Slack, inflation, and the Fed

February 15th, 2017 at 12:02 pm

What with Chair Yellen testifying in Congress over the last couple of days, I’ve been trying to dig into the case for forthcoming Fed rate hikes. Clearly, there is more price pressure in the system than in recent months, but there are also these factors to consider:

–The data-driven case for rate hikes is far from a slam dunk, according to evidence I present in the WaPo today.*

–Today’s inflation report is interesting in that it gives ammo to both hawks and doves. Here’s the figure from BLS:

Source: BLS

What’s happening here is that energy costs are normalizing, after being freakishly low for awhile (see figure below). From the perspective of Fed and monetary policy, the key insight here is that energy costs are set on global markets and thus not a reflection of US capacity constraints. That’s why they’ve largely focused on the core, which reveals little acceleration in the above figure. (Dean Baker also pointed out a spike in prices of new cars last month–that’s a monthly anomaly.)

I should also note that the CPI core runs about 0.5 ppts above the PCE core, so think of the Fed’s target for CPI core as ~2.5 percent (as the PCE is their preferred inflation gauge).

Yr/yr energy costs

Source: BLS

So while I understand the case for tightening, and have tried not to get too wound up about small rate hikes, neither do I see a compelling, data-driven case for rate hikes, and that judgement includes this morning’s CPI report.

*For econometric types, there are different ways of running “rolling regressions” of the type I used in the figure in the WaPo piece. Considering that we have T observations (calendar-year quarters in this case), the approach I used estimates the equation using the sample T-n, where n is about half the sample, and then adds back one quarter at time until n is used up. The figure, which plots the coefficient on the slack variable, thus shows how that variable evolves as I add quarterly observations.

But you can also do a “fixed window” approach where you take, say, 20 year samples, for example, and then move the full window up one observation at a time (so, in this case, each regression will have 80 observations). That gives you the picture below (using the same data on core PCE as in the WaPo piece) which tells a similar story re the decreasing sensitivity of inflation to slack.

Source: my analysis (see data note in WaPo piece)

CBO: There’s more slack in the labor market than you thought

February 14th, 2017 at 4:58 pm

[co-authored with Ben Spielberg]

OTE readers know that in the quest for full employment, we pay a lot of attention to the extent of slack in the labor market (and btw, our next podcast episode will focus on this concept of labor market slack—what is it, how much is there, etc. We know…we can hardly wait, too!). One way economists try to gauge this concept of slack is to compare the actual value of labor market indicators to the theoretical value of where they’d be at full employment.

So when a recent CBO revision pretty significantly raised the budget office’s estimate of the potential labor force, we took notice: their revision suggests there’s more slack in the job market than they previously thought.

What is “potential labor force?” It’s CBO’s estimate of what the labor force would be if the economy were at full capacity and the unemployment rate was at its “natural rate” (the lowest rate consistent with stable inflation). In order to project budget outlays and receipts, CBO needs to guesstimate various quantities in the economy, like employment, the labor force, unemployment, and average compensation. They’re often revising such estimates, as they should when new info comes upon the scene, and in their latest revision, they tweaked up the size of the 2016 and 2017 potential labor force by almost one million for this year, or 0.6% of the total. CBO’s incorporation of race (and hence the rising share of the population that is Hispanic) for the first time and increases in educational attainment were two of the revision’s main drivers.

The following figure shows actual and potential labor force participation rates, which we’ll call LFPR and LFPR* (the rates are just the actual and potential labor force as a share of the working-age population). The gap between the two has diminished as the job market has tightened, but it has yet to close.

Source: CBO, our analysis (see data note)

So what does that mean for labor market slack? While there’s no single, reliable indicator that can tell us that, we have found Andy Levin’s total employment gap to be a useful composite of three measures: unemployment, involuntary part-time employment (IPT), and labor force participation. Following Andy’s method, we compare each measure to its estimated potential at full employment.

The unemployment rate—which for many economists is “all she wrote” when it comes to evaluating slack—is just about equal to CBOs “natural rate,” so if that’s all you were looking at, you might think we were at full employment. But IPT is still elevated, and, given CBOs LFPR* upward revision, there’s more room for improvement there, too. The figure below plots Levin’s slack measure before and after the CBO revision, which raised last month’s result from 1 percent to 1.6 percent (an increase of over 800,000 full-time-equivalent-jobs worth of slack).

Source: Andy Levin, our calculations

Caveats abound. Every one of the potential measures has a large confidence interval around it (see here for what we mean re the “natural rate” of unemployment). For years now, economists have been trying to figure out how much of the decline in the LFPR is a function of the aging workforce and how much is a function of insufficient labor demand, and such estimates are always speculative.

But many economists use these data to calibrate their models of the labor force, and we wanted to make sure that everyone was aware of this revision. It suggests that, while we continue making steady progress towards full employment, we’re not there yet.

Data note: CBO does not publish their estimate of LFPR*. They do publish the numerator–LF*–and they use a smoothed version of the BLS 16+ non-institutional population to calculate the rate (smoothing is necessary because the BLS often updates the population weights). Using BLS’s adjustment factors, we created our own smoothed series of the 16+ population, and thus our version of CBO’s LFPR*. Also, we interpolated CBO’s annual labor force estimates to make them monthly.

The dollar goes up and down and yet…life goes on.

February 10th, 2017 at 5:53 pm

The always thoughtful Neil Irwin has a good piece on why tax reform is so damn hard to pull off, citing a concept that’s big here at OTE: path dependency, or “where you end up is significantly a function of where you start out.”

His case study is about leading Republicans’ idea for replacing the corporate tax with a sales-based, border adjusted tax, or the BAT I recently wrote about.


The tax code has been flawed and inefficient for a very long time, precisely because fixing it could be so terribly disruptive. In a nutshell, the corporate tax issue provides an excellent case study of the problem of “path dependency” in public policy.

The United States might well have a better, more efficient tax code today if, starting a century ago, lawmakers had designed it so that businesses were taxed on where their sales and expenses take place, as the Republicans’ plan calls for.

But that is not what happened. Instead, lawmakers took what seemed to be a logical approach: They focused on taxing businesses on their profits. Today, that choice shapes arrangements in every corner of the economy. It affects the values of currencies and financial assets. Every business has devised its structure and organization to maximize its advantage within the existing system.

All true.

But Neil makes another point about which I’m not so sure: “A 25 percent rise in the value of the dollar, the most widely used currency on the planet, would have enormous consequences.”

Hmmm. In fact, as shown in the figure below, the real value of the dollar compared to the currencies of countries with which we trade is up almost that much since 2014, and while there have certainly been consequences, they’ve not been enormous and clearly haven’t derailed the expansion (a sudden, large appreciation could be a bigger deal, but I don’t think that’s a realistic reaction to the BAT).

Source: Fed

No question, the stronger dollar has dampened inflationary pressures, and has thus influenced Fed policy. Very importantly in today’s political climate, it raises the costs of our exports and lowers the cost of imports. Thus, it is a factor in the trade deficit, which has gotten more negative since the appreciation shown above. That, in turn, has contributed to weak factory employment, down 46,000 over the past year, surely an undesirable and important outcome.

But the recovery has proceeded apace over this period, which itself was one reason that the dollar strengthened. We’re growing faster than other advanced economies and contrary to theirs, our central bank is in interest-rate-raising mode, which also strengthens the dollar. All of which is a problem for team Trump, of course, as per the trade deficit point noted above.

And, of course, who knows how much the dollar would appreciate in reaction to the introduction of the BAT? I’m sure it would appreciate somewhat, but I don’t believe the immaculate/immediate full appreciation story (i.e., I don’t believe the dollar would immediately appreciate enough to fully offset its impact on imports).

But getting back to Neil’s discussion of the BAT: while I’m concerned about various aspects of the proposal—higher costs of imports for low-income households, the too-low rate (see point #4 here), the inconsistent revenue estimates (if the tax reduces the trade deficit, then the revenues it generates fall)—it’s worth recognizing that the dollar goes up and down all the time, and its consequences are not necessarily that disruptive.

What you want to worry about, and I worry about it a lot, is a systematically 0vervalued dollar due to currency interventions by trading partners who want a competitive edge over us.

And with that, let the weekend begin!