The Geography of Actual Sales Prices

The recently releaseed Residential Property Price Register provides actual sales prices of houses and apartments in Ireland since January 2010.  Yesterday we put up a set of interactive graphs of the data along with some commentary concerning its scope and quality.  Today is the turn of some maps and a look at the geography of the actual sales prices.  Below are five maps – the median price of property in each local authority for 2010, 2011 and 2012, actual change in price and percentage change in price 2010-2012.  We’ve used median rather than the mean to try and control for the skewing effects of outliers and errors in the data (as detailed in our post yesterday).

What the maps show is a clear drop in prices across the country (click on the maps for higher-res versions).  In 2010 no local authority had a median below €127,000.  By 2012, nine local authorities have median prices below €100,000 and a further nine below €127,000.  All of these local authorities are predominately rural in character with a clear divide evident between the principal cities and their commuting hinterlands and everywhere else.  In absolute terms, the biggest drop in median prices between 2010-2012 were in Wicklow, Laois and Waterford, all with inexcess of €67,000 drops in median prices. In percentage terms, Laois and Waterford both sustained large drops in median prices, in excess of -40%, and are joined by similar drops in Longford and Roscommon, with Monaghan not far behind (-39.8%).  In contrast, median prices in Dublin, Kildare and Limerick only dropped by between -20-25%.  Perhaps somewhat surprisingly, the percentage median change for Leitrim is only -23.5%, though this is partly reflective of its overall, relatively low prices.  Also see the interactive graphs.

What the maps reveal, in contrast to CSO price index which only provides an overview of residential property prices for Dublin and elsewhere, is that there is a geography to actual sales prices, with prices falling more in some parts of the country than others, affected by local conditions and markets.  There will also be a geography to the market bottoming out and to market recovery.  Whilst the Central Bank report that the market may take up to 18 years to recover, where and when will vary spatially, and we’ll now be able to track such patterns using the PSRA data.

Median residential property price, 2010 (PRSA data)

Median residential property price, 2011 (PRSA data)

 

Median residential property price, 2012 (PRSA data)

Absolute change in median prices 2010-2012 (PSRA data)

% change median prices 2010-2012 (PSRA data)

 

Eoghan McCarthy and Rob Kitchin

 

What to make of the property price data?

The CSO’s residential property price index for June was published yesterday.  After a slight rise of 0.2% in prices nationally in May, the index fell by -1.1% in June.  So after the speculation in the media that property prices might have levelled off, especially in Dublin, it’s back to wondering when they might bottom out.  Last month we argued that we would need 6-9 months of prices staying even or rising slightly before the bottom could be called, that the rise was very marginal at 0.2% and prices were still falling for apartments, and pointed out that as prices have fallen since the peak in 2007 they have gone through periods where the drops have slowed down before falling again (see the interactive graph produced by AIRO).  In other words, not too much should be read into last month’s data as we need a time-series of data before we can talk about a trend with confidence.

There are also other reasons to be cautious about interpreting the data, which are based on mortgage transactions by eight lenders and constitute a three month rolling average.   Here are five of them.

First, because the market is so weak the number of transactions per month is relatively small.  Second, those transactions relate to a market that is not representative of the full range of stock that would be open to the market in normal conditions.  The present market contains a lot of distressed stock and many homeowners are keeping their properties off the market whilst prices are falling.  Third, as yet, the index does not include cash sales which the property sector are suggesting account for up to 30% of the market.  Fourth, due to the first three reasons the CSO itself warns that the index is subject to short-term volatility (“care should still be taken when interpreting monthly figures which may indicate short-term volatility rather than underlying change in longer term price trends”).

Fifth, the data are very circumscribed geographically providing an overview at the national scale, for Dublin only, and nationally excluding Dublin.  The housing market is geographically segmented and becoming more so in the crash.  Areas vary in the type and quality of stock available.  They have varying economic conditions, labour market activity and rates of unemployment.  They have different demographic trends, with some areas experiencing out-migration.  Those looking to buy in different areas have varying access to mortgage credit and some areas are redlined (it is just about impossible to get a mortgage for an apartment outside the four principle cities).  Areas have different rates of oversupply.  Housing vacancy is above 10% just about everywhere except Dublin, Kildare and Meath.  Apartment vacancy is above 18% everywhere and above 40% in a number of local authorities.  As constituted, the CSO index tells us very little with respect to how the market is spatially segmented.  The best data we have for that is the AIRO/DAFT house price mapping tool that provides asking price data 2007-2012 for 2, 3, 4 bed properties for c.1100 areas.  What that data shows is that the range of asking price drops varies from -35% to -65% across the country dependent on the factors above.

So where does that leave us?  Basically, as the CSO itself notes, care needs to be taken when interpreting the RPPI.  Whilst the index provides us with a good long-term overview of the trend in prices nationally and in Dublin, we should be careful not to read too much into monthly figures without putting them into the context of the longer trend and the various limitations with the data.  Moreover, we should be careful about drawing conclusions about local prices from the generalized large-scale aggregations (a classic ecological fallacy issue).  As the AIRO/DAFT data illustrates, National/Dublin aggregated figures are hiding a lot of local variability.  Hopefully, the new house price register might help, though it will not extend back to the peak in 2007 (it will start with 2010).

What is clear from the long-term trend is that prices have fallen substantially from the peak and they are still very fragile and are liable to fall further.  It is only with a run of data where prices are level or rising that the bottom can be called (and the depth of the bottom and its timing will vary around the country depending on the factors above).  Any attempt to call the bottom before then and to talk up the market will be premature.

Rob Kitchin

 

Census 2011: Socio-economic group and class

This is Ireland, Part 2, was released this morning.  It provides macro-level (national and county) results for a broad set of socio-economic data: labour force, occupation, education, health, social class, travel pattern. There are some maps at ED level for unemployment and a couple of occupational sectors, but the full ED and Small Area data set will not be released until later in the summer.  At that stage, we’ll be able to get a much more detailed sense of how the economic crash has played out socio-economically at a local scale.

In this post, I’m just going to concentrate on the socio-economic group and class results.  Analysing these at a county level is problematic because aggregation effects mask the highly variable way in which these play out locally, nevertheless we can see the broad pattern changes.

Socio-economic grouping classifies the entire population into one of ten categories based on the level of skill and educational attainment of their occupation (inc. those at work, unemployed or retired, with dependents classed on the basis of whom they are deemed to be dependent).  There has been growth between 2006-11 (see Figure 1) at the higher, more skilled end of this classification, with increases in employers/managers, higher professional, lower professional and non-manual, whilst those dependent on manual work have declined (in line with job losses in related sectors such as construction).  Moreover, there is a broad spatial pattern to the data with a greater proportion of the highest two categories in and around Dublin reflecting the higher proportion of FDI and public sector jobs around the capital (see Figure 2).

There are also some marked gender contrasts in socio-economic group (Figure 3), with strong differences in the gender profile of some classes.  For example, men make up a much stronger proportion of manual, farmers, agricultural workers, self-employed, and are marginally more likely to be employers/managers, higher professional, semi-skilled and unskilled.  Women make up a strong proportion of lower professional, non-manual and other.  Whilst the balance of the top two classes of employers/managers and higher professional are getting better, it seems that a glass ceiling does still exist.

 

Figure 1

Figure 2

Figure 3

The socio-economic group data is used as the basis for assigning households into a social class, based on almagmating occupations with similar skill sets together to produce seven classes: professional workers, managerial and technical, non-manual, skilled manual, semi-skilled, unskilled and other.  Figure 4 shows the distribution of social class by local authority.  Clearly the standout LAs are in the cities.  DLR has a disproportionate number of professional and managerial/technical classes, whereas Cork City, Waterford City and Limerick City have low rates compared to their surrounding hinterlands, reflecting the suburbanisation of professional/managerial labour.

Figure 4

Rob Kitchin

 

 

Deconstructing the BANAMA Republic – Notes from Monday’s seminar

Much as NAMA merits ridicule and revulsion, it would be a mistake to focus our discussions and analysis on NAMA itself.  Ultimately, NAMA exists because of key dysfunctionalities both in global capitalism and its petty Irish variant, and we should focus on these dysfunctionalities rather than NAMA itself.

This is not to say that we should ignore NAMA in our analyses.  There are two key and interconnected aspects of  NAMA upon which we should focus as geographers.  Firstly there is the very strong geography associated with the building bubble which triggered off the crisis and NAMA i.e. the concentration of bubble investments in the Dublin region and especially the crazy prices being paid for property in the Dublin 4 area, as well illustrated by Sinéad on Monday.  Secondly, there is the geography of sell-off of toxic assets which is what NAMA will essentially be trying to do over the next several years.  A key feature of the whole NAMA debate/discourse has been the absence of any broader vision apart from the singular focus on maximising the return to the state of the sale of NAMA assets.  There has been no mention of the broader economic and social dimensions of the pursuit of high property prices which this focus necessarily entails e.g. keeping house prices above affordable levels, deterring inward investment or skilled in-migration.  There has been no mention of the idea of diverting empty or uncompleted houses to the homeless or those who cannot afford proper accommodation.  And what are the chances that NAMA will utilise its huge property portfolio as a vehicle for creative and imaginative urban planning?

Nevertheless, in my view our prime focus as geographers should be on the processes which brought NAMA into being in the first place, and the negative outcomes of these processes such as the exclusion of large swathes of the population from access to decent housing, the condemnation of further swathes to lengthy commutes with all their environmental and social downsides, the destruction of urban and rural landscapes by ghastly housing developments with no social facilities attached, the plastering of flood plains with concrete with no accountability on the part of those responsible and, following the crash, the creation of ghost estates and the sacrificing of public services for the needy in order to bail out the very people who got us into this mess in the first place.  We also need to look at how communites have been coping, or can cope, with the impending nightmares of NAMA-land and how resistance can be mobilised against the “There is no alternative” brigade.  Above all, we need to identify a different vision for Irish society in which bubble behavious has no part.

In terms of specific pieces of research, the following ideas were aired at last Monday’s sessions:

Local inventories of empty and unfinished housing, shopping and commercial developments, and of land bought for development purposes but now lying idle.  Can we organise geography students to carry out the required research on the ground?  This would be a wonderful form of education and consciousness for the students concerned as well as generating the data required for a detailed deconstruction of the NAMA-scape.

The local geographies of commuter towns created by the bubble, and the ghost estates created by its bursting.

How are people trapped in negative equity and in unfinished housing developments coping and organising?

New forms of land management and planning which give priority to social need over private profit.

New forms of regional planning which will spatially disperse development pressures and cool down property markets.

How have cities and communities in other countries been impacted by the downturn and how are they coping?

What will be the spatial impacts of the measures to be introduced in the forthcoming budget?

The distinctive geographies of the new unemployed.

The geography of loan defaults and foreclosures.

Emerging geographies of post-crash social pathologies (drugs, illness, suicide, crime, violence).

Identify and monitor a set of indicators of distress arising from the crash.

A geography of An Bord Pleanála decision-making and how this might have fed the crisis.

Create a central repository for titbits of information relating to the crisis which may be of use for research purposes.

Proinnsias Breathnach