RDP 2020-03: The Determinants of Mortgage Defaults in Australia – Evidence for the Double-trigger Hypothesis 2. What Can Previous Research Tell Us?

The literature on mortgage defaults is large and broad-ranging, particularly for the United States. Studies use a variety of empirical techniques, and tend to find that both ability-to-pay factors and negative equity are important for mortgage defaults (see Foote and Willen (2017) for a more detailed review of the literature). Overall, the literature finds that most defaults appear to be associated with double-trigger factors and relatively few defaults appear to be driven by purely strategic motives.

Early studies focused on ‘strategic defaults’, framing mortgage default as a rational response by borrowers to negative equity. For example, in the ‘frictionless option model’, borrowers rationally choose to default to maximise their financial wealth when the value of their mortgage falls below its cost (Foster and Van Order 1984). Simulation studies, taking into consideration factors such as expected housing price returns, housing rents and interest rates, suggested that there should be a steep increase in the probability of default when negative equity reaches around 20 per cent (Kau, Keenan and Kim 1994).

As more loan-level data became available, empirical studies called the predictions of the frictionless option model into doubt. Far fewer borrowers defaulted than the frictionless option model predicted, even at very high values of negative equity. For example, Bhutta, Dokko and Shan (2017) estimated that the median US non-prime borrower did not strategically default until negative equity reached 70 per cent. As an explanation, researchers pointed to very high costs associated with foreclosure, including legal fees, moving expenses, recourse to other assets, sentimental attachment to the property and reputational costs that may affect job prospects and credit applications. Studies using survey data suggested that the willingness to default is significantly affected by non-monetary factors such as moral aversion and loss aversion (Guiso, Sapienza and Zingales 2013).

The double-trigger hypothesis was posed as an alternative hypothesis to better explain observed default rates, which, while increasing in the degree of negative equity, were not as high as predicted by the frictionless option model. The double-trigger hypothesis posited that it is an unanticipated negative change (henceforth, shock) to an individual borrower's ability to repay their mortgage that leads to missed payments, and the combination with negative equity that leads to foreclosures.

The empirical literature commonly finds that mortgage default is correlated with both ability-to-pay factors and negative equity, which is consistent with the double-trigger hypothesis. Binary choice models, such as logistic regression, and hazard models are widely used in the empirical literature. These are typically single-stage models that estimate the probability of loans entering either 60+ or 90+ day arrears.

Yet single-stage models are insufficient to test the double-trigger hypothesis. In the context of the double-trigger hypothesis, entering arrears can best be viewed as the first step in the process – that of experiencing an ability-to-pay shock. The second step, proceeding to foreclosure based on a loan's equity position, is untested in these studies. Moreover, many loans that enter arrears will subsequently cure. It is common for papers to argue that examining entries to 60+ or 90+ day arrears is sufficient to understand defaults, but these papers are often estimated using data for subprime loans during the global financial crisis, for which foreclosure was more common (e.g. Bhutta et al 2017). Adelino, Gerardi and Willen (2013) show that up to 70 per cent of loans that entered 60+ day arrears self-cure in a more representative dataset of loans (although this percentage fell during the financial crisis). Conversely, papers that study foreclosure alone miss the many loans that may enter arrears but subsequently cure (e.g. Bajari, Chu and Park 2008).

The set of papers that study the transition from arrears to foreclosure is relatively small. These studies typically examine either foreclosure mitigation policies or the role of securitisation, rather than the double-trigger hypothesis (Piskorski, Seru and Vig 2010; Kruger 2018). An exception is Ambrose and Capone (1998), who similarly argue that foreclosure is a separate process to a borrower entering arrears. They estimate a multinomial logit for whether borrowers in arrears go on to foreclose or to cure. Do, Rösch and Scheule (2020) examine the dollar value of losses given that loans have defaulted; they find that borrower liquidity constraints and negative equity affect whether loans cure and negative equity also increases the dollar value of losses.

A problem commonly encountered in the empirical literature is measurement error. While most studies provide good estimates of a loan's equity (utilising loan-to-valuation ratios, indexed for changes in regional housing prices), they frequently fail to identify individual shocks to a borrower's ability to repay.[1] Instead, papers often rely on regional economic data, such as regional unemployment rates, as a proxy for individual shocks. Gyourko and Tracy (2014) find that the attenuation bias from using regional variables may understate the true effect of unemployment by a factor of 100. With a loan-level dataset, I have access to borrower and loan characteristics, but similarly resort to more aggregated proxies such as the regional unemployment rate where necessary.

As noted above, studies of the determinants of mortgage default in Australia have been scarce. Read et al (2014) use a hazard model framework and find that loans with riskier characteristics and higher servicing costs are more likely to enter arrears. However, very few loans in their sample have negative equity, preventing a thorough analysis of the implications of negative equity. Likewise, a lack of foreclosures in their dataset prohibits their examination. In a survey of borrowers that underwent foreclosure proceedings, Berry, Dalton and Nelson (2010) find that a combination of factors tend to be involved in foreclosures, with the most common initial causes being the loss of income, high servicing costs and illness. However, the sample size of this survey is low, partly reflecting low foreclosure rates in Australia. Kearns (2019) examines developments in aggregate arrears rates in Australia and concludes that the interaction of weak income growth, housing price falls and rising unemployment in some regions, particularly mining-exposed regions, have contributed to an increase in arrears rates in recent years.

Empirical research examining the implications of regional stress events for mortgage default has been limited, but Gerardi et al (2008) show that this can be a fruitful exercise. When predicting defaults during the early stages of the financial crisis, they show that models estimated using data on the early 1990s Massachusetts recession and housing downturn outperform models estimated using a broader dataset of US loans from 2000 to 2004. This is attributed to the lack of loans with negative equity through the latter period and highlights the need for an appropriate sample period. An earlier study by Deng, Quigley and Van Order (2000) compares models estimated for loans in California and Texas through 1976 to 1992, when California experienced strong housing price growth and Texas was affected by an oil price shock and housing price declines. They find that coefficients tend to be larger for the Texan loans and conclude that unobservable differences between the regions may be important; these differences could include nonlinearities associated with the stress event.

A number of empirical studies examine the influence of institutions and legal systems on mortgage default, such as the effect of full recourse or judicial foreclosure (Mian, Sufi and Trebbi 2015; Linn and Lyons 2019). Australia has full recourse loans, which raises the cost of defaulting for borrowers that have other assets. Research comparing defaults across US states finds that full recourse acts as a deterrent to defaults, particularly strategic defaults, and raises the amount of negative equity that is required for a borrower to default by 20 to 30 percentage points (Ghent and Kudlyak 2011; Bhutta et al 2017). By raising the cost of foreclosure for borrowers with multiple assets, full recourse may cause borrowers to rationally attempt to avoid foreclosure even when their mortgage is deeply in negative equity. For sufficiently large values of negative equity, however, foreclosure will still be the rational response even in the presence of full recourse.


There are some exceptions. Elul et al (2010) use borrowers' credit card data as a proxy for liquidity constraints. Gerardi et al (2018) highlight the importance of unemployment and disability shocks using household-level survey data. [1]