced by the Northern and Western Region, so in 2018 the Northern Region has the highest deprivation rate (17.2%), compared to the Southern region (15.2%) and the Eastern and Midland region (14.4%).

Consistent Poverty

A similar pattern is evident when examining the consistent poverty rates by region. In 2017 the Northern and Western Region had the lowest rate (6.4%) but a year later the region reported the highest rate – up to 7.8%. This contrasts with the performance and trends in the other regions both of which recorded declines in consistent poverty levels. The Southern region rate declined from 7.1% in 2017 to 6.5% in 2018. The Eastern and Midland region rate declined from 6.6% to 4.2% in 2018.

Overall the CSO recent data show that rural areas have a higher at risk of poverty rate, compared to their urban cousins, but have lower deprivation rates while the consistent poverty rate is most recently showing an upward trend in rural areas and the Northern and Western region and is higher than urban areas and the Eastern and Southern regions.

Measuring Deprivation: Access to Services?

In a previous blogpost in early 2019, see here, I argued that any measurement of deprivation and poverty is more complicated and other considerations such as access to services need to be taken into account.

Access to services

It is often said that rural poverty and deprivation is more hidden or less visible than that in urban areas and one aspect of this is access to services. The CSO SILC definition of deprivation is based on enforced deprivation where there is an inability to afford goods and services. But what of the inability to access goods and services because they are not available in the locality. The case of broadband is a good example. Most people who cannot access good quality broadband see it as a deprivation. It impacts on a person’s ability to access goods and services on-line and often impacts on their ability to generate their incomes, for small businesses and the self-employed.

What about access to other services? Can limited or no access be considered an indicator or measure of deprivation? The CSO have just published data which provides insights into access to a wide range of services, including transport, health and other services see here. There is extensive data and mapping resources which the WDC will revisit but a snapshot illustrates some interesting differences:

  • The average distance to most everyday services was at least three times longer for rural dwellings compared with urban dwellings. For a supermarket/convenience store, pharmacy and a GP, the average distance for rural residents was about seven times longer.
  • Examining differences by county, residents in Galway County, Donegal, Mayo, Leitrim and Roscommon had higher average distances to most everyday services when compared against other counties.
  • The average distance to 24-hour Garda stations ranged between 1.5km in Dublin City to 19.3km in Donegal, while the average distance to a GP was 3.1km, but was more than 5km in Roscommon, Galway County and Cork County.
  • Half of the people living in Roscommon had to travel 5km or more to visit a GP, followed by Monaghan (48%), Leitrim (43%) and Galway County (43%) as illustrated in the Map below. The darker the colour the higher the percentage of the population living 5km or more from a general practitioner.

Map 1  Percentage of Population 5km or more from a GP location by county

The CSO also provide a useful data dashboard to illustrate in a visual way access to services, see here.

Also this November Trinity published data on data on health and Health services, The Trinity National Deprivation Index 2016 see here . This research examines health and health services at a detailed spatial level (Electoral Division) and highlights regional inequalities.

Conclusions

These different data sources provide really useful insights into the geographic distribution of poverty, deprivation and access to services. Overall, the CSO SILC data indicate that along with rising incomes nationally there is evidence of a decline in poverty rates. However, the exception to this is evidence of rising consistent poverty rates in rural areas and in the Northern and Western region.

After a period of sustained economic growth and rising incomes, it is clear that not all boats are being raised in the rising tide. These data provide a wealth of information highlighting regional and spatial difference and an evidence base for effective policy change. This is a tool to inform Government policy to focus on eradicating poverty and in doing so being cognizant of the spatial patterns of poverty. Various policies ranging from consideration of a new Rural Strategy in the short term to Project Ireland 2040 over the medium to long term are some of the policy frameworks which need to respond to these findings.

 

Deirdre Frost

[1] Urban or Rural are defined as follows: Urban – population density greater than 1,000. Rural is Population density <199 – 999 and Rural areas in counties.

[2] This is the share of persons with an equivalised income below 60% of the national median income.

[3] Two pairs of strong shoes, A warm waterproof overcoat, Buy new (not second-hand) clothes.

Eat meal with meat, chicken, fish (or vegetarian equivalent) every second day, Have a roast joint or its equivalent once a week. Had to go without heating during the last year through lack of money, Keep the home adequately warm. Buy presents for family or friends at least once a year. Replace any worn out furniture. Have family or friends for a drink or meal once a month, Have a morning, afternoon or evening out in the last fortnight for entertainment.

How are we doing? Annual earning in Western Region and other counties

Data on earnings of employees in different counties has just been released by the CSO, providing another important contribution to our understanding of local and regional economic development.

Earnings Analysis Using Administrative Data Sources (EAADS) provides statistics on earnings for which the primary data source is the Revenue Commissioner’s P35L dataset of employee annual earnings which is linked to CSO and other data to provide economic and demographic characteristics.  This new data, along with the Geographical Profiles of Income (also released for the first time this year and discussed on the blog here) and the County Incomes data (discussed here) gives us an opportunity to triangulate different data and gain a better understanding of patterns in earnings and some of the factors contributing to income differences in the region.  Having this data at county level allows for a more nuanced understanding of the situation and trends in the Western Region.

In this post the EADDS annual earnings data is discussed for Western Region counties.  It should be remembered that this data is specifically employee earnings data which is just one element of individual or household incomes.  Other incomes sources (e.g. social welfare, earnings from wealth or profits from business) are not included in this data set.

Annual Earnings, 2018

Looking first at median[1] annual earnings[2] for 2018 (Figure 1), even though all Western Region counties (green) are below the national figure of €36,095 both Galway (€35,632) and Clare (€35,568) are only slightly below, in sixth and seventh place nationally.

Note Total includes Northern Ireland counties not listed above.

Source: CSO Ireland, 2019, Earnings Analysis Using Administrative Data Sources Table 8.15 Median1 annual earnings by county and sex 2018

Donegal had the lowest earnings (€29,298), almost a thousand euro less than Monaghan, the next highest, and more than €10,000 less than the earnings in Dublin (the highest county (€39,408).  Earnings in Roscommon are higher than might have been expected (€34,082, 13th place) from other data such as that for County Incomes, though  in line with Geographical Profiles of Income.

Annual Earnings in Western Region counties

Focussing more specifically on the range of earnings per employee in the Western Region (Figure 2), the gap between the lowest (Donegal) and the highest (Galway) is a €6,334 per year while annual earnings in Mayo and Leitrim are both around €2,500 less than in Galway.  There is only €64 difference in the annual median income per person in Clare and Galway.

Note Total includes Northern Ireland counties not listed above.

Source: CSO Ireland, 2019, Earnings Analysis Using Administrative Data Sources Table 8.15 Median1 annual earnings by county and sex 2018

Changes in Mean Earnings 2016-2018

This data is available for the years 2016, 2017 and 2018.  While this covers a relatively short period it is interesting to examine the change in mean[3] annual earnings over this period throughout Ireland (Figure 3).  Nationally earnings grew by 6.1% over the period with the highest growth rate in Dublin (7.6%) followed by Cork (6.6%) and Kilkenny (6.2%).  The lowest rates of growth were in Cavan (4.4% and Longford (4.4%).

Note: Total includes Northern Ireland counties not listed above.

Source: CSO Ireland, 2019, Earnings Analysis Using Administrative Data Sources Table 8.14 Mean annual earnings by county and sex

Looking more closely at the Western Region (Figure 4), the highest rate of earnings growth was in

Galway (5.8%), and the lowest in Roscommon (4.7%) and Sligo (4.7%).  No Western Region county had earnings growth higher than the national rate.

Note: Total includes Northern Ireland counties not listed above.

Source: CSO Ireland, 2019, Earnings Analysis Using Administrative Data Sources Table 8.14 Mean annual earnings by county and sex

Gender Differences in Earnings

County data is also available by sex, so it is possible to compare earnings in each county for males and females (Figure 5).  In all counties male earnings were higher than female earnings in 2018, with the largest difference in Cork, a very significant €10,205 per year (female earnings were only 76% of male).  Nationally the difference between male and female earnings was €7,394 and the smallest difference in both amount and proportion was in Donegal (€3,153, female earnings 90% of male).  In general, the largest differences between male and female earnings were in the highest earning counties, but Waterford (€8,511), Limerick (€8,318) and Kerry (€7,234), which has the third lowest medial annual earnings, were exceptions to this.

Source: Source: CSO Ireland, 2019, Earnings Analysis Using Administrative Data Sources Table 8.15 Median annual earnings by county and sex

Gender Differences in Earnings in the Western Region

The difference between male and female earnings was smallest in the Western Region.  Six of the nine counties where female earnings were 85% or more of male earnings were in our Region.  Sligo had the narrowest gap nationally (female earnings 91% of male), followed by Donegal (90%), Leitrim (89%), Galway and Mayo (86%) and Roscommon (85%)[4].  Clare was the exception in the region, with female earnings only 80% of male earnings.

The difference in the Western Region are shown more clearly in Figure 6 which highlights the earnings gap (percentage difference in what females earn compared to males).  Clearly Sligo (9%) and Donegal (11%) perform best.  Nationally the picture is bleaker with a 23% annual earnings gap, and in Clare males earn 25% more than females.

Source: Source: CSO Ireland, 2019, Earnings Analysis Using Administrative Data Sources Table 8.15 Median annual earnings by county and sex

Some of this earnings gap is likely to be accounted for by the higher instance of part time working among females. The differences may also relate to earning levels in the different sectors where men and women tend to work, as well as differences in employment types.  Nonetheless, the gap in earnings is very significant but, at least in relation to this statistic, the Western Region is a good performer.  The prevalence of public sector employment in the Western Region (discussed here), along with employment in Education (3 out of 4 people working in the Education sector in the Western Region are women) and Health (21.4% of all working women in the Western Region work in Health & Care, it is the largest employment sector for women in the region), probably influences this.

Changes in male and female earnings over time.

There is no clear pattern for the growth in mean earnings for males and females between 2016 and 2018 in the Western Region counties (Figure 7 below).  In four of the seven Western Region counties female earnings increased by more than male earnings between 2016 and 2018.  This was also the situation nationally (though the difference is small (0.1%)).   Female earnings in Sligo grew by 5.0% while male earnings in the same period grew by 4.0%.  In Clare the difference in earnings growth was more significant (5.7% for females and 4.3% for males).  Galway had the largest growth in female earnings over the period in the region at 6.1%, while male earnings grew by 5.3%.  If this pattern were to continue the gap in male and female earnings would narrow, or even disappear.

Source: Source: CSO Ireland, 2019, Earnings Analysis Using Administrative Data Sources Table 8.14 Mean annual earnings by county and sex

In contrast in three Western Region counties (and a total of nine counties nationally) male earnings grew by more than female earnings between 2016 and 2018.  Leitrim and Roscommon had the lowest female earning growth (4.4%) in the region and nationally.  The difference was most significant in Leitrim where male earnings grew by 5.3% over the same period.  In Donegal the difference was less marked (4.8% for males and 4.6% for females).  Unlike the other Western Region counties discussed above, if this pattern persists in these counties the gap in male and female earnings will widen.

Conclusion

This data set is focused on earning for those in employment rather than broader income data covering households or adults not in employment so it does not give a full picture of income levels.  It is, nonetheless, very useful to have this data at county level.  We can now make robust comparisons between counties and see some of the changes over time.  In future analysis it may be possible to consider in more depth how the different employment patterns and sectors in the counties in turn influence earnings.  Similarly correlations between education and training levels, and skill sets in the counties will help us better understand the needs and opportunities for counties and regions.

In the New Year I hope to have time to compare the data in this release with the other income data available at county level to get a better understanding of what each source is telling us about the trends and differences in the earnings and incomes in the Western Region.

 

Helen McHenry

 

[1] 1Median annual earnings: Half of the employees earn more than this amount and half earn less.  Median is used as it reduces the influence of outliers, in particular exceptionally high earners who could increase the mean significantly.

[2] Employees who worked for less than 50 weeks in the reference year are excluded from the calculations for annual earnings. This is done to improve comparability of the data over time.

[3] Mean is used here for comparison over time to maintain consistency with gender data discussed later.

[4] Monaghan (86%), Cavan (85%) and Kilkenny (85%) were the other counties.

e-Work, Remote work and Hubs, Some Recent Evidence

Introduction

The WDC produced the Policy Briefing e-Working in the Western Region in March 2017, see here. This briefing aimed to quantify the extent of e-working in the Western Region and nationally and set out policy recommendations. Since then e-working or remote working and co-working spaces such as hubs have received a lot of attention, but to what extent is the activity on the increase?

In the Policy briefing, the WDC noted that the extent of e-Working is hard to measure, in part because of the paucity of data, and in part because the practice is sometimes not very visible; it is often in the absence of company policy and at the discretion of local management. Some recent data in relation to official statistics and company practice is presented here.

CSO Pilot for Census 2021

There has been limited official statistics measuring the incidence of working from home. To date the Census has asked the question ‘how you usually travel to work’? with one of the answers being ‘work mainly at or from home’. This is very limited as it only captures those that work from home most of the working week and excludes those who work from home one or two days per week, which some suggest is the most common pattern.

The CSO invited submissions to the consultation on questions for inclusion in Census 2021. In its submission, the WDC advocated for the inclusion of a question to more effectively capture the extent of Working from home/ e-working. Following the consultation exercise and a pilot exercise the CSO have now agreed to include a question measuring the number of days people work from home on a weekly basis in Census 2021. The results of the pilot survey were released earlier this year and they provide an insight into e-working. Some of the findings are highlighted below.

Among those at work, 18% declared they worked from home. The level of non-response among workers was low at 3%. Of those working from home, the breakdown by number of days was as follows:

Working from home 1 day per week was the most popular practice (35%), followed by 2 days a week (13%) and 5 days per week (by 11%). It should be noted over a quarter of those who said they worked from home did not state the number of days. One possibility may be that their pattern changes on a weekly basis.

Profile of those working from home

  • The pilot results showed that the percentage of those working from home increased as age increased, peaking at 19.6% of those at work in the age group 45-49. The proportion of home workers decreased among workers in older age groups. Among those in the 45-49 year age group, 32% worked one day from home.
  • Approximately 60% of people who work from home were male.
  • There were notable differences in the occupation of those who worked from home. e.g. 13.5% of those who worked from home worked in the ‘Science, research, engineering and technology professional’ occupation category.
  • In contrast only 0.6% of those who worked from home indicated they were in the ‘Process, plant and machine operatives’ occupation category
  • Over half of those who worked in ‘Computer programming, consultancy and information service activities’ indicated that they worked from home. This industry comprised 3% of all workers in the Pilot but 11% of all home workers were in this industry.
  • Of those who worked from home, 79% had fixed broadband internet, 18% had mobile broadband internet, and 3% indicated they had no internet connection. It is possible that that much of this 3% do not depend on internet access to conduct their work, for example those engaged in agriculture. See the CSO release here.

The WDC very much welcomes the inclusion by the CSO of the question on working from home in the next Census. This will allow a more thorough analysis of the practice based on comprehensive Census data.

Company Practice- Incidence of e-work in Ireland

Another part of the evidence base is data collected by companies on the extent to which they provide for flexible work practices such as e-working and the extent to which this is practiced by their employees.

IBEC have collected survey data on the extent of e-working for a few years now. Data has been recently published which shows an increasing prevalence of the practice based on a survey of IBEC members. For example,

  • In 2018, 37% of IBEC members (152 companies) had a practice of e-Working/ home-working, on one or two days per week basis, up from 30% (110) in 2016.
  • In 2018, 7% had a practice of e-Working five days per week, up from 5% in 2016.
  • The IBEC survey shows that the likelihood of e-Working among companies increases with company size, so that 54% of companies with 500+ employees cite a practice of e-Working on a 1 or 2 days a week basis.
  • There is a slightly higher rate of e-Work among foreign owned compared to Irish owned companies, 40% and 33% respectively, and both these figures are up on two years previously – 34% and 27% respectively.
  • Sectorally the highest rates are within the Electronic services sector (69%), followed by the Financial services sector (58%).
  • At a regional level IBEC members in the Dublin region have the highest incidence, with almost half (49%) report having an e-working policy of 1-2 days working from home per week. This rate drops to one-third of companies in the Cork region, one-quarter in the Mid-West and South-East and 24% in the West/North West.

This regional variation supports the idea that at least some of the e-working demand and take-up by employers is driven by congestion in larger urban centres.

Demand for e-working/co-working spaces/ Hubs

Another aspect of e-working or remote working is where the worker works from a hub rather than home. The success of initiatives variously called e-working spaces/ co-working spaces/ hubs also suggests e-working is on the increase. Some working spaces are funded by Department of Business, Enterprise and Innovation and some by the Department of Rural and Community Development. The hubs are variously classed as innovation, enterprise or community hubs, and many are focussed on start-ups and incubation spaces as well as providing e-working spaces for individual employees.

The Western Development Commission is coordinating an initiative with the Department of Community and Rural Development (DCRD) called the Atlantic Economic Corridor (AEC) Enterprise Hubs project. This three year project aims to create an interconnected community network from the 101 hubs identified in the AEC region (the region from Donegal to Kerry) along the Western Seaboard.

This week the WDC is convening two workshops, one in Limerick (19th November) and the second in Sligo (Thursday 21st November) aimed at bringing all key stakeholders together to work together to optimise the operation of the hubs and how they can support regional and rural development, e-workers and remote workers throughout the region. For further information see here for more information.

 

 

Deirdre Frost

Agency Workers – How Many Are There and Where do they Work?

Introduction

There is much discussion about the growth of ‘atypical’ forms of work – such as e-working, remote working, the gig, shared economy and temporary work etc.

The WDC has previously examined various aspects of atypical ways of working, identifying the extent to which it occurs in the Western Region, whether patterns differ to that elsewhere in the country, all aimed at informing labour market policy and identifying recommendations to support better employment opportunities in the Region.

The WDC Policy Briefing (No. 7) e-Working in the Western Region: A Review of the Evidence, examined the extent of e-work (also referred to as teleworking or remote working) in the Western Region, see here. Working at or from home can take different forms and this Policy Briefing examines e-working in traditional employer-employee relationships. The WDC also published case-studies of e-working in the Western Region which highlights a wide range of e-working experiences, see here.

A two page WDC Insights paper examined the gig or shared economy and how broadband and online platforms have enabled new forms of work and income generation to emerge. The paper examines the evidence on the extent to which Gig economy exists in the Western Region, download here.

In the third of the series, the WDC examined working from home. Based on Census of Population data which identifies whether people work ‘mainly at or from home’. The Census definition is self-assigned and can include those who work full-time from home or working from home on at least three days of a five day working week, see here. The WDC have suggested a change to Census 2021, to which the CSO has agreed, which will include a question asking people to list the number of days per week in which they work from home.

Agency Worker Employment

Another aspect of atypical working includes agency worker employment. Sometimes it is suggested that this type of employment is on the rise and is often less secure or more precarious than traditional employment forms.  Agency work, especially that which is temporary, is often considered insecure employment. Is it a phenomenon largely associated with periods of high unemployment and a fragile economy where employers are reluctant to recruit permanent employees or is it a feature of the business model of some companies?

Research conducted for the European Parliament found evidence of an increase in temporary employment as a consequence of the global economic crash a decade ago. The report noted, The financial crisis and its aftermath has been one driver affecting risk of precariousness in Europe. As employers and employees find themselves operating in a more competitive and uncertain context post-crisis, new hirings have increasingly taken place on the basis of temporary and marginal part-time contracts. This rise in atypical contracting has meant that job insecurity has increased significantly in some countries, such as Portugal, Spain, Ireland, Latvia and Greece, involuntary temporary work has increased significantly in Ireland, but also in Latvia and involuntary part-time working has increased significantly in Italy, Lithuania, Spain, Ireland, Latvia and Greece. The link to the full report (5.4MB) is here.

Examining more recent data at a regional level in Ireland, the CSO provide a broad regional breakdown at NUTS 3 level. In this blogpost we review the latest CSO data on agency worker employment examining trends and how the regions compare, see here for full release published in August 2019.

CSO definition

The CSO Labour Force Survey captures the levels of agency workers by asking the following question of all employees in the LFS: Do you have a contract with an employment agency that placed you in your current job and your salary? Yes or No. Responses are therefore based on self-reporting.

Nationally, in Q4 2017, there were 56,200 employees classified as agency workers, and in Q1 2019 the number had decreased to 50,400, a decrease of 5,800.

Examining trends by region, the trends are somewhat different as graph 1 below shows. Both the Northern and Western region and the Eastern and Midland region have a somewhat similar trend, albeit at different levels, unsurprising given the relative size of the numbers employed in each region.

In the Northern and Western Region, (depicted by the black line), the numbers of agency workers at the start of the period was 12,700, there was a decline to 4,300 in Q4 2018 and at the end of the period (Q1 2019) it was 7,500. It should be noted that the LFS is a survey and the results are weighted to conform to population estimates broken down by age, sex and region. Where there are smaller numbers, estimates are considered to have a wider margin of error and so should be treated with caution. In the data above, this wider margin of error has occurred where numbers fall below 7,500.

The Eastern and Midland Region (the orange line), starts with a level of agency workers of 27,000 at the end of 2017. At the end of the period the number of agency workers in the Eastern and Midland region was 22,200.

The Southern region (green line), displays a different trend, starting at 16,500, rising to 20,900 in Q2 2018, dipping at the end of Q4 2018 and then rising again in Q1 2019 to 20,700. It is not clear why the trend in the Southern region is somewhat different and this will be discussed further below.

Regional Share of Agency Workers

Examining agency workers as a share and proportion of all employees, Graph 2 below shows the regional share of employees who are agency workers over the period Q4 2017 to Q1 2019.

At the end of the period, in Q1 2019, the Northern & Western Region accounts for 14.9% of all agency workers in the country, the Southern Region accounts for 41.1% and the Eastern and Midland region accounts for 44%. The respective shares have changed over the last two years, with the Northern and Western Region accounting for a decreased share (22.6% in Q4 2017 to [14.9%] in Q1 2019. The Southern Region has increased its share (from 29.4% in 2017 to 41.1% in Q1 2019.

Proportion of employees who are agency workers

Given the different sizes of each regional labour market it is important to see the extent to which agency workers as a proportion of all employees, varies across time and region. This is illustrated in Graph 3 below.

Nationally (depicted by the blue line), in Q4 2017 agency workers comprised 3% of all employees. This proportion declined to 2.6% at the start of 2019. Both the Northern and Western and Eastern and Midland regions had proportions below the national average.

The Northern and Western region, depicted by the black line, started the period with the highest proportion of employees as agency workers (4.1%), but this has since declined to 1.4% and was recorded at 2.4% in Q1 2019. The Eastern and Midland region trend (depicted by the orange line) is very similar to the national trend albeit at a lower level.

For most of the period, the proportion of employees who are agency workers is the highest in the Southern region (depicted by the green line). At the start of the period under review, Q4 2017, the rate in the Southern region is lower than the national figure – 2.8% and 3.0% respectively. However, from Q1 2018 through to the end of 2019 the proportion of employees that are agency workers is consistently higher in the Southern Region than the national average.

Conclusions

The Southern region comprises the Mid-West (Clare, Limerick & North Tipperary), the South-East (Carlow, Kilkenny, Waterford and Wexford) and the South-West (Cork and Kerry). In the absence of NUTS 3 regional data it is difficult to know whether there may be specific concentrations associated with a concentration in industry sectors that may be more prevalent in the Southern region.

The CSO data does provide other information on the profile of agency worker employment. For example, nationally 52% of agency workers are female. There is a sectoral concentration within the Agriculture, Forestry, Fishing, Industry and Construction sectors where a quarter of all agency employees are employed. There is also a high concentration of agency workers in the Human health and social work activities sector, see here for full release.

Discussions with the CSO indicate it is difficult to ascertain why there is a relatively high share in the Southern region. The CSO point out that the LFS is a survey, the margin of error of the estimates can be greater with smaller cell sizes. More trend data will be needed to see if it is a more established trend and a particularly stronger feature of employment in the Southern Region or if it becomes a stronger feature of employment when economic growth is not as strong.

However, the availability of these data does allow us to monitor trends and helps us build a picture of the range and types of employment, all of which is critical to formulating and improving employment policy.

 

 

Deirdre Frost

Energy efficient homes in the Western Region: some thoughts on retrofit.

The government target of improving home energy efficiency through the retrofitting of 500,000 buildings by 2030 (see the Climate Action Plan 2019) is ambitious.  It is therefore useful to look at the retrofits in more depth, and consider the target and issues from a rural Western Region perspective.

While new buildings have significant potential to incorporate the reduction or elimination of energy consumption (particularly for space heating and cooling purposes) into their design, a focus on existing buildings is essential.  The longevity of buildings and the building stock (typically 50–100 years) means that for a very long time ahead the majority of the building stock will be from before the current era of low energy regulation[1].  In the last blog on this topic  the baseline information on homes in the Western Region was set out.  In this post some of the issues associated with retrofitting these homes is considered in more detail.

Energy efficiency in Western Region homes

As discussed in detail in my previous post, recent improvement in building standards mean that it is generally assumed that homes built after 2010 will require least upgrading and therefore the focus for retrofitting is likely to be on homes built before 2011.  In the Western Region, the Census of population 2016 shows that there are 280,949 homes built before 2011, that is 93% of all the homes in the Western Region (excluding ‘not stated’).  Currently, only 4% of homes in the region, with a BER, have a rating of B2 and higher (the target energy rating in the Climate Action Plan is BER B2 or cost optimal or carbon equivalent).  If these BER ratings already recorded are translated to the Western Region housing stock, it means that 269,711 homes would need to be retrofitted.  The challenge to improve energy efficiency is, therefore, very significant. It is likely, however,  that the BER ratings we have are not reflective of the general housing stock, as they are mainly comprised of houses which are to be sold and new homes and therefore may show higher BER levels than would be the case if all homes had been rated.  On the other hand, some homes have been improved and while some of them will have a new BER rating (included in figures above), others will be better than recorded.

What is retrofit?

Before considering the targets and how they might be applied in the Western Region it is useful to understand what ‘retrofit’ means in an energy efficiency context.  Retrofits are often referred to as ‘shallow’ or ‘deep’.

The SEAI provides the following information on Deep Retrofit:

The Deep retrofit of a home means carrying out multiple energy upgrades all at once to achieve a BER of A-rating.

  • Firstly, you will need to reduce the level of heat loss so that you keep heat in the home for longer. This involves some or all of the following: wall insulation, roof insulation, floor insulation, window upgrades.
  • The next step is to look at an efficient renewable heating system to support the transition away from fossil fuels. The typical heating system installed on a Deep Retrofit Pilot Project is an air-source heat pump.
  • It also includes mechanical ventilation to maintain good indoor air quality.
  • Other renewable energy technologies such as solar water heating panels and solar photovoltaic panels may be appropriate for your home.

In contrast, shallow retrofit may include cavity wall insulation, window replacement, attic insulation, draught proofing, energy efficient lighting and improved heating controls, and these may be done one at a time and not as part of a complete plan.

The government target to bring 500,000 to a BER B2 equivalent does not specify the kind of retrofit required, but it is likely to be closer to a ‘deep’ retrofit approach (although not to an A rating but to a B2), particularly as a proposal is to be developed to phase out grants for ‘shallow’ energy efficiency measures by 2022 (Action 52, Climate Action Plan, Annex of Actions (718KB).

How much will the homeowner save?

Improving the energy efficiency of the home through retrofit should provide energy savings,  the larger the move up the BER scale the larger the savings.  The SEAI has provided an indication of energy costs for different house types at different BER ratings ((see Figure 1 below).

Figure 1: SEAI Indicative annual CO2 emissions and running costs for different rating bands for space and water heating

Source: https://www.seai.ie/publications/Your-Guide-to-Building-Energy-Rating.pdf This table gives estimated annual fuel cost and CO2 emissions on the basis of typical occupancy and heating the entire dwelling to a comfortable level.  The Tables above are based on fuel and electricity factors from February 2014.

According to this table, an owner of an F rated ‘3 Bed Semi Detached House’ could save €2,400 in energy costs a year, while an F rated ‘Large House’ could save €7,200 annually following retrofit.  It should be noted, however, in relation to potential savings, the energy cost estimates usually refer to heating a whole house to ‘a comfortable level’.  It has been found that people living in less efficient homes may not be heating the house to that level, while those in more efficient, upgraded homes may not be achieving the savings estimated as “inhabitants’ everyday practices and norms of comfort are often changed in parallel to retrofitting of the home”.  In other words they may heat their home more (see reference in footnote 1 for more discussion).  Thus the savings are not likely to be as much as predicted.

How much does a deep retrofit it cost?

It is difficult to find generalised cost estimates for deep retrofitting given the significant variation among house types, size and the upgrades required, but it is usually agreed that it is very expensive.

Information from the SEAI pilot deep retrofitting programme found that for 250 homes that completed deep retrofits under SEAI’s pilot programme the average cost to upgrade a home from an average BER rating of F rating to an average A3 rating was €48,417.

Information from Superhomes (a retrofit service providing a ‘one stop shop’ for energy retrofit projects) again highlights the variation in costs depending on the extent of the retrofit.  It notes that the lowest cost for a SuperHomes retrofit in 2019 was €35,000. A grant of €11, 000 was secured, bringing the net cost down to €24,000. This retrofit included a heatpump, wall & attic insulation, external door replacement, airtightness measures and a demand control ventilation system.

SuperHomes suggests that the typical cost of a full scale deep retrofit to BER A3 standard in 2019 was between €50,000 and €70,000 (before grants). These retrofits would include a heatpump, wall and attic insulation, external doors, airtightness measures and a demand control ventilation system. They may also include a mix of external wall insulation, floor insulation, Solar PV and full window replacement. SuperHomes applied for and secured grant funding of a minimum of 35% of costs on all these retrofits. As a result the net spend was typically between €30, 000 and €45,000.

The government retrofit target is a B2 energy rating, rather than the A3 ratings being achieved above.  Thus the cost should be somewhat less, though it is not clear by how much as I have not been able to find data on costs to achieve a B2 rating.  Overall costs of achieving the target will, of course, depend on the type and size of houses which are being retrofitted.  This is turn will partially depend on the incentives available.

However, it should be noted that the cost of the retrofit is very significant, and when compared to the value of homes in Western Region it is clear that it would be equivalent to a large proportion of the home value.  While in more expensive areas the cost of the upgrade may account for less than 10% of the home’s value, it could be double that in counties like Leitrim and Roscommon where house prices are lower (see Figure 2[2]).

Figure 2: Median House price by county 12 months to August 2019

 

Source: CSO residential Property Price index https://www.cso.ie/en/releasesandpublications/ep/p-rppi/residentialpropertypriceindexaugust2019/additionalindicators/

There is little data available as yet on the impact of the BER rating on the value of a house though it would be expected to become more important as the carbon tax increases. The level of increase in a home’s value following a retrofit will also become clearer over time.

Conclusion

it is not clear what mechanisms will be used to achieve the government retrofitting target, but it is clear that it is ambitious.  The cost of retrofits, the means of paying for such energy efficiency, the incentives which will be provided have not yet been fixed.

There are a huge range of issues to be considered when deciding how we should best reduce our emissions for the built environment.  My interest is in rural dwellings in particular and this post has explored only a few of the issues relating to retrofit.  I hope to continue this exploration over the coming months so that the ways rural dwellers in the Western Region can participate in our move to a low carbon region can be better understood.

 

 

Helen McHenry

[1] Kirsten Gram-Hanssen, 2014, Retrofitting owner-occupied housing: remember the people.  https://www.tandfonline.com/doi/full/10.1080/09613218.2014.911572

 

[2] While the price of homes sold in the last 12 months in each country is not the same as the average value of homes in the county it gives a useful indication of relative values.