Paper examining the residential preferences of creative and knowledge workers in Dublin (by Philip Lawton, Enda Murphy and Declan Redmond) published in Cities (Vol 31, April 2013) available on the UCD Research Repository. Click here for PDF
Data
April 19, 2013
Residential Preferences of the ‘Creative Class’?
Posted by irelandafternama under Data | Tags: 'Creative Class', Dublin, Residential Preferences |Leave a Comment
February 19, 2013
Vacancy at individual property and town level
Posted by irelandafternama under Data | Tags: apartments, Census 2011, holiday homes, houses, Ireland, towns, vacancy |1 Comment
Prompted by a colleague, I’ve been browsing the CSO Census report, The Roof over our Heads. It is full of information from the Census 2011 on households and housing in Ireland. I’ll probably blog about some of the other material at some point, but I thought it might be useful to point to some of their data on housing vacancy, a familiar topic on this blog.
In the report, the CSO produce an interesting map of all vacant residential address points in the country classified as vacant houses, vacant apartments and holiday homes. There is little chance of identifying individual properties from this map as it is a scale of 1: 1 million, but by plotting the individual units as opposed to shading in areas we can get a sense of the scale of the issue (which in numeric terms is: 168,427 vacant houses; 61,629 vacant apartments; 59,395 holiday homes; out of total stock of 1,994,845 residential units).
There is clearly a patterns to holiday homes, concentrating on the coast, as well as the upper and lower Shannon. Vacant apartments are mainly confined to large urban areas. And whilst, there is much media talk at present concerning a shortage of family homes in Dublin, the data reveal there is no shortage of apartments. In fact, there are 16,321 empty apartments in Dublin City, let alone the other Dublin local authorities. As for vacant houses, they are everywhere. The few blank spots are mountains or remote areas.
The CSO report also provide some data on towns with the highest levels of vacancy, both including and excluding holiday homes. The table below lists the seven towns with the highest levels of vacancy excluding holiday homes. In the case of Tulsk and Ballaghaderreen, two places I have some familiarity with, there is a strong correlation with the presence of unfinished estates. However, as we have discussed elsewhere, unfinished estates are just one element of vacancy given that there are only 16,881 vacant properties on such estates, meaning there is a high degree of background vacancy in many locations beyond unfinished estates (see our AIRO VacantIreland interactive mapping tool that let’s you examine vacancy at Small Area level and individual unfinished estates).
Rob Kitchin
February 15, 2013
Ireland’s house prices in comparison to EU27, 2007-2012
Posted by irelandafternama under Commentaries, Data | Tags: comparison, EU27, Europe, Eurostat, house prices, Ireland |Leave a Comment
Eurostat, the European statistics agency, recently released the Q3 2012 results for its pan-European house price index (HPI). The data charts house prices on a standardized basis for 2007-2012, baselined against Q2 2010 (=100). The index tracks price changes of residential properties purchased by households (flats, detached houses, terraced houses, etc.), both newly-built and existing stock. The Member States’ HPIs are compiled by the national statistical institutes, while Eurostat calculates the euro area and EU HPIs.
The AIRO team have compiled these data into an interactive data visualization accessible on the AIRO website.
What the data allow is a comparison of whether house prices have gone up or down over time with respect to the baseline. For example, if we consider Ireland against a baseline of 100 in Q2 2010, in Q3 2007 house prices were indexed at 151.7 but had fallen to 75.3 by Q2 2012. In other words, house prices had halved in valued over that period.
What the data reveal is that during this period of European financial crisis property markets behaved in four different ways across Europe.
1. Prices have declined continuously, either steeply in the case of Ireland, Spain, Romania and Bulgaria or more modestly such as the Netherlands and Cyprus.
2. Prices declined and then have either levelled off (e.g. Denmark, Slovenia) or have bounced back modestly (Estonia, Latvia, Lithuania, which all experienced very dramatic and rapid declines).
3. Prices have bounced along within a few percentage points of the baseline (e.g., Austria, Czech Republic, France, Greece, Hungary, Italy, Malta, Slovenia, UK) and effectively have flatlined.
4. Prices have increased modestly but steadily (e.g., Belgium, Finland, Germany, Luxembourg, Sweden).
These differences arise due to issues such as the nature of the national housing markets (e.g. proportion of renters/owner-occupiers), the robustness of the wider economy during the crisis, and wider property market issues such as levels of oversupply where excess supply, coupled with a financial crisis linked to property, work to depress prices in the absence of sufficient demand that would halt decline.
There is tentative evidence that the Irish decline might be starting to level off, but we need a few more quarters of data to reveal whether this is a sustained trend. The decline, however, has been the worst in Europe in terms of sustained, rapid decline with no levelling off or bounce back.
Justin Gleeson, Eoghan McCarthy, Rob Kitchin
January 31, 2013
Initial Output Area maps of Northern Ireland Census 2011
Posted by irelandafternama under Data | Tags: Census 2011, mapping, Northern Ireland, output areas |[2] Comments
The latest tranche of Census 2011 results for Northern Ireland were released yesterday. They provide information of demography, identity, health, housing, education, labour markets, and travel and migration at a variety of geographic scales: 18 Assembly Areas, 26 Local Government Areas, 582 electoral wards, 890 Super Output Areas, and 4,537 Small Areas. Data is available for download here and accompanying mapping boundaries here (Great work by NISRA and a good example of open data)
The rich diversity of data released, and its detailed geographic resolution, enables the general public, policy makers, government and business to better understand the people and places of Northern Ireland in 2011, and the trajectories of change over time, and provides a fresh evidence base for formulating new policy and business plans. Indeed, fresh evidence was needed as Census 2001 has been used as a core base for policy formulation right up to this new release, despite it being over a decade old. What the data makes clear is that whilst there is some continuity, there has also been much change with respect to Northern Irish society and economy over the past decade. By mapping the data and undertaking time-series analysis it will be possible to understand the processes shaping different facets of everyday life and to model future scenarios for planning purposes.
To get started on all of this we have developed an interactive mapping tool for the Northern Ireland Output Areas (OA) and selected some interesting variables for Day 1: Population, National Identity, Religion, Qualifications and Unemployment. Have a look at the new mapping tool here
Over the coming weeks we’ll add to this tool and will also start on our new INTERREG funded project (with colleagues at ICLRD) that will allow us to develop a very comprehensive All-Island Census Mapping Atlas that will look at change on the island from 2001 to 2011.
Justin Gleeson
January 25, 2013
EU27 Unemployment Rates – Jan 2007 to Nov 2012
Posted by irelandafternama under Data | Tags: AIRO, Data, data visualization, unemployment |1 Comment
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:
http://www.airo.ie/news/eu27-unemployment-rates-jan-2007-nov-2012
Eoghan McCarthy
December 12, 2012
Northern Ireland census data visualization
Posted by irelandafternama under Commentaries, Data | Tags: 2011, age groups, census, country of birth, data visualization, economic status, national identity, Northern Ireland, religion |1 Comment
The AIRO team have produced an interactive data visualization of the initial results of the Northern Ireland census 2011. The data visualization shows the results at district and province level for religion, economic status, national identity, country of birth, and age groups.
With respect to religion the headline statistics was that the percentage of the population who self-declared themselves Catholic has risen to 45.1%, just three percent less than self-declared Protestants (48.4%). 5.6% declared no religion and 0.9% other. However, it one looks at the data at district level it is clear that very few districts have such a near 50/50 ratio of Catholics/Protestants. Rather, most districts have a clear religious majority.
The economic status shows that 467,805 people are in employment, but also that 10,957 people who are unemployed have never worked and 29,324 are classed as long term unemployed. Worryingly, of those unemployed over 40 percent in all districts are long term unemployed, illustrating the difficulties of re-entering the labour force after job loss in the present recession.
38.9% of the population of Northern Ireland declare themselves to be British, 25.3% Irish, 20.9% as Northern Irish, 6.1% as both British and Irish, and 5% as other. Clearly the declaration of British maps somewhat imperfectly onto Protestant and the relationship between religion and nationality is by no means synonymous.
More than ten percent of the population were not born in Northern Ireland. 3.6% were born in England, 2.1% in the Republic of Ireland, 2% in EU Accession countries, 2% other, 0.85% Scotland, 0.54% elsewhere in Europe, 0.14% in Wales.
The population is quite youthful with 20.9% of people aged 0-15 and 12.6% aged 16-24. 27.5% are aged 25-44 and 24.4% aged 45-64. 14.6% of the population is at retirement age or older (65+) (the EU average is 16%).
Rob Kitchin and Eoghan McCarthy
November 21, 2012
Travel to Work Catchments – 2011 POWSCAR results
Posted by irelandafternama under Commentaries, Data | Tags: census, CSO, Data, powscar, travel to work |[8] Comments
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 |
AIRO POWCAR Mapping:
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
October 10, 2012
Measuring Ireland’s progress: benchmarking against the past and other EU countries
Posted by irelandafternama under Data | Tags: 2011, CSO, economy, environment, Measuring Ireland's Progress, society |[2] Comments
Today saw the publication of Measuring Ireland’s Progress 2011 by the Central Statistics Office. Based on 109 indicators, the report provides a fascinating summary of (a) how Ireland has changed over the past decade as it has transitioned from the Celtic Tiger to the crash; (b) a comparison of how Ireland is performing with respect to 32 other European countries. The full report is here and a short, but detailed, summary is here.
In total, data is provided with respect to 109 indicators covering 10 domains and 49 sub-domains. I’ve list all these domains, sub-domains and indicators below to illustrate the richness of this resource for making sense of how Ireland was faring economically, socially and environmentally in 2011. The report is well illustrated with graphs and maps, and provides data in table form. Well worth a read if you want to get a synoptic overview of the country vis-a-vis the past and our neighbours.
1. Economy
Gross Domestic Product
1.1 Ireland: GDP and GNI
1.2 EU: GDP and GNI at current market prices
1.3 EU: GDP growth rates
1.4 EU: GDP per capita in Purchasing Power Standards
Government debt
1.5 Ireland, EU and Eurozone: General government consolidated gross debt
1.6 EU: General government consolidated gross debt
1.7 EU: General government consolidated gross debt map
Public balance
1.8 EU: Public balance map
1.9 Ireland and Eurozone: Public balance
1.10 EU: Public balance
1.11 Ireland: Central and Local Government current expenditure
Gross fixed capital formation
1.12 Ireland and EU: Gross fixed capital formation
1.13 EU: Gross fixed capital formation
International transactions
1.14 EU: Current account balance
1.15 EU: Direct investment flows
International trade
1.16 EU: Exports of goods and services
1.17 EU: Imports of goods and services
Exchange rates
1.18 International: Bilateral euro exchange rates
1.19 Ireland: Harmonised competitiveness indicator
Harmonised Index of Consumer Prices
1.20 Ireland and EU: Harmonised Index of Consumer Prices
1.21 EU: Harmonised Index of Consumer Prices
Price levels
1.22 Ireland and EU: Comparative price levels of final consumption by private households
including indirect taxes
1.23 EU: Comparative price levels of final consumption by private households including
indirect taxes
2. Innovation and technology
Science and technology
2.1 Ireland: Mathematics, science and technology graduates
graduates
2.2 EU: Mathematics, science and technology PhDs awarded
Research and development expenditure
2.3 Ireland and EU: Gross domestic expenditure on R&D
2.4 EU: Gross domestic expenditure on R&D
Patent applications
2.5 Ireland and EU: European Patent Office applications
2.6 EU: European Patent Office applications
Household Internet access
2.7 Ireland: Private households with a computer connected to the Internet
2.8 EU: Private households with Internet access
3. Employment and unemployment
Employment rate
3.1 Ireland: Employment rates by sex
3.2 EU: Employment rates by sex
Labour productivity
3.3 Ireland: GDP in Purchasing Power Standards per hour worked and per person employed
3.4 EU: GDP in Purchasing Power Standards per person employed
Unemployment rate
3.5 Ireland and EU: Unemployment rates
3.6 EU: Unemployment rates by sex
3.7 Ireland and EU: Long-term unemployment rates
3.8 EU: Long-term unemployment rates by sex
Jobless households
3.9 Ireland: Population aged 18-59 living in jobless households
3.10 EU: Population aged 18-59 living in jobless households
Older workers
3.11 EU: Employment rate of persons aged 55-64 by sex
4. Social cohesion
Social protection expenditure
4.1 Ireland and EU: Social protection expenditure
4.2 EU: Social protection expenditure in Purchasing Power Parities per capita
4.3 EU: Social protection expenditure by type
Risk of poverty
4.4 EU: At risk of poverty rates
4.5 Ireland: At risk of poverty rates by age and sex
4.6 Ireland: Persons in consistent poverty by age and sex
4.7 Ireland: Persons in consistent poverty by principal economic status
Gender pay gap
4.8 EU: Gender pay gap
Voter turnout
4.9 Ireland: Numbers voting in Dáil elections
4.10 EU: Votes recorded at national parliamentary elections
Official development assistance
4.11 Ireland: Net official development assistance
4.12 EU: Net official development assistance
5. Education
Education expenditure
5.1 Ireland: Real current public expenditure on education
5.2 Ireland: Student numbers by level
5.3 EU: Public expenditure on education
Pupil-teacher ratio
5.4 EU: Ratio of students to teachers
5.5 EU: Primary and lower secondary average class size
Third-level education
5.6 Ireland: Persons aged 25-34 with third-level education
5.7 EU: Persons aged 25-34 with third-level education by sex
Literacy
5.8 Ireland: Student performance on the reading, mathematical and scientific literacy
scales by sex
5.9 EU: Student performance on the reading, mathematical and scientific literacy scales
Early school leavers
5.10 Ireland: Early school leavers by labour force status and sex
5.11 Ireland: Proportion of the population aged 20-64 with at least upper secondary education
5.12 EU: Early school leavers
6. Health
Health care expenditure
6.1 Ireland: Current public expenditure on health care
6.2 EU: Total expenditure on health as percentage of GDP
Life expectancy
6.3 Ireland: Life expectancy at birth and at age 65 by sex
6.4 EU: Life expectancy at birth by sex
7. Population
Population distribution
7.1 Ireland: Population distribution by age group
7.2 Ireland: Household composition
7.3 EU: Population
7.4 EU: Population change
Migration
7.5 Ireland: Migration and natural increase
7.6 Ireland: Immigration by country of origin
7.7 Ireland and EU: Rate of natural increase of population
Age of population 7.8 Ireland: Age dependency ratio
7.9 EU: Young and old as proportion of population aged 15-64
Fertility
7.10 Ireland and EU: Total fertility rate
7.11 EU: Total fertility rate
Lone parent families
7.12 Ireland: Lone parent families with children aged under 20 by sex of parent
Living alone
7.13 Ireland: Persons aged 65 and over living alone by sex
Divorce
7.14 EU: Divorce rate
8. Housing
Dwelling completions
8.1 Ireland: Dwellings completed
8.2 Ireland: Nature of occupancy of private households
Mortgages
8.3 Ireland: Housing loans paid
8.4 Eurozone: Interest rates for household mortgages (new business)
9. Crime
Recorded crimes and detection
9.1 Ireland: Recorded crimes by type of offence rates
9.2 Ireland: Detection rates for recorded crimes
Recorded incidents
9.3 Ireland: Recorded incidents of driving/in charge of a vehicle while over legal alcohol
limit per 100,000 population
9.4 Ireland: Recorded incidents of burglary per 100,000 population
9.5 Ireland: Recorded incidents of controlled drug offences per 100,000 population
Murder/manslaughters
9.6 Ireland: Recorded victims of murder/manslaughter
10. Environment
Greenhouse gases
10.1 Ireland: Total net greenhouse gas emissions
10.2 EU: Net greenhouse gas emissions and Kyoto 2008-2012 target
Energy intensity of economy
10.3 Ireland: Gross inland consumption of energy divided by GDP
10.4 EU: Gross inland consumption of energy divided by GDP
River water quality
10.5 Ireland: River water quality
Urban air quality
10.6 Ireland: Particulate matter in urban areas
Acid rain precursors
10.7 Ireland: Acid rain precursor emissions
Waste management
10.8 Ireland: Total municipal waste generated, recovered and landfilled
10.9 EU: Municipal waste generated and treated
Transport
10.10 Ireland: Private cars under current licence
10.11 EU: Passenger cars per 1,000 population aged 15 and over
10.12 Ireland and EU: Share of road transport in total inland freight transport
10.13 EU: Share of road transport in total inland freight transport
10.14 Ireland and EU: Index of inland freight transport volume
10.15 EU: Index of inland freight transport volume
Rob Kitchin







March 11, 2013
Property tax evaluation model and what it means for residential property owners
Posted by irelandafternama under Commentaries, Data | Tags: Ireland, method, model, property tax, technical paper, valuation |[3] Comments
The Revenue Commissioners have published a technical paper setting out the method used to calculate the estimated property tax values to guide home owners in the self-evaluation of the tax due on their property. The model is a hedonic econometric regression model, which is the standard method of estimating and tracking property values.
In many ways, the problem for the Revenue has not been the method to use, but assembling a set of data that can provide robust estimates. To this end, they have bought together property characteristics from a range of sources:
• Valuation data from the Revenue’s electronic stamp duty system, NAMA, and valuations commissioned by Revenue from professional valuers.
• Geo-Directory (the national address database): a list of all properties in Ireland, their type and location;
• Spatially derived data that indicate relative distances of all residential properties from a series of key amenities and services that add value to property;
• Geographically linked data from sources such as the CSO’s 2011 Census that provide characteristics about areas.
Sources of data used in estimating property tax
Having excluded a number of transactional data for various reasons (where the return indicates the transaction is a part of a larger series of transactions; where the return indicates a fractional interest in the property is being transferred; where the return indicates shared ownership; values under €25,000) the result is a dataset of 17,400, 15,000 and 19,200 transactions for 2010, 2011 and 2012 respectively. This set is relatively small as it based only on transactions since 2010.
34,400 (67 per cent) of these 51,600 properties were successfully matched to a Geo-Directory address point, thus providing property values for units at known locations. These are spread:
• Dublin (Dublin City Council, Dun Laoghaire-Rathdown County Council, Fingal County Council and South Dublin County Council) – 15,693 properties;
• Other cities (Cork Corporation, Limerick Corporation, Galway City Council and Waterford Corporation) – 3,039 properties;
• Rest of the country (all remaining county councils) – 18,014 properties.
These properties with known values provided a basis on which to estimate the value of near-by property with similar characteristics in each Electoral District in the country. Ideally, it would have been preferable to provide estimates for Small Areas given the variation in stock in an ED, but the relatively small data set precludes doing this robustly and EDs are the best that can presently be achieved.
Given that the value of property varies geographically, rates differ across the country, with the highest mean values in Dublin and the Leinster region.
The vast majority of properties are valued in the lower bands, reflecting the 50% fall in residential prices since 2008. Indeed, 91.3% of residential units are estimated to be worth less than 300K, with 60.6% less than 150K. I can imagine that the low estimated value of many properties might come as a shock to many homeowners and reveal the extent to which they might be in negative equity.
What this means is that the property tax value for 60.6% of residential property owners is estimated to be €225 or less per annum. For another 22.7% it will be €315, 8% it will be €405, and 3.1% it will be €495. Only 8.3% of residential property owners will pay €585 or more.
As with any model, the one developed by Revenue is not going to be 100 percent accurate and they provide some estimate as to the probability that the valuation is in the correct band. 91% are either in the right band, or one band above or below.
This suggests that there might be some horse-trading between property owners and Revenue as to whether they are in the right band or one very close to it, but in the main their estimates will be quite near to the actual value and the haggling will be over c.80-90 euro difference in cost between adjacent bands (with I suspect all challengers looking to move downwards).
To be fair to the Revenue Commissioners the approach they have taken is the industry standard and they have used all the possible data at their disposal. Their problem has been the small number of known valuations to work from and a lack of information about every property (type, number of rooms, etc). As such, the model seems to be as robust as it can be given the data constraints, though it is not without its issues such as having to provide estimates for EDs rather than Small Areas.
Rob Kitchin
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