Posts filed under “Wages & Income”

The Impact of Unemployment Duration on Compensation Growth

The Long and Short of It: The Impact of Unemployment Duration on Compensation Growth
M. Henry Linder, Richard Peach, and Robert Rich
Liberty Street Economics, February 12, 2014



How tight is the labor market? The unemployment rate is down substantially from its October 2009 peak, but two-thirds of the decline is due to people dropping out of the labor force. In addition, an unusually large share of the unemployed has been out of work for twenty-seven weeks or more—the long-duration unemployed. These statistics suggest that there remains a great deal of slack in U.S. labor markets, which should be putting downward pressure on labor compensation. Instead, compensation growth has moved modestly higher since 2009. A potential explanation is that the long-duration unemployed exert less influence on wages than the short-duration unemployed, a hypothesis we examine here. While preliminary, our findings provide some support for this hypothesis and show that models taking into account unemployment duration produce more accurate forecasts of compensation growth.

        The hypothesis that individuals who are unemployed for long durations have less impact on the behavior of wages than the recently unemployed is not new. Insider-outsider models make this prediction, and a paper by Ricardo Llaudes finds strong support for this proposed explanation in data for European countries. What is new is the relevance of this hypothesis for movements in wage rates in the United States. In particular, conventional models—such as Phillips curve models—have generally underpredicted compensation growth since 2009. These models typically rely on the total unemployment rate as the measure of labor market tightness. If the long-duration unemployment rate has limited impact on the compensation growth process, then its relatively large share in the unemployment rate in recent years could account for the underprediction of standard Phillips curve models.

The chart below plots the total, long-duration, and short-duration unemployment rates, with the division between short- and long-duration unemployment defined, respectively, by unemployment spells of 26 weeks or less and 27 weeks or more. Until the past few years, the U.S. experience has been that most fluctuations in the total unemployment rate were driven by the short-duration unemployment rate. The average of the long-duration unemployment rate was only 1.0 percent from 1960:Q1 to 2007:Q4, with deviations around the average fairly muted and short-lived. However, the long-duration unemployment rate rose to over 4.0 percent during 2009-10, and by December 2013 has only moved down to 2.6 percent.


So, is it important to distinguish between short-duration and long-duration unemployment in the United States? In a recent study, Robert Gordon of Northwestern University uses a Phillips curve model to examine the behavior of price inflation from the early 1960s through early 2013. His findings indicate that short-duration unemployment has a much greater impact on price inflation than does long-duration unemployment. Further, out-of-sample forecasts using short-duration unemployment track price inflation much more closely than those based on the total unemployment rate, especially during the post-2008 period. Our analysis complements the recent work of Gordon and offers some evidence on the robustness of his results by looking at compensation growth, as well as by specifying a different Phillips curve model and by examining a shorter sample period that runs from 1997 through the present.

In a conventional compensation Phillips curve model, the indicator of resource utilization is the unemployment gap, measured as the difference between the unemployment rate and the non-accelerating inflation rate of unemployment (NAIRU). Conceptually, if the economy were operating with the unemployment rate at NAIRU, inflation would not have a tendency to either increase or decrease. Positive values of the unemployment gap indicate excess supply conditions in the labor market which should put downward pressure on compensation growth (and vice versa).

We compare forecasts of compensation growth using two alternative measures of the unemployment gap—one based on the total unemployment rate and another based on the short-duration unemployment rate. The total unemployment gap measure is the difference, measured in percentage points, between the total unemployment rate and the Congressional Budget Office (CBO) estimate of NAIRU. The short-duration unemployment gap is constructed as the difference between the short-duration unemployment rate and our estimate of the short-duration NAIRU. The latter is the CBO estimate of NAIRU less the average of the long-duration unemployment rate calculated over the 1997-2007 period.

As shown in the chart below, there had been a very close correspondence between the two unemployment gaps until the onset of the most recent recession. Currently, the total unemployment gap indicates a large amount of slack in the labor market, while the short-duration unemployment gap indicates little, if any slack.


Following an earlier post on compensation growth, we specify a nonlinear compensation Phillips curve model (see this paper by Fuhrer, Olivei, and Tootell for a discussion of modeling the nonlinearity). The model relates the four-quarter growth rate in compensation per hour in the nonfarm business sector, relative to trend productivity growth and long-run inflation expectations, to resource utilization. For trend productivity growth, we use a twelve-quarter moving average of the (annualized) quarterly growth rate of productivity. For expected inflation, we construct a measure for the personal consumption expenditure index (PCE) by adjusting the Survey of Professional Forecasters ten-year expected CPI inflation series to account for the usual differential between CPI and PCE inflation. As in our previous post, we focus on the post-1997 period because it represents a low-inflation environment, based on the level and stability of the expected inflation series, and because we believe the nonlinearity may be especially relevant in such an environment.

We examine both the within-sample fit and out-of-sample forecasts of the models to evaluate the alternative unemployment gap measures. The out-of-sample forecast performance is based on estimation of the model using data through 2007:Q4. With the resulting estimated model, we input the actual values of the unemployment gap, trend productivity growth, and expected inflation series for the post-2007:Q4 period to generate forecasts of compensation growth. The first forecast corresponds to compensation growth from 2008:Q1 to 2009:Q1.

The next chart plots the four-quarter change in compensation growth, the within-sample fit of the models through 2007:Q4, and the post-2007:Q4 out-of-sample forecasts.


Not surprisingly, the within-sample fit of the two models is very similar due to the two unemployment gap measures closely tracking each other during this period. The out-of-sample forecasts, however, reveal the different implications of the two unemployment gap measures. While the compensation growth series displays some volatility and both models missed the initial slowing and subsequent rebound in the series, the forecast using the short-duration unemployment gap does a better job tracking the subsequent movements in compensation growth and is about 10 percent more accurate than the forecast that ignores the duration of unemployment. The graph also illustrates that the forecast using the total unemployment gap have consistently underpredicted compensation growth, a feature shared by price-inflation Phillips curve models. Although they are not shown, we obtain similar results if we start the out-of-sample forecasts in 2004:Q4.

Our results raise an interesting question—why has the distinction between short-duration and long-duration unemployment in the United States previously received so little attention? One answer is that the close correspondence between the total unemployment rate and the short-duration unemployment rate has masked the importance of the latter variable. If movements in the unemployment rate are largely driven by the short-duration unemployment rate, then the unemployment gap is a suitable proxy for measuring slack in the labor market—even if the appropriate measure is the short-duration unemployment gap. It is only since the last recession and its aftermath, when the composition of the total unemployment rate deviated from its historical pattern, that we can observe the differential effects of unemployment duration on compensation growth.

The views expressed in this post are those of the authors and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the authors.

M. Henry Linder is a senior research associate in the Federal Reserve Bank of New York’s Research and Statistics Group.

Richard Peach is a senior vice president in the Federal Reserve Bank of New York’s Research and Statistics Group.

Robert Rich is an assistant vice president in the Federal Reserve Bank of New York’s Research and Statistics Group.

Category: Employment, Think Tank, Wages & Income

The Spending and Debt Responses to Minimum Wage Increases

Category: Think Tank, Wages & Income

Nations Ranked by Quality of Life

From National Journal: Money is important, but it isn’t everything. The Organization for Economic Cooperation and Development created the Your Better Life Index to compare the quality of life as well as economic prowess of its 34 member countries. The index measures each country using 11 different lines, including income, employment, health, education, environmental quality,…Read More

Category: Economy, Taxes and Policy, Wages & Income

Another Meaningless Non Farms Payroll Report

Regular readers may recall that I’m not a big fan of this Bureau of Labor Statistics Employment Situation data series, as it is unusually noisy and subject to further revisions and modeling adjustments. (See Ignore Today’s — and Most — Jobs Reports). As we discussed not too long ago, the Employment Situation report is “the…Read More

Category: Employment, Wages & Income

Half the Nation’s Uninsured Live in Just 116 Counties

Source: Washington Post

Category: Taxes and Policy, Wages & Income

Minimum Wage: Research Papers

Category: Think Tank, Wages & Income

Follow Up: Daily Show Blowback

Last night’s Daily Show appearance (described here: How I Ended Up On The Daily Show) generated a surprising amount of interest. As much as I would like to claim responsibility for the buzz — my calm demeanor and rational approach as the cause — in reality, the person on the other side of the argument, Peter…Read More

Category: Humor, Media, Television, Wages & Income

Cities and Minimum Wages

Source: Center for Economic and Policy Research   Minimum wage policy was part of the SOTU address last night. As it turns out, 20 states plus DC have minimum wages higher than the federal level. CEPR notes that: As of January 1, 2014, 13 states raised their minimum wage, with California set to follow suit…Read More

Category: Wages & Income

TDS: Wage Against the Machine

Below is my Daily Show debut.

The segment was pretty good. As noted last night, we shot for 2 hours, and lots of great stuff was left on the cutting room floor. The discussion on higher paying retailers such as Costco and Trader Joes versus Walmart was actually interesting, and Samantha was really funny in that section. I guess if I wanted more screen time, I should have spoken about retarded people deserving to earn less than minimum wage (watch the video to understand).

Samantha Bee explores the devastating economic effects of raising the minimum wage to the poverty level.

(04:59) January 28, 2014

Category: Humor, Media, Television, Video, Wages & Income

How I Ended Up On The Daily Show

Tonight, after the opening segment but before Louis CK comes on, I am deeply involved in the middle segment of The Daily Show. How this came about is an interesting story — one that is strange enough to be worth sharing. [Update: Here]

I am either brave or foolish publishing this before the show airs, but I don’t think I made too big an arse of myself. Regardless, it would not be the first time I did so on Television in my professional career.

This episode came about thanks to a post I did for Bloomberg View on the minimum wage. I was at a hotel in Hartford, waiting to give pension fund investors my Romancing Alpha schtick. I had 90 minutes to kill, so I banged out this commentary titled How McDonald’s and Wal-Mart Became Welfare Queens. The story of the McResource hotline had already broken, and I wanted to address it from a perspective of a corporate subsidy from taxpayers. (The follow up are here and here) [Update: This interview was on December 18th, long before tonight's SOTU address, which hit on many of the same issues]

I don’t use a publicist, so you can imagine my pleasant surprise when an email came in from the Daily Show producers asking me questions about the minimum wage and corporate subsidy column. We chatted a few times, the idea got kicked around by the writers and producers . . . and then the call came. “Hey, can we shoot you next week?” My response: Sure. (Why didn’t I get a haircut?)

This wasn’t the first time I had been tagged by them — When Alan Greenspan retired from the Fed, they reached out (I put them in touch with Kudlow & Cramer instead). And it looked as if Bailout Nation might have landed me in the guest chair, but that never quite materialized. So this was quite a lot of fun, and felt like a long time coming.

As the photos below show, they arrived in our midtown office with tons of equipment. It took over 90 minutes for them to set up.

Shortly afterwards, Samantha Bee showed up. She is a combination of hilarious and delightful. We settle into the chairs, and she begins to fire questions at me. For this 4 minute segment, we shot for two hours.  The hardest part was not cracking up. Her facial expressions and cacophony of shrieks, whines and laughs are infectious. I ruined a few takes breaking up laughing.

A few interesting things I learned about The Daily Show over the course of our shooting — first, they don’t want to tell you who is on the other side of the argument. I had suggested to them that Peter Schiff was a perfect guy for this, as he had been haranguing Wal-Mart shoppers in the parking lot (See this and this).  The next night at dinner with a group of media folks and strategists they confirmed that it was indeed Schiff on the other side of the debate (he apparently told them). Fun!

Second, it appears that TDS has some smart lawyers who’ve thought this thing through. All of the answers were recorded following each question in one continuous segment. When I screwed up or ruined a shot, they had to go back to ask the question again, with the response immediately following in the same shot.

In other words, they don’t cut up your answers or pull them out of context. Question, Answer, Question, Answer. I assume this keeps litigation from angry remote guests to a minimum.

Over the course of two hours, its pretty easy to say something stupid — especially when one of the funniest people on earth is two feet away making faces and saying very funny things. I hope I didn’t embarass myself. We”ll find out at 11:06pm or so.

Anyway, here are some of the snaps I grabbed with the phone. The last one is a spoiler so its after the jump . . .


They brought a ton of equipment, which raised eyebrows on our floor
TDS equiptment hall 2

Setting up in my office, Camera 1
TDS office set up 1


Setting up in my office, Camera 2
TDS office set up 2

Lights, Cameras, Electrical, Booms
TDS office set up 3

Samantha Bee was delightful
TDS Samantha Bee

She worked the entire time, tweaking & rewriting lines. She is quite the Pro
TDS Shes a pro


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Category: Humor, Television, Wages & Income