Will the funds rate have time to get back to “normal” (wherever that is) before the next recession?

August 24th, 2016 at 1:20 pm

I’ve got  a piece up at WaPo riffing off of this new paper by Fed economist David Reifschneider (DR). I wanted to add an interesting figure here that I couldn’t jam in the WaPo post.

Some of the data in the figure comes from DR’s table 1 showing the number of basis points (hundredths of a percent, so 100 bps is one percentage point) that the Fed has reduced the main tool it controls–the Federal funds rate–over a number of recessions. The black dot shows where the funds rate was when they began their lowering campaign, the arrows show how much they lowered, and the green box shows where they stopped (this excellent graphic was custom made for me by Ben Spielberg; see data note below). For example, to apply countercyclical monetary policy in the case of the Great Recession–the last bar in the figure–the Fed took the rate down from about 500 bps to zero.

Source: Reifschneider, Federal Reserve

Source: Reifschneider, Federal Reserve

The last dot shows where the rate is today–close to zero (~40 bps)–which is where it should be IMHO as we’re not yet at full employment and there’s no worrisome signs of overheating; inflation remains quiescent such that the Fed keeps missing their 2% inflation target on the downside.

DR’s simulations assume that last dot climbs in time to give the Fed some height to drop from when the next downturn hits (importantly, he stresses that the neutral funds rate is very likely lower than it used to be), but, as I argue in the piece, with some evidence from market expectations of the funds rate, I’m skeptical.

Data note for graph: The maximum and minimum federal funds rates before 1990 were almost all calculated using the methodology described in Reifschneider’s footnote 1, table 1. They are the maximum and minimum effective federal funds rates in any given month spanning from 6 months before the recession began to 6 months after the recession ended, with only one exception: the end period extends to only the official end of the 1980 recession in July of 1980, and not 6 months afterwards, because rates began rising afterwards and including those months would have made the drop appear larger than it actually was. During the three most recent recessions, the time periods used to determine the maximum and minimum effective federal funds rates were June 1990 to December 1992 (DR’s ftnt has January 2002 for the latter date for this period but we assume that’s a typo), December 2000 to January 2002, and August 2007 to December 2008. The methodology for the post-1980 recessions is slightly different than that Reifschneider used, as he uses “intended” fund rates beginning in 1990, which differ slightly from effective rates, but they tell the same story.

Monday music: harmonic geniuses at work.

August 22nd, 2016 at 3:21 pm

One of my favorite jazz vibraphonists, Bobby Hutcherson, died last week. I gotta say, I listened to every recording he made and if Bobby played a note in there somewhere that wasn’t as swinging as it was interesting, I missed it. And the dude played a lot of notes. Here’s a classic Hutch solo from a date with the alto saxophonist Frank Morgan. Bobby takes the first solo, and just listen to how he develops it, increasing stretching the rhythms and harmonics.

I don’t like to mix musical styles in these posts (though really, great music is just that: great music), but this past weekend I was reminded how much I love the last movement of Beethoven’s Piano Concerto #3 (~28:30). I mean, the whole piece is pretty blissful but there’s something about the last movement that completely demands my attention.

One of the things that grabs me is the wonderful argument between the major and the minor keys. The piece is in minor, but the major keeps fighting its way in there, and Beethoven keeps your ears on edge as you try to determine who’s making the best case for tonal dominance. The minor-key argument is loud and bossy, but the major key is not the slightest bit intimidated.

If you do nothing else this week, listen carefully to this movement and see if you hear the piano and orchestra having that argument, or alternatively, if I’m losing my mind.

Ban the Box: Recent critics of the policy are not nearly as convincing as they think they are

August 22nd, 2016 at 2:18 pm

As any student of policy analysis knows, when we analyze the impact of a real policy on real people, we must look for “unintended consequences,” a kind of backfiring where for some unforeseen reason, the policy hurts those it’s trying to help.

This came up recently in a couple of research papers evaluating the impact of “ban the box,” or BTB, an initiative intended to meet an extremely venerable goal: to help those with criminal records make their way back into the workforce. BTB does so by moving background checks from the beginning of the application process to the end, often after a conditional offer of employment has been extended.

The problem, according to some critics of the policy, is that while BTB might help those with criminal records get their feet in the door, employers without criminal record information will engage in “statistical discrimination.” That is, they’ll discriminate against applicants they believe most likely to have criminal records: young black and Latino men. Based on this dynamic, one author of a critical analysis of BTB concluded that the policy “does more harm than good.”

Not so, and here’s where policy analysts need to be a lot more careful. Are they identifying a problem with the policy or with employer behavior more generally? Especially if it is the latter, are there better ways to address that behavior than policy repeal? Do the policy’s beneficiaries outweigh anyone hurt by unintended consequences?

That’s why a new policy brief from Maurice Emsellem and Beth Avery (E&A) of the National Employment Law Project (disclosure: I chair NELP’s board) is so important. Media reports haven’t done enough to contextualize those studies’ findings and have been too quick to dismiss a policy that, while only a limited part of what’s needed to help disadvantaged individuals get a fair shake in the job market, generally appears to be having its intended effects.

As E&A note, evidence from cities across the United States – from Durham, North Carolina to Washington, DC to Atlanta, Georgia – indicates that ban the box is increasing employment among people with criminal records. The critical studies don’t challenge that claim directly, but, as noted above, argue that employers respond to ban-the-box policies by discriminating broadly against all young black and/or Latino men. But while employer discrimination surely exists, the studies fail to make the case that this is due to BTB.

One study, by Amanda Agan and Sonja Starr, relies on fictitious job applications for young men ages 21-22 submitted to New Jersey and New York employers both “shortly before and after the New York City and New Jersey private sector ban-the-box laws took effect in 2015.” The study found that the gap in callbacks between white applicants and black applicants (whom were given distinctively racial-sounding names) increased following the introduction of ban the box.

But does this prove unintended consequences? For firms that used and then banned the box, black callback rates were about 11 percent before and after the policy change, while white callback rates went up, from around 11 percent to 15 percent. It appears that these results were driven by increased callbacks for applicants with criminal records of both races, as black applicants with records had only an 8.4 percent callback rate and white applicants with records had only an 8.8 percent callback rate prior to the change.

In other words, there were increased callbacks for applicants of both races with records (though more so for whites): a good example of an intended consequence. The NYT also got this wrong, asserting that the paper found that “employers became much less likely to call back any apparently black applicant.”

The other study, from Jennifer Doleac and Benjamin Hanson, compared employment across the United States between metropolitan areas that did and didn’t enact ban the box laws. While the authors found reduced employment for black men without college degrees between the ages of 25 and 34, they also found increased employment for other black workers.

There are also some potentially serious modelling problems with this study. First, the authors consider every worker in an entire metropolitan statistical area (MSA) to be covered by a ban-the-box law “if any jurisdiction in their MSA has a BTB policy.” A BTB law passed in East Palo Alto, CA in January of 2005, for example – a city with around 30,000 people – looks to me like it would have caused the entire San Francisco-Oakland-Hayward, CA MSA, which has a population of closer to 4.7 million, to be considered covered, despite no other jurisdiction within that MSA adopting ban the box until San Francisco did so in October of that year.

What’s more, public-sector-only BTB laws count, and they’re all that’s in place in nearly 80 percent of months the authors examine in MSAs covered in this way (including in the aforementioned California MSA until July of 2013). It’s not clear why we’d expect public-sector BTB laws to affect the hiring behavior of private employers, or the behavior of both public and private employers in neighboring cities and counties that don’t have BTB laws. The authors also neglect to control for local unemployment, which I’d guess matters in a model that predicts employment outcomes.

My conclusion from the studies and the NELP report is that it’s not clear that employer responses to ban-the-box laws are the problem. What is clear, from these and many other studies, is that there are serious discrepancies in job opportunities for people of different races. Those discrepancies have nothing to do with BTB and must be addressed. And if the critics are right—if some employers are actually responding to ban-the-box laws by ramping up statistical discrimination—then they’re doing so in violation of federal civil rights law.

E&A conclude correctly that “a comprehensive policy response is necessary to fundamentally increase job opportunities for people with records and reduce race discrimination in hiring.” That policy response must include ban the box, enforcement of federal civil rights law, policing reforms, prison reforms, education about implicit bias, and a suite of other policies. It takes a village of such policies to achieve economic justice.

What if the Fed is just really good with anchors?

August 22nd, 2016 at 11:30 am

I’ve got a piece over at WaPo that OTE’ers might enjoy on the Fed’s 5, 3, 2 problem. As in their unemployment and interest rate targets (~5 and 3 percent) are too high and their inflation target (2 percent) is too low.

Let’s talk about this last bit—the inflation target—a bit more, though this conversation also applies to the other stuff in the piece, as you’ll see.

First, and this isn’t the main point of this post, but a bit of venting. Actually, never mind—I dealt with this through a cathartic tweet (the 2% target is an average, not a ceiling! Can I please get some symmetry!).


The actual point of this post is just to reflect a bit more on the phlat Phillips Curve (PC), as shown in this recent analysis by Fed economist Michael Kiley (whose work on all this is thoughtful and compelling). One of Kiley’s figures, below, shows the extent to which the PC has flattened in recent years.

Source: Michael Kiley

Source: Michael Kiley

The question is “why so phlat?” and one answer that I don’t get into in my WaPo piece is that the Fed has gotten really good at convincing everyone that damn it, inflation is going to stay low and stable and that’s all there is to it. In Fed-speak, that’s saying “inflationary expectations are well-anchored” around their target of 2%.

Kiley and others provide some evidence to that effect, but what’s interesting to me is how this explains important findings like these which show the collapse of traditional statistical measures that used to explain the variance in inflation using measures of economic slack.

A friend provides a useful analogy: Trying to estimate the PC these days is a little like testing the impact of outside temperature changes on an inside room that’s climate controlled. You’re not going to pick up a lot of variance because the climate is effectively controlled by the thermostat. If you, say, regress the inside room temperature on the outside temp, your coefficient will wiggle around zero, because the thermostat is doing its job.

In other words, the PC is flat because the Fed is effectively controlling inflation.

This seems convincing (if it sounds really obvious, I assure you, as an old person, that wasn’t always the case) but one would like to disprove other explanations, especially since the extent of the anchoring would have be really strong to explain how little inflation has responded to output gaps either when they were really very large or when they were closing pretty quickly. Kiley takes you through numerous other suggested explanations, including basic rigidities in prices and wages.

But I’ve always wondered if there’s a globalization piece to all this. Surely increased global supply chains put downward pressure on prices. Also, inequality, low worker bargaining clout, and the decrease in collective bargaining have long diminished the link between productivity and real wages…and perhaps prices as well.

Last point: as I stress in the WaPo piece, the inflation target is too low—at 2%, it invokes possible zero-lower-bound problems the next time we hit a downturn, and especially with a…um…difficult Congress (meaning adequate countercyclical fiscal policy may well not be forthcoming), that’s a really serious problem.

If they can anchor so effectively at 2%, why not 4%?

It’s all connected…4 referrals from today’s papers.

August 19th, 2016 at 8:49 am

Three articles, one blog post.

First, Dean Baker points to this great Bloomberg article by former Fed regional bank pres Narayana Kocherlakota (NK) on how, since black unemployment typical runs 2x the overall rate, Fed policy is especially consequential for them (and other minorities). It’s really just the old adage that when the economy sniffles, less advantaged workers catch pneumonia, and–a key theme of my own work–less advantaged workers are disproportionately helped when the economy is strong. Full employment is especially important for blacks, as I’ll show again in a moment.

The piece points out that these relationships came up in the minutes from the recent Fed meeting, something that hasn’t happened much at all in the past. Some, and not a little, credit for that goes to the activist group Fed Up, which continues to have real impact on these critical debates.

One could certainly ask “what took them so long?” As NK’s figure shows, this 2x relationship persists through the long history of this data series. But it’s still progress.

Second, I wanted to link to a piece I recently did that ties a lot of NK’s insights together, adding the unemployment/wage dimension. I took that ~2x relation and mapped it onto a wage/unemployment elasticity for low-wage workers in the spirit of Val Wilson’s work.

Source: my analysis

Source: my analysis


Until recently, growth in this expansion has been a spectator sport for many disadvantaged workers. One way to help them is for the Fed to accommodate very low unemployment. That could conceivably trigger inflationary concerns, but based on how weak that correlation is these days, lower unemployment seems an extremely favorable trade-off to the low-wage workers who would benefit disproportionately in terms of faster wage growth.

But I also don’t want to forget the larger picture:

Of course, life is more complicated than these relatively simple connections imply. It will take a lot more than just the Fed holding off on interest-rate increases to generate true racial economic justice. Getting there will also require, as a basic starting point, both criminal justice reform and direct job creation in neighborhoods that have historically been left behind (even when the rest of the country is at full employment).

Third, speaking of that larger picture, here’s a little piece in today’s WaPo (print edition) that thinks about the structural forces driving inequality–taxes and transfers can help and are helping. But we need to do much more and think much bigger to deal with the power imbalances behind these inequities.

Finally, one reason productivity is so low is that investment is so low. And one reason investment is so low is that public companies would rather do stuff that boosts their near-term stock price–share buybacks and dividend payouts–than their long-term productivity. It’s a big, serious, long-term problem that relates to the structural shifts alluded to in my WaPo piece, not to mention the institutional forces that NK and I document.

In other words, Buddha was right: it’s all connected…