There is no official data regarding negative equity in Ireland in general, nor its geographical distribution.  By mid-2012, once house prices had fallen to 50% of their 2007 values Davy Stockbrokers estimated that more than 50% of residential mortgages were in negative equity.  Consequently, any house bought from 2000 onwards is likely to be in negative equity.

Negative equity is a significant issue because it creates a spatial trap that restricts mobility. Because the value of the property is less than was paid for it, owners cannot sell and move to another property without realising a loss.  This trap has three consequences.  First, it restricts labour market mobility.  Second, it keeps families in homes that may no longer be suitable to their needs.  Third, it restricts the pool of properties available to the market and limits any recovery to first time buyers, those prepared to realise a loss, those whose property is not in negative equity or have investment capital.  All three have social and economic consequences causing hardship and stress and slowing the recovery of the wider economy.

Negative equity is not evenly distributed because it is determined by the price paid relative to present prices and this is largely shaped by when the house was bought.  So where might this spatial trap be operating most perniciously in Ireland?

This is not an easy question to answer given publicly available data sources.  We have been looking at proxy measures and present one here, though it should be noted that it only captures one kind of property in negative equity – houses that were built post-2001.  It does not include secondhand houses in negative equity, nor buy-to-let properties in negative equity (though the latter can be estimated using a same method).

Our solution is to use two Census 2011 variables at the Small Area level. The first variable is the ‘% of housing units built post 2001’.  The second variable is the ‘% of outstanding mortgages in an area’ (i.e., the property has been purchased not rented privately or from a local authority or voluntary body).  These variables are not perfect, but when combined do give us, we think, a reasonably good proxy.

The figure below is a density smoothed scatterplot of the two variables for all 18,488 Small Areas in the country.  Each Small Area has approximately 80-130 households.  We have divided up the scatterplot into four quadrants, one of which is subdivided based on the clear pattern of points, to create six categories that denote different levels of negative equity (category 1 has very low rates of both post-2001 build and outstanding mortgages), which we have then mapped from the country and for Dublin.

negative equity



It is important to note that all the Small Areas potentially have some households in negative equity, but that some areas have greater concentrations than others.  In broad terms, categories 5 and 4 are likely to have similar levels of private residential negative equity, but we have left them separate to denote their different characteristics.

When these categories are mapped the pattern that emerges is perhaps what one would expect.  The areas with the highest concentrations of negative equity are in the outer suburbs of the cities and the fringes of commuter towns.  These areas experienced high rates of newly built properties and new household formation all through the boom, but especially in the latter years when the inner suburbs became too expensive for first time buyers and those trading up to a family home.

This pattern is very clear around Dublin, Cork and Limerick, but is slightly different around Galway, where a number of rural Small Areas are highlighted where there was a lot of one-off housing and small nucleated settlement.  This pattern is repeated for many smaller rural towns.

Owner occupiers in these areas are more likely to be spatially trapped, though as noted any individual household in any part of the country could be suffering such a fate.  It is also likely that the same areas will have higher concentrations of mortgage arrears, given that negative equity and mortgage arrears are related.

Whilst further research is needed to refine this analysis it does give a proxy measure of one kind of negative equity in the absence of detailed data from mortgage providers.  We would be interested in any feedback about the approach taken.

Rob Kitchin


Today marks the launch of the property value interactive map tool, put together by Ronan Lyons (Oxford University) and Justin Gleeson (AIRO/NIRSA, NUI Maynooth). The system provides the first, detailed localised view of the property market in Ireland based on 1.1 million property records (the CSO residential property price index divides the data into national and Dublin only).

Importantly, it provides comparable data from 2007-2012, allowing us to see the change in sales and rental prices and expected yield over the course of the crash for 2, 3 and 4 bed properties (the new government house price database when it is released will only provide data concerning 2010 onwards). Sales data is provided for 1,117 areas, rental data for 312 areas, and yields for 4,509 areas. The method for calculating the average price per area is set out in this paper by Ronan Lyons.  The methodology used makes each area comparable by controlling for differences in properties (such as type and size), and it should be noted that each area covers a range of locales and provides an average drop in price.

The tool is fully interactive and free to use; to access it go to  To get detail on any area click on it and a pop-up box will appear providing data about that locale.  Scroll down the pop-up box to see a graph relating to the area.  If you hover over the bars in the graph the specific data will appeal.

The data is broadly in line with the CSO data re. total price drop, but shows the variance across the country. Nearly all areas in the range -40 to -60% (a reasonably large range).  A few areas are above -60%, and a few below -40%.  What the data reveals that there are local markets operating across country reflecting local conditions.  Whilst the data are asking prices they are very strongly reflective of actual sales price (which the property sector generally reports as being between 10-15% less than asking price) and shows relative prices and change across country as the data is consistent across space and time.

Hopefully the server will hold up this morning as people try out the tool.  If you have difficulty getting access, please try again later.  Also check out the dozens of other mapping and data visualisation tools on the AIRO website.

Rob Kitchin (@robkitchin) and Justin Gleeson (@AIRO_NUIM) (Ronan is on twitter at @ronanlyons)

Following on from our Census mapping work from last week, we thought it would be interesting to overlay the 2,876 unfinished estates identified by the Dept of Environment through their housing development survey over the vacancy rates at Small Area level calculated from Census 2011.  (more…)