RDP 2014-04: Home Price Beliefs in Australia Appendix D: Economic Decisions Output

Callan Windsor, Gianni La Cava and James Hansen

May 2014 – ISSN 1320-7229 (Print), ISSN 1448-5109 (Online)

The regression output from Equation (8) is presented in Table D1.

Table D1: Homeowners' Decisions and Home Valuation Differences
SPENDINGpt DEBTpt HDEBTpt FINSHAREpt EQSHAREpt
Sale price Inline Equation 0.304*** 0.298** 0.466*** −0.017 0.031***
Valuation difference 0.338*** 0.817** 0.384*** 0.159*** 0.072***
Adults 0.101*** −0.110 −0.071 −0.010 −0.007
Children 0.105*** 0.320*** 0.116*** −0.028** −0.008
Age 0.034*** −0.026 −0.019 0.023*** 0.005**
Age2 −0.0004*** 0.0001 0.0001 −0.0002*** −0.0000
Tenure −0.000 −0.082*** −0.048*** 0.006*** 0.002
Tenure2 −0.0000 0.0014*** 0.0005*** −0.0001** −0.0000
Log income 0.174*** 0.167 0.077* 0.072*** 0.024***
Unemployment −0.017 −0.021 0.048 0.040*** 0.023***
Education 0.073 0.101 −0.083 0.066*** 0.015
Time fixed effects Yes Yes Yes Yes Yes
R2 0.499 0.243 0.293 0.320 0.209
Observations 1,708 731 2,423 747 747

Notes: Bootstrapped robust standard errors clustered at the postcode level; ***, ** and * indicate significance at the 1, 5 and 10 per cent level, respectively; the dependent variables SPENDINGpt , DEBTpt and HDEBTpt are in log levels; the dependent variables FINSHAREpt and EQSHAREpt are measured as ratios; the SPENDINGpt regression is estimated over the period 2006 to 2011, for which there was comprehensive expenditure data; the DEBTpt , FINSHAREpt and EQSHAREpt regressions are estimated on the wealth module years of 2002, 2006 and 2010; the HDEBTpt regression is estimated over the period 2002 to 2011

Sources: APM; HILDA Release 11.0; authors' calculations

The coefficients on the control variables for the spending regression are unsurprising. The sign and significance of the age variables – capturing the average age of homeowners within postcodes – as well as the variables for the average number of children and adults per family within postcodes, suggest that these variables capture the life cycle of spending. Furthermore, the coefficients on education and disposable income levels within postcodes show that postcode-level spending is associated with our proxies for lifetime income.

Looking at the estimated coefficients on the controls for the other dependent variables, we find that, on average, postcodes with older homeowners hold more wealth in financial assets; higher-income postcodes hold more housing debt and more wealth in financial assets while more educated postcodes also hold more wealth in financial assets.