1 — U.S. BUREAU OF LABOR STATISTICS • bls.gov

How Much is US Labor Productivity 

Revised?

Peter B. Meyer, Kendra Asher, John Glaser,

Jay Stewart, and Jerin Varghese

Authors did the work at U.S. Bureau of Labor Statistics

Asher now at U.S. Bureau of Economic Analysis

Views and findings are those of the authors, and do not necessarily reflect the views of the Bureaus

FCSM Conference

November, 2021
Labor productivity definition

 Labor Productivity LP growth =

OOOOOOOOOOOO gggggggg g (BBBBBB)

HH HH WW WWWWWW gggggggg g (BBBBBB)

We focus on U.S. nonfarm business labor productivity

About 75% of GDP, excluding general government and nonprofits

Hours worked by matching workforce

The data sources are revised over time.

 Mostly “transitory uncertainty,” as more information becomes available

 Some is definitional or change in methods

 Related studies: Aruoba (2008), Sinclair and Stekler (2013), Manski (2015), Jacobs and van Norden 

(2010, 2016), Fixler et al (2018), Galvao et al (2019), our new Asher et al (2021)
Definitions and notation

 Key variables: Hours worked, output, and labor productivity (LP)

 A figure for Q1 is a change from the previous Q4

 Measured as quarter-to-quarter growth rate, annualized

 Overall hours grew at a bit under 1% rate, LP around 2%, and output at almost 3%

 We have data as of each LP news releases: 8 per year, 1994-2020

 Estimates from releases R0, R1, R2, . . . R40, are shown with subscripts 0, 2, 40

 Previous quarters are updated at the time of each release (available: bls.gov/lpc)

 Revisions are changes in estimates between releases. Release # is subscript

 So if LP growth is revised from LP0 = 1.8 to LP2 = 2.0, that revision is .2
Growth rates as of first releases (R0)

Charts show distributions at R0, before revisions, as annualized growth rates

 Reference quarters 1994-2019, missing one because of government shutdown in 2018: N=103

 Test for normal distribution rejects it for all three

 Output growth shows some skew and downward tail. Mean = 2.91%

 Hours-worked is peaked, tightly clustered. Mean = .96%

 Resulting Labor Productivity growth distribution is slightly peaked. Mean = 1.93%

Output growth (OutputR0) Hours-worked growth (HoursR0) Labor productivity growth (LPR0)
Summary statistics of variables across releases

LP R0 LPR2 LPR40

Mean 2.07 2.26 1.96

Std. dev. 2.28 2.53 2.68

Min -3.02 -4.45 -3.39

Max 9.45 9.50 10.34

 These are averages of growth rates

 Reference quarters 1995 Q1 – 2016 Q2

 Effects of revisions

 Slightly raise then lower output and 

labor productivity estimates

 Hours estimates drift down

 The distributions spread out; their 

standard deviation goes up

OutputR0 OutputR2 OutputR40

Mean 2.84 2.97 2.63

Std. dev. 2.62 3.02 3.35

Min -8.19 -8.84 -12.03

Max 8.80 10.40 11.01

HoursR0 HoursR2 HoursR40

Mean .78 .72 .67

Std. dev. 2.57 2.53 2.81

Min -8.95 -9.04 -10.15

Max 5.06 4.88 4.56
Magnitude of revisions over time

Chart shows absolute values of revisions 

averaged over reference quarters for which we 

have ten years of data

 Hours-worked estimates avg change: .85% 

 Output and LP estimates avg change: 1.7%

After two years, revisions to hours are small

After 3-5 years, revisions to output and

labor productivity are small.
Data flow for hours-worked estimates

Current 

Employment 

Statistics

Self-employed, supervisory 

and non-production workers

Hours-worked-to-hourspaid ratios

Wage and salary employment

& Production worker hours

Current 

Population 

Survey

National 

Compensation 

Survey

Aggregate hours-worked

for U.S. nonfarm business 

sector workforce

Here we’ll focus on statistical properties of the aggregate.
Sources of Revisions

 Additional data in sources (GDP and CES) 

 Benchmarking (CES to QCEW)

 Updating of seasonal adjustment in GDP, CES, CPS

 Annual revisions to GDP data

 Methodology changes to all sources

Largest revisions occur on regular annual schedules.

 March incorporates the CES benchmark revision of previous year

 August release incorporates the annual NIPA/GDP benchmark revisions, and 

Comprehensive Revisions to GDP every 5 years
Prediction intervals for LP: 70, 80 and 90% ranges

The leftmost point is first estimate 

of labor productivity for 2014Q4

(LPR0)

The dark region is 70% prediction 

interval based on 20 years of 

historical data.

The fan shows ranges of likely 

estimates for that reference 

quarter for the next five years.

The downward range spreads 

more than the upward range.
Distributions of productivity revisions

Revisions to LP growth in the first 3 months 

are peaked, with small positive mean

Revisions from 3 months to 5 years out 

are normal, with small negative mean
Revisions vary by reference quarter
Decomposition of Revisions

Revisions to labor productivity growth can be accounted for by 

changes to output or hours, and to the current or prior quarter.

For R0-to-R2, we find that changes to the previous year’s Q4, 

e.g. from annual benchmarking, cause large effects on revisions 

to Q1 growth estimates.
Are productivity revisions predictable ?

We tested how well LP40 is predicted by early estimates and other variables.

Several compressed OLS regression results below.

N=90 for reference quarters 1994Q1-2016Q2. Regressions include a constant.

 Regress LP40 on LP0 : R2 = .39

 Regress LP40 on LP2 : R2 = .51

 Regress LP40 on component hours and output growth rates from R0 & R2: R2 = .54

 Add quarter-of-year and recession indicators: R2 = .57 (not feasible in practice)

 The later LP estimate is better predicted by later data, and slightly better with 

components of earlier estimates and other controls
Are Hours and Output revisions predictable?

Predictions of the components of LP40:

 Regress Hours40 on Hours0 : R2 =.89

 Regress Hours40 on Hours2 : R2 = .92

 Regress Hours40 on Hours2 and quarter and recession indicators: R2 = .94

 Regress Output40 on Output0 : R2 =.61

 Regress Output40 on Output2: R2 =.68

 Regress Output40 on Output2 and quarter and recession indicators: R2 =. 74

 R40 estimates are predicted better by R2 than by R0 data 
Can we predict magnitudes of revisions?

 Are big revisions followed by big revisions? Only slightly.

 Regress abs(LP40 – LP2) on abs(LP2 – LP0): R2 =.01

 Coefficients on previous magnitudes are positive for magnitude

 Add regressors for LP0 , LP2, abs(LP0), abs(LP2), quarter of year

 R2 is less than .2
Predictability in special periods

Do properties of reference quarter predict revisions of LP?

In preliminary regressions, these predictors are not statistically 

significant for R2-to-R40 revisions or abs(R2-to-R40 revisions)

Recessions

1990s vs 2000s vs 2010s

9/11

2008 Q4 is an outlier, associated with financial crisis

Output, hours, and productivity were revised down a lot
Comprehensive revisions to GDP

 BEA adopts conceptual and methodology changes in Comprehensive Revisions to GDP every 5 years

 Major changes adopted in 2013 recognized expenditures on R&D and original works of 

entertainment, art, and literature as capital, not just short-term expenses.

 This raised measured GDP levels by an average of 3.1% for the 1993-2012 period (Fixler, 2012)

 We find measured productivity growth for previous quarters increased on average by .15% per year.

 The new elements were growing faster than the rest of GDP.

 The effect varies greatly across quarters.

 The 2018 Comprehensive Revision raised measured labor productivity by .06% per year.

Release 

month Reference periods

Average and range of 

revisions to output 

growth rate

Average and range of 

revisions to hoursworked growth rate

Average and range of 

revisions to labor 

productivity growth rate

Aug. 2013 1994-2011 (N=72 qtrs) 0.174 (-2.43, 2.54) .023 (-0.056, 0.159) 0.150 (-2.74, 2.55)

Aug. 2018 1994-2016 (N=92 qtrs) 0.057 (-1.30, 1.431) -.003 (-.071, 0.066) 0.062 (-1.26, 1.45)
2020, the start of the covid period

 2020’s output and hours quarterly growth rates were extreme

 Downturn starting in March and in Q2, then up in Q3, at 30% annual pace

 Agencies adopted special methods to capture this rapid change

 BEA used high frequency data (e.g. credit cards transactions) and will continue

 BLS used initial Unemployment Insurance claims to adjust hours (one time only)

 Revisions from LP0 to LP2 were of the size of the 2008Q4 revisions

 Possibly using high frequency data will reduce revision sizes permanently
Updated news releases

SIZE OF REVISIONS: Productivity and cost measures are revised on a regular schedule 

as more complete data become available. . . . 

Based on past revisions, the third estimate of nonfarm business sector quarterly 

labor productivity growth has differed from the first estimate by -1.0 to +1.4 

percentage point about 80 percent of the time. This interval is based on estimates 

for reference quarters from the first quarter of 2001 to the first quarter of 2021.

For more about revisions to labor productivity growth see “How large are revisions to 

estimates of quarterly labor productivity growth?” at 

https://www.bls.gov/osmr/research-papers/2021/ec210040.htm.
Conclusions

 We measure revisions to output, hours, and labor productivity

 Revisions to output after R2 tend to be negative, especially for Q1

 Methodology changes may have reduced size and quarterly variation

 Fan chart shows revisions distribution are not symmetric

 Early revisions are not normally distributed, especially for output

 Underlying distribution of hours-worked growth is peaked, not normal

 We offer prediction intervals based on history, with no distribution assumptions

 Later revisions are not highly predicted by early ones

 We can evaluate effects of methodology changes

 2013 Comprehensive Revision raised measured labor productivity growth, .15%/yr
Contact Information

21 — U.S. BUREAU OF LABOR STATISTICS • bls.gov

Peter B. Meyer

Research Economist

BLS/OPT/DPRPD 

www.bls.gov/dpr

202-691-5678

Meyer.Peter@bls.gov
Decomposition of R0-to-R2 Revisions

Revisions to Q1 output growth incorporate large revisions to the previous Q4

Sample: 2000-2019, excluding 2018Q4 due to government shutdown (For more see Asher et al., 2021)
Decomposition of Revisions

Revisions to growth can be accounted for in terms of changes to 

output or hours, and to current or prior quarter.

We find that changes to the previous year’s Q4 cause substantial 

effects on revisions to Q1 growth estimates.

Labor productivity growth can be approximated as: 

LLLL GGGGGGGGGGG −1,≈ ln QQ − ln QQ −1 − ln HH − ln HH −1

where Q and H are indexes of output and hours

This gives us an additive framework to analyze revisions

LLLL RRRRRRRRRRRR RR0,2 = LLLL GGGGGGGGGGG −1,

RRR − LLLL GGGGGGGGGGG −1,

RRR