Latest Greater Sydney Mortgage Stress Mapping

Following on from yesterday’s post, where we listed the post codes with the largest number of currently mortgage stressed households, we will now go into more detail across the main states. We commence this journey of pain by looking at NSW, where of course home prices have risen strongly, mortgages are large, and incomes static. Not a good recipe in a rising interest rate environment.

First we list out the top 20 post codes in stress across the state (by number of households in stress). The top three are Leumeah (2560), Chipping Norton (2170) and Bidwell (2770), all in the Sydney region. Next is South Tamworth (2340) and then Macmasters Beach on the Central Coast (2251).

Next, here is a geo-map of the Greater Sydney region with the counts of households shown. The blue areas are those with the highest counts.

We should make the point that mortgage stress measurement is getting at the current state of household finances, and is an indication the relative pressure on household budgets among households with owner occupied mortgages in the low wage growth economy. These in severe stress are nearer the edge in terms of mortgage repayments, but of course, given the significant capital growth in the region, most households will have sufficient equity to sell and repay the mortgage if need be. Thus, when we overlay our economic projections to derive a measure of default probability by end 2017, this is an indication of households missing a mortgage repayment (30-day default), not bank losses, which in our modelling remain extremely low.

The mortgage books in this region are bolstered by rising equity, Lenders Mortgage Insurance on higher LVR loans, many households paying ahead (though not those in stress) and current low interest rates. However, the scenario might change were rates to rise, home prices to slide and unemployment or underemployment were to rise.

We will look at Brisbane next time.

 

Author: Martin North

Martin North is the Principal of Digital Finance Analytics