Credit Suisse wealth inequality data

Bob Gregory's latest rant against the evils of neoliberals inspired me to pull together the latest Credit Suisse wealth figures. The social democracies in Europe usually turn up as a lot more unequal in wealth than NZ, and I was curious where the latest numbers might put things. 

The latest iteration has NZ with the 145th most unequal wealth distribution of the 168 countries in the data set, or the 24th most equal. I've highlighted NZ in red and Sweden, Germany, Finland and Denmark in Green (from left to right). NZ is way over on the right, just to the right of France which you can't really see. 

NZ has more traditionally been toward the middle of the pack. The 2017 data had us 80th most unequal of 171, and a bit more unequal than France. This time we're a bit less unequal than France. 

Recall that Gini measures the area between the Lorenz Curve and the line of perfect equality. So a Gini of 0 means we're on the line of perfect equality. It's a measure of all against all; other inequality measures measure different things. 

In this case, I'd bet that sharp housing price increases are driving increases in wealth portfolios for middle-wealth households for whom house is the primary asset, and that the equalising effect of that is currently dominating the effect on households who don't own any house. 

So it'll come down again in due course if housing gets corrected, and presumably at that point the inequality-shouters will shout about the rise in measured inequality back to where it was a few years ago. 

Note that this is a PDF to Excel conversion by SmallPDF which looks to have done just a superb job of things - but there could be OCR errors that I hadn't caught. 

It probably highlights one of the problems in just using Gini. The more important growing inequality is between insiders and outsiders in housing markets, but Gini has wealth as having become more equal. 

I have come to expect Oxfam NZ reports shouting about the latest Credit Suisse figures, taking whatever they can from them to provide reason to worry about inequality and give them money. This year's Credit Suisse report was delayed. I wonder whether Oxfam will have noticed that NZ's wealth distribution became far more equal. 

Wealth and the life cycle

It's frustrating how hard it is to know some perfectly knowable things.

Over the weekend, the Greens announced that they support a wealth tax on individual net wealth in excess of $1m. 

In a country that had sensible priorities for its statistics department, I would have an easy time answering a simple question. Fixing the underlying problem here I understand to be a big job. But it would be a solution to problems that just keep coming up - not just this one. And it isn't like there aren't other things that the government has tasked Stats with doing that seem rather less important than fixing this problem. 

I would like to know the distribution of wealth by age bands. The 2018 wealth module of the Household Economic Survey has information on the distribution of households by net worth bands, and household net worth by household characteristics, and by a few other ways of slicing the data that would have occurred to a Stats analyst might be useful when they did the thing up in 2018, but nothing that can let me look at it by age. I don't blame anyone for not having this slice in - there are huge numbers of ways of slicing the data and it would be impossible to have all of them up in every release. 

In a system that had functional back-end systems, you'd be able to put in a query and it would just spit out the relevant cross-tabs - generating them on request from the underlying data. IPUMS has had this kind of functionality for ages - you can even run regressions on their data from inside your web browser.

Here, I can't even tell the age distribution of the 216,000 households with net worth in excess of $1.5m - the topcode in their income buckets. 

Why does this matter?

Imagine two states of the world. 

In state of the world A, 5% of individuals have net assets in excess of $1m. They are born with those assets endowed by bequest, and they die leaving those assets to their kids. Nobody else ever accumulates net assets in excess of $1m. There's a landed gentry, and everyone else. 

In state of the world B, 5% of individuals have net assets in excess of $1m. As people move through the life cycle, they move from being net debtors to net asset positions, and retire at age 65. Their wealth holdings peak around then, with draw-downs exceeding the return on their investments. 5% of people are aged 65-69, and every one of them has assets in excess of $1m when they retire, before they start drawing it down. They're all back below $1m at age 70.

We are absolutely not in either of those states of the world. But static numbers on wealth accumulation say nothing about the life cycle. The presumed equity considerations around a wealth tax would have to be different if small numbers of people are ever subject to it as compared to if large numbers of people became subject to it as they reached retirement. In state of the world B, a wealth tax transfers money from individuals' future richer selves to their current poorer selves in an overlapping generations sense, but where people tend to save money in anticipation of retirement it's an odd way of running things. The rest of the system (NZ Super) is designed around taxing people when they're working to help them fund their retirement. Not the other way round. 

Some of what Stats has is suggestive: couple-only households (retirees will be more likely to be couple-only) have median wealth of almost double that of couples with dependent kids. But that's highly imperfect - professional couples without kids will almost certainly find it easier to accumulate wealth if they don't have kids. And, even if you just lumped together everyone over 65, that would also catch lots of people who'd substantially drawn down their savings. The median across that bigger group wouldn't be the right answer either. 

While it would be nice if Stats would pull the number for me - I've requested it, and I understand that there's a two-week lag these days on custom data requests - it's still not a solution to the general problem. It's just frustrating that back-end systems have not been updated so that cross-tabs like this can be generated dynamically by users on the web interface, rather than by specialised request. Fixing this kind of thing once would save the custom data team a lot of work. It's impossible to anticipate all the cross-tabs that might wind up proving useful down the track; adding more tabs to downloaded excel sheets isn't the answer and can't be the answer. The systems need to be fixed so that things that are dead simple to know in principle can actually be known. 

In an election campaign, two-week lags for basic fact checking about the contours of policy can be an awfully long time. I'm not blaming the team at all for it - Stats is always crazy helpful. But the system really needs to be fixed so that things that should be knowable at a click on a browser don't require custom data pulls. 

Household wealth and housing wealth: first quintile oddities edition

In my column over at Newsroom this week, I noted one strange feature of New Zealand's household wealth statistics:

Unfortunately, data on wealth is far worse than data on income – the Government gathers a lot less data on wealth. For example, Statistics New Zealand reports that people in the least wealthy 20 percent have $1.75 in property debt for every $1 in property assets – but no bank in the country would extend a loan on that basis. It is more likely that the survey data misses some houses owned through family trusts where, for example, a 25-year-old takes over the mortgage and effective ownership of their parents’ second home held in the family trust. The mortgage payments and mortgage debt are noted in Household Economic Survey data, but the ownership may be missed. This means their parents’ net wealth will be overstated, their own net wealth will be understated, and measured wealth inequality among younger cohorts would be somewhat understated but overall measured wealth inequality would be somewhat overstated. 

There's an ungated version of the column here.

The effect wouldn't be large because there aren't many households in that situation. But it's odd. So I asked Statistics New Zealand what's up with that, wondering whether the trusts explanation might be what's going on. I'd also asked whether Stats were able to ask follow-up questions of their HES respondents to see what's going on.

Stats' Statistical Analyst Michelle Griffin helps me out:

We’ve had a look at the distribution of owner-occupied property assets and owner-occupied mortgages for those in net worth quintile one. There are about 30 more households (unweighted) with mortgages than homes, and because of this difference, you need to go further along the mortgage distribution to get to the median, resulting in a larger mortgage median and hence a larger debt to asset ratio. So it’s looking like the high ratio is due to a mix of under-reporting and distribution differences.

We’ve had a look at only those with both a home and a mortgage to see what they look like (this is excluding those with a home in a business or trust), and this brings the ratio down to $1.44. This drops even further when you take the median of each household’s individual debt to asset ratio (to $1.26).

We’ve had a quick look at the households with only a mortgage to try and see what might be happening. They appear to be a mix of households with the home in a trust or business which is assigned to someone else (which could be a situation like you’ve described below), and households which say the home is in a trust or business but then don’t mention this trust/business later on (could be partly due to misreporting or respondent burden leading to households not answering fully). I think the fact that there are so few households in net worth quintile one with owner-occupied property is making this quintile more sensitive to these issues. Unfortunately, we can’t follow up with the respondents later on to confirm these situations – although it would certainly be interesting!

So restricting things to those households in the first quintile fixes some of the problem, but we're still at a debt-to-equity ratio on housing debt well out of step with sane banking practice, let alone existing LVR rules. And while there aren't many households with mortgages without homes, it's hard to tell whether debt to asset ratios for a broader set of respondents elsewhere mightn't be wrong too. 

Michelle suggests that keeners might apply for microdata access to really drill down into what's going on. It would be a great Honours thesis for somebody wanting to get microdata experience who has a qualified supervisor.

Many thanks to Michelle and to Statistics NZ for the helpful and detailed response.

Update: An informed reader writes:

A couple of thoughts about the data on wealth:

• There is a wider problem with data for people at the top and bottom of the distribution. Surverys include lots of trade offs between clarity, comprehensiveness and accuracy. For instance survey data on the benefit population substntially under-reports income from second and third tier payments (that is all loans, one off payments, disability allowance and accommodation supplement). Since this is a relatively small part of the population, SNZ makes the reasonable decision not to overcomplicate their survey to deal with the problem, but the consequence is continuous understatement of income for many people. The same applies at teh top where it is hard for surveys to capture the many different assets people with many assets have.


• More technically there is problem using a small number of  discrete categories like quintiles to describe a continuous variable. The general point is that if someone makes a mistake they have have to go somewhere in the discrete categories, so effectively there is a cut off at the top and bottom that will skew the results. It's easy to think of this through an intuition. If a person's income is roughly in the middle, say $50 000, and they miss a zero then they drop to the bottom of the distribution ($5000) while if they add a zero by accident ($500 000) they go to the top of the distribution. However a person whose income really was $5000 who makes a mistake either stays in the same place or goes up (ie income is $500 or $50 000); while a person with income at $500000 either goes down, or stay at the top. Even if we assume the liklihood of a person making an error and its direction are independent of income, the measured income will be pushed to the extreme quintiles. "On average" it may be right, but it will overstate the dispersion. My guess is this will be even more pronounced with wealth because it is so much harder to measure and thus more likely to generate error-prone answers.


• Finally, they are using snapshots for variables that change over time. I know this is a problem with flows like income and employment, but I sometimes wonder what it means for wealth. In particular, there is an issue with measuring transitions. The following example is made up, but gives a clue what might be happening. Say some % of people selling a house to buy another spent a couple of weeks where they had two mortgages while the paper work was settled. For the individuals the cost might be a few hundred dollars - which is not a lot when you get real estate agents involved! - but two weeks is approx 4% of the year so you would expect your snapshot survey to include some small % of people with double the mortgage debt relative to their asset. It is not many people, but it does not need to be because they will be a small percentage of the population but they will concentrated in decile/quintile. 

To me the deeper problem is that surveys tend to be designed to be "on average right", whereas the data is often used to make distributional statements. And Bryan Perry’s incomes report notes the problems with the extreme tails of the distribution.

Wealth inequality - reader mailbag

An informed reader reminds me of a couple points on wealth inequality in response to this morning's post:

Just saw your piece on wealth. To add to the points you make:

• Strongly agree with your point about the use of cross sectional data. This is particularly true in a country where a large number of people in the first ten to 15 years of adulthood go abroad. We would expect the distribution to be highly skewed if the most effective means of building capital is to go abroad.

• There is likely to be a depressing effect on saving associated with the generosity of the state superannuation scheme. Or to be more precise: people have an implicit overlapping generations model in the minds that sees long run intergenerational transfers by government as credible. This means they see the tax and transfer system as an implicit saving scheme. When combined with home ownership and universal health care, it is a reasonable question to ask what purpose would it serve people in the lower half of the income distribution to build up assets? (there is a paper by Andrew Coleman somewhere on this)

Both points are good. The latter one especially should be better recognised. NZ Super guarantees you a decent basic retirement income. NZ Super currently pays $926 per fortnight if you're single, or $701 per fortnight per person in a couple. After tax, it's $617 per person in a couple. 

So a retired couple gets $1234 per fortnight after tax in NZ Super, so $32,000 per year. That's in the middle of the second decile of equivalised household income for a couple, before housing costs. So anyone earning less than that could easily be forgiven for not building any retirement savings: they would be reducing their current consumption in order to gift themselves higher consumption in retirement than they were ever able to afford when working. What does that mean? It is completely rational for the lowest income twenty percent of the population to not be building wealth. 

Or, to put it another and perhaps better way, we should view NZ Super eligibility as being equivalent to lump sum wealth holdings for each person, rich or poor, equivalent to the present discounted value of the stream of entitlement payments once you turn 65. But that's not all! Government provides other services as well. There's a retirement care subsidy (which draws against your Super entitlement, but also involves additional subsidy from the government). Government provided health care too. Entitlements to all of these should be viewed as part of the lump-sum entitlement that's fairly evenly distributed. 

And what happens to any inequality measure if you ignore a giant lump sum that's provided across-the-board? The inequality measure will overstate real inequality. 

Household net wealth

My take on the latest Stats NZ Household Wealth survey is a bit different from Max Rashbrooke's.

Here's Max:

The Household Net Worth survey by Statistics New Zealand shows the wealthiest one percent have 20 percent of all assets and the wealthiest tenth have 59 percent. The poorest half of adults - 1.8 million New Zealanders - have just 2 percent of all wealth. Māori net wealth is significantly lower than that of Pakeha.

These figures are broadly unchanged since the last such survey in 2015. But that's barely reason to celebrate.

Wealth - in the sense of things that people own, like houses, cars, financial investments and cash in the bank - provides security and stability. It is something people can draw on during tough times, a stake in the community, a base from which to plan for the future.

So it is hugely concerning that so many New Zealanders have so little wealth. And their position is not improving. Statistics New Zealand reports that the poorest 40 percent have seen no increase in their wealth in the last three years.

But look at the chart underlying this:

There was a half a percentage point increase in the number of people with net wealth of less than $100,000: those will be people with substantial debt. When I check the student loan tables, about 0.075% of the domestic population has student loan debt into those figures - the rest has to be other stuff. 

Once we get into the positive net wealth categories, every net wealth category up to and including the $400-500k band had a smaller proportion of the population falling into it. Most bands above that saw an increase in the proportion of the population in the band, barring the $700-900k group. And the proportion of people with more than $1.5m in net wealth increased from 8.3% of the population in 2015 to 12.5% of the population in 2018.

It would then be fair to characterise this as an overall upward shift in wealth, barring a small increase in the proportion of the population with substantial net debt.

The median person in 2015 would have been in the $200-$300k net wealth range. The median person in 2018 is in the $300-$400k net wealth range. But note that the figures are not inflation adjusted.

The overall curve looks to me to have shifted to the right, barring the increase in the proportion of people with substantial net debt of more than $100,000. All the focus on what proportion of the population has what proportion of overall wealth misses what looks like an overall increase in wealth.

And recall too that life-cycle stuff enters heavily here. These annual snapshots give a picture of the cross-section in any particular year. But people accrue wealth as they age, then start consuming from that wealth in retirement. Stats' press release has young people (age 15-24) with median net worth of $2k and older people (age 65-74) with net wealth of $416k. 

Every year, new people are born, existing people age, and some people die. Looking at annual snapshots doesn't tell us anything about how people move through the life cycle. Every person in 2015's bottom 40% could have increased in wealth, with no change to the wealth band of 2018's 40th percentile person, as the 2015 people move up through the age ranks and new people come in at the bottom. 

I'd also be pretty nervous about claims around the proportion of wealth held by different quintiles if substantial net debt held by a small proportion counts at the bottom. Some of it is student loan debt where the human capital generated by that education is not counted in the wealth tables - but only a small amount. I wonder if some of it is mortgage debt where the corresponding housing asset is held in a family trust not included in the wealth. Does it really seem likely that anybody would lend over $100,000 to those unlikely to be in a position to be able to pay it off?