Nice work by George Megalogenis in The Australian. He (and the Oz) commissioned some housing price data from an outfit called Australian Property Monitors, looking at changes in housing prices by electorate. George and the Oz have presented the electorates recording the top 20 price falls, and the top 20 price increases. The interesting thing is that among the 20 price falls, only four are designated as “marginal seats”. And of those, only three are notionally or actually Liberal-held seats, Lindsay, Dobell and Parramatta (notionally Lib after the 2006 redistribution), and the 2004-2007 housing price falls range between 11.7% in Banks (ALP) to 2.9% in Dobell (Liberal).
Among the divisions recording the 20 highest price increases, 15 are in Western Australia (!), 4 are Queensland (but not in Brisbane), and the other is the Northern Territory; 6 divisions are designated as marginal, but only two are held by the Liberals (Stirling and Hasluck in WA, where housing prices are up 100% and 114.7% since 2004, respectively); I say “but” since the idea is that since housing prices are doing so well there, then perhaps these seats will buck what looks like a substantial trend against the government. Continuing this line, is it possible that voters in places like Capricornia (114% price gains, ALP held seat on a 4.4% margin), will also buck the trend? I also note that WA has made for some interesting election nights, posting surprisingly strong results for the Coalition around the time the picture on the Eastern states has become clear. In short, I don’t see the housing market story as all one-way traffic for either side, but this research certainly does offer a rationalization for the pattern of poll results reported on last week, where NSW seems to be the most pro-ALP state at the moment.
The Oz has been relatively “research-forward” of late; they also commissioned some aggregations of census data from ABS that they published two Mondays ago. Its heartening to see the media actually rounding up data like this: even better would be if they would push it up on their site as a spreadsheet for the rest of us to download and play with (while the Oz can commission data and analysis from ABS and commercial data providers, academics can’t afford it).
Megalogenis foreshadowed this stuff in his appearance on Insiders on Sunday, with some references to housing prices in Sydney’s west, a “two-speed housing market” etc, made me curious as to where he was getting his info, now we know.
In a piece I wrote for Mortgage Nation, the Sims and Warhurst edited collection of essays on the 2004 election, I created a mortgage exposure (“stress”) variable for each electorate by taking [tex]p_i[/tex], the proportion of dwellings in division [tex]i[/tex] classified as “being purchased” in the 2001 Census, [tex]m_i[/tex] the median monthly housing loan repayment in division [tex]i[/tex], and [tex]y_i[/tex], median family weekly income, and forming the indicator [tex]z_i = (p_i m_i)/y_i[/tex], and then normalizing [tex]z_i[/tex] to range from zero to one.
The result is a variable that has a mean of .42, with the 5-th percentile at .11 and a 95-th percentile at .81. The minimum value of this variable, zero, is recorded in Wentworth (NSW), a seat that is both reasonably wealthy and has a high proportion of fully owned and rented dwellings, while the maximum value of one is recorded in Holt (VIC), an outer-metropolitan division in Melbourne with 48.4% of dwellings classified as ‘‘being purchased’’ (the highest such percentage in the country).
This variable held its own in a multiple regression analysis of swing, division by division, recorded at the 2004 election (coefficient of 3, standard error of 1.31, in the presence of numerous other predictors; dependent variable was two-candidate swing to the Coalition, so the implication is that as mortgage exposure goes up, net of other predictors, then so too did Coalition support). The full table of regression results appears below; lots of other controls, including change in Coalition candidate ballot position, incumbency status, etc.
I know this is aggregate-level analysis, and I’m mindful of the perils of cross-level inference, but I’m actually reasonably fond of this model of analysis: the data are reasonably good (Australia has a census every five years), there are 150 divisions in the country, there usually isn’t wild amounts of heterogeneity within each division, and its of great political relevance (since governments are elected division-by-division, not from the national-level 2PP number or preferred PM or whatever). It would be interesting to re-do this analysis either in predictive fashion this time around, or (a little more safely!) post-election, with actual housing price data.
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[...] on housing using a clever mortgage stress variable in a regression on 2004 election outcomes over HERE. Well worth a read if you’re that way [...]
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