Now here's a report that will excite you!
Alan Oster Chief Economist NAB Ltd
It is from an Economics Paper presented at the Uni of WA
What Determines House Prices: What the Australian Data Tells Us page 10
In this section, we attempt to put a little more rigour into an explanation of what drives house prices – or at least what the Australian data points to. In terms of a longer run relationship clearly one would expect that the key drivers of HBA to be important – namely interest rates and household incomes. Beyond that, population growth, on the supply side, could also be expected to be important. Thus, we begin by estimating a long run (co-integrating) log linear equation of the type:
LnHPt = α0 + α1 Ln (Pop) t + α2 Ln (HDY)t + α3 Ln (i/p)t
Where: HPt equals Australian house prices (as calculated in the previous section – i.e. using REIA state data, weighted by state real estate transfer expenses from the national accounts)7; Popt is Australian population; HDYt is nominal household disposable income; and i/p t is real interest rates using the 90 bill rate deflated by the previous twelve month rate of increase in the trimmed mean CPI. We would expect that α1 α2>0 and α3<0 – that is, house prices move up with further growth in population and income but down in the face of higher real interest rates. Estimating the equation from 1983(1) to 2005(1) produced the following:
LnHPt = -38.69** + 3.80 Ln(Pop)t** + 0.489 Ln (HDY)t** - .108 Ln(i/p)t**
R^2 = .982 σ = .02 **is significant at the 5% level.
Isn't that just rivetting?
Enjoy
cheers
Alan Oster Chief Economist NAB Ltd
It is from an Economics Paper presented at the Uni of WA
What Determines House Prices: What the Australian Data Tells Us page 10
In this section, we attempt to put a little more rigour into an explanation of what drives house prices – or at least what the Australian data points to. In terms of a longer run relationship clearly one would expect that the key drivers of HBA to be important – namely interest rates and household incomes. Beyond that, population growth, on the supply side, could also be expected to be important. Thus, we begin by estimating a long run (co-integrating) log linear equation of the type:
LnHPt = α0 + α1 Ln (Pop) t + α2 Ln (HDY)t + α3 Ln (i/p)t
Where: HPt equals Australian house prices (as calculated in the previous section – i.e. using REIA state data, weighted by state real estate transfer expenses from the national accounts)7; Popt is Australian population; HDYt is nominal household disposable income; and i/p t is real interest rates using the 90 bill rate deflated by the previous twelve month rate of increase in the trimmed mean CPI. We would expect that α1 α2>0 and α3<0 – that is, house prices move up with further growth in population and income but down in the face of higher real interest rates. Estimating the equation from 1983(1) to 2005(1) produced the following:
LnHPt = -38.69** + 3.80 Ln(Pop)t** + 0.489 Ln (HDY)t** - .108 Ln(i/p)t**
R^2 = .982 σ = .02 **is significant at the 5% level.
Isn't that just rivetting?
Enjoy
cheers
