Saving and Borrowing: A Response to Klein

Matthew Klein has a characteristically thoughtful post disagreeing with my new paper on income distribution and debt. I think his post has some valid arguments, but also, from my point of view, some misunderstandings. In any case, this is the conversation we should be having.

I want to respond on the specific points Klein raises. But first, in this post, I want to clarify some background conceptual issues. In particular, I want to explain why I think it’s unhelpful to think about the issues of debt and demand in terms of saving.

Klein talks a great deal about saving in his post. Like most people writing on these issues, he treats the concepts of rising debt-income ratios, higher borrowing and lower saving as if they were interchangeable. In common parlance, the question “why have households borrowed more?” is equivalent to “why have households saved less?” And either way, the spending that raises debt and reduces saving, is also understood to contribute to aggregate demand.

This conception is laid out in Figure 1 below. These are accounting rather than causal relationships. A minus sign in the link means the relationship is negative.

 

We start with households’ decision to consume more or less out of their income. Implicitly, all household outlays are for consumption, or at least, this is the only flow of household spending that varies significantly. An additional dollar of household consumption spending means an additional dollar of demand for goods and services; it also means a dollar less of savings. A dollar less of savings equals a dollar more of borrowing. More borrowing obviously means higher debt, or — equivalently in this view — a higher debt-GDP ratio.

There’s nothing particularly orthodox or heterodox about this way of looking at things. You can hear the claim that a rise in the household debt-income ratio contributes more or less one for one to aggregate demand as easily from Paul Krugman as from Steve Keen. Similarly, the idea that a decline in savings rates is equivalent to an increase in borrowing is used by Marxists as well as by mainstream economists, not to mention eclectic business journalists like Klein. Of course no one actually says “we assume that household assets are fixed or nonexistent.” But implicitly that’s what you’re doing when you treat the question of what has happened to household borrowing as if it were the equivalent of what has happened to household saving.

There is nothing wrong, in principle, with thinking in terms of the logic of Figure 1, or constructing models on that basis. Social science is impossible without abstraction. It’s often useful, even necessary, to think through the implications of a small subset of the relationships between economic variables, while ignoring the rest. But when we turn to  the concrete historical changes in macroeconomic quantities like household debt and aggregate demand in the US, the ceteris paribus condition is no longer available. We can’t reason in terms of the hypothetical case where all else was equal. We have to take into account all the factors that actually did contribute to those changes.

This is one of the main points of the debt-inequality paper, and of my work with Arjun Jayadev on household debt. In reality, much of the historical variation in debt-income ratios and related variables cannot be explained in terms of the factors in Figure 1. You need something more like Figure 2.

Figure 2 shows a broader set of factors that we need to include in a historical account of household sector balances. I should emphasize, again, that this is not about cause and effect. The links shown in the diagram are accounting relationships. You cannot explain the outcomes at the bottom without the factors shown here. [1] I realize it looks like a lot of detail. But this is not complexity for complexity’s sake. All the links shown in Figure 2 are quantitatively important.

The dark black links are the same as in the previous diagram. It is still true that higher household consumption spending reduces saving and raises aggregate demand, and contributes to lower saving and higher borrowing, which in turn contributes to lower net wealth and an increase in the debt ratio. Note, though, that I’ve separated saving from balance sheet improvement. The economic saving used in the national accounts is quite different from the financial saving that results in changes in the household balance sheet.

In addition to the factors the debt-demand story of Figure 1 focuses on, we also have to consider: various actual and imputed payment flows that the national accounts attribute to the household sector, but which do not involve any money payments to or fro households (blue); the asset side of household balance sheets (gray); factors other than current spending that contribute to changes in debt-income ratios (red); and change in value of existing assets (cyan).

The blue factors are discussed in Section 5 of the debt-distribution paper. There is a much fuller discussion in a superb paper by Barry Cynamon and Steve Fazzari, which should be read by anyone who uses macroeconomic data on household income and consumption. Saving, remember, is defined as the difference between income and consumption. But as Cynamon and Fazzari point out, on the order of a quarter of both household income and consumption spending in the national accounts is accounted for by items that involve no actual money income or payments for households, and thus cannot affect household balance sheets.

These transactions include, first, payments by third parties for services used by households, mainly employer-paid premiums for health insurance and payments to healthcare providers by Medicaid and Medicare. These payments are counted as both income and consumption spending for households, exactly as if Medicare were a cash transfer program that recipients then chose to use to purchase healthcare. If we are interested in changes in household balance sheets, we must exclude these payments, since they do not involve any actual outlays by households; but they still do contribute to aggregate demand. Second, there are imputed purchases where no money really changes hands at all.  The most important of these are owners’ equivalent rent that homeowners are imputed to pay to themselves, and the imputed financial services that households are supposed to purchase (paid for with imputed interest income) when they hold bank deposits and similar assets paying less than the market interest rate. Like the third party payments, these imputed interest payments are counted as both income and expenditure for households. Owners’ equivalent rent is also added to household income, but net of mortgage interest, property taxes and maintenance costs. Finally, the national accounts treat the assets of pension and similar trust funds as if they were directly owned by households. This means that employer contributions and asset income for these funds are counted as household income (and therefore add to measured saving) while benefit payments are not.

These items make up a substantial part of household payments as recorded in the national accounts – Medicare, Medicaid and employer-paid health premiums together account for 14 percent of official household consumption; owners’ equivalent rent accounts for another 10 percent; and imputed financial services for 4 percent; while consolidating pension funds with households adds about 2 percent to household income (down from 5 percent in the 1980s). More importantly, the relative size of these components has changed substantially in the past generation, enough to substantially change the picture of household consumption and income.

Incidentally, Klein says I exclude all healthcare spending in my adjusted consumption series. This is a misunderstanding on his part. I exclude only third-party health care spending — healthcare spending by employers and the federal government. I’m not surprised he missed this point, given how counterintuitive it is that Medicare is counted as household consumption spending in the first place.

This is all shown in Figure 3 below (an improved version of the paper’s Figure 1):

The two dotted lines remove public and employer payments for healthcare, respectively, from household consumption. As you can see, the bulk of the reported increase in household consumption as a share of GDP is accounted for by healthcare spending by units other than households. The gray line then removes owners’ equivalent rent. The final, heavy black line removes imputed financial services, pension income net of benefits payments, and a few other, much smaller imputed items. What we are left with is monetary expenditure for consumption by households. The trend here is essentially flat since 1980; it is simply not the case that household consumption spending has increased as a share of GDP.

So Figure 3 is showing the contributions of the blue factors in Figure 2. Note that while these do not involve any monetary outlay by households and thus cannot affect household balance sheets or debt, they do all contribute to measured household saving.

The gray factors involve household assets. No one denies, in principle, that balance sheets have both an asset side and a liability side; but it’s striking how much this is ignored in practice, with net and gross measures used interchangeably. In the first place, we have to take into account residential investment. Purchase of new housing is considered investment, and does not reduce measured saving; but it does of course involve monetary outlay and affects household balance sheets just as consumption spending does. [2] We also have take into account net acquisition of financial assets. An increase in spending relative to income moves household balance sheets toward deficit; this may be accommodated by increased borrowing, but it can just as well be accommodated by lower net purchases of financial assets. In some cases, higher desired accumulation of financial asset can also be an autonomous factor requiring balance sheet adjustment. (This is probably more important for other sectors, especially state and local governments, than for households.) The fact that adjustment can take place on the asset as well as the liability side is another reason there is no necessary connection between saving and debt growth.

Net accumulation of financial assets affects household borrowing, but not saving or aggregate demand. Residential investment also does not reduce measured saving, but it does increase aggregate demand as well as borrowing. The red line in Figure 3 adds residential investment by households to adjusted consumption spending. Now we can see that household spending on goods and services did indeed increase during the housing bubble period – conventional wisdom is right on that point. But this was a  spike of limited duration, not the secular increase that the standard consumption figures suggest.

Again, this is not just an issue in principle; historical variation in net acquisition of assets by the household sector is comparable to variation in borrowing. The decline in observed savings rates in the 1980s, in particular, was much more reflected in slower acquisition of assets than faster growth of debt. And the sharp fall in saving immediately prior to the great recession in part reflects the decline in residential investment, which peaked in 2005 and fell rapidly thereafter.

The cyan item is capital gains, the other factor, along with net accumulation, in growth of assets and net wealth. For the debt-demand story this is not important. But in other contexts it is. As I pointed out in my Crooked Timber post on Piketty, the growth in capital relative to GDP in the US is entirely explained by capital gains on existing assets, not by the accumulation dynamics described by his formula “r > g”.

Finally, the red items in Figure 2 are factors other than current spending and income that affect the debt-income ratio. Arjun Jayadev and I call this set of factors “Fisher dynamics,” after Irving Fisher’s discussion of them in his famous paper on the Great Depression. Interest payments reduce measured saving and shift balance sheets toward deficit, just like consumption; but they don’t contribute to aggregate demand. Defaults or charge-offs reduce the outstanding stock of debt, without affecting demand or measured savings. Like capital gains, they are a change in a stock without any corresponding flow. [3] Finally, the debt-income ratio has a denominator as well as a numerator; it can be raised just as well by slower nominal income growth as by higher borrowing.

These factors are the subject of two papers you can find here and here. The bottom line is that a large part of historical changes in debt ratios — including the entire long-term increase since 1980 — are the result of the items shown in red here.

So what’s the point of all this?

First, borrowing is not the opposite of saving. Not even roughly. Matthew Klein, like most people, immediately translates rising debt into declining saving. The first half of his post is all about that. But saving and debt are very different things. True, increased consumption spending does reduce saving and increase debt, all else equal. But saving also depends on third party spending and imputed spending and income that has no effect on household balance sheets. While debt growth depends, in addition to saving, on residential investment, net acquisition of financial assets, and the rate of chargeoffs; if we are talking about the debt-income ratio, as we usually are, then it also depends on nominal income growth. And these differences matter, historically. If you are interested in debt and household expenditure, you have to look at debt and expenditure. Not saving.

Second, when we do look at expenditure by households, there is no long-term increase in consumption. Consumption spending is flat since 1980. Housing investment – which does involve outlays by households and may require debt financing – does increase in the late 1990s and early 2000s, before falling back. Yes, this investment was associated with a big rise in borrowing, and yes, this borrowing did come significantly lower in the income distribution that borrowing in most periods. (Though still almost all in the upper half.) There was a debt-financed housing bubble. But we need to be careful to distinguish this episode from the longer-term rise in household debt, which has different roots.

 

[1] Think of it this way: If I ask why the return on an investment was 20 percent, there is no end to causal factors you can bring in, from favorable macroeconomic conditions to a sound business plan to your investing savvy or inside knowledge. But in accounting terms, the return is always explained by the income and the capital gains over the period. If you know both those components, you know the return; if you don’t, you don’t. The relationships in the figure are the second kind of explanation.

[2] Improvement of existing housing is also counted as investment, as are brokers’ commissions and other ownership transfer costs. This kind of spending will absorb some part of the flow of mortgage financing to the household sector — including the cash-out refinancing of the bubble period — but I haven’t seen an estimate of how much.

[3] There’s a strand of heterodox macro called “stock-flow consistent modeling.” Insofar as this simply means macroeconomics that takes aggregate accounting relationships seriously, I’m very much in favor of it. Social accounting matrices (SAMs) are an important and underused tool. But it’s important not to take the name too literally — economic reality is not stock-flow consistent!

 

Two Papers in Progress

There are two new papers on the articles page on this site. Both are work in progress – they haven’t been submitted anywhere yet.

 

[I’ve taken the debt-distribution paper down. It’s being revised.]

The Evolution of State-Local Balance Sheets in the US, 1953-2013

Slides

The first paper, which I presented in January in Chicago, is a critical assessment of the idea of a close link between income distribution and household debt. The idea is that rising debt is the result of rising inequality as lower-income households borrowed to maintain rising consumption standards in the face of stagnant incomes; this debt-financed consumption was critical to supporting aggregate demand in the period before 2008. This story is often associated with Ragnuram Rajan and Mian and Sufi but is also widely embraced on the left; it’s become almost conventional wisdom among Post Keynesian and Marxist economists. In my paper, I suggest some reasons for skepticism. First, there is not necessarily a close link between rising aggregate debt ratios and higher borrowing, and even less with higher consumption. Debt ratios depend on nominal income growth and interest payments as well as new borrowing, and debt mainly finances asset ownership, not current consumption. Second, aggregate consumption spending has not, contrary to common perceptions, risen as a share of GDP; it’s essentially flat since 1980. The apparent rise in the consumption share is entirely due to the combination of higher imputed noncash expenditure, such as owners’ equivalent rent; and third party health care spending (mostly Medicare). Both of these expenditure flows are  treated as household consumption in the national accounts. But neither involves cash outlays by households, so they cannot affect household balance sheets. Third, household debt is concentrated near the top of the income distribution, not the bottom. Debt-income ratios peak between the 85th and 90th percentiles, with very low ratios in the lower half of the distribution. Most household debt is owed by the top 20 percent by income. Finally, most studies of consumption inequality find that it has risen hand-in-hand with income inequality; it appears that stagnant incomes for most households have simply meant stagnant living standards. To the extent demand has been sustained by “excess” consumption, it was more likely by the top 5 percent.

The paper as written is too polemical. I need to make the tone more neutral, tentative, exploratory. But I think the points here are important and have not been sufficiently grappled with by almost anyone claiming a strong link between debt and distribution.

The second paper is on state and local debt – I’ve blogged a bit about it here in the past few months. The paper uses budget and balance sheet data from the census of governments to make two main points. First, rising state and local government debt does not imply state and local government budget deficits. higher debt does not imply higher deficits: Debt ratios can also rise either because nominal income growth slows, or because governments are accumulating assets more rapidly. For the state and local sector as a whole, both these latter factors explain more of the rise in debt ratios than does the fiscal balance. (For variation in debt ratios across state governments, nominal income growth is not important, but asset accumulation is.) Second, despite balanced budget requirements, state and local governments do show substantial variation in fiscal balances, with the sector as a whole showing deficits and surpluses up to almost one percent of GDP. But unlike the federal government, the state and local governments accommodate fiscal imbalances entirely by varying the pace of asset accumulation. Credit-market borrowing does not seem to play any role — either in the aggregate or in individual states — in bridging gaps between current expenditure and revenue.

I will try to blog some more about both these papers in the coming days. Needless to say, comments are very welcome.

Making Sense of Changes in State-Local Debt

In a previous post, I pointed out that state and local governments in the US have large asset positions — 33 percent of GDP in total, down from nearly 40 percent before the recession. This is close to double state and local debt, which totals 17 percent of GDP. Among other things, this means that a discussion of public balance sheets that looks only at debt is missing at least half the picture.

On the other hand, a bit over half of those assets are in pension funds. Some people would argue that it’s misleading to attribute those holdings to the sponsoring governments, or that if you do you should also include the present value of future pension benefits as a liability. I’m not sure; I think there are interesting questions here.

But there are also interesting questions that don’t depend on how you treat the existing stocks of pension assets and liabilities. Here are a couple. First, how how do changes in state credit-market debt break down between the current fiscal balance and other factors, including pension fund contributions? And second, how much of state and local fiscal imbalances are financed by borrowing, and how much by changes in the asset position?

Most economists faced with questions like these would answer them by running a regression. [1] But as I mentioned in the previous post, I don’t think a regression is the right tool for this job. (If you don’t care about the methods and just want to hear the results, you can skip the next several paragraphs, all the way down to “So what do we find?”)

Think about it: what is a regression doing? Basically, we have a variable a that we think is influenced by some others: b, c, d … Our observations of whatever social process we’re interested in consist of sets of values for a, b, c, d… , all of them different each time. A regression, fundamentally, is an imaginary experiment where we adjusted the value of just one of b, c, d… and observed how a changed as a result. That’s the meaning of the coefficients that are the main outputs of a regression, along with some measure of our confidence in them.

But in the case of state budgets we already know the coefficients! If you increase state spending by one dollar, holding all other variables constant, well then, you increase state debt by one dollar. If you increase revenue by one dollar, again holding everything else constant, you reduce debt by one dollar. Budgets are governed by accounting identities, which means we know all the coefficients — they are one or negative one as the case may be. What we are interested in is not the coefficients in a hypothetical “data generating process” that produces changes in state debt (or whatever). What we’re interested in is how much of the observed historical variation in the variable of interest is explained by the variation in each of the other variables. I’m always puzzled when I see people regressing the change in debt on expenditure and reporting a coefficient — what did they think they were going to find?

For the question we’re interested in, I think the right tool is a covariance matrix. (Covariance is the basic measure of the variation that is shared between two variables.) Here we are taking advantage of the fact that covariance is linear: cov(x, y + z) = cov(x, y) + cov(x, z). Variance, meanwhile, is just a variable’s covariance with itself. So if we know that a = b + c + d, then we know that the variance of a is equal to the sum of its covariances with each of the others. In other words, if y = Σ xn then:

(1) var(y) = Σ cov(y, xn)

So for example: If the budget balance is defined as revenue – spending, then the variance of some observed budget balances must be equal to the covariance of the balance with revenue, minus the covariance of the balance with spending.

This makes a covariance matrix an obvious tool to use when we want to allocate the observed variation in a variable among various known causes. But for whatever reason, economists turn to variance decompositions only in few specific contexts. It’s common, for instance, to see a variance decomposition of this kind used to distinguish between-group from within-group inequality in a discussion of income distribution. But the same approach can be used any time we have a set of variables linked by accounting identities (or other known relationships) and we want to assess their relative importance in explaining some concrete variation.

In the case of state and local budgets, we can start with the identity that sources of funds = uses of funds. (Of course this is true of any economic unit.) Breaking things up a bit more, we can write:

revenues + borrowing = expenditure + net acquisition of financial assets (NAFA).

Since we are interested in borrowing, we rearrange this to:

(2) net borrowing = expenditure – revenue + NAFA = fiscal balance – NAFA

But we are not simply interested in borrowing,w e are interested in the change in the debt-GDP ratio (or debt-GSP ratio, in the case of individual states.) And this has a denominator as well as a numerator. So we write:

(3) change in debt ratio = net borrowing – nominal growth rate

This is also an accounting identity, but not an exact one; it’s a linear approximation of the true relationship, which is nonlinear. But with annual debt and income growth rates in the single digits, the approximation is very close.

So we have:

(4) change in debt ratio = expenditure – revenue + NAFA – nominal growth rate * current debt ratio

It follows from equation (1) that  the variance of change in the debt ratio is equal to the sum of the covariances of the change with each of the right-side variables. In other words, if we are interested in understanding why debt-GDP ratios have risen in some years and fallen in others, it’s straightforward to decompose this variation into the contributions of variation in each of the other variables. There’s no reason to do a regression here. [2]

So what do we find?

Here’s the covariance matrix for combined state and local debt for 1955 to 2013.  “Growth contrib.” refers to the last term in Equation (4). To make reading the table easier, I’ve reversed the sign of the growth contribution, fiscal balance and revenue; that means that positive values in the table all refer to factors that increase the variance of debt-ratio growth and negative values are factors that reduce it. [3]

Debt Ratio Growth Growth Contrib. Fiscal Balance Revenue Expenditure NAFA & Trusts
Debt Ratio Growth 0.18
Growth Contrib. (-) 0.10 0.11
Fiscal Balance (-) 0.03 0.04 0.13
Revenue (-) 0.08 0.24 0.12 5.98
Expenditure 0.11 0.28 -0.01 5.86 5.87
NAFA & Trusts 0.06 -0.05 0.13 -0.01 -0.14 0.23

How do we read this? First of all, note the bolded terms along the main diagonal — those are the covariance of each variable with itself, that is, its variance.  It is a measure of how much individual observations of this variable differ from each other. The off-diagonal terms, then, show how much of this variation is shared between two variables. Again, we know that if one variable is the sum of several others, then its variance will be the sum of its covariances with each of the others.

So for example, total variance of debt ratio growth is 0.18. (That means that the debt ratio growth  in a given year is, on average, about 0.4 percentage points above or below the average growth rate for the full period.) The covariance of debt-ratio growth and (negative) growth contribution is 0.10. So a bit over half the debt-ratio variance is attributable to nominal GDP growth. In other words, if we are looking at why the debt-GDP ratio rises more in some years than in others, more of the variation is going to be explained by the denominator of the ratio than the numerator. Next, we see that the covariance of debt growth with the (negative) fiscal balance is 0.03. In other words, about one-sixth of the variation in annual debt ratio growth is explained by fiscal deficits or surpluses.

This is important, because most discussions of state and local debt implicitly assume that all change in the debt ratio is explained this way. But in fact, while the fiscal balance does play some role in changes in the debt ratio — the covariance is greater than zero — it’s a distinctly secondary role.  Finally, the last variable, “NAFA & Trusts,” explains about a third of variation in debt ratio growth. In other words, years when state and local government debt is rising more rapidly relative to GDP, are also years in which those governments are adding more rapidly to their holdings of financial assets. And this source of variation explains about twice as much of the historical pattern of debt ratio changes, as the fiscal balance does.

Since this is probably still a bit confusing, the next table presents the same information in a hopefully clearer way. Here see only the covariances with debt ratio growth — the first column of the previous table — and they are normalized by the variance of debt ratio growth. Again, I’ve flipped the sign of variables that reduce debt-ratio growth. So each value of the table shows the share of variation in the growth of state-local growth ratios that is explained by that component. There is also a second column, showing the same thing for state governments only.  

Component State + Local State Only
Nominal Growth (-) 0.52 0.30
Fiscal Balance (-) 0.17 0.31
Revenue (-) -0.41 0.07
Expenditure 0.58 0.24
… of which: Interest 0.06 0.03
Trust Contrib. and NAFA 0.33 0.37
… of which: Pensions 0.01 0.02

I’ve added a couple variables here — interest payments under expenditure and pension contributions under NAFA and Trusts. Note in particular the small value of the latter. Pension contributions are quite stable from year to year. (The standard deviation of state/local pension contributions as a percent of GDP is just 0.07, versus around 0.5 for nontrust NAFA.)  This says that even though most state and local assets are in pension funds, pension contributions contribute only a little to the variation in asset acquisition. Most of the year to year variability is in governments’ acquisition of assets on their own behalf. This is helpful: It means that if we are interested in understanding variation in the growth of debt over time, or the role of assets vs. liabilities in accommodating fiscal imbalances, we don’t need to worry too much about how to think about pension funds. (If we want to focus on the total increase in state debt, as opposed to the variation over time, then pensions are still very important.)

If we compare the overall state-local sector with state governments only, the picture is broadly similar, but there are some interesting differences. First of all, nominal growth rates are somewhat less important, and the fiscal balance more important, for state government debt ratio. This isn’t surprising. State governments have more flexibility than local ones to independently adjust their spending and revenue; and state debt ratios are lower, so the effect on the ratio from a given change in growth rates is proportionately smaller. For the same reason, the effect of interest rate changes on the debt ratio, while small in both cases, is even smaller for the lower-debt state governments. [4]

So now we have shown more rigorously what we suggested in the previous post: While the fiscal balance plays some role in explaining why state and local debt ratios rise at some times and fall at others, it is not the main factor. Nominal growth rates and asset acquisition both play larger roles.

Let’s turn to the next question: How do state and local government balance sheets adjust to fiscal imbalances? Again, this is just a re-presentation of the data in the first table, this time focusing on the third column/row. Again, we’re also doing the decomposition for states in isolation, and adding a couple more items — in this case, the taxes and intergovernmental assistance components of revenue, and the pension contribution component of NAFA. The values are normalized here by the variance of the fiscal balance. The first four lines sum to 1, as do the last three. In effect, the first four rows of the table tells us where fiscal imbalances come from; the final three tell us where they go.


Component State + Local State Only
Revenue, of which: 0.94 1.01
… Taxes 0.50 0.93
… Intergovernmental 0.18 -0.04
Expenditure (-) 0.06 -0.01
Trust Contrib. and NAFA, of which: 1.04 0.92
… Pensions 0.10 -0.49
Borrowing (-) -0.04 0.08

So what do we see? Looking at the first set of lines, we see that state-local fiscal imbalances are entirely expenditure-driven. Surprisingly, revenues are no lower in deficit years than in surplus ones. Note that this is true of total revenues, but not of taxes. Deficit years are indeed associated with lower tax revenue and surplus years with higher taxes, as we would expect. (That’s what the positive values in the “taxes” row mean.) But this is fully offset by the opposite variation in payments from the federal government, which are lower in surplus years and higher in deficit years. During the most recent recession, for example, aggregate state and local taxes declined by about 0.4 percent of GDP. But federal assistance to state and local governments increased by 0.9 percent of GDP. This was unexpected to me: I had expected most of the variation in state budget balances to come from the revenue side. But evidently it doesn’t. The covariance matrix is confirming, and quantifying, what you can see in the figure below: Deficit years for the state-local sector are associated with peaks in spending, not troughs in revenue.

muni-budgets
Aggregate State-Local Revenue and Expenditure, 1953-2013

Turning to the question of how imbalances are accommodated, we find a similarly one-sided story. None of the changes in state-local budget balances result in changes in borrowing; all of them go to changes in fund contributions and direct asset purchases. [5] For the sector as a whole, in fact, asset purchases absorb more than all the variation in fiscal imbalances; borrowing is lower in deficit years than in surplus years. (For state governments, borrowing does absorb about ten percent of variation in the fiscal balance.) Note that very little of this is accounted for by pensions — less than none in the case of state governments, which see lower overall asset accumulation but higher pension fund contributions in deficit years. Again, even though pension funds account for most state-local assets, they account for very little of the year to year variation in asset purchases.

So the data tells a very clear story: Variation in state-local budget balances is driven entirely by the expenditure side; cyclical changes in their own revenue are entirely offset by changes in federal aid. And state budget imbalances are accommodated entirely by changes in the rate at which governments buy or sell assets. Over the postwar period, the state-local government sector has not used borrowing to smooth over imbalances between revenue and spending.

 

[1] The interesting historical meta-question, to which I have no idea of the answer, when and why regression analysis came to so completely dominate empirical work in economics. I suspect there are some deep reasons why economists are more attracted to methodologies that treat observed data as a sample or “draw” from a universal set of rules, rather than methodologies that focus on the observed data as the object of inquiry in itself.

[2] I confess I only realized recently that variance decompositions can be used this way. In retrospect, we should have done this in our papers in household debt.

[3] Revenue and expenditure here include everything except trust fund income and payments. In other words, unlike in the previous post, I am following the standard practice of treating state and local budgets separate from pension funds and other trust funds. The last line, “NAFA and Trusts”, includes both contributions to trust funds and acquisition of financial assets by the local government itself. But income generated by trust fund assets, and employee contributions to pension funds, are not included in revenue, and benefits paid are not included in expenditure. So the “fiscal balance” term here is basically the same as that reported by the NIPAs and other standard sources.

[4] This is different from households and the federal government, where higher debt and, in the case of households, more variable interest rates, mean that interest rates are of first-order importance in explaining the evolution of debt ratios over time.

[5] It might seem contradictory to say that a third of the variation in changes in the debt ratio is due to the fiscal balance, even though none of the variation in the fiscal balance is passed through to changes in borrowing. The reason this is possible is that those periods when there are both deficits and higher borrowing, also are periods of slower nominal income growth. This implies additional variance in debt growth, which is attributed to both growth and the fiscal balance. There’s some helpful discussion here.

 

(This post is based on a paper in process. I probably will not post any more material from this project for the next month or so, since I need to return to the question of potential output.)

 

New Article in the Review of Keynesian Economics

My paper with Arjun Jayadev, “The Post-1980 Debt Disinflation: An Exercise in Historical Accounting,” has now been published in the Review of Keynesian Economics. (There is some other stuff that looks interesting in there as well, but unfortunately most of the content is paywalled, a choice I’ve complained to the editors about.) I’ve posted the full article on the articles page on this site.

Here’s the abstract:

The conventional division of household payment flows between consumption and saving is not suitable for investigating either the causes of changing household debt–income ratios, or the interaction of household debt with aggregate demand. To explain changes in household debt, it is necessary to use an accounting framework that isolates net credit-market flows to the household sector, and that takes account of changes in the debt–income ratio resulting from nominal income growth as well as from new borrowing. To understand the implications of changing household income and expenditure flows for aggregate demand, it is necessary to distinguish expenditures that contribute to demand from expenditures that do not. Applying a conceptually appropriate accounting framework to the historical data reveals that the rise in household leverage over the past 3 decades cannot be understood in terms of increased household borrowing. For both the decade of the 1980s and the full post-1980 period, rising household debt–income ratios are entirely explained by the rise in nominal interest rates relative to nominal income growth. The rise in household debt after 1980 is best thought of as a debt disinflation, analogous to the debt deflation of the 1930s.

You can read the rest here.

Are US Households Done Deleveraging?

This Tuesday, I’ll be  at Joseph Stiglitz’s event at Columbia University on finance and inequality, presenting my work with Arjun Jayadev on household debt. You can find the latest version of our paper here.

In preparation, I’ve been updating the numbers and the results are interesting. As folks at the Fed have noted, the post-2007 period of household deleveraging seems to have reached its end. Here’s what the household debt picture looks like, in the accounting framework that Arjun and I prefer.

The units are percent of adjusted household income. (We can ignore the adjustments here.) The heavy black line shows the year-over-year change in household debt-income ratios. The bars then disaggregate that change into new borrowing by households — the primary deficit — and the respective contributions of interest payments, inflation, income growth, and defaults. A negative bar indicates a factor that reduces leverage; in most years, this includes both (real) income and inflation, since by raising the denominator they reduce the debt-income ratio. A positive bar indicates a factor that increases leverage; this includes interest payments (which are always positive), and the primary deficit in years in which households are on net receiving funds from credit markets.

Here’s what we are seeing:

In 2006 and 2007, debt-income ratios rose by about 3 percent each year; this is well below the six-point annual increases earlier in the 2000s, but still substantial. In 2008, the first year of the recession, the household debt-income ratio rises by another 3 points, despite the fact that households are now paying down debt, with repayments exceeding new borrowing by nearly 8 percent of household income. This is an astonishing rate of net repayment, the greatest since at least 1931. But despite this desperate effort to deleveraging, household debt-income ratios actually rose in 2008, thanks to the sharp fall in income and to near-zero inflation — in most years, the rise in prices automatically erodes the debt-income ratio. The combination of negative net borrowing and a rising debt burden is eerily reminiscent of the early Depression — it’s a clear sign of how, absent Big Government, the US at the start of the last recession was on track for a reprise of the Depression.

Interest payments make a stable positive contribution to the debt-incoem ratio throughout this period. Debt-service payments do fall somewhat, from around 7 percent of household income in 2006 to around 5 percent in 2013. But compared with other variables important to debt dynamics, debt-service payments are quite stable in the short-term. (Over longer periods, changes in effective interest rates are a ] bigger deal.) It’s worth noting in particular that the dramatic reduction in the federal funds rate in 2007-2008 had a negligible effect on the average interest rate paid by households.

In 2009-2012, the household debt-income ratio does fall, by around 5 points per year. But note that household surpluses (i.e. negative deficits) are no larger in these years than in 2008; the difference is that we see resumed positive growth of inflation and, a bit later, real incomes, raising the denominator of the debt-income ratio. This is what failed to happen in the 1930s. Equally important, there is a sharp rise in the share of debt written off by default, exceeding 3 percent in each year, compared with a writeoff rate below one percent in all pre-recession years. Note that the checked bar and the white bar are of similar magnitudes: In other words, repayment and default contributed about equally to the reduction of household debt. If deleveraging was an important requirement for renewed economic growth then it’s a good thing that it’s still possible to discharge our debts through bankruptcy. Otherwise, there would have been essentially no reduction in debt-income ratios between 2007 and 2012. [*]

This much is in the paper. But in 2013 the story changes a bit. The household debt-income ratio rises again, for the first time since 2008. And the household balance movers into deficit, for the first time since 2007 — for the first time in six years, households are receiving more funds from the credit markets than they are paying back to them. These events are linked. While the central point of our paper is that changes in leverage cannot be reduced to changes in borrowing, for the US households in 2013, it is in fact increased borrowing that drove the rise in debt-income ratios. Inflation and income growth were basically constant between 2012 and 2013. The 5-point acceleration in the growth of the household debt-income ratio is explained by a 4.5 point rise in new borrowing by households (plus a 1.5 point fall in defaults, offset by a 1-point acceleration in real income growth).

So what do we make of this? Well, first, boringly perhaps but importantly, it’s important to acknowledge that sometimes the familiar story is the correct story. If households owe more today than a year ago, it’s because they borrowed more over the past year. It’s profoundly misleading to suppose this is always the case. But in this case it is the case. Secondly, I think this vindicates the conclusion of our paper, that sustained deleveraging is impossible in the absence of substantially higher inflation, higher defaults, or lower interest rates. These are not likely to be seen without deliberate, imaginative policy to increase inflation, directly reduce the interest rates facing households, and/or write off much more of household debt than will happen through the existing bankruptcy process. Otherwise, in today’s low-inflation environment, as soon as the acute crisis period ends leverage is likely to resume its rise. Which seems to be what we are seeing.

[*] More precisely: By our calculations, defaults reduced the aggregate household debt-income ratio by 20 points over 2008-2012, out of a total reduction of 21.5 points.

The Nonexistent Rise in Household Consumption

Did you know that about 10 percent of private consumption in the US consists of Medicare and Medicaid? Despite the fact that these are payments by the government to health care providers, they are counted by the BEA both as income and consumption spending for households.

I bet you didn’t know that. I bet plenty of people who work with the national income accounts for a living don’t know that. I know I didn’t know it, until I read this new working paper by Barry Cynamon and Steve Fazzari.

I’ve often thought that the best macroeconomics is just accounting plus history. This paper is an accounting tour de force. What they’ve done is go through the national accounts and separate out the components of household income and expenditure that represent cashflows received and made by households, from everything else.

Most people don’t realize how much of what goes into the headline measures of household income and household consumption does not actually correspond to any flow of money to or from households. In 2011 (the last year covered by the paper), personal consumption expenditure was given as just over $10 trillion. But of that, only about $7.5 trillion was money spent by households on goods and services. Of the rest, as of 2011:

– $1.2 trillion was imputed rents on owner-occupied housing. The national income and product accounts treat housing on the principle that the real output of housing should be the same whether or not the person living in the house happens to be the same person who owns it. So for owner-occupied housing, they impute an “owner equivalent rent” that the resident is implicitly paying to themselves for use of the house.  This sounds reasonable, but it conflicts with another principle of the national accounts, which is that only market transactions are recorded. It also creates measurement problems since most owned residences are single-family homes, for which there isn’t a big rental market, so the BEA has to resort to various procedures to estimate what the rent should be. One result of the procedures they use is that a rise in hoe prices, as in the 2000s, shows up as a rise in consumption spending on imputed rents even if no additional dollars change hands.

– $970 billion was Medicare and Medicaid payments; another $600 billion was employer purchases of group health insurance. The official measures of household consumption are constructed as if all spending on health benefits took the form of cash payments, which they then chose to spend on health care. This isn’t entirely crazy as applied to employer health benefits, since presumably workers do have some say in how much of their compensation takes the form of cash vs. health benefits; tho one wouldn’t want to push that assumption that too far. But it’s harder to justify for public health benefits. And, justifiable or not, it means the common habit of referring to personal consumption expenditure as “private” consumption needs a large asterix.

– $250 billion was imputed bank services. The BEA assumes that people accept below-market interest on bank deposits only as a way of purchasing some equivalent service in return. So the difference between interest from bank deposits and what it would be given some benchmark rate is counted as consumption of banking services.

– $400 billion in consumption by nonprofits. Nonprofits are grouped with the household sector in the national accounts. This is not necessarily unreasonable, but it creates confusion when people assume the household sector refers only to what we normally think of households, or when people try to match up the aggregate data with surveys or other individual-level data.

Take these items, plus a bunch of smaller ones, and you have over one-quarter of reported household consumption that does not correspond to what we normally think of as consumption: market purchases of goods and services to be used by the buyer.

The adjustments are even more interesting when you look at trends over time. Medicare and Medicaid don’t just represent close to 10 percent of reported “private” consumption; they represent over three quarters of the increase in consumption over the past 50 years. More broadly, if we limit “consumption” to purchases by households, the long term rise in household consumption — taken for granted by nearly everyone, heterodox or mainstream — disappears.

By the official measure, personal consumption has risen from around 60 percent of GDP in the 1950s, 60s and 70s, to close to 70 percent today. While there are great differences in stories about why this increase has taken place, almost everyone takes for granted that it has. But if you look at Cynamon and Fazzari’s measure, which reflects only market purchases by households themselves, there is no such trend. Consumption declines steadily from 55 percent of GDP in 1950 to around 47 percent today. In the earlier part of this period, impute rents for owner occupied housing are by far the biggest part of the difference; but in more recent years third-party medical expenditures have become more important. Just removing public health care spending from household consumption, as shown in the pal red line in the figure, is enough to change a 9 point rise in the consumption share of GDP into a 2 point rise. In other words, around 80 percent of the long-term rise in household consumption actually consists of public spending on health care.

In our “Fisher dynamics” paper, Arjun Jayadev and I showed that the rise in debt-income ratios for the household sector is not due to any increase in household borrowing, but can be entirely explained by higher interest rates relative to income growth and inflation. For that paper, we wanted to adjust reported income in the way that Fazzari and Cynamon do here, but we didn’t make a serious effort at it. Now with their data, we can see that not only does the rise in household debt have nothing to do with any household decisions, neither does the rise in consumption. What’s actually happened over recent decades is that household consumption as a share of income has remained roughly constant. Meanwhile, on the one hand disinflation and high interest rates have increased debt-income ratios, and on the other hand increased public health care spending and, in the 2000s high home prices, have increased reported household consumption. But these two trends have nothing to do with each other, or with any choices made by households.

There’s a common trope in left and heterodox circles that macroeconomic developments in recent decades have been shaped by “financialization.” In particular, it’s often argued that the development of new financial markets and instruments for consumer credit has allowed households to choose higher levels of consumption relative to income than they otherwise would. This is not true. Rising debt over the past 30 years is entirely a matter of disinflation and higher interest rates; there has been no long run increase in borrowing. Meanwhile, rising consumption really consists of increased non-market activity — direct provision of housing services through owner-occupied housing, and public provision of health services. This is if anything a kind of anti-financialization.

The Fazzari and Cynamon paper has radical implications, despite its moderate tone. It’s the best kind of macroeconomics. No models. No econometrics. Just read the damn tables, and think about what the numbers mean.

Borrowing ≠ Debt

There’s a common shorthand that makes “debt” and “borrowing” interchangeable. The question of why an economic unit had rising debt over some period, is treated as equivalent to the question of why it was borrowing more over that period, or why its expenditure was higher relative to its income. This is a natural way of talking, but it isn’t really correct.

The point of Arjun’s and my paper on debt dynamics was to show that for household debt, borrowing and changes in debt don’t line up well at all. While some periods of rising household leverage — like the housing bubble of the 2000s — were also periods of high household borrowing, only a small part of longer-term changes in household debt can be explained this way. This is because interest, income growth and inflation rates also affect debt-income ratios, and movements in these other variables often swamp any change in household borrowing.
As far as I know, we were the first people to make this argument in a systematic way for household debt. For government debt, it’s a bit better known — but only a bit. People like Willem Buiter or Jamie Galbraith do point out that the fall in US debt after World War II had much more to do with growth and inflation than with large primary surpluses. You can find the argument more fully developed for the US in papers by Hall and Sargent  or Aizenman and Marion, and for a large sample of countries by Abbas et al., which I’ve discussed here before. But while many of the people making it are hardly marginal, the point that government borrowing and government debt are not equivalent, or even always closely linked, hasn’t really made it into the larger conversation. It’s still common to find even very smart people saying things like this:

We didn’t have anything you could call a deficit problem until 1980. We then saw rising debt under Reagan-Bush; falling debt under Clinton; rising under Bush II; and a sharp rise in the aftermath of the financial crisis. This is not a bipartisan problem of runaway deficits! 

Note how the terms “deficits” and “rising debt” are used interchangeably; and though the text mostly says deficits, the chart next to this passage shows the ratio of debt to GDP.
What we have here is a kind of morality tale where responsible policy — keeping government spending in line with revenues — is rewarded with falling debt; while irresponsible policy — deficits! — gets its just desserts in the form of rising debt ratios. It’s a seductive story, in part because it does have an element of truth. But it’s mostly false, and misleading. More precisely, it’s about one quarter true and three quarters false.
Here’s the same graph of federal debt since World War II, showing the annual change in debt ratio (red bars) and the primary deficit (black bars), both measured as a fraction of GDP. (The primary deficit is the difference between spending other than interest payments and revenue; it’s the standard measure of the difference between current expenditure and current revenue.) So what do we see?
It is true that the federal government mostly ran primary surpluses from the end of the war until 1980, and more generally, that periods of surpluses were mostly periods of rising debt, and conversely. So it might seem that using “deficits” and “rising debt” interchangeably, while not strictly correct, doesn’t distort the picture in any major way. But it does! Look more carefully at the 1970s and 1980s — the black bars look very similar, don’t they? In fact, deficits under Reagan were hardy larger than under Ford and Carter —  a cumulative 6.2 percent of GDP over 1982-1986, compared with 5.6 percent of GDP over 1975-1978. Yet the debt-GDP ratio rose by just a single point (from 24 to 25) in the first episode, but by 8 points (from 32 to 40) in the second. Why did debt increase in the 1980s but not in the 1970s? Because in the 1980s the interest rate on federal debt was well above the economy’s growth rate, while in the 1970s, it was well below it. In that precise sense, if debt is a problem it very much is a bipartisan one; Volcker was the appointee of both Carter and Reagan.
Here’s the same data by decades, and for the pre- and post-1980 periods and some politically salient subperiods.  The third column shows the part of debt changes not explained by the primary balance. This corresponds to what Arjun and I call “Fisher dynamics” — the contribution of growth, inflation and interest rates to changes in leverage. [*] The units are percent of GDP.
Totals by Decade
Primary Deficit Change in Debt Residual Debt Change
1950s -8.6 -29.6 -20.9
1960s -7.3 -17.7 -10.4
1970s 2.8 -1.7 -4.6
1980s 3.3 16.0 12.7
1990s -15.9 -7.3 8.6
2000s 23.7 27.9 4.2
Annual averages
Primary Deficit Change in Debt Residual Debt Change
1947-1980 -0.7 -2.0 -1.2
1981-2011 0.1 1.3 1.2
   1981-1992 0.3 1.8 1.5
   1993-2000 -2.7 -1.6 1.1
   2001-2008 -0.1 0.8 0.9
   2009-2011 7.3 8.9 1.6

Here again, we see that while the growth of debt looks very different between the 1970s and 1980s, the behavior of deficits does not. Despite Reagan’s tax cuts and military buildup, the overall relationship between government revenues and expenditures was essentially the same in the two decades. Practically all of the acceleration in debt growth in the 1980s compared with the 1970s is due to higher interest rates and lower inflation.

Over the longer run, it is true that there is a shift from primary surpluses before 1980 to primary deficits afterward. (This is different from our finding for households, where borrowing actually fell after 1980.) But the change in fiscal balances is less than 25 percent the change in debt growth. In other words, the shift toward deficit spending, while real, only accounts for a quarter of the change in the trajectory of the federal debt. This is why I said above that the morality-tale version of the rising debt story is a quarter right and three quarters wrong.

By the way, this is strikingly consistent with the results of the big IMF study on the evolution of government debt ratios around the world. Looking at 60 episodes of large increases in debt-GDP ratios over the 20th century, they find that only about a third of the average increase is accounted for by primary deficits. [2] For episodes of falling debt, the role of primary surpluses is somewhat larger, especially in Europe, but if we focus on the postwar decades specifically then, again, primary surpluses accounted for only a about a third of the average fall. So while the link between government debt and deficits has been a bit weaker in the US than elsewhere, it’s quite weak in general.

So. Why should we care?

Most obviously, you should care if you’re worried about government debt. Now maybe you shouldn’t worry. But if you do think debt is a problem, then you are looking in the wrong place if you think holding down government borrowing is the solution. What matters is holding down i – (g + π) — that is, keeping interest rates low relative to growth and inflation. And while higher growth may not be within reach of policy, higher inflation and lower interest rates certainly are.

Even if you insist on worrying not just about government debt but about government borrowing, it’s important to note that the cumulative deficits of 2009-2011, at 22 percent of GDP, were exactly equal to the cumulative surpluses over the Clinton years, and only slightly smaller than the cumulative primary surpluses over the whole period 1947-1979. So if for whatever reason you want to keep borrowing down, policies to avoid deep recessions are more important than policies to control spending and raise revenue.

More broadly, I keep harping on this because I think the assumption that the path of government debt is the result of government borrowing choices, is symptomatic of a larger failure to think clearly about this stuff. Most practically, the idea that the long-run “sustainability” of the  debt requires efforts to control government borrowing — an idea which goes unquestioned even at the far liberal-Keynesian end of the policy spectrum —  is a serious fetter on proposals for more stimulus in the short run, and is a convenient justification for all sorts of appalling ideas. And in general, I just reject the whole idea of responsibility. It’s ideology in the strict sense — treating the conditions of existence of the dominant class as if they were natural law. Keynes was right to see this tendency to view of all of life through a financial lens — to see saving and accumulating as the highest goals in life, to think we should forego real goods to improve our financial position — as “one of those semicriminal, semi-pathological propensities which one hands over with a shudder to the specialists in mental disease.”

On a methodological level, I see reframing the question of the evolution of debt in terms of the independent contributions of primary deficits, growth, inflation and interest rates as part of a larger effort to think about the economy in historical, dynamic terms, rather than in terms of equilibrium. But we’ll save that thought for another time.

The important point is that, historically, changes in government borrowing have not been the main factor in the evolution of debt-GDP ratios. Acknowledging that fact should be the price of admission to any serious discussion of fiscal policy.

[1] Strictly speaking, debt ratios can change for reasons other than either the primary balance or Fisher dynamics, such as defaults or the effects of exchange rate movements on foreign-currency-denominated debt. But none of these apply to the postwar US.

[2] The picture is a bit different from the US, since adverse exchange-rate movements are quite important in many of these episodes. But it remains true that high deficits are the main factor in only a minority of large increases in debt-GDP ratios.

The Dynamics of Household Debt

Regular readers of this blog will remember some interesting discussions here a few months ago of the dynamics of public debt. The point — which is taught in any graduate macro course, but seldom emphasized in public debates — is that the change in debt-GDP ratios over time depends not just on government deficits or surpluses, but also on growth, inflation and interest rates. In particular, for the US, the UK and many other countries [1], the decline in debt/GDP in the postwar decades is entirely due to growth rates in excess of interest rates, with primary surpluses contributing nothing or less than nothing.
An obvious extension of that discussion is the question, What about private debt? After all, the rise in private leverage over the past few  decades is even more dramatic than the rise in public leverage:
Sectoral Debt as Share of GDP, 1929-2010. Click to embiggen.
So what if you apply the same kind of decomposition to private debt that is done for public debt, and ask how much of the change in sector’s debt in a given period is due to changes in borrowing behavior, and how much is due to changes in interest rates, growth rates, and or inflation? Surprisingly, no one seems to have done this. So Arjun Jayadev and I decided to try it, for household debt specifically, with (IMO) some very interesting results. A preliminary draft of our paper is here.
I’ll have more on the content shortly, but if you’re interested please take a look at the paper. We’re in the process of revising it now, and any comments/questions/thoughts on making it better would be most welcome.