Social Trends – Page 157 – Digital Finance Analytics (DFA) Blog

How Households Will Respond To Interest Rate Rises

We have updated our analysis of how sensitive households with an owner occupied mortgage are to an interest rate rise, using data from our household surveys. This is important because we now expect mortgage rates to rise over the next few months, as higher funding costs and competitive dynamics come into pay, and as regulators bear down on lending standards.

To complete this analysis we examine how much headroom households have to rising rates, taking account of their income, size of mortgage, whether they have paid ahead, and other financial commitments. We then run scenarios across the data, until they trip the mortgage stress threshold.

At this level, they will be in difficulty. The chart shows the relative distribution of borrowing households, by number. So, around 20% would have difficulty with even a rise of less than 0.5%, whilst an additional 4% would be troubled by a rise between 0.5% and 1%, and so on. Around 35% could cope with even a full 7% rise.

If we overlay our household segments, we find that young growing families and young affluent households are most exposed to a small rate rise. However, some in other segments are also at risk.

State analysis highlights that households in NSW are most sensitive, a combination of larger volumes of loans as well a larger loans, relative to incomes resulting is less headroom.

Younger households are relatively more exposed, because their incomes tend to be more limited and are not growing in real terms relative to mortgage repayments.

Analysis by DFA property segment shows that whilst some first time buyers are exposed at low rate movements, those holding a mortgage with no plans to change their properties (holders) are also exposed. In addition, some seeking to refinance are doing so in the hope of reducing payments, because they have limited headroom.

Finally we turn to other insights from our data. First, those households who sourced their mortgage via a mortgage broker are more likely to be in difficulty with a small rate rise, compared with those who went direct to a bank. This, once again, shows third party loans are more risky. This perhaps is connected to the types of people using brokers, as well as the broker’s ability to suggest lenders with more generous underwriting standards and coaching on how to apply successfully.

We also see that rate seekers (we call these soloists) who are driven primarily by best rates, are more sensitive to small rate rises, compared with those who are more inclined to seek advice, and appreciate service more than price (we call these delegators).

Soloists who went via a broker are the most exposed should rates rise even a little, whereas delegators going to a bank, are more able to handle future rises.

Segmentation, effectively applied can results in quite different portfolio outcomes!

The End Is in Sight for the U.S. Foreclosure Crisis

From The St. Louis Fed.

The extended period of historically elevated rates of extreme mortgage distress and defaults in the U.S. housing market, better known as “the foreclosure crisis,” has faded from view as the economy continues its slow recovery. A deeper look at mortgage performance data from the Mortgage Bankers Association suggests the crisis has ended in some states, while it is not quite over yet for the nation as a whole. However, the end is near. The condition of current mortgage borrowers considered as a group—nationwide or state by state—is once again comparable to the period just before the Great Recession and the onset of the foreclosure crisis.

As explained below, we identify the fourth quarter of 2007 as the beginning of the nationwide foreclosure crisis; we judge that it had not yet ended as of the third quarter of 2016. Based on current trends, we expect it should end in early 2017. This nearly 10-year nationwide foreclosure crisis will have been longer and deeper than anything we’ve seen since the Great Depression. As many as 10 million mortgage borrowers may have lost their homes.

Some states and regions have experienced severe recessions and housing crises worse than the nation as a whole, while others have suffered less. The result is a wide range of foreclosure-crisis experiences. Among the seven states that make up the Eighth Federal Reserve District, we conclude that only Missouri and Tennessee have exited their foreclosure crises as of the third quarter of 2016 when judged by a national standard; Arkansas likely will follow soon. Meanwhile, Illinois, Indiana, Kentucky and Mississippi may be a year or more away from exiting. If we take into account long-standing differences in mortgage conditions across states, our conclusions are more favorable. Only Illinois has failed to return to its own pre-crisis level and, even there, the end of the foreclosure crisis appears imminent.

Using Data to Define the Start and End of the Foreclosure Crisis

We define the recent foreclosure crisis as the period during which the share of mortgages that are seriously delinquent (90 days or more past due) or in foreclosure in a particular state or nationwide was above the worst level experienced in recent memory (i.e., not including the Great Depression).² To recognize secular changes in mortgage practices and performance—in particular, steadily rising levels of outstanding mortgage debt and a proliferation of new types of mortgages—we calculate a crisis threshold for the nation and for individual states as the combined rate of serious delinquency plus foreclosure inventory that first exceeds its own five-year moving average by an amount greater than any previously experienced in the data.

We define the end of a foreclosure crisis as the first quarter in which the combined rate drops below its initial crisis reading.

The Foreclosure Crisis at a National Level

Mortgage Bankers Association data show that the U.S. foreclosure crisis started in the fourth quarter of 2007, when the combined rate reached 2.81 percent, a level that exceeded its five-year moving average by 0.67 percentage points, more than any other previous level. Given that the combined rate stood at 3.2 percent in the third quarter of 2016, this suggests that the nationwide foreclosure crisis has not yet quite ended. However, based on the rate of decline in recent quarters, the data-defined end of the crisis on a national scale is likely to occur as soon as the first quarter of 2017. Indeed, comparable data from Lender Processing Services, as shown in the recently released Housing Market Conditions report from the St. Louis Fed, also suggest the foreclosure crisis is nearing its end.

It Has Been a Long, Hard Slog

However it is defined, the mortgage foreclosure crisis will go down as one of the worst periods in our nation’s financial history. For the nation as a whole, the crisis will have lasted almost a decade—about as long as the Great Depression. For most states in the Eighth District, the slightly shorter duration of their foreclosure crises, when measured against their own data trends, has been offset by higher average rates of serious mortgage distress seen even in non-crisis periods.

The conclusion that the foreclosure crisis has been a long, miserable experience for many is unavoidable. And many Americans continue to suffer lasting financial, emotional and even physical pain as a result of their experiences during this time. However, a look at the data today shows that, at least, the end is in sight.

The Changing Work Roles of Wives and Husbands

Interesting US research featured by The Federal Reserve of St. Louis, on changing work patterns, highlighting the falling participation rates and decline in hours, especially among men, as women increase their representation in the US work force. Married women in particular are having a big impact on the market. They suggest the changes in the labor supply of men and women may be related,

It is well-known that the labor force participation rate for men and the hours worked by men have declined over the past four decades. More men are reporting that they either are not employed and not actively searching for a job or are working part time; these two trends are contributing to the decline in the average hours worked by men in the past four or five decades.

During this same time, women have increased their representation in the labor market: The fraction of women participating in the labor force has increased, as has the number of hours women work outside the home, with the majority of the increases driven by growth in the labor supply of married women.

The changes in the labor supply of men and women may be related, especially if we consider married men and women. Time allocation—that is, how much a spouse works, how much time each spends on housework and child care, and how much leisure each enjoys—is decided within households. This context is needed to analyze married individuals’ decisions to withdraw from the labor market or to work part time. Although many papers have documented the decline in the labor supply of males,2 this article focuses on the changing role of wives in providing economic support for their families and changes in the labor supply of prime-age (25-54) married males.

We focus on prime-age married males because of this group’s traditional role of being the breadwinners; these men are typically attached to the labor market and work full time.

This shows changes in the labor force participation rate of this group. The trend is similar to that for men in general. In 1970, more than 97 percent of these husbands participated in the labor market, dropping below 93 percent in 2011 and staying there. Meanwhile, the rate of part-time workers among prime-age husbands increased substantially since the 1970s: Less than 1.5 percent of the men worked part time in 1970; this fraction has been about 4 percent or more since 2009. As for wives, close to 26 percent of married women in the labor force worked part time in 1970, but only about 22 percent worked part time after 2000.

Household Labor Supply

Several factors could contribute to the decline in labor force participation and hours worked by married prime-age men and to the increase in labor supply of their wives. The explanations include both demand- and supply-side motives. One explanation for the declines related to men is that there is a drop in demand, especially in the manufacturing sector; this decline in demand is related to skill bias, technological changes and offshoring. The increase in married female labor supply can be partly explained by the increase in educational attainment of women and the increase in relative wages in high-skill occupations.

In the context of household labor supply, however, a decline in the gender pay gap can cause an increase in the female labor supply and a decrease in the male labor supply as a response to the household’s joint decision on labor and to the household’s overall income. In other words, the higher income generated by wives may reduce the incentive of husbands to work many hours or to work at all.

Furthermore, increases in labor force participation of married women and their hours worked can also be due to an increase in risk pooling in households, especially in households in which women are married to low-skilled men or to men working in declining industries. With women’s strides in education, they can provide insurance within the household by working more when men lose their jobs or when the wages offered to men are low. This insurance motive may kick in even before the husband loses his job. Wives may decide to work outside the home when there is just a threat of unemployment or a decline in their husbands’ earnings.

Another possible explanation for the increase in married males’ working part time has to do with the fact that finding jobs can take time and effort. Working part time allows the individual to spend more time searching for a better-paying job or investing in the acquisition and enhancement of skills, which often means going back to school or even acquiring skills that allow individuals to change occupation or sector.7 Thus, in households in which wives work full time, husbands might be able to be choosier in accepting jobs—they can afford to be less willing to take full-time jobs for low pay or jobs that may not offer good promotion prospects or other nonpecuniary qualities. These men may take part-time jobs while searching for better jobs.

Next, we explore changes in characteristics of households in which prime-age men were not participating in the labor force or worked part time between 1970 and 2015.

Labor Supply and Education Composition

The education composition of husbands who either work part time or are nonparticipating has changed significantly over time.

As shown above, in both groups, the respective fraction of husbands with high school education or less decreased, and the fraction of husbands with at least some college education increased since 1970. (During and after the Great Recession of 2007-09, however, the fraction of males who worked part time and had no more than a high school diploma went up but has since reverted to its decreasing trend. As for better-educated husbands, there was a relative decline in the fraction working part time during the recession. The differences between the experiences of the two groups during the recession can be due to the differences in the demand for the skills of educated and less-educated men; another factor is that more-educated husbands are more likely to have more-educated wives with different labor market prospects.)

To further explore the changes in the composition of households in which husbands do not participate in the labor force or work part time, we turn to the education compositions of the wives.

This demonstrates, the fraction of these husbands who are married to women with high school education or less declined significantly. The fact that women in households in which males work part time or do not participate are more educated than in the past (and given the decline in the gender earnings gap) may imply that these women are more likely to work, earn relatively more and provide more economic support for their families.

In addition to the education composition of the men and women, the relative earning potential of the spouses in the household can be important to understanding how the spouses allocate their time among jobs, housework, child care and leisure.

This presents the change in composition of part-time and nonparticipating husbands by their education status relative to that of their wives. Interestingly, among these two groups of men, there is a clear decline in those who are married to women with the same education level or less and an increase in the fraction of those who are married to women who are more educated than they are. The percentage of those married to wives who are relatively more educated than them increased from about 9 percent in 1970 to about 27 percent in 2015.

The patterns in both increasing education of women in households in which men work part-time jobs and the fact that in an increasing fraction of these households women are more educated than the men suggest that the earning potential of women in these households is higher than it used to be. These patterns also suggest that these women might have better labor market prospects than men and have an important role in providing economic support for their families.

Relative Share of Wives’ Earnings

This describes the employment status of women in households in which the husbands work part time or are nonparticipating. Despite the short dip after the Great Recession, the overall increasing trend of the fraction of men who work part time and are married to women who work full time is clear. The patterns for wives of nonparticipating husbands are similar.

Next, we describe the role of the wife’s income relative to the husband’s income and how that relationship changed over time.

This shows the median share of the wife’s income in the total household income for married households. In the overall sample, the share was close to 2 percent in 1970, which is consistent with traditional families in which the men are the breadwinners. This share rose to about 30 percent by the late 1990s and has fluctuated around 30 percent since then. The share of the wife’s income in families with husbands who work part time or are nonparticipating is always higher than the share of the wife’s income in all married families. However, in families in which men work part time or do not participate, the wife’s income in recent years has been equal to or has exceeded that of the husband.

Conclusion

Despite the findings that most of the increase in nonparticipation of prime-age males stems from relatively less-educated males,9 the fraction of educated, prime-age husbands who do not participate or who work part time has increased over the past few decades. At the same time, in these households, the fraction of educated women and the fraction of women who are more educated than their husbands increased.

Increase in nonparticipation of prime-age males stems from relatively less-educated males, the fraction of educated, prime-age husbands who do not participate or who work part time has increased over the past few decades. At the same time, in these households, the fraction of educated women and the fraction of women who are more educated than their husbands increased.

These data partly reflect decades of demographic changes: rising college graduation rates in the overall population, with women’s educational achievements surpassing men’s; a decline in the marriage rate, especially for those with less education; and changes in the marriage markets. Thus, the composition of the households in which males do not work or who work part time has also changed. We found that in these households the role of women in providing income to the family is higher than it was in the past. These changes are likely to affect households’ labor supply and job-search behavior (the intensity of search and what kinds of jobs and pay people are willing to accept).

In addition, the data show that changes in labor supply during and right after the Great Recession vary by the education of the spouses: The fraction of males working part time who had no more than a high school education or who were married to women with no more than a high school education increased during the recession; meanwhile, the fraction of better-educated males working part time and of males working part time who were married to better-educated females declined during the recession, suggesting differences in both labor market opportunities and labor-search behavior for more-educated families.

Although many papers suggest that the role of the changes in labor demand is important, the descriptive analysis cannot be used to infer causal effect and to separate demand and supply factors. However, it is important to assess the role of the marriage market and the role of both spouses in generating income and providing housework in order to fully understand trends in labor participation and hours worked and how they interact with business cycles and labor market conditions.

In particular, assessment is needed of job-search behavior and the choice of sector in which people want to work. Whether to remain in a sector with high probability of unemployment or to acquire new skills, whether to work outside the home and, if so, how many hours to work—all of these decisions for husbands may depend on their wives’ employment opportunities, as well as their own employment opportunities.

Aussies feel pressure on household budget

From AAP. Only one-fifth of Australians think the national economy is in good shape, a new survey has found, in a grim assessment of consumer cheer heading into Christmas.

A quarterly survey by consumer advocacy firm CHOICE has found only about one in five people believe the Australian economy is in good shape – the lowest positive rating since its Consumer Pulse survey began in 2014.

The December results show that consumers are under increasing financial pressure and feel less positive about their household budget and the economy.

“Many Australians start to feel sharper financial pressures leading into the holiday period, as gifts and parties eat into our savings or credit balance,” acting CHOICE chief executive Matt Levey said.

Australians are also reporting a drop in spending on non-essentials, with more than half of respondents tightening the belt and putting off purchase of big ticket items.

CHOICE’s Consumer Pulse report found fears over the economy are the worst they have been since the survey began two years ago, with just one in four households saying they’re living comfortably.

“In particular, our survey shows that Australians between 30 and 49 are more likely to live off credit cards if they run out of money before pay day,” Mr Levey said.

A third of people under 30 said they dipped into their savings in the last year to make it to pay day, while a quarter had borrowed money from family or friends. About 20 per cent of people aged 30 to 49 reported they deliberately missed the due date on a bill.

CHOICE’s report follows the release this week of the federal government’s mid-year budget review, which forecast that despite lower savings, consumers will likely boost spending on the back of low interest rates and employment growth.

However, the Consumer Pulse figures show that consumers are not necessarily feeling confident enough about their financial future to take on more debt or spending.

“MYEFO’s predictions about household savings match what Australians have told our survey,” Mr Levey said.

“But this won’t necessarily translate into higher consumer spending. In the next 12 months, a majority of people say they are planning to cut back on discretionary and non-essential purchases.”

CHOICE’s Consumer Pulse report, which tracks Australians’ views about the economy and household spending, was based on online responses from 1025 people aged between 18 to 75 years.

A Deep Dive On Household Rate Sensitivity

Today we look at a Interest Rate Sensitivity – a specific slice of data from our household surveys which we use to drive the mortgage stress data series, as we discussed recently.

Using data from our surveys we are able to estimate the amount of headroom households would have if mortgage interest rates were to rise. We are expecting rises through 2017.

We look at a range of scenarios, and as rates rise estimate the “pain point” for specific households, taking into account their other commitments, income, type of loan and mortgage repayments. Today we look at owner occupied loans.

Looking at sensitivity by age of household, more than 65% of those under 40 years with a mortgage would have difficulty if rates rose just 0.5% (50 basis points). Households who are older, on average have more headroom. In the “more than 7%” category, 60% of households are over 40 years.

Another interesting cut is the penetration of Lenders Mortgage Insurance (LMI). Around half of households with an LMI protected loan (remember the LMI Insurance protects the BANK, not the Household) would have difficulty if rates rose bu 50 basis points. Households with no need for LMI (normally because they have a lower loan-to-value ratio) have more headroom.

We see from our property segmentation that a greater proportion of first time buyers would be caught if rates rose 50 basis points, but property holders are the largest segment at the high end of the risk profile.

A look at our master segments shows that young growing families and young affluent households are relatively the most exposed if rates rise. Interestingly our battling urban, and disadvantaged fringe groups (who would generally be regarded as the worst credit risk) have more headroom. This is because they have smaller mortgages, so are less leveraged.

By state, NSW have the highest proportion of households which would be exposed by a 50 basis point rise – again because of large mortgages and high home prices. By comparison, households in QLD AND VIC have more headroom. Some households in WA are also exposed at 50 basis points.

Finally, we also see that the majority of households we identified as in severe mortgage stress appear in the band who would be under pressure if rates rose just 50 basis points. This is a validation of our modelling, and shows the alignment between mortgage stress and rate movements.

A further illustration of the power of effective segmentation!

Mortgage Stress And Probability Of Default Is Rising

We have just finished the December update of our mortgage stress and probability of default modelling for the Australian mortgage market.

Our model has been updated to take account of the latest employment, wage, interest rate and growth data, and we look are the current distribution of mortgage stress (can households settle their mortgage repayments, on time without financial pressure?) and make an estimate of the probability of households defaulting on their repayments by more than 30 days. The former uses our survey data on mortgages held, interest rates applied, and income available in the light of other financial commitments. Probability of default overlays the broader economic drivers. The base analysis is completed at a customer segment level by post code then rolled up to form various data views. In the next few days, we will discuss the findings in some detail. You can read more about our approach here. We also also reveal the current top 100 post codes for mortgage stress and mortgage defaults across the nation.

To begin, here is a summary by states, split down by CBD and rest of state.

The highest probability of default can be found in regional WA, thanks to pressure in the mining belt. 30 days defaults will be close to 4%. Here, around 25% of households are in mortgage stress, including some in severe stress – see our descriptions here.

Default expectations are also high in and around Perth, where employment prospects are faltering, and incomes under pressure. In QLD, away from Brisbane, we see similar issues. The ACT has the lowest level of default probability.

The highest levels of mortgage stress are found in Tasmania, and across Regional NT, where more than 30% of households are under pressure. We also see hot spots in regional areas.

Of note is the high proportion of households in greater Sydney in severe mortgage stress – at 6.2% of borrowing households. This is a function of large mortgages (driven by high prices), rising interest rates AND flat incomes. By way of comparison, Melbourne households in severe stress sit at 3.3%, as mortgages are a little smaller. They are both higher than the national average of 2.8% of households.

Combined, across the country, more than 22% of all households are now in some degree of mortgage stress.

Next time we will dig into the more specific geographic footprints, because you really have to get granular to make sense of what is going on. Averages across the national simply mask what is going on. Later will will look at loan-to-income and debt servicing ratios which are also deteriorating for many. Then finally we will look at the loss implications for the banking sector.

‘Fake news’ – why people believe it and what can be done to counter it

From The Conversation.

Barack Obama believes “fake news” is a threat to democracy. The outgoing US president said he was worried about the way that “so much active misinformation” can be “packaged very well” and presented as fact on people’s social media feeds. He told a recent conference in Germany:

If we are not serious about facts and what’s true and what’s not, if we can’t discriminate between serious arguments and propaganda, then we have problems.

But how do we distinguish between facts, legitimate debate and propaganda? Since the Brexit vote and the Donald Trump victory a huge amount of journalists’ ink has been used up discussing the impact of social media and the spread of “fake news” on political discourse, the functioning of democracy and on journalism. Detailed social science research is yet to emerge, though a lot can be learnt from existing studies of online and offline behaviour.

Matter of trust

Let’s start with a broad definition of “fake news” as information distributed via a medium – often for the benefit of specific social actors – that then proves unverifiable or materially incorrect. As has been noted, “fake news” used to be called propaganda. And there is an extensive social science literature on propaganda, its history, function and links to the state – both democratic and dictatorial.
British poster from World War I attacking German atrocities in Belgium.
In fact, as the investigations in the US and Italy show, one of the major sources of fake news is Russia. Full Fact, a site in the UK, is dedicated to rooting out media stories that play fast and loose with the truth – and there is no shortage.

An argument could be made that as the “mainstream” media have become seen as less trustworthy (rightly or wrongly) in the eyes of their audiences, it makes it hard to distinguish between those who have supposedly got a vested interest in telling the truth and those that don’t necessarily share the same ethical foundation. How does mainstream journalism that is also clearly politically biased – on all sides – claim the moral high ground? This problem certainly predates digital technology.

Bubbles and echo chambers

This leaves us with the question of whether social media makes it worse? Almost as much ink has been used up talking about social media “bubbles” – how we all tend to talk with people who share our outlook – something, again, which is not necessarily unique to the digital age. This operates in two distinct ways.

Bubbles are a product of class and cultural position. A recent UK study on social class pointed this out. An important subtlety here is that though those with higher “social status” may congregate, they are also likely to have more socially diverse acquaintance networks than those in lower income and status groups. They are also likely to have a greater diversity of media, especially internet usage patterns. Not all bubbles are the same size nor as monochromatic and our social media bubbles reflect our everyday “offline” bubbles.

In fact social media bubbles may be very pertinent to journalist-politician interactions as one of the best-defined Twitter bubbles is the one that surrounds politicians and journalists.

This brings back into focus older models of media effects such as the two-step flow model where key “opinion leaders” – influential nodes in our social networks – have an impact on our consumption of media. Analyses of a “fake news story” appears to point – not to social media per se – but to how stories moving through social media can be picked up by leading sites and actors with many followers and become amplified.

The false assumption in a tweet from an individual becomes a “fake news” story on an ideologically-driven news site or becomes a tweet from the president-elect and becomes a “fact” for many. And we panic more about this as social media make both the message and how it moves very visible.

Outing fake news

What fuels this and can we address it? First, the economics of social media favour gossip, novelty, speed and “shareability”. They mistake sociability for social value. There is evidence that “fake news” that plays to existing prejudice is more likely to be “liked” and so generate more revenue for the creators. This is no different than “celebrity” magazines. Well researched and documented news is far less likely to be widely shared.

The other key point here is that – as Obama noted – it becomes hard to distinguish fake from fact, and there is evidence that many struggle to do this. As my colleagues and I argued nearly 20 years ago, digital media make it harder to distinguish the veracity of content simply by the physical format it comes in (broadsheet newspaper, high-quality news broadcast, textbook or tabloid story). Online news is harder to distinguish.

The next problem is that retracting “fake news” on social media is currently poorly supported by the technology. Though posts can be deleted, this is a passive act, less impactful than even the single-paragraph retractions in newspapers. In order to have an impact, it would be necessary not simply to delete posts but to highlight and require users to see and acknowledge items removed as “fake news”.

So whether or not fake news is a manifestation of the digital and social media age, it seems likely that social media is able to amplify the spread of misinformation. Their economics favour shareability over veracity and distribution over retraction. These are not technology “requirements” but choices – by the systems’ designers and their regulators (where there are any). And mainstream media may have tarnished their own reputation through “fake” and visibly ideological news coverage, opening the door to other news sources.

Understanding this complex mix of factors is the job of the social sciences. But maybe the real message here is that we as societies and individuals have questions to answer about educating people to read the news, about our choice not to regulate social media (as we do TV and print) and in our own behaviour – ask yourself, how often do you fact-check a story before reposting it?

Author: Simeon Yates, Director Institute of Cultural Capital, University of Liverpool