Now for the update—we finally started blogging again, as of today, although we decided to start a new blog. You’ll find our work at ffwiley.com. After reflecting on what we liked and didn’t like from older articles (reading your own moss-covered prose can be disturbing), the new blog may be improved, but you’ll be the judge of that. We’ll write about the usual topics and would be more than happy to see our former readers subscribe to the new blog.

And that’s not all—FF finally finished and published his book, which is titled Economics for Independent Thinkers: A Practical, No-Nonsense Guide to Understanding Economic Risks. You can learn more about it on this website, which includes sample chapters. Or, to buy it on Amazon, go here. (You’ll see that we didn’t wait for Susan Rice to “unmask” us. But we can always be FF and Ginger to you.)

Thank you again for showing interest in our work and sharing it with others!

FF Wiley and Ginger Snap

#5 with 41,690 views: “Why You Shouldn’t Fall For These Corporate Capex Fallacies.”

We critique four popular arguments about capital expenditures, while showing that history contradicts all but one of the four.

#4 with 44,509 views: “Reviving the ‘Real World’ Scenario That’s Disappeared from Government Reports.”

We adjust the CBO’s official budget projections for glaring deficiencies in its “baseline scenario,” from an overly optimistic economic outlook (better even than the Great Moderation of the mid-1980s to mid-2000s) to the tax break extensions that Congress always enacts even as it requires the CBO to exclude them from its baseline.

#3 with 47,079 views: “Where $1 of QE Goes: The Untold Story.”

We explore how QE works its way through the financial sector. After separating financial flows history into QE periods and non-QE periods, we find a curious “argyle effect.”

#2 with 51,120 views: “Is This What a Credit Bubble Looks Like?”

With corporate borrowing picking up in 2014, we compare key metrics to past credit cycles.

#1 with 79,753 views: “Why the Next Global Crisis Will Be Unlike Any in the Last 200 Years.”

We remove military spending from 200 years of developed market budget histories – to isolate fiscal policy trends independently from wars and revolutions.

. . .

Many thanks to our readers and to bloggers who directed their readers to our site. Best wishes for 2015. We expect to start posting again soon.

In the meantime, check out our friend Nicholas Carlson’s new book on Yahoo and Marissa Mayer (Marissa Mayer and the Fight to Save Yahoo!). Nicholas has the inside story on one of our most fascinating CEOs, following up the “unauthorized biography” that he published on Business Insider in 2013.  For a teaser (the book doesn’t ship until next week), you can also check out the December 17 New York Times Magazine cover story, “What Happened When Marissa Mayer Tried to Be Steve Jobs.”

Why do you show three different series in the first chart?

We show “Net Private Debt from Census Bureau” because it has the longest history. We use it later to calculate 5-year credit growth figures for the period before the Fed’s “flow of funds” becomes available.

We deduct financial and real estate corporation debt in the second dotted line to show that private debt growth in the late 1920s wasn’t skewed by financial debt (as it was in the 2000s). We can only back out financial debt from 1926 (not enough data to use in the “savings rates and credit growth” chart), but this series jumped even more than “Net Private Debt from Census Bureau” between 1926 and 1929.

Where can I find your data?

Here’s a list:

Peak GDP or GNP

• Calculated using GDP estimates from the BEA for 1929 to 2013.
• Before 1929, calculated using GNP estimates from the Smits, Woltjer and Ma database: J.P. Smits, P.J. Woltjer and D. Ma (2009), ‘A Dataset on Comparative Historical National Accounts, ca. 1870-1950: A Time-Series Perspective’, Groningen Growth and Development Centre Research Memorandum GD-107, Groningen: University of Groningen.”

Private debt

• “Net Private Debt per Census Bureau” is calculated from Series X 398 of the Bicentennial Edition of the Historical Statistics of the United States.
• “Less Financial and RE Corporation Debt” is calculated from Series X 402 (private individual and noncorporate debt), V 174 (accounts payable and short-term debt) and V 175 (long-term debt) of the Historical Statistics.
• “Nonfinancial Private Debt per ‘Flow of Funds’” is from the Fed’s Z.1 report.

Savings rates

• From the BEA for 1929 to 2013.
• Before 1929, calculated from Series F 9 and G 470 of Historical Statistics. Consumption data is available for odd numbered years only.

Change in private debt-to-GDP ratio

• Calculated from Z.1 data for nonfinancial private debt from 1951 and from Series X 398 of Historical Statistics before that.

“Risky Lending” and “Lending from Domestic, Non-Money Savings”

• From the Z.1.
• “Risky Lending” combines the net flows in credit market instruments, repos and some interbank lending categories for the “Rest of the World” (Table F.106), the Fed (F.108) and private banks (F.109). It also includes the estimated credit market asset and repo portion of the money market fund and mutual fund holdings of each of those entities.
• “Lending from Domestic, Non-Money Savings” combines credit market assets and repos for households (Table F.100), nonfinancial corporates (F.102), nonfinancial noncorporate businesses (F.103), insurance companies (F.114 and F.115), pension funds (F.116), closed-end funds and ETFs (F.122) and equity REITs (F.127e). It also includes the estimated credit market asset and repo portion of the money market fund and mutual fund holdings of each of those entities.
• For further detail, see “Technical Notes for ‘3 Underappreciated Indicators’.”

Can you send us your data?

We offer worksheets and/or consulting, but not for free.  Email ffwiley@gmail.com.

[O]f all the economic bubbles that have been pricked, few have burst more spectacularly than the reputation of economics itself.
– From The Economist, July 16, 2009.

It’s been five years since the The Economist magazine published the critical commentary  excerpted above. In hindsight, the noted reputational damage was neither lasting nor spectacular. As of today, we’d say it’s almost non-existent.

Mainstream economists continue to dominate their profession and wield huge influence on public policies. They merely needed to close ranks after the financial crisis and wait for people to forget that their key theories and models were wholly discredited.

Meanwhile, heterodox economists who stress credit market risks and financial fragilities – the Austrians, the Minskyites – remain stuck on the fringes of the field. It doesn’t much matter that the crisis validated their thinking.

There may be no better example of mainstream economists’ Machiavellian preservation of position than in the cadre of left-wing, Keynesian bloggers led by Paul Krugman. We say “led by Krugman” because he seems to set the tone and tactics that many of his cohorts mimic. If you happen to read a blog post that attacks ideological foes through a combination of ridicule, name-calling and false narratives – such as the absurd claim that all conservatives (alternatively, all Austrians) predicted rising inflation in recent years – it was probably inspired by Krugman.

Readers of this blog know that we would welcome a genuine shake-up in the field. Wouldn’t it be nice to have a Colonel Jessup moment – when the code of silence breaks and everyone finally knows the truth?

Lt. Kaffee: “Did you order the Code Red?”
Col. Jessup: “I did the job I…”
Lt. Kaffee: “DID YOU ORDER THE CODE RED?”
Col. Jessup: “YOU’RE GODDAMN RIGHT I DID!”

In other words: we want the impossible. Hollywood endings only happen in Hollywood studios. The real life Jessup would have denied the Code Red, smirked through his acquittal and caught the first flight back to Gitmo. He may have even felt the need to send a message to his troops by ordering another Code Red at the first opportunity. That’s pretty much what we’ve witnessed in the economics profession.

“Mythbusting” the theories of mainstream economists

Nonetheless, we’ll continue to explain why we think a shake-up is overdue. In prior posts, we demonstrated the risks of Keynesian fiscal policies using 200 years of government budget balances and 63 high debt episodes, and by working through the implausible arithmetic in Krugman’s debt reduction formula. More recently, we argued the Austrian/Minskyite position that bank lending is riskier than lending funded by prior savings, and also discussed many economists’ ignorance of the way that bank lending works.

We’ll tie the last two points together here, by taking a closer look at what happens when credit growth disconnects from naturally occurring (not through bank money creation) or “prior” savings.

This time, though, we look further back than the inception dates of the BEA’s National Income and Product Accounts (NIPA) and the Fed’s “flow of funds.” For debt, we include older Census Bureau data recorded in the Historical Statistics of the United States. With adjustments, we can show that the Census Bureau series tracks a similar “flow of funds” series fairly closely during the overlap:

We also look at pre-NIPA savings rates, calculated from data on disposable personal income and consumption:

The earlier savings rates don’t match NIPA exactly because: 1) they’re calculated from different surveys, and 2) they ignore personal interest and transfer payments, skewing the figures higher than they should be. In any case, true savings rates were surely low during the late 1920s – when both consumer credit and durable goods purchases were in bubble mode – and quite possibly even lower than the data in the chart.

Which brings us back to our reason for looking at history – to consider what happens when savings and credit run in opposite directions.  Here’s our answer:

Although there are only two episodes combining low savings with rapid credit growth, the outcomes couldn’t be clearer.

What’s more, quarterly data available from 1952 tells a similar story. With this more complete data set, we can cleanly separate total credit growth into two components:

1. “Risky lending” financed by bank money creation or foreigners (as discussed in “3 Underappreciated Indicators to Guide You through a Debt-Saturated Economy.”)
2. Lending from domestic, “non-money” savings (essentially prior savings).

Here’s the chart:

Risky lending tends to peak before lending from domestic, non-money savings, and also before recessions. In other words, once risky lending maxes out, the ensuing weakness feeds into the broader economy.

Moreover, the earlier chart running from the Great Depression to the global financial crisis adds a giant exclamation point to the post-WW2 results. It seems clear that risky lending is a key driver of the business cycle, while extreme differences between lending and savings lead to fully-fledged busts.

Needless to say, our conclusions aren’t exactly mainstream when it comes to economic theory. There’s no place in mainstream models for the idea that money-creating bank lending is any different to lending from prior savings. Nor is there a place for other fundamental features of credit booms, such as the malinvestment that deepens recessions or balance sheets that are unsustainably swollen with debt. Mainstream models don’t include balance sheets, after effects of malinvestment or even the very existence of banks!

To take the most basic steps towards understanding booms and busts, you need to venture outside the mainstream. The Austrian school, in particular, stresses key differences between money creation and lending from prior savings, matching the real world results in the charts above.

About the title

If you happen to show this post to your favorite Austrian economist, we wouldn’t be surprised if you’re told it’s too empirical. The Austrian school’s distrust of empirical research is well-defended by our friend Detlev Schlichter here, and we don’t completely disagree with him. But we do believe that many ideas in economics are reasonably refuted by observing real world happenings, while others are reasonably validated (though never proven). At least that’s how we see it, as you may have guessed from our content.

Think of the show Mythbusters, where all kinds of theories, rumors, adages, movie scenes and more are tested through experiments. While the experiments are often inconclusive, they’re informative enough for the presenters to make a judgment call – is the myth “busted” or not? We take essentially the same approach. Our experiments can’t be controlled, for obvious reasons, and this is the greatest limitation to empirical research in economics. Nonetheless, it shouldn’t prevent us from gleaning whatever information we can from history, and then considering what it tells us about the accuracy of economic theory.

Even Murray Rothbard, we might add in closing, made the occasional empirical argument.

Data sources and Q&A

See “Technical Notes for ‘Never Mind Their Distrust of Data and Forecasts…’.”

More from A Few Good Men

I don’t understand the calculations in your charts – can you walk me through one of the figures?

Sure, we’ll do this for the figure depicted by the first bar (6.1%) on the real fixed investment chart:

We start by isolating all 4 quarter periods over which the fed funds rate dropped by more than 2%. There were 37 such periods in our data set, as shown in the first chart of the main article. For each of these periods, we record the growth in real fixed investment over the next 4 quarters. This is what we mean by lagged growth – we’re lagging the economic outcome against the change in interest rates.

So, for example, if the fed funds rate fell by 2.0% from the fourth quarter of 1959 to the fourth quarter of 1960 (it did), then we’re interested in real fixed investment growth from the fourth quarter of 1960 to the fourth quarter of 1961 (which was 6.5%).

Once we’ve recorded the lagged growth in real fixed investment for all 37 periods over which the fed funds rate dropped by more than 2%, we calculate the median across those data points. This is the 6.1% figure depicted by the chart’s first bar.

Are you always comparing 4 quarter rate changes to 4 quarter economic outcomes and 8 quarter rate changes to 8 quarter economic outcomes?

That’s right, all of the blue bars represent 4 quarter periods for both rate changes and economic outcomes, and all of the red bars represent 8 quarter periods for both rate changes and economic outcomes.

Where can I find your data?

Here’s a list, with links to the original sources:

• Fed funds rates are sourced from the St. Louis Fed’s database.
• Real fixed investment and real GDP growth are sourced from Table 1.1.3 of the National Income and Product Accounts.
• S&P 500 earnings and returns are sourced from Robert Shiller’s database and updated from Standard and Poor’s website.
• For inflation (used to convert nominal figures to real), we use the headline CPI maintained by the Bureau of Labor Statistics.
• Unemployment rates are also sourced from the BLS.
• For house prices, we combine the seasonally adjusted S&P/Case-Shiller 20 City Home Price Index with earlier data that was compiled by Robert Shiller and used in his book, Irrational Exuberance.

1. Fixed investment and business earnings dropping sharply
2. GDP growth following investment and earnings lower
3. Many people losing their jobs
4. Risky assets performing poorly

These consequences follow not only from the arithmetic of debt service and present value calculations, but also from the mood swinging psychology of entrepreneurs, lenders and investors.

Yet, policy economists claim that interest rates can be “normalized” at no cost.

For example, while speaking last week about the fed funds rate, St. Louis Fed President James Bullard said the economy was strong enough to “tolerate at least a little bit of the central bank getting back to a more normal stance.”

And how should we interpret “a little bit”?

According to FOMC projections, a little bit of normalization gets underway sometime next year and then leads to a steady pace of policy adjustments that doesn’t stop until the fed funds rate reaches almost 4%. These projections are accompanied by predictions for an improving economy as policy tightens.

Escape velocity or escape from reality?

The FOMC simply doesn’t acknowledge the time-tested effects of rising interest rates noted above. Instead, central bankers argue that today’s monetary stimulus will produce such economic vitality that there’s no sting in tomorrow’s tightening. In other words, they forecast an “escape velocity” where the economy is presumed immune to monetary restraint.

But is there any basis for their beliefs in the economy’s actual workings?

Or, is escape velocity merely a convenient story for central bankers predisposed towards easy money and short-term thinking?

We’ve argued that the Fed’s current policymakers have exactly this predisposition, and that there’s no such thing as escape velocity. We’ve also shared historical evidence supporting our views – in “M.C. Escher and the Impossibility of the Establishment Economic View,” for example – and take another look at history in this post.

Our analysis starts with a breakdown of interest rate changes over all 4 and 8 quarter periods since 1955:

We then review economic outcomes conditioned on the rate buckets above, recording the median outcome for each bucket. In most cases, we compare interest rate changes to outcomes for subsequent (lagged) 4 and 8 quarter periods.

(See this technical notes post for further detail. Also, look for a future follow-up post where we’ll contrast the history shown below to the Fed’s forecasts.)

Here are the results for fixed investment, corporate earnings, GDP and unemployment:

And here are charts showing the effects of changing interest rates on stock and house prices:

Now, many readers will surely dismiss these results by insisting that “this time is different.” We beg to differ. By our estimates, the economy and financial markets are as vulnerable to higher rates as they’ve ever been. Here are a few reasons:

1. The present expansion is weaker than any other post-World War 2 expansion, suggesting that it won’t take much of a slowdown to push the economy into recession.
2. Monetary policy has been exceptionally loose for longer than ever before, allowing financial markets more time to become overpriced and complacent.
3. There are many more risk-takers in the global economy who’ve learned how to exploit cheap dollar policies than there were in, say, 1955, the start of the period shown in the charts.
4. Most importantly, aggregate debt is at or near record levels, not only in the U.S. but also in other large economies.

Bottom line

Our conclusion is to reject forecasts calling for the economy to power right through interest rate hikes without stumbling. A more likely scenario is that policy “normalization” leads us directly into the next bust. Alternatively, the Fed might abort its planned rate hikes, allowing economic and financial market imbalances to continue growing. Either way, we can expect recurring booms and busts until our monetary approach is rebuilt on stronger policy principles.

Exports picked up towards the end of the decade, helped along by the G-7’s historic 1985 powwow at New York’s Plaza Hotel, which led to a coordinated effort to slam back the dollar. Nonetheless, some export industries never fully recovered.

Fast forward to the present, and export performance may soon be as noteworthy as it was 30 years ago. Risks to the global economy (and exports) include turmoil in oil-producing nations, credit markets that are teetering in China and comatose in Europe, and the backside of Japan’s April sales tax hike.

Worse still, export growth already lags behind every one of the past ten expansions, even the 1980s, thanks to a drop in the first quarter:

The chart shows that exports are no longer distinct from other parts of the economy (nearly all of them) that haven’t measured up to a “normal,” credit-infused, post-World War 2 business cycle.

Together with emerging global risks, it begs the question of whether sagging exports can drag the U.S. into recession.

We think it’s too early to make that call, especially while domestic lending continues to grow, credit standards remain relaxed, and most delinquency rates are falling. (For our research on links between lending and the business cycle, see “3 Underappreciated Indicators to Guide You through a Debt-Saturated Economy.”)

Nonetheless, export performance bears watching, and especially as the first quarter’s result mirrored a big drop in corporate profits. Falling export volumes surely contributed to the weak profits result.

Moreover, profits are an excellent leading indicator, as shown below:

Should exports and profits weaken further, that would cause us to reevaluate risks in both financial markets and the economy.

Extra chart (free)

Some readers may prefer this version of the export chart, with each cycle labeled:

His new policies on student loans include greater access to both payment reductions and loan forgiveness.

And, needless to say, his Rose Garden speech oozed election year politics.

As the Boston Herald put it: “This is nothing more than politics as official policy … the president’s shout-out to U.S. Rep. John Tierney, a vulnerable Democrat, at yesterday’s White House ceremony was just one of the clues.”

To be clear, student debt has become a huge problem that demands attention. Alongside other challenges, such as finding a decent job in a stagnant economy, student borrowers face daunting payment burdens that they’re failing to meet at record rates.

But the problem requires more than just a political instinct to bail out a wide swath of the voting public.

In a better world, policymakers would take a cold, hard look at the effects of federally-funded student loan programs, including the good and the bad. Here are a few such observations that you’re unlikely to hear from your president:

1)  Student loans are a fiscal time bomb, notwithstanding the government’s ridiculously flawed cost estimates, which Obama chose not to update despite this week’s policy changes. Official cost estimates ignore the near certainty of continued bailouts, while relying on shoddy accounting practices that you wouldn’t get away with in the private sector. In an editorial published after Obama’s latest announcements, the Wall Street Journal wrote:

Democrats claim to care about inequality, but kids who don’t go to college are in even worse economic shape than college kids, with even higher unemployment rates. Yet when the cost of defaults and debt forgiveness finally comes due, it will be paid by all taxpayers, including those who didn’t go to college. So the townies with jobs will end up paying more in taxes to give former college kids and grad students a break on their student debt.

2)  Skyrocketing college tuition costs are explained partly by extensive public subsidies to higher education, including past enhancements to federal student loan programs that all but eliminated private lenders. Ample government support allows universities the kind of pricing power that other industries only dream of. Obama characteristically framed his preferred policies as a choice between “lower tax bills for millionaires or lower student loan bills for the middle class.” To see the absurdity in this bit of rhetoric, you only need to look up the generous incomes and perks enjoyed by administrators and senior faculty at your local university. Arnold Kling put it this way:

The right way to think about student loans is that they are a gift from taxpayers to the higher education industry, both non-profit and for-profit. Most of the benefit goes to those who work in that industry, not to students. Most of the risk is borne by students and taxpayers, not by those who work in the industry.

3)  Public support for higher education helps to create unnecessary barriers in many fields where advanced degrees are now required credentials. Economics – a frequent topic for this blog – is just one example of a profession where “entry” requires indoctrination in methods that are useless if your goal is to actually understand your subject (rather than maximizing your publication count). Neal McCluskey argues that “cheap college has almost certainly fueled credential inflation, not major increases in knowledge or skills.”

4)  McCluskey’s position is supported by a recent study showing that borrowing for graduate school explains much of the increase in student loan issuance since 2004. The WSJ attributes the surge in graduate school loans partly to “an open spigot of government credit,” while quoting the study’s author, Jason Delisle:

Graduate schools have essentially found a way to capture more of someone’s future income and future spending than what would probably occur if we had some sort of underwriting standards and loan limits.

5)  Data shows that substantial portions of student loan proceeds are used for rent, bills and lifestyle expenses for borrowers with questionable ability to meet repayment obligations. Some of these “students” appear to have little intention of actually putting in the class and study time to obtain a degree. Again from the WSJ: “Even when schools suspect students are over-borrowing, they are restricted by federal law and Education Department policy from denying funds.”

6)  Moreover, reckless decisions about how much to borrow are not only enabled but encouraged by government policies. Back to McCluskey:

In the name of helping them, federal politicians, and many other people, massively oversell higher education to the detriment of students. Perhaps as much as half of people who enter college don’t finish; a third of people with a bachelor’s degree are in jobs not requiring the credential [and]; underemployment is even worse for graduate-degree holders…

7)  Special provisions for public sector employees, who can achieve loan forgiveness after only 10 repayment years compared to 20 for those in the private sector, are arguably the most heinous of all student loan policies. They are the political equivalent of a flagrant foul on the producing classes. Those who choose to put their efforts to the test of the market are penalized, to the benefit of public “servants” who live comfortably off the taxpayer without any accountability to the market. Such public sector perks can only be explained by the hubris, sense of entitlement and government-run-amok cronyism of the political class.

. . .

Now, none of our observations and editorial comments are meant to deny that there are many student loan success stories.

We’ve deliberately focused on the risks of federally-funded student loan programs, as these are too often swept under the carpet.

Problems with student loan programs are deep-rooted – thanks mostly to the government’s domination of the market – and were only worsened by Obama’s actions this week.

Why don’t the time periods on your chart match up exactly with QE start and end dates?  For example, why was the second quarter of 2010, when the Fed was winding down QE1, not included in the first period?

We grouped quarters into longer periods according to whether the Fed was using its balance sheet to expand the supply of credit, and by more than a token amount. In the second quarter of 2010, the Fed’s asset purchases were mostly offset by reductions in lending programs initiated during the financial crisis. The net lending amount was negligible (about $10 billion for the quarter or less than $50 billion annualized), and therefore, we grouped it with other quarters during which the Fed didn’t meaningfully expand its balance sheet.

What types of credit do you include in net lending?

From a recent post based on the same calculations:

Our borrowing and lending figures include the Fed’s “credit market instruments” category, repos and some types of interbank lending. The idea is to track any loan or debt security to its ultimate source of funding. For example, if a money market fund loans money to a dealer through the repo market and the dealer invests the proceeds in a Treasury bond (the collateral for the repo), then there’s no effect on the dealer’s net position as a lender/borrower. The dealer’s asset and liability flows can be netted out, leaving a borrowing by the Treasury that’s ultimately funded by money market fund shareholders through the repo loan.

What do you mean by “some types of interbank lending”?

There are two types of interbank lending that need to be considered when the goal is to track credit back to the ultimate source of funds. These are: 1) lending between U.S. banks and foreign banks and 2) loans from the Fed (e.g. through the AMLF facility). When a bank based in the U.S. borrows from a foreign bank, a matching amount of the U.S. bank’s lending should be traced to the foreign bank if you’re trying to establish the ultimate source of financing. The same logic applies to borrowing from the Fed.

Although the flow of funds report also includes reserves held at the Fed in its “interbank lending” category, reserves are basically deposits and should be excluded from net lending calculations. If we didn’t do this, the results would be nonsensical.

(Consider that deposits are created at the same time that loans are made and extinguished when loans are moved off bank balance sheets. Therefore, if you net out loans and deposits, you’re not measuring anything. The same goes for reserves, which are created at the same time that the Fed adds securities to its balance sheet.)

Other credit that the Fed classifies as interbank loans either nets out across different types of banks or isn’t relevant to net lending (namely, vault cash).

In other words, our net lending figures combine net positions in credit market instruments, repo loans and non-deposit, non-vault cash interbank loans.

I understand that banks were reducing their loan books during QE1, but what’s driving the reduction in net lending during QE2 and QE3?

Data points to several different factors. The biggest appears to be an increase in borrowing by U.S.-based banks from foreign banks. Moreover, most of the increased borrowing is by U.S. offices of foreign banks themselves, and the proceeds of the loans appear to be placed with the Fed as reserves. In other words, foreign banks are playing a large role in absorbing the additional liquidity provided by QE. (For more discussion, see this post by blogger Tyler Durden.) You might think of this as a substitution of reserves at the Fed for other types of dollar assets that foreigners would otherwise hold.

Anything else?

The second biggest factor is a reduction in net lending by broker-dealers. In between QEs, loan and bond portfolios held by broker-dealers grew more quickly than borrowings. During QE2 and QE3, borrowings grew more quickly than loan and bond portfolios, which shrank as dealers sold bonds to the Fed.

The third biggest factor is a slowing or reversal of net bond purchases by banks (referring to the Fed’s “depository institutions” category). While banks bought bonds at a pretty good pace in between QEs, they slowed or reversed these purchases during QEs.

Didn’t banks and broker-dealers front run QE, and doesn’t this explain some of the results in your chart?

Banks ramped up their bond holdings before the beginnings of QE2 and QE3, although they were buying mostly bonds not included in the Fed’s asset purchase program. In any case, some of their bond purchases were likely explained by banks anticipating QE. The broker-dealer data is more difficult to decipher, with one of the larger effects being a simultaneous reduction in “miscellaneous” assets and repo liabilities immediately after QE1 and QE2. These factors explain some, but not all, of the argyle pattern in our chart.

Can you send us more detail?

We can provide detailed calculations and spreadsheets, as well as other types of research or consulting on themes we’ve covered, although on a more commercial basis than the blog. If interested, e-mail ffwiley@gmail.com.

“We don’t understand fully how large-scale asset purchase programs work to ease financial market conditions.”
– New York Fed President Bill Dudley

“I don’t think there’s any doubt that quantitative easing enabled the rich and the quick. It was a massive gift… It was deliberate in the sense that we were hoping to create the wealth effect… I hope that we do indeed succeed in being able to say in the end the wealth effect was more evenly distributed. I doubt it.”
– Dallas Fed President Richard Fisher

“Just as I thought it was going alright, I find out I’m wrong when I thought I was right, it’s always the same it’s just a shame, that’s all.”
– Genesis front man Phil Collins

Sometimes the most interesting results are the ones you didn’t see coming.

We recently picked through financial flows data looking for clues about where a dollar of quantitative easing (QE) ends up.

For example, we wondered who parts with the bonds that find new homes on the Fed’s balance sheet. Dealers sometimes pass bonds straight from the Treasury to the Fed, but are they buying other QE-ready bonds mostly from households, pension funds, foreigners or other financial institutions? Also, can financial flows help us to guess at how much (if any) a dollar of QE adds to spending?

We didn’t expect clear answers and were surprised to stumble across this:

Needless to say, the chart raises a bunch of new questions, such as:

• Didn’t the Fed expect QE to complement other types of bank credit?
• What do they think of data suggesting it only displaced private sources of credit?
• Do they have any other explanations for the results in the chart?

Unfortunately, our direct line to the Eccles Building isn’t working this week, which prevents us from answering these questions. We’re left to form our own conclusions.

What to make of the “argyle effect”?

Our main takeaway is that the extra reserves created by QE aren’t so much an addition to bank balance sheets as a substitution. The addition story is the one we normally hear. It often leads to confused commentary, such as the mistaken ideas that banks “multiply up” or can “lend out” reserves. (We discussed these fallacies here.) But even without the confused commentary, the addition story doesn’t, well, add up.

According to financial flows data, it’s more accurate to say that QE’s extra reserves merely replaced other forms of balance sheet expansion. That’s a substitution story. It’s consistent with the fact that banks can neutralize QE’s effects with derivatives overlays and other portfolio adjustments. They can rearrange exposures to mimic a balance sheet of equal size and risk that’s not stuffed with reserves. (See this related discussion by blogger Tyler Durden.)

Think of it this way:

Your banker already knows how many slices of meat he wants in his sandwich. When the Fed shows up with a thick package straight from the deli, it saves him a trip of his own. He still makes the same sized sandwich, but it’s filled mostly by central bankers, and he adjusts it to his liking by varying the condiments.

Now, the full picture is more complicated than that, mainly because reserves move from bank to bank. For example, data shows a large amount of QE reserves accumulating at U.S. offices of foreign banks, where they appear to be funded by foreign lenders. You can think of these reserves as a means of recycling America’s current account deficits back into U.S. dollar assets. In other words, QE seems to encourage foreigners to swap other types of dollar assets for reserves at the Fed, supporting the substitution story.

Moreover, reserves can migrate from stronger banks to highly levered banks that are trying to improve capital ratios by lowering risk-weighted assets. This, too, is likely to result in balance sheet substitutions rather than additions.

Other banking practices may also help to explain the argyle effect, but there’s only so much we can learn from available data. For example, it’s impossible to determine how much banks were front running QE by buying bonds just before the Fed’s asset purchases began (although we consider clues in the appendix, which is linked below).

Bottom line

Whatever the interpretation, our chart fits nicely alongside Dudley’s and Fisher’s comments above. It says there’s much the Fed doesn’t understand, while at the same time showing that QE may have little purpose beyond providing a massive gift to wealthy traders and investors.

Getting back to our question of where a dollar of QE goes, the answer is “not far.” Outside of pushing up asset prices and encouraging an occasional luxury purchase, it doesn’t seem to escape the financial sector. Liquidity that might otherwise be offered by private institutions is instead provided by the Fed, and – as Phil Collins might put it – that’s all.

(Click here for an appendix to this post. Also, don’t miss our related research, including “Is This What a Credit Bubble Looks Like” and “3 Underappreciated Indicators to Guide You Through a Debt-Saturated Economy.”)