MetLife

What does "systemically important" mean? How can an institution, per se, be "systemically important?"  The WSJ coverage of Judge Rosemary Collyer’s decision rescinding MetLife’s designation as a "systemically important financial institution:" gives an interesting clue to how our regulators' thinking is evolving on this issue:

The [Financial Stability Oversight] council argued — bromide alert — that “contagion can result when relatively modest direct, individual losses cause financial institutions with widely dispersed exposures to actively manage their balance sheets in a way that destabilizes markets.”

It's not a bromide. It is a revealing capsule of how the FSOC headed by Treasury thinks about this issue.


"Actively manage balance sheets" is a fancy word for "sell assets." So there you have it. "Systemically important" now just means that an institution might sell assets, because selling assets might lower asset prices. "Contagion" and "systemically important" are no longer about runs; you see one bank in trouble and go take your money out of a different one. "Contagion" and "systemically important"  is no longer the (false, but plausible) domino theory, that if I default and owe you money, you default.

Policy is no longer just about stopping runs. Policy is not just about stopping any large bank from failing, or ever just losing money. Policy is about  stopping asset prices from falling, and stopping even the small marginal additional fall in prices that might accompany one  large institution's sales.  (Except that leverage and capital ratios now force institutions to sell even if they don't want to, a delicious case of contradictory regulatory commands.)

Owen Lamont's classic characterizatiion of policy-maker's attitude toward selling short, now applies to selling at all.

 Policymakers and the general public seem to have an instinctive reaction that short selling is morally wrong. Short selling has been characterized as inhuman, un-American, and against God

The journal nails the basic problem

For eight years, federal regulators have failed to define precisely the “systemic risks” they claim they can identify across the financial landscape.

But no definition makes it easy to endlessly expand the word's meaning.

Find patients with missing email addresses

In our age of technology, more and more people are tethered to their mobile phones, tablets and laptops 24/7. I am not only a practice management coach and trainer, but I am also a dental patient. Like an estimated 88% of smartphone owners*, if you want to contact me and confirm my appointment, the preferred method of contact is email or text message. Many times, the practice is calling patients to confirm their appointments from a back office phone line and the patient might not recognize the phone number … so the call goes to voicemail. In our busy lives, we might not check our voicemail until that evening or a couple days later. By then, it is more than likely after office hours or too late to call back.

If you are using a third-party software for email and/or text messaging, you need to make sure that you are reaching out to as many patients as possible. If you have been spotty on asking for email addresses, you can search your Dentrix software and find patients who have a missing email address. This will help you grow your email list and connect with patients in a more efficient and effective way. You will save time and your patients will appreciate it.

• ·        The first way you can search for patients without an email address is with the Dentrix letter merge feature and generate a list of patients. Go to the Office Manager > Letters & Custom Lists > highlight the Patient Report by Filters > Edit. In the lower left corner, there is a dropdown menu for email. Select only without (see the image below). Check mark patients, but I would not filter it with any other options because then you might skip some people. Click Close and click on the button for Open in List Manager. This will give you a list of patient names who do not have email addresses.

• ·        The second way you can search for patients without an email address is on a daily basis using the Daily Huddle Report. Go to the Office Manager > Analysis > Daily Huddle Report > (see image below). Click on the Selected Patient List > check mark the patients with no email. This will generate a page on the Daily Huddle that will give you a list of patients coming in today. If there is an “x” next to the no email column, then you can ask those patients for their email address.

Communicating with patients using today’s technology and in a way that is more convenient for your patients will increase your confirmations and help increase your patient retention. Do you want to learn more about Patient Retention? CLICK HERE

* Pew Market Research Study

NBER AP

On Friday I attended the NBER Asset Pricing meeting (program here) in Chicago, organized by Adrien Verdelhan and Debby Lucas. The papers were unusually interesting, even by the high standards of this meeting. Alas the NBER doesn't post slides so I don't have great visuals to show you.


Lars Hansen started with the latest in the Hansen-Sargent ambiguity / robustness work,Sets of Models and Prices of Uncertainty. Stavros Panageas gave a beautiful discussion,  complete with power point animations. He characterized the paper as a major advance, for reducing the range of models over which an ambiguous agent looks for the worst case scenario, and for making that range state-dependent.

In the application, the agent worries that the mean growth rate of consumption and the AR(1) coefficient might be wrong; a more persistent consumption growth process is hurtful, and that pain is more in bad times.

I haven't followed this work closely enough. I still wonder what the testable implcations are -- how different is the asset pricing model from one in which the true consumption growth process is just a bit different from our estimate, in the worst possible way?

Still, it's nice to see a Nobel Prize winner leading off a conference, and with easily the most technical paper at that conference, with another one (Rob Engle) in the audience. That tells you something about the seriousness of this group. Also, this is serious behavioral finance by any metric -- a disciplined model of probability misperceptions, which is nice to see.

Robert Novy-Marx presented  Testing Strategies Based on Multiple Signals, discussed by Moto Yogo. We're all familiar with the phenomenon that if you try 10 characteristics and pick the best few to forecast returns, t statistics are biased and performance falls out of sample.

Robert pointed out that if you put those best 3 in a portfolio, they diversify each other, reducing the in-sample variance of the portfolio, and boosting Sharpe ratios and t-statistics even further.

Many ``smart beta'' funds are doing this, so the fall-off in performance from backtest to real money is relevant beyond academia.

The extent of this bias is impressive. Here is the distribution of t statistics that results when you pick the best three of 20 completely useless signals, and put them in a portfolio. Critical values of 4 and 5 show up routinely in Robert's calculations.

Laura Veldkamp presented her work with Nina Boyarchenko, David Lucca, and Laura Veldkamp,  Taking Orders and Taking Notes: Dealer Information Sharing in Financial Markets. Discussed ably (of course) by Darrell Duffie. Is it a problem that the dealers who are the prime bidders at treasury auctions have been caught talking to each other ahead of the auction?  Surprisingly, no: The Treasury can come out ahead when dealers share information with each other, and investors can potentially come out ahead too.

This warms my contrarian economist heart. We know so little about how markets work, and regulators are so quick to jump on supposedly bad behavor, it's lovely to see a clear and convincing model, that explains the kind of second-order and equilibrium effects that economists are good at.

Brian Weller presented Measuring Tail Risks at High Frequency, discussed nicely by Mike Chernov. Brian's basic idea is to run cross-sectional regressions of bid/ask spreads, normalized by volume and depth, on the cross-section of factor betas. Since spreads are larger when dealers are more worried about big jumps, this produces a measure of time-varying probability x size of such jumps. The measure correlates well with the VIX.

Michael Bauer presented his paper with Jim Hamilton Robust Bond Risk Premia discussed very nicely by Greg Duffee. (My discussion of a previous presentation). This paper is really about whether macro variables help to forecast bond returns. We're used to "Stambaugh bias:'' if you forecast returns with a persistent regressor, and the innovation in the regressor is strongly negatively correlated with the innovation in the return, then the near-unit-root downward bias in the regressor autocorrelation seeps over into upward bias of return predictability. But macro variables forecasting bond returns have innovations nearly uncorrelated with the returns, so that's not much of a problem. Michael and Jim show another problem: with overlappping returns, t statistics can be biased down too.

This led to a pleasant reassessment of bond return forecasts. Some points that came up: econometrics aside, many return forecasters don't do well out of sample. Many of the issues are specification issues orthogonal to this econometric point. For example, evaluating the huge forecastability of bond returns from a combination of level and inflation documented by Anna Cieslak and Pavol Povala, where the forecasters look a lot like a trend, is really about specification and interpretation, not econometrics. I held out the view that the important part of my paper with Monika Piazzesi is the single-factor structure of expected returns, not whether small principal components help to forecast returns. We had a pleasant interchange on whether it's a good or terrible idea to run one-year horizon forecasting regressions. I like them, because they attenuate measurement error. Raising a weekly autoregression to the 52nd power yields junk. Greg likes them, and gave a stirring reminder of Bob Hodrick's point that you can include lags of the forecasting variables instead.

Nick Roussanov presented his paper with Erik Gilje and Robert Ready, Fracking, Drilling, and Asset Pricing: Estimating the Economic Benefits of the Shale Revolution with Wei Xiong discussing. They track the reaction of stock prices to the shale oil boom. In particular, they showed that stocks which rose on a huge shale announcement subsequently rose even more as more good shale news came in. Until, as Wei pointed out, prices collapsed.

Nick also used stock market value to try to get at an estimate of the economics benefits of fracking. It's a worthy effort, but let's remember the difficulties. In a competitive no-adjustment cost world, profits are zero and there are no abnormal stock returns. Stock capitalization may rise, as firms issue stock to invest. But that measures the value of capital invested, not the consumer surplus of shale. Still, the general idea of mixing asset pricing, energy economics, and making economic measurements from stock prices is intriguing.

Jonathan Sokobin, Chief Economist, FINRA presented "An Overview of FINRA Data" which I alas had to miss. I'm delighted anyone from the government wants us to use their data!

The AP meeting has a nice tradition. Usually the most boring part of a conference is the author's response to discussant. The AP meetings do away with this -- or rather, the author can respond if someone in the audience raises his or her hand and says "I'd like to hear your response to x." That actually happened! But by and large the AP meetings preserve time and a tradition of very active participation and discussion, and this one was no different.

Next Steps for FTPL

Last Friday April 1, Eric Leeper Tom Coleman and I organized a conference at the Becker-Friedman Institute,  "Next Steps for the Fiscal Theory of the Price Level." Follow the link for the whole agenda, slides, and papers.

The theoretical controversies are behind us. But how do we use the fiscal theory, to understand historical episodes, data, policy, and policy regimes? The idea of the conference was to get together and help each other to map out this the agenda. The day started with history, moved on to monetary policy, and then to international issues.

A common theme was various forms of price-related fiscal rules, fiscal analogues to the Taylor rule of monetary policy. In a simple form, suppose primary surpluses rise with the price level, as
\[ b_t = \sum_{j=0}^{\infty} \beta^j \left( s_{0,t+j} + s_1 (P_{t+j} - P^\ast) \right) \]
where \(b_t\) is the real value of debt, \(s_{0,t}\) is a sequence of primary surpluses budgeted to pay off that debt, \(P^\ast\) is a price-level target and \(P_t\) is the price level. \(b_t\) can be real or nominal debt \( b_{t}= B_{t-1}/P_t\), but I write it as real debt to emphasize the point: This equation too can determine price levels \(P_t\). If inflation rises, the government raises taxes or cuts spending to soak up extra money. If inflation declines, the government does the opposite, putting extra money and debt in the economy but in a way that does not trigger higher future surpluses, so it does push up prices.

(Note: this post has embedded figures and mathjax equations. If the last paragraph is garbled or you don't see graphs below, go here.)

That idea surfaced in many of the papers.


The morning had several papers studying the gold standard and related historical arrangements. To a fiscal theorist the gold standard is really a fiscal commitment. No gold standard has ever backed its note issue 100%; and none has even dreamed of backing its nominal government debt 100%. If a government had that much gold, there would be no point to borrowing.

So a gold standard is a  commitment to raise taxes, or to borrow against credible future taxes, to get enough gold should it ever be needed. The gold standard says, we commit to pay off this debt at one, and only one, price level. If inflation gets big, people will start to want to exchange money for gold, and we'll raise taxes. If inflation gets too low, people wills tart to exchange gold for money, and we'll print it up as needed. Usually, in the fiscal theory,
\[ \frac{B_{t-1}}{P_t} = E_t \sum_{j=0}^{\infty} \beta^j s_{t+j}\]
the expectation of future surpluses is a bit nebulous, so inflation might wander around a lot like stock prices. The gold standard is a way to commit to just the right path of surpluses that stabilize the price level.

A summary, with apologies in advance to authors whose points I missed or misunderstood:

Part I: History

George Hall presented his work with Tom Sargent on the history of US debt limits, together with a fantastic new data set on US debt that will be very useful going forward.

Price of a Chariot Horse: 100,000 Denarii

François Velde and Christophe Chalmley took us on a lighting tour of monetary arrangements across history, prompting a thoughtful discussion on just where Fiscal theory starts to matter and where it really is not relevant. (François easily gets the prize for the best set of slides. Picking just one was hard.)

Michael Bordo and Arunima Sinha presented an analysis of suspensions of convertibility: Governments temporarily abandon the gold standard during war, then go back at parity afterward. Maybe. By going back afterward, people are willing to hold a lot of unbacked debt and currency during the war. But sometimes the fiscal resources to go back afterward are tough to get, the benefits of establishing credibility so you can borrow in the next war seem further off. When people are unsure whether the country will go back, the wartime inflation is worse, and the cost of going back on parity are heavier. They analyze France vs. UK after WWI.

Martin Kleim took us on a tour of a big inflation in a previous European currency union, the Holy Roman Empire in the early 1600s. Europe has had currency union without fiscal union for a long time, under various metallic standards and coinages.  In this case small states, under fiscal pressure from the 30 years' war, started to debase small coins, leading to a large inflation. It ended with an agreement to go back to parity, with the states absorbing the losses. (In my equation, they needed a lot of surpluses to match \(P\) with \(P^\ast\)). We had an interesting discussion on just where those funds came from. Disinflation is always and everywhere a fiscal reform.

Margaret Jacobson presented her work with Eric Leeper and Bruce Preston on the end of the gold standard in the US in the 1930s. (Eric modestly stated his contribution to the paper as finding the matlab color code for gold, as shown in the graph.)  Margaret and Eric interpret the fiscal statements of the Roosevelt Administration to say that they would run unbacked deficits until the price level returned to its previous level, the \(P^\ast\) in my above equation.  Much discussion followed on how governments today, if they really want inflation, could achieve something similar.

 Part II Monetary Policy 

Chris Sims took on that issue directly. If you want inflation, just running big deficits might not help. Hundreds of years in which governments built up hard-won reputations that when they borrow money, they pay it off, are hard to upend immediately. Even if you want to break that expectation -- all our governments have mixed promises of stimulus now with deficit reduction later.  A devaluation would help, but we don't have a gold standard against which to devalue, and not everyone can devalue relative to each other's currency.

Chris' bottom line is a lot like Margaret and Eric's, and my fiscal Taylor rule,

Coordinating fiscal and monetary policy so that both are explicitly contingent on reaching an inflation target — not only interest rates low, but no tax increases or spending cuts until inflation rises. 

But,

• This might work because it would represent such a shift in political economy that people would rethink their inflation expectations.

Chris led a long discussion including thoughts on rational expectations -- it's a stretch to impose rational expectations on policies that have never been tried before (though our history lesson reminded us just how few genuinely novel policies there are!)

Steve Williamson followed with a thoughtful model full of surprising results. The stock of money does not matter, but fed transfers to the treasury do. (I hope I got that right!)

My presentation (slides also  here  on my webpage) took on the "agenda" question. The basic fiscal equation is
\[\frac{B_{t-1}}{P_t} = E_t \sum M_{t,t+j} s_{t+j} \]
For the project of matching history, data, analyzing policy and finding better regimes, I opined we have spent too much time on the \(s\) fiscal part, and not nearly enough time on the \(M\) discount rate part, or the \(B\) part, which I map to monetary policy.

I argued that in order to understand the cyclical variation of inflation -- in recessions inflation declines while \(B\) is rising and \(s\) is declining -- we need to focus on discount rate variation. More generally, changes in the value of government debt due to interest rate variation are plausibly much bigger than changes in expected surpluses. As interest rates rise, government debt will be worth a lot less, an additionan inflationary pressure that is often overlooked.

Then I presented short versions of recent papers analyzing monetary policy in the fiscal theory of the price level. Interest rate targets with no change in surpluses can determine expected inflation, but the neo-Fisherian conundrum remains.

Harald Uhlig presented a skeptical view, provoking much discussion.  Some main points: large debt and deficits are not associated with inflation, and M2 demand is stable.

I found Harald's critique quite useful. Even if you don't agree with something, knowing that this is how a really sharp and well informed macroeconomist perceives the issues is a vital lesson. I answered somewhat impertinently that we addressed these issues 15 years ago: High debt comes with large expected surpluses, just as in financing a war, because governments want to borrow without creating inflation. The stability of M2 velocity does not isolate cause and effect. The chocolate/GDP ratio is stable too, but eating more chocolate will not increase GDP.

But Harald knows this, and his overall point resonates: You guys need to find something like MV=PY that easily organizes historical events. The obvious graph doesn't work. Irving Fisher came up with MV=PY, but it took Friedman and Schwartz using it to make the idea come alive. That is the purpose of the whole conference.

Francesco Bianchi presented his work with Leonardo Melosi on the Great Recession. New Keynesian models typically predict huge deflation at the zero bound. Why didn't this happen? They specify a model with shifting fiscal vs money dominant regimes. The standard model specifies that once we leave the zero bound we go right back to a money-dominant, Taylor-rule regime with passive fiscal policy. However, if there is a chance of going back to a fiscal-dominant regime for a while, that changes expectations of inflation at the end of the zero bound. Even small changes in those expectations have big effects on inflation during the zero bound (Shameless plug for the New Keynesian Liquidity Trap which explains this point very simply.) So, as you see in the graph above, the "benchmark" model which includes a probability of reverting to a fiscal regime after the zero bound, produces the mild recession and disinflation we have seen, compared to the standard model prediction of a huge depression.

Fiscal policy is political of course. Campbell Leith presented, among other things,  an intriguing tour of how political scientists think about political determinants of debt and deficits. My snarky quip, we learned with great precision that political scientists don't know a heck of a lot more than we do! But if so, that is also wisdom.

Part III International

red line regime switching probability of 30%, blue line 0 % 

Alexander Kriwoluzky presented thoughts on a fiscal theory of exchange rates, applying it to the US vs. Germany, the abandonment of the gold standard and switch to floating rates in the early 1970s. An exchange rate peg means that Germany must import US fiscal policy as well, importing the deficits that support more inflation. Germany didn't want to do that.  People knew that, so a shift to floating rates was in the air. Expectations of that shift can explain the interest differential and apparent failure of uncovered interest parity.

Last but certainly not least, Bartosz Maćkowiak presented a thoughtful analysis of "Monetary-Fiscal Interactions and the Euro Area’s Malaise" joint work with Marek Jarosińsky.

Echoing the fiscal Taylor rule idea running through so many talks, they propose a fiscal rule
\[ S_{n,t} = \Psi_n + \Psi_B \left( B_{n,t-1} - \sum_n \theta_n B_{n,t-1} \right) + \psi_n (Y_{n,t}-Y_n) \]
In words, each country's surplus must react to that country's debt \(B_n\), but total EU surpluses do not react to total EU debt. In this way, the EU is "Ricardian" or "fiscal passive" for each country, but it is "non-Ricardian" or "fiscal active" for the EU as a whole. In their simulations, this fiscal commitment has the same beneficial effects running through Leeper and Jabcobson, Bianchi and Melosi, Sims, and others -- but maintaining the idea that individual countries pay their debts.

A big thanks to the Harris School and the Becker-Friedman Institute who sponsored the conference.

Recare is the lifeblood of your practice

If you are a general practice or pediatric dental practice, your recare system is the lifeblood of your practice. Your doctor’s schedule feeds off the hygiene patients so it is critical that you have a seamless system. But are your hygiene systems working as well as you think they are? You may have patients falling through the cracks or not receiving the reminders that you think they are.

The most important component of your recare system is the setup and making sure your team understands the details. I want to take some time today to walk you through proper setup, checking your individual patients continuing care, and which report to manage.

First, the setup is key. I wrote a blog post on May 23, 2012, called “KISS your Continuing Care Types,” but obviously not everyone read it so I am going to take some of those tips and re-apply them today. Many offices, understandably, try and create a system for 3-month Perio, 4-month Prophy, etc., by setting up new Continuing Care types but trust me . . . IT DOESN’T WORK! Remember that you can only attach one Continuing Care type to the procedure code. To

understand what I am talking about, go to the Office Manager > Maintenance > Practice Setup > Procedure Code Setup, then highlight the D1110 and click edit. You will notice in the middle of the window there is a >> Auto Continuing Care where you can attach one Continuing Care Type to this code. This means you cannot link up a 4-month Prophy and 6-month Prophy to the same code.

Your options are Prophy and Perio or Recare. You can link the Prophy to the D1110 and the D1120 and the Perio to the D4910, or link the Recare to all three.

After you have this setup corrected, when you schedule your patient for a cleaning, it will link up to the appointment correctly. When you set complete, it will update your patient’s due date.

But what if your patient is a 3-month Perio or 4-month Prophy? How do you get it up update the due date correctly? You can update the patient’s frequency on his or her Family File in the Continuing Care window. Once you change the patient’s recare frequency, then your reports will be accurate. When you schedule the patient for his or her next visit, the system will know when he or she is due.

After you get this setup fixed and the patient’s frequency updated on the Family File, then you can feel confident that your Continuing Care Report is accurate. If you are using the Dentrix eCentral communication manager, you will know that your patients are receiving reminders when they are due. For a full article on the Continuing Care report, CLICK HERE.

Neo-Fisherian caveats

Raise interest rates to raise inflation? Lower interest rates to lower inflation? It's not that simple.

A correspondent from an emerging market wrote enthusiastically. His country has somewhat too high inflation, currency depreciation and slightly negative real rates. A discussion is going on about raising rates to combat inflation. Do I think that lowering rates in this circumstance is instead the way to go about it?

As you can tell, posing the question this way makes me very uncomfortable! So, thinking out loud, why might one pause at jumping this far, this fast?

Fiscal policy.  Fiscal policy deeply underlies monetary policy. In my own "Fisherian" explorations, the fiscal theory of price level is a deep foundation. If the government is printing up money to pay its bills, the central bank can do what it wants with interest rates, inflation is coming anyway.


Conversely, underlying the decline in inflation in the US, Europe, and Japan is an extraordinary demand for nominal government debt.

Bond markets seem to think we'll pay it off. And that is not too terribly an irrational expectation. Sovereign debts are self-inflicted wounds. A little structural reform to get growing again, tweaks to social security and medicare, and next thing you know we're back in the 1990s and wondering what to do when all the government bonds are paid off. Also, valuation is more about discount rates than cashflows. People seem happy -- for now -- to hold government debt despite unusually low prospective returns.

My correspondent answers that his country is actually doing well fiscally.  However, his country is also a bit low on reserves and having exchange rate and capital flight problems.

But current deficits are not that important to inflation either in theory or in fact. The fiscal policy that matters is expectations of very long term stability, not just a few years of surpluses. Also, contingent liabilities matter a lot. If investors in government debt see a government that will bail out all and sundry in the next downturn, or faces political risks, even temporary surpluses are not an assurance to investors.  (Craig Burnside, Marty Eichenbaum and Sergio Rebelo's "Prospective Deficits and the Asian Currency Crises, in the JPE and ungated here is a brilliant paper on this point.)

Rational expectations. The Fisherian proposition also relies deeply on rational expectations. In the simplest version, \( i_t = r + E_t \pi_{t+1} \), people see nominal interest rates rise, they expect inflation to be higher, so they raise their prices. As a result of that expectation inflation is, on average, higher. (Loose story alert.)

How do they expect such a thing? Well,  rational expectations is sensible when there is a long history in one regime. People see higher interest rates, they remember times of high interest rates in the past, like the late 1970s, so they ratchet up their inflation expectations. Or, people see higher interest rates, and they've gotten used to the Fed raising interest rates when the Fed sees inflation coming, so they raise their expectations. The motto of rational expectations is "you can't fool all of the people all of the time," not "you can never fool anyone," nor "people are clairvoyant."

The Fisherian prediction relies on the interest rate change to be credible, long-lasting, and to lead to the right expectations. A one-off experiment, that might be read as cover for a dovish desire to boost growth at the expense of more inflation, and that might be quickly reversed doesn't really map to the equations. Europe and Japan, stuck at the zero bound, with a fiscal bonanza (low interest costs on the debt) and slowly decreasing inflation expectations is much more consistent with those equations.

Liquidity. When interest rates are positive and money does not pay interest, lowering rates means more money in the system, and potentially more lending too. This classic liquidity channel, which goes the other way, is absent for the US, UK, Japan and Europe, since we're at the zero bound and since reserves pay interest.  (Granted, I couldn't get the equations of the liquidity effect to be large enough to offset the Fisher effect, but that depends on the particulars of a model. )

Successful disinflations. Disinflations are a combination of fiscal policy, monetary policy, expectations, and liquidity. Tom Sargent's classic ends of four hyperinflations tells the story beautifully.

Large inflations result from intractable fiscal problems, not central bank stupidity. In Tom's examples, the government solves the fiscal problem; not just immediately, but credibly solves it for the forseeable future. For example, the German government in the 1920s faced enormous reparations payments. Renegotiating these payments fixed the underlying fiscal problem. When the long-term fiscal problem was fixed, inflation stopped immediately. Since everybody knew what the fiscal problem was, expectations were quickly rational.

The end of inflation coincided with a large money expansion and a steep reduction in nominal interest rates. During a time of high inflation, people use as little money as possible. With inflation over, real money demand expands.  There was no period of monetary stringency or interest-rate raising preceding these disinflations.

So these are great examples in which the Fisher story works well -- lower interest rates correspond to lower inflation, immediately. But you can see that lower interest rates are not the whole story. The central bank of Germany 1922 could not have stopped inflation on its own by lowering rates.  I suspect the same is true of high inflation countries today -- usually something is wrong other than just the history of interest rates.

So, apply new theories with caution!

To the raising interest rates question for the US and Europe, some of the same considerations apply. We won't have any liquidity effects, as central banks are planning to just pay more interest on abundant reserves. Higher real interest rates will raise fiscal interest costs, which is an inflationary shock by fiscal theory considerations. The big question is expectations. Will people read higher interest rates as a warning of inflation about to break out, or as a sign that inflation will be even lower?

A very simple neo-Fisherian model

A sharp colleague recently pushed me to write down a really simple model that can clarify the intuition of how raising interest rates might raise, rather than lower, inflation. Here is an answer.

(This follows the last post on the question, which links to a paper. Warning: this post uses mathjax and has graphs. If you don't see them, come back to the original. I have to hit shift-reload twice to see math in Safari. )

I'll use the standard intertemporal-substitution relation, that higher real interest rates induce you to postpone consumption, \[ c_t = E_t c_{t+1} - \sigma(i_t - E_t \pi_{t+1}) \] I'll pair it here with the simplest possible Phillips curve, that inflation is higher when output is higher. \[ \pi_t = \kappa c_t \] I'll also assume that people know about the interest rate rise ahead of time, so \(\pi_{t+1}=E_t\pi_{t+1}\).

Now substitute \(\pi_t\) for \(c_t\), \[ \pi_t = \pi_{t+1} - \sigma \kappa(i_t - \pi_{t+1})\] So the solution is \[ E_t \pi_{t+1} = \frac{1}{1+\sigma\kappa} \pi_t + \frac{\sigma \kappa}{1+\sigma\kappa}i_t \]

Inflation is stable. You can solve this backwards to \[ \pi_{t} = \frac{\sigma \kappa}{1+\sigma\kappa} \sum_{j=0}^\infty \left( \frac{1}{1+\sigma\kappa}\right)^j i_{t-j} \]

Here is a plot of what happens when the Fed raises nominal interest rates, using \(\sigma=1, \kappa=1\):

When interest rates rise, inflation rises steadily.

Now, intuition. (In economics intuition describes equations. If you have intuition but can't quite come up with the equations, you have a hunch not a result.) During the time of high real interest rates -- when the nominal rate has risen, but inflation has not yet caught up -- consumption must grow faster.

People consume less ahead of the time of high real interest rates, so they have more savings, and earn more interest on those savings. Afterwards, they can consume more. Since more consumption pushes up prices, giving more inflation, inflation must also rise during the period of high consumption growth.

One way to look at this is that consumption and inflation was depressed before the rise, because people knew the rise was going to happen. In that sense, higher interest rates do lower consumption, but rational expectations reverses the arrow of time: higher future interest rates lower consumption and inflation today.

(The case of a surprise rise in interest rates is a bit more subtle. It's possible in that case that \(\pi_t\) and \(c_t\) jump down unexpectedly at time \(t\) when \(i_t\) jumps up. Analyzing that case, like all the other complications, takes a paper not a blog post. The point here was to show a simple model that illustrates the possibility of a neo-Fisherian result, not to argue that the result is general. My skeptical colleauge wanted to see how it's even possible.)

I really like that the Phillips curve here is so completely old fashioned. This is Phillips' Phillips curve, with a permanent inflation-output tradeoff. That fact shows squarely where the neo-Fisherian result comes from. The forward-looking intertemporal-substitution IS equation is the central ingredient.

Model 2:

You might object that with this static Phillips curve, there is a permanent inflation-output tradeoff. Maybe we're getting the permanent rise in inflation from the permanent rise in output? No, but let's see it. Here's the same model with an accelerationist Phillips curve, with slowly adaptive expectations. Change the Phillips curve to \[ c_{t} = \kappa(\pi_{t}-\pi_{t-1}^{e}) \] \[ \pi_{t}^{e} = \lambda\pi_{t-1}^{e}+(1-\lambda)\pi_{t} \] or, equivalently, \[ \pi_{t}^{e}=(1-\lambda)\sum_{j=0}^{\infty}\lambda^{j}\pi_{t-j}. \]

Substituting out consumption again, \[ (\pi_{t}-\pi_{t-1}^{e})=(\pi_{t+1}-\pi_{t}^{e})-\sigma\kappa(i_{t}-\pi_{t+1}) \] \[ (1+\sigma\kappa)\pi_{t+1}=\pi_{t}+\pi_{t}^{e}-\pi_{t-1}^{e}+\sigma\kappa i_{t} \] \[ \pi_{t+1}=\frac{1}{1+\sigma\kappa}\left( \pi_{t}+\pi_{t}^{e}-\pi_{t-1} ^{e}\right) +\frac{\sigma\kappa}{1+\sigma\kappa}i_{t}. \] Explicitly, \[ (1+\sigma\kappa)\pi_{t+1}=\pi_{t}+\gamma(1-\lambda)\left[ \sum_{j=0}^{\infty }\lambda^{j}\Delta\pi_{t-j}\right] +\sigma\kappa i_{t} \]

Simulating this model, with \(\lambda=0.9\).

As you can see, we still have a completely positive response. Inflation ends up moving one for one with the rate change. Consumption booms and then slowly reverts to zero. The words are really about the same.

The positive consumption response does not survive with more realistic or better grounded Phillips curves. With the standard forward looking new Keynesian Phillips curve inflation looks about the same, but output goes down throughout the episode: you get stagflation.

The absolutely simplest model is, of course, just \[i_t = r + E_t \pi_{t+1}\]. Then if the Fed raises
the nominal interest rate, inflation must follow. But my challenge was to spell out the market forces
that push inflation up. I'm less able to tell the corresponding story in very simple terms.