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 – vacanthomes.ie – 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.
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:
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
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