1. Dale Jorgenson, Mun Ho, Jon Samuels
Measuring Labor Input
Dale Jorgenson, Mun Ho, Jon Samuels
Harvard University
World KLEMS Conference, Harvard University
August 19, 2010

2. Topics Measurement Issues and Methodology Data and Implementation
Results
Contribution of labor input to productivity revival
Criticisms of this method

3. Information Technology and the American Growth Resurgence
Jorgenson, Ho and Stiroh (2005); Chapter 6
New Data on U.S. Productivity Growth by Industry
Jorgenson, Ho and Samuels (2010)

4. Issues in Measuring Labor Input
Number of workers, or Hours worked, are not suitable units of measure for heterogenous labor
Wide range of market wages indicate wide range of productivities
A wage-weighted index have been growing faster than simple sum of hours, productivity residual using hours will overstate the growth of TFP.
Need tractable method of handling this great heterogeneity

6. Methodology for a tractable measure of labor input
Cross classify workers in each industry by demographic characteristics
* In Jorgenson, Gollop & Fraumeni (1987):
sex, class, age, education, occupation
* Now: sex, class, age, education
-Define industry labor input as a Tornqvist index of the demographic components

7. Classification of demographic groups for each industry
2x2x7x6 = 168

8. Index of labor input for industry j, Ljt as Tornqvist index of components
scae: sex, class, age, education
j: industry j or aggregate economy

9. Index Ljt, cont. Constant Quality Index
Assume labor input is proportional to hours worked:
Qscae is the quality of hours of group scae, fixed for all t.
Thus input index becomes:
Compared to simple hours:

10. Index Ljt, cont. Price of industry labor input is simply value/Lj
after choosing a normalization like:
Quality of industry labor input is labor input index divided by hours worked:

11. Decomposing the labor input index
How much of the quality change is due to changes
..in educational attainment?
..in the aging of the labor force? …
Partial indices of labor input.
E.g. first-order index by age
Contribution of age to labor quality

12. Data
Need number of workers, hours and compensation to fill matrices of dimension (2sex, 2 class, 7age, 6educ, 70indus).
Total of cells.
Household survey data
(hours/week, weeks/year, wages/year, demographics, industry)
Census of Population.
- every 10 years
- 1% percent sample (1 million workers)
Current Population Survey, Annual Supplement (ASEC)
- every year, 1964+
- about 100,000 households
Establishment survey data
Bureau of Economic Analysis tabulations of total employment,
total compensation, wages for 72 industries;
annual hours for 18 industries

13. Implementation
-Begin with Census microdata (1% sample, ~1 mil. workers) to populate EMP, HOURS, COMP matrices for benchmark years
-From CPS annual microdata, construct marginal matrices: EMP, HOURS, COMP matrices of lower dimension (e.g. indus x edu, sex x age x edu, …)
-Interpolate between benchmark years using these annual marginal matrices
-Scale to industry totals in the National Accounts

14. Data Issues -Change from SIC to NAICS classification
(CPS and Census 2000 uses NAICS)
-Change in education classification in 1992
-Small sample size in CPS (use fewer industries)
-Household data is “top-coded” for wages
Workers in multiple jobs (multiple industries)
Estimating wages for self employed
No data on fringe (non-wage) benefits by person

25. December 23, 2000 issue

27. Labor Contributions to Aggregate Growth

31. Criticisms of this methodology
Equation of wages with marginal product is not valid with non-competitive markets and discrimination
Small sample sizes for many industries give poor estimates of cell averages
Education is not directly productive and merely a “signal”
Intensity of work effort is not recognized

32. Summary
Simple sum of hours understate labor contribution, overstate TFP growth
Our labor input index – an aggregate over hours by demographic groups, weighted by wages – is a tractable measure with the use of U.S. Census microdata.
The growth of labor quality was about 0.4% per year, or, ¼ of the labor contribution to GDP growth is due to labor quality and ¾ due to hours growth.