In the last couple of days I’ve been asked to comment on two issues around property data, both relating to vacancy (though we could easily have a similar discussion with regards to housing completions, homelessness, etc).  The first relates to housing vacancy and a report by Fingal County Council that contends that the vacancy levels in the local authority have been ‘grossly overstated’. The second about commercial vacancy and present rates. In both cases it’s difficult to provide strong answers because systematic data collection with respect to both is problematic and the state does not provide official data on either, except on housing vacancy every five years through the census which is a sub-optimal timeframe to be working from.

With respect to housing vacancy. I can’t find the report or press release from Fingal CC, but a story in the Irish Times reports that they believe vacancy levels are well below those reported in the census. It’s difficult to assess fully whether that’s the case without seeing the full methodology or data. What is reported in the IT is:

“The council initially conducted a desktop exercise on the 3,000 supposedly vacant properties. When commercial properties, as well as those in construction or in the planning process, were eliminated the figure fell to 361 properties. ”  They then visited 74 of the 361 homes to check on occupancy, though it’s not stated how those 74 were sampled.

Of those 74 visited, they discovered that only 13 were actually vacant. In other words, rather than having a vacancy rate of 5% (as reported in the 2016 census – 4,944 vacant units + 289 holiday homes), they have a rate of about 1% – far below what might be an expected base vacancy level of 6% (there are always some units vacant due to selling, gaps between renting, working temporarily elsewhere, people in healthcare, etc.). I have no doubt in the 18 months since the census in April 2016 properties that were vacant will have been occupied, however it seems unlikely that vacancy is so far below base vacancy, which is what the IT piece seems to be suggesting.

In terms of method it is unlikely that the CSO shared the individual addresses of vacant properties as identified in the census with Fingal. But if they were working from census data then it does not include commercial properties, nor properties under-construction, or in the planning process, or derelict. So removing those properties from census counts would make no sense – they were never counted by the CSO. Indeed, in a rebuttal story in the Irish Times, the CSO stand over their data and method – which is to send enumerators to every property in the country, to visit upwards of ten times if they fail to get an answer, and to talk to neighbours to try and ascertain the use status. I’m assuming that Fingal got their data instead from Geodirectory who source the information on occupancy from postal workers delivering or not mail. How accurate those data are I’m not sure and presumably the company would stand over their fidelity.

Regardless of the method, there is clearly a large discrepancy between what Fingal CC are finding on the ground in their small sample and what the census enumerators found 18 months ago, and presumably what An Post workers are finding. That discrepancy suggests we need a much more systematic and timely way of generating data on housing vacancy.  The government have set up a crowdsourcing means to generate vacancy information – – where members of the public can log homes that they think are vacant, which can then be checked by local authority staff. There are well known problems with crowdsourcing such information, including coverage, representativeness and keeping the data up-to-date, and these data certainly could not be used as official statistics. Much more realistic would be a quarterly vacancy survey (much like the quarterly household survey) – probably carried out by the CSO who have no vested interest in local housing/planning data.

In terms of commercial vacancy, the state produces no statistics on the rates of vacancy for offices, retail units or industrial sites. It is a massive hole in our knowledge of the property sector. The only data that are produced are those by Geodirectory (which are limited in detail) or the property sector itself (hardly an unvested party, and the data are a product and can disappear from websites or go behind paywalls, and lack spatial granularity – usually just Dublin/rest of country or regions). In relation to commercial properties there is also a need to understand their characteristics, such as type, spec, condition, location, etc. as well as the size of space vacant, not just how many units. For example, imagine that there are ten units on a high street.  Nine of them are 1000 sqm in size and one is 5000 sqm.  If the larger unit is vacant then the vacancy rate per unit is 10 percent. However, the vacancy rate by floor area is 35 percent.  In other words, one cannot simply look at the absolute number of vacant units, rather we also need to consider the type and size of the units that are vacant. Trying to prepare local and county development plans with a fuzzy knowledge of existing development is a sub-optimal way of conducting planning and can lead to oversupply and property crashes (as per the last 20 years). Like housing, we therefore need good, reliable, timely data to understand the commercial property sector and we need the state to produce them.

In my view, there needs to be a branch-and-root review of property data in Ireland. This needs to start with asking the question: what data do we need to generate to best understand planning, housing, commercial property, infrastructure need, etc? Then to discover where the gaps are and to review the veracity and fidelity and fit-for-purpose of existing data generation and to fix as necessary. This includes assessing whether the data are being generated by the most appropriate generator. We then need to put in place the processes to produce those data.

With good quality data that people trust we might avoid different agencies producing wildly varying estimates of some element of housing or commercial property, such as vacancy rates, and we would greatly aid our planning and economic development. However, if we carry on as we are, we’re going to continue to fly half-blind and only have a partial or flawed understanding of present conditions and we are going to replicate mistakes of the past.

Rob Kitchin

The visualisation below represents a summary of unemployment rates across the EU27 by month since January 2007 until November 2012. Each country within the EU27 may be selected, compared and contrasted to assess how the economic crisis impacted each state in terms of unemployment. The rate presented here is the seasonally adjusted unemployment rate which represents the percentage of the labour force classified as unemployed. The report, raw data along with metadata is available from Eurostat.

By visualising this data across a time line we can identify the numerous unemployment spikes that occurred due to the various economic events across the EU27. Stand out trends for example are the rise in Irish unemployment between 2007 (4%) to 2010 (14.8%) and its subsequent plateau or the dramatic rise in unemployment in Greece (26.6%) and Spain (26.8%) laterally.

In terms of raw numbers Eurostat reports that the November 2012 unemployment rate of 10.9% equates to 26.06 million people unemployed across the EU27.

By using the select filter located on the left side of the visualisation, countries may be selected for comparison and then for a more detailed analysis at the base of the viz a single country may be selected. In each case by hovering over any part of the viz a detailed value will be shown in a pop up window.   The data and images of this visualisation may be extracted using the tools located at the bottom of the page.

See the Viz on the AIRO site here:

Eoghan McCarthy


Yesterday Minister Jan O’Sullivan published the 2012 National Housing Development Survey.  The headline story from this is that the number of estates categorised as unfinished has fallen from 2,876 in 2011 to 1,770 in 2012, and that decisions will be taken in the new year on which estates are commercially unviable and need to have parts of them demolished (especially in the midlands and border region).

Along with the report, the Department of Environment also published the data they used in the report in three separate files comparing counties, profiling individual counties, and profiling individual estates.

So, have the number of unfinished estates fallen by 1,106 and is the problem of unfinished estates receding?

Technically, yes.  But this is where I link to the title of this post.  The drop is principally because the DECLG have changed the definition of an unfinished estate.  The definition used in 2010 and 2011 refers to estates that have issues of vacancy and oversupply as well as outstanding development works.  In 2012 the definition refers only to estates where there is outstanding development work.  At one level, this change makes sense.  The 1,770 estates that need development work are the most problematic.  At the same time, the issue of vacancy and oversupply has not gone away, affect the overall market, and have consequence re. anti-social behaviour, sense of place and community, etc.  Indeed, on the old definition the number of estates surveyed rose in 2012 to 2,973.

This is not the only bit of being creative with the numbers.  Oddly, the figures both work for and against the government.

For the government

Overall occupancy: the overall level of occupancy in unfinished is reported as 91,692 – this is occupancy across the 2,973 estates surveyed not the 1,770 we’re told now constitute unfinished estates.  It is useful to have the data for the 2,973 estates but it also needs to be reported specifically for the 1,770.

Complete and vacant units: the overall level of vacancy is reported as 16,881, down from 18,638 in 2011 – again this is refers to the 2,973 estates surveyed.

Vacancy per county: the report provides a table and map of vacancy per 1,000 households for each county.  This actually refers to vacancy in unfinished estates, not overall residential vacancy in a county.  Making sense of vacancy in unfinished estates needs to be contextualised with respect to overall vacancy and oversupply, not simply the number of households.  The housing market is not simply unfinished estates and the data as presented is misleading.

Against the government

Services: In the comparing counties data file the reported figures for services are all shockingly bad.  Across the 2,973 estates (again there is no specific data for the 1,770) 57% of units have incomplete roads, 40.1% have incomplete paths, 42.5% have no lighting, 41.1% have no potable (drinking) water, 39.3% have no storm water drainage, 41.3% have no water waste (sewage), with 91,693 families living on these estates.  Actually these figures are grossly overstated because of how they are calculated and the numbers are much less.  They have been calculated against all housing units that had original planning permission, not those that were started.  There are two problems here.  First, planning permission has expired for 24,864 units, second why calculate for units that don’t exist?  The fact that 60,055 phantom houses don’t have potable water, and these are included in the rate of units that don’t have potable water, doesn’t make any sense.  The rates are actually much smaller, though nonetheless are a significant problem on many estates.

What are my headline stories from the report?

I have two main observations from the report.  The first is that 1,100 of the estates are in a ‘seriously problematic condition‘.  Families in these estates are living on building sites.  Second is that only 250 estates (8.5% of 1,770) are active – that is, the developer is on site and is undertaking works.  In 2010 it was 429, in 2011 it was 244.  That means that 1,520 of the estates that require development work are not in receipt of it and given that developers have gone bust they are not likely to receive it in the short to mid-term. The number of underconstruction units in 2011 was 17,872 and in 2012 it was 17,032.  All but 38 of the reduction is ‘nearly complete’ units being fitted out.  Anything half-built is staying half-built.  In the vast majority of cases then, unfinished estates are being left to wither on the vine, the great majority of which are in a ‘seriously problematic condition’.

To be fair to Minister O’Sullivan she fully recognizes these issues.  On the other hand, the actions of the government are painfully slow, some would say pathetic.  As we’ve argued before, the policy of Site Resolution Plans (SRPs) is a minimal cost, minimal effort approach to unfinished estates that give the impression of policy-at-work, but is really a sticking plaster that tries to stop a problem getting worse before the ‘surgeon’ in the form of the market re-appears to fix things.  In the present and foreseeable property market that ‘surgeon’ is not going to appear any time soon.  In the meantime, families are left living on developments that are substandard with huge negative equity that locks them in.

Five years after the property crash started to plummet its time unfinished estates problem was tackled properly, rather than simply messing about with the numbers.  That’s not to say the numbers are not important – we need to know what is going on (preferably with non-creative and meaningless data) – but what we really need is action for the families living on these estates.

Rob Kitchin

Earlier this month Deputy Willie Penrose introduced the Environment and Public Health (Wind Turbines) Bill 2012 into the Dáil. This follows the previous introduction by Senator John Kelly of the Wind Turbines Bill 2012 into the Seanad which failed to progress past second stage.

The history of non-government, private member’s bills would suggest that this latest legislation is largely a political gesture with little chance of advancing into law. The current Government is a strong proponent of renewable energy and is currently negotiating with the British government to boost renewable exports to the United Kingdom. However, it does reflect the growing public and political unease in some rural areas with regard to the increasing number of planning applications for new wind farm developments.

The main feature of the Bill is to establish mandatory minimum setback distances between proposed wind turbines and residential dwellings. These are:

  1. 500 metres, where the height of the wind turbine is up to 50 metres
  2. 1,000 metres, where the height of the wind turbine is up to 100 metres
  3. 1,500 metres, where the height of the wind turbine is up to 150 metres
  4. 2,000 metres, where the height of the wind turbine is greater than 150 metres

Note: Maps now updated with additional 750 metres analysis.

Working with the research team at AIRO, we thought it would be an interesting exercise to examine what such setback distances would mean in practice. Each of the maps below illustrates the extent of the land area in the Republic of Ireland that would remain following the introduction of these exclusion buffers.

Map 1: Set-back > 500m, where the height of the wind turbine is up to 50 metres

Additional Map: Set-back > 750m


Map 2: Set-back > 1,000m, where the height of the wind turbine is up to 100 metres

Map 3: Set-back > 1,500m, where the height of the wind turbine is up to 150 metres

Map 4: Set-back > 2,000m, where the height of the wind turbine is greater than 150 metres

In the case of the 500m setback, just under a quarter (23.75%) of the total land area of the country would remain available for new wind farm development. However, this drops to 13.8% for the 750 metre setback, 9.4% for the 1,000 metre setback, 5.2% for the 1,500 setback and 3% for the 2,000m setback. The vast majority of new wind turbines currently proposed in Ireland are between 100-150m in height. Therefore, in effect, the implementation of these setback distances would result in 95% of the country being excluded for the development of new onshore wind farms.

It is clear from the maps below that majority of the land which would remain available for development is located in mountainous regions, largely along the western seaboard. While these regions do generally have the highest wind speeds, they are also some of our most important sensitive landscapes and tourist assets. They are also the regions where there is the heaviest concentration of important EU designated nature conservation sites. Development in these protected sites is governed by the ‘Precautionary Principle’ where the threshold for permitting new development is set at an extremely high bar. In fact, taking the 1,500 metre setback distance, just 3.25% of the remaining land area lies outside of an EU designated conservation site.

Ireland remains critically dependent on imported fossil fuels and, given energy security and climate change concerns, it is in the vital national interest that we progressively wean ourselves off oil and gas imports.  In the short to medium-term, the achievement of Ireland’s renewable energy targets will require a massive ramping up of onshore wind farms. Currently there is approximately 2,000 MW of installed wind energy capacity in 176 wind farms on the island of Ireland (c.1,100 wind turbines). The Irish Government has an ambitious 2020 target of 40% renewable energy production which will, in broad terms, entail the construction of approximately 6,000 MW. This level of onshore wind energy development will require in the order of 3,000 additional wind turbines. Off-course, post-2020 Ireland will quickly have to move beyond 40% renewable energy production.

Allied to this there is also an ambitious export agenda and Irish Wind Energy Association recently called for a joint government policy to facilitate the achievement of at least 3,000MW of on-shore wind energy to be identified as a minimum deliverable export potential for Ireland in advance of 2020. The proposed “Greenwire” project, which is currently at pre-application stage with An Bord Pleanála, proposes 3,000MW in 40 wind farms throughout the midlands using the world’s largest wind turbines. Mainstream Renewable Power’s “Energy Bridge” project proposes the installation of a further 5,000MW.

There may be a perception that Ireland is full of wide open spaces with plenty of uninhabited regions capable of accommodating new wind farms and associated grid connections. The reality is, however, that Ireland has a highly diffuse settlement pattern and rural Ireland is increasingly becoming a contested space. EU environmental law mandates that a high level of protection is afforded to many remote wilderness areas pushing new wind energy development into ever greater proximity to human settlement. Ireland has an abundant natural wind resource with the potential to deliver clean green energy to sustain our economy and society. However, in order to ensure competing interests are accommodated greater long-term strategic spatial planning is required. The recently published Strategy for Renewable Energy: 2012 – 2020 sets out a series of high-level actions to pump-prime the renewable energy sector. However, it fails to address these pressing and competing issues facing rural Ireland in any meaningful way.

Gavin Daly, Ainhoa González and Justin Gleeson

Since the launch of Census 2011 the AIRO mapping team have developed a series of interactive mapping tools to visualise the results on a national and local authority/regional authority level (see here). This has been a joint project with the Central Statistics Office (CSO) and to date has been very successful with a high number of users viewing and interacting with this publically funded dataset. The aim of this collaboration was to improve access to the results of Census 2011 and thereby make a contribution towards improving evidence informed planning in Ireland. Over the last couple of weeks the team have been working on the recently released Place of Work, School or College Census of Anonymised Records (POWSCAR) dataset.

This dataset contains 2.78 million records where the location of the place of work, school or college was coded for each person on the basis of the reply that was given to Question 34 on  the census form: “What is the Full Name and Address of your place of work, school or college”.

Using this information the CSO matched the employer/school name and address against addresses on the An Post GeoDirectory. In the case of workers, where the coder could not find an exact match they coded to a near match if they could find a GeoDirectory address on the same street or in the same town as the address stated on the form. In the case of students, an exact match was only accepted for the school or college address. The coordinates retrieved from the GeoDirectory match were then linked back to the place of work, school or college Electoral District (ED) and Town and Small Area by superimposing digital boundaries. In some cases it was not possible to match the destination of the worker/student with GeoDirectory, this was a result of a very poor return of address information or the workers destination was classed as being ‘mobile’.  The final dataset is effectively an origin-destination matrix that links the place of residence of the worker/student, either at Electoral Division (ED) or Small Area (SA) level, to the work/school/college destination of the worker/student at the ED, SA and 250m grid level. The dataset contain a wealth of information about each work trip such as age, gender, industry of employment, education level, mode of transport, household occupancy status, one-off housing indicator, socio-economic group etc. Similar data is available about those attending schools/college although not as detailed and much of the data is compressed for disclosure reasons – we will do a further piece on this in a couple of weeks.

In 2011, places of work, school or college with an address in Northern Ireland were also coded in the same way by utilising the NI Pointer address database. NI County, Ward, Towns (2001) and 2001 Census output areas were derived by superimposing digital boundaries. This is a big step forward in understanding the cross-border travel to work catchments that exist in Ireland and the CSO should be commended for realising the benefits of going this extra step in the development of this dataset. Where the person indicated a work, school or college address abroad these records were coded to a specific code to indicate that the person was working abroad i.e. outside Ireland or Northern Ireland.

Due to the level of detail available within the dataset it is not as ‘open’ as the rest of the Census 2011. As there are some minor risks to data disclosure, use of the dataset is restricted and is only available to bone fide researchers who are approved by CSO and signed up as Officers of Statistics for the duration of the research they propose to undertake. A key point on all of this is that All material published from POWSCAR must be approved in advance by CSO.

The following table gives a summary of the POWSCAR address coding process:

  Students Workers Total %
Persons in private households or establishmentsenumerated and resident in Ireland 1,013,292 1,770,644 2,783,936 100.0
Place of work, school or college address (Q34)was matched to a GeoDirectory address point 929,154 1,362,742 2,291,896 82.3
Place of work, school or college address (Q34)blank or uncodeable 78,956 147,251 226,207 8.1
No fixed place of work indicated at Q34 148,177 148,177 5.3
Works from home indicated in Q34 106,055 106,055 3.8
Place of work, school or college address (Q34)was matched to a NI Pointer database addresspoint 3,117 6,419 9,536 0.3
Place of work, school or college address (Q34)overseas 1,447   0.1
Home school indicated at Q34 618   0.0


To get started on work with the POWSCAR dataset the AIRO team have developed travel to work catchments for all 22 Gateways and Hubs and made these accessible via an interactive mapping tool. Each map is based on the percentage of workers within each ED that work within the selected settlement boundary (boundaries based on CSO Settlements). Our analysis here is only based on the workfore where we have information on the destination of workers and therefore excludes those classed as Mobile workers (148,177 or 10% of workers) and workers with an uncodable or Blank destination (147,251 or 9.9%). Users can select a settlement to view the extent of the catchment and then click on an ED to get information on the number/percentage of workers employed within the selected settlement.

The map below details the extent of the travel to work catchment for the Dublin City settlement boundary, an area of about 317 sqkm and including all major employment locations in the local authorities of Dublin City, South County Dublin and DLR. The settlement boundary does not however include many of the large employment locations in south Fingal such as Dublin Airport, Swords, Malahide and Portmarnock. In total there are 457,046 people with a work destination in the Dublin Settlement boundary. Of these, 74% also reside within the Dublin City settlement and 26% reside outside the settlement boundary highlighting the high levels of inward commuting. Of the workers who reside within the Dublin City settlement boundary a total of 12.5% (48,801) commute out of the settlement to employmant destinations.

Red areas on the map highlight where >50% of the workers in an ED are employed within the settlement boundary. The orange band represents areas where over 30% of workers in an ED commute to the Dublin settlement boundary and extend to towns such as Drogheda, Ashbourne, Maynooth, Newbridge, Blessington and Wicklow town. The pale orange band is  based on 10% to 30% of workers and extends much further towards the Mid East, Midlands and parts of the Border region with towns such as Kells, Navan, Mullingar, Portarlington, Portlaoise, Gorey and Dundalk.

To access the tool and view the different catchments for all Gateways and Hubs please click here.  In the map viewer, click on an area to get specific information on that ED.

A link to the tool is also available on our census mapping home page on the AIRO site where you can also access other mapping tools developed over the last number of months. View Census Mapping home page

This is the first step at mapping the travel to work catchments for the main settlements in Ireland. We’re hoping to do some additional work on job’s desnity within settlements and also roll out catchments for other towns. Happy to take suggestions on what is useful for planners, policy makers and general public who would find this information of use.

Justin Gleeson & Eoghan McCarthy

Since the launch of our National Census Mapping Viewer we’ve have been doing some additional work on the Small Area (SA) datasets and are now in a position to add the new maps to the viewer. The availability of SA level data is a major step forward for socio-demographic mapping and evidence informed planning in Ireland and provides a completely new insight to the trends and patterns that are in place across the country.

If we take Maynooth as an example we can see that up to this point the best level of data we had was for the Maynooth ED as a whole. The introduction of the new SA geography now means that Maynooth can be broken down into 49 individual pieces of information for each census variable. As you can imagine this allows for a much greater level of analysis and understanding of what’s happening in the town when looking at variables such as unemployment, population cohorts (0-14, 65plus etc), health, disability, housing type etc.

This morning we’ve added SA maps to the ‘Population’, ‘Religion’ and ‘Nationality’ themes. Users now have a choice of viewing each variable at either the ED or SA spatial scale. Rather than keeping the legends the same for each variable (at ED and SA level) we have opted to let the data distribution define the legends by using ‘natural breaks’ for each variable. For example, this means that a yellow colour on the ED map may not be the exact same range as on the SA map. This is just something to be aware of. Some examples of the maps are below:

Population 65 plus in DLR at SA level

Polish population in Cork City at SA level

Religion (No Religion/Not Stated) mapping in Sligo at SA level

Over the next week we are going to add to the other themes and have organised a release schedule as follows:

  • Population, Religion and Nationality: Friday, 31th August
  • Education and Social Class: Monday, 3rd Sept
  • Principal Economic Status, Industry of Employment and Occupation: Wednesday, 5th Sept
  • Housing, Transport and Communication: Friday, 7th Sept
  • Health and Disability: Monday, 10th September

You can access the National Census Mapping Viewer here:

To view all our other census mapping tools click here: AIRO Census home page

AIRO team

Information Commissioner Emily O’Reilly at the launch of her annual report yesterday argued that:

“Members of the public, who ultimately shoulder the burden of this country’s debt . . . have a right to have all information at their disposal to analyse in an informed manner, the decisions which had, and will continue to have, such a profound effect on their lives.”

She notes a growing trend for public bodies to be removed from the FOI process and demanded it be extended to every public body.

Given that it is taxpayers money that is being used to fund public bodies and generate the data and decisions in the first place, it seems to me that an extremely compelling reason is needed to keep data and information from the public domain.  Often the reasons given are spurious and a smokescreen, such as that of commercial sensitivity used by NAMA.  Whilst there may well be some limited data that would affect the ability of NAMA to operate effectively, to shroud the whole organisation behind such excuses is lamentable.  The same for the Central Bank, NTMA, the Financial Services Authority, and other bodies.

Our AIRO project has been working to persuade state agencies to make their data sets available and to allow us to put their data in the public domain in map and statistical form.   Presently we have around 150 interactive mapping modules online for different geographies (regions, counties, constituencies, local partnerships) including modules concerning housing, unfinished estates, commuting, social deprivation, the live register, crime, all the census data, etc.  The restriction is that the data cannot be used for commercial gain due to data license issues (which is why it requires a login username and password).

There is a massive amount of very useful data locked inside of public bodies that is either not analyzed at all, including by the agency that holds it, or is severly under-analyzed.  We need to gain access to this data both to be able to hold public bodies to account, but just as importantly to undertake evidence-informed analysis and decision making.  My hope is that the government listens and responds constructively to Emily O’Reilly’s plea, and doesn’t try to come up with all kinds of spurious and bogus reasons to dismiss or ignore her argument.

Rob Kitchin

In order to help politicians formulate evidence-based policy and to more fully understand the socio-economic geography of the 43 constituencies, and to be able to compare areas within and between constituencies, the All-Island Research Observatory (AIRO –, a NIRSA project based at NUI Maynooth, is providing free access to its mapping modules for candidates and parties contesting the forthcoming election.  The modules are also free to use for anyone working in the public sector for non-commercial purposes.

Each constituency mapping module has data at the electoral division scale relating to potential voters; population demographics; marital status; religion; economic status; industry; housing; households; social class; socio-economic group; education; transport; deprivation indexes.

Associated mapping modules map the Live Register at office level, unfinished housing estates, planning permissions and housing development, and voting in the last election.

AIRO Election Module Interface

Elsewhere on the AIRO site there is access to data on 12 different themes and hundreds of pre-prepared maps for the whole island. A point and click interface means no mapping expertise is required.

To access the mapping modules
1. Visit
2. Register as a user (top right of screen) or log-on
3. Click on the ‘mapping module’ tab
4. Select ‘Election Constituency Module’
5. In the ‘Choose theme’ box select the constituency you are interested in, then click ‘View’
6. The mapping module will now open
7. To zoom in and out of the map use the scale bar in the top left of the map panel
8. To change the data being mapped click on the ‘Indicators’ button and select the information you wish to view
9. All the panels are interlinked, so if you click in the tables it will highlight on the map and as you hover over the map the area is highlighted in the table
10. The buttons in the bottom right of the panel will open other relevant modules

Justin Gleeson and Rob Kitchin

Unfinished Estates per 1000 Households

Number of inspected unfinished estates per county


According to the latest Quarterly National Household Survey (Q2 2010, QNHS) from the CSO the national unemployment rate currently stands at 13.6%. The current rate has increased from 12.9% in the previous quarter and increased from a rate of 12% a year ago.

The QNHS has been in operation since September 1997 (replacing the old Labour Force Survey) and therefore provides a useful means of illustrating and monitoring labour market trends over time. The bulk of the data available through the survey is only available at a national level, however the survey does provide a breakdown of ILO Economic Status (In employment, Unemployed, In Labour Force, Unemployment Rate and Participation Rate) at a NUTS3 regional level. The unemployment rate here is calculated using the number of unemployed as a percentage of the total labour force and is based on the ILO (International Labour Office) labour force classification. This means that it’s also possible to put the Irish unemployment figures (national and regional) in context with international figures.


From the beginning of the survey up to the end of 2007 the unemployment rate In Ireland initially dropped from 10.4% in Q4 1997 to a low of 3.5% in Q3 2000. From this point up until the end of 2007 the rate remained relatively stable with an average rate of 4.3%. In early 2008 we started to feel the full effects of the downturn with large numbers signing on the live register (see here) and witnessed the subsequent unrelenting climb of the unemployment rate to today’s lofty heights of 13.6% (Figure 1).

Figure 1: ILO Unemployment Rate 2007 to 2010

Much of this increase has been attributed to the collapse of the construction industry and housing boom in Ireland. This has had a major effect on the unemployment rate due to the strong over-dependence of the workforce on construction related employment. A significant number of redundancies in industry related employment have also significantly contributed towards this increasing rate. Figure 2 details the strong dependence of the workforce on construction – at the end of 2006 almost 12.5%(268,400) of the labour force (employed and unemployed) were employed in construction related employment. This figure is now at 5.8% (125,300).

Figure 2: Sectoral Employment as a proportion of Labour Force

Another worrying aspect of the current unemployment trend is the increased number who are now classed as being ‘long-term unemployed’. According to the CSO this relates to those unemployed for one year or more expressed as a percentage of the total labour force. Since the beginning of 2008 the number of people now classed as ‘Long-term Unemployed’ has increased by 97,000. The Q1 2010 figure now represents 5.9% of the total labour force (Figure 3).

Figure 3: % of Labour Force classed as Long-Term Unemployed

European context

As per Q1 2010 the unemployment rate (12.9%) for Ireland was the 6th highest in the EU27 with only the Slovak Republic (15.1%), Lithuania (18.1%), Estonia (19.8%), Spain (20%) and Latvia (20.4%) with higher rates. Our current standing is in stark contrast to the situation 4 years ago when the unemployment rate in Ireland was the lowest in the EU27 at 4.2% (Figure 4). Over this 4 year period Ireland, Estonia, Lithuania, Latvia and Spain have witnessed the greatest increases in unemployment rates. On the other hand countries such as Poland, Germany, Auatria and Malta have improved and unemployment rates have decreased (Figure 5).

Figure 4: ILO Unemployment Rate - Q1 2010

Figure 5: ILO Unemployment Rate - Q1 2006


There is considerable variance in unemployment rates across the country with the highest rate of unemployment currently in the South-East (18.1%) and the lowest in Dublin (11.5%). Dublin currently accounts for 23% of all those classed as unemployed in the country with a total of 69,500. This number has increased by 3.8% since Q1 2010 and by 7.5% in the last year. The rate of increase outside Dublin has been much higher and since Q2 2007 the regions that have been hit the hardest are the South-East, South-West and the West (Figure 6).

Figure 6: % of Labour Forced classed as Unemployed, Q2 2007 and Q2 2010

Justin Gleeson