Skill Use and Technical Change: International

Evidence

National Institute of Economic and Social Research

Mary O’MahonyCatherine Robinson

Michela Vecchi(m.omahony@niesr.ac.uk)

Previous literatureConsider the impact of information and communications technology (ICT) on skill use.

Previous literature focused on skill bias technical change.

The evidence on balance suggests technical change has been moving in a skill biased direction.

and some evidence this is linked to ICT.

Focus of previous work has been on comparing highest and lowest skill groups.

Misses the dynamics within intermediate groups.

This paper:

Examines skill use in the 1980s and 1990s for three countries, the US, the UK and France.

The analysis is based on industry data covering all sectors within the non-agricultural market economy.

Labour input is divided into five types (six for France) according to education/qualification levels.

We also separately identify IT occupational groups, with a division into two qualification levels, those with degrees and others.

Table 1: Skills categories employed in the analysis.

UK

1. First degrees and above

2. Other National Vocational Qualifications: level 4

3. National Vocational Qualifications: level 3

4. National Vocational Qualifications: levels 2 and 1

5. No formal qualifications

US

1. Bachelor degrees and above

2. Associate degrees

3. Some college, no degree

4. High school graduate

5. Did not complete high school

France

1. Bachelor degrees and above

2. Baccalauréat plus 2 years college

3. Baccalauréat

4. Vocational 1 (CAP, BEP etc.)

5. Vocational 2 (BEPC)

6. No formal qualifications

Chart 1.a. Trends in labour shares US.

0.0

50.0

100.0

150.0

200.0

250.0

300.0

1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000

High

Associate

SCND

High-school

None

Chart 1.b. Trends in labour shares UK.

0.0

50.0

100.0

150.0

200.0

250.0

300.0

1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000

Higher

NVQ4

NVQ3

NVQ12

None

Chart 1.c. Trends in labour shares France.

0.0

50.0

100.0

150.0

200.0

250.0

300.0

1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000

higher

Bacc+2

Bacc

Voc1

Voc2

None

IT labour: occupations

Computer systems managersSoftware engineersComputer analysts, programmersComputer operatorsComputer engineers, installationand maintenance

The decomposition approach (Berman, Bound and Griliches, 1994)

i

iSjiP

ijiPiSjP

for i=1, …, n industries, j skill groups.

Pj is the share of each skill type in total employment,

Pji. is are the industry shares of type j skill group,

- denotes average across industries.

Si is the share of employment in industry i.

If within effect dominates then supports SBTC

Can do similar decomposition for wage bill shares

between within

Chart 2a. Decomposition results, US employment

0.000

0.200

0.400

0.600

0.800

1.000

1.200

IT workers IT higher IT other Non-IT higher Non-ITAssociate

degree

Non-IT somecollege, no

degree

Non-IT highschool diploma

Non-IT noqualifications

between

within

Chart 2b. Decomposition results, UK employment

-0.2

0

0.2

0.4

0.6

0.8

1

1.2

IT workers IT higher IT other Non-IT higher Non-IT NVQ4 Non-IT NVQ3 Non-IT NVQ21 Non-IT no quals

between

within

Chart 2c. Decomposition results, French employment

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

1.2

1.4

it workers it higher it other Non-IT higher Non-IT Bacc. +2 Non-IT Bacc. Non-IT Voc. 1 Non-IT Voc. 2 No quals

between

within

Wage share equationsTranslog cost function: standard wage share (Ws) equation, i industries, j skill types, w = wage rates, K = capital and Y = output, n is the lowest skill group and WT is the total wage bill

iTTiYiK

Kniwjiw

WiWTjiWs

lnlnln0

Wage bill share Substitution Capital-skillcomplementarity New technology

Wage share equations

Adoption versus use of new technology (Chun 2003)

Use: Share of ICT in total capital services - standard technology variable

Adoption: Chun - age of ICT capital

This paper: IT specific labour requirements

ratio IT workers to ICT capital

Industry data setUS: 31 industries, annual 1979-2000

UK: 27 industries, annual 1982-2000

France: 30 industries, annual 1982-2000

Output: Value added

Capital: Tornqvist index of capital services, three ICT types (computers, software and communications equipment) and three non-ICT (structures, other equipment, transport equipment)

Regression ResultsFor the US:

First degree and

higher degree

Associate

degree

Some college, no

degree

High school

graduate

yw_kln 0.161* (0.042)

-0.003 (0.004)

-0.019 (0.031)

-0.092* (0.032)

ktw_ictln 0.029* (0.010)

0.017* (0.003)

0.035* (0.008)

0.068* (0.010)

itratioln 0.038* (0.007)

0.008* (0.001)

0.016* (0.003)

0.044* (0.005)

NB: time dummies were included for all specifications

US results continued… First degree and

higher degree

Associate

degree

Some college, no

degree

High school

graduate

yw_kln 7988 0.036* (0.013)

0.000 (0.003)

0.019* (0.008)

-0.028* (0.011)

yw_kln *8900 0.266* (0.067)

-0.003 (0.008)

-0.049 (0.056)

-0.135* (0.061)

ktw_ictln 7988 0.057* (0.011)

0.009* (0.001)

0.024* (0.005)

0.033* (0.005)

ktw_ictln *8900 0.010 (0.015)

0.017* (0.003)

0.039* (0.012)

0.071* (0.015)

itratioln 7988 0.039* (0.004)

0.005* (0.000)

0.014* (0.002)

0.027* (0.002)

itratioln *8900 0.042* (0.009)

0.008* (0.001)

0.016* (0.005)

0.047* (0.008)

Results for the UK

First degree and

higher degree

NVQ 4

(professional)

NVQ3

(A-level)

NVQ21

(O-level)

yw_kln 0.127* (0.059)

-0.030** (0.017)

-0.018 (0.084)

0.002 (0.047)

ktw_ictln 0.059* (0.014)

0.017 (0.012)

0.078* (0.019)

0.032* (0.010)

itratioln 0.004 (0.003)

0.005* (0.002)

0.005 (0.011)

0.034* (0.007)

UK results continued… First degree and

higher degree

NVQ 4

(professional)

NVQ3

(A-level)

NVQ21

(O-level)

yw_kln 7988 0.093 (0.063)

-0.026 (0.018)

0.208 (0.176)

-0.043 (0.036)

yw_kln *8900 0.144** (0.079)

-0.031 (0.022)

-0.108 (0.078)

0.013 (0.068)

ktw_ictln 7988 0.053* (0.014)

0.011* (0.005)

0.036 (0.050)

0.037* (0.011)

ktw_ictln *8900 0.063* (0.018)

0.018 (0.016)

0.098* (0.019)

0.017 (0.014)

itratioln 7988 0.008* (0.004)

0.004* (0.001)

0.014 (0.011)

0.017* (0.003)

itratioln *8900 -0.006 (0.008)

0.006 (0.005)

-0.015 (0.022)

0.070* (0.019)

Results for France

First degree and above

(SE)

Bacc. +2yrs (SE)

Baccalauréat (SE)

Voc. 1 (SE)

Voc.2 (SE)

yw_kln 0.040* (0.015)

0.025** (0.015)

0.046* (0.011)

0.034* (0.013)

0.014 (0.010)

ktw_ictln 0.042 (0.035)

0.053** (0.029)

0.024 (0.028)

0.005 (0.029)

-0.051 (0.034)

itratioln 0.017 (0.032)

0.014 (0.018)

0.022 (0.018)

0.004 (0.022)

-0.032 (0.023)

French results continued…

First degree and above

(SE)

Bacc. +2yrs (SE)

Baccalauréat (SE)

Voc. 1 (SE)

Voc.2 (SE)

yw_kln *8288 0.040 (0.026)

0.011 (0.011)

0.040* (0.012)

0.040* (0.016)

-0.001 (0.007)

yw_kln *8900 0.041* (0.017)

0.029 (0.024)

0.052* (0.016)

0.038* (0.019)

0.023 (0.017)

ktw_ictln *8288 0.031 (0.079)

0.059** (0.032)

0.051 (0.044)

-0.056 (0.037)

-0.006 (0.028)

ktw_ictln *8900 0.047 (0.035)

0.046 (0.037)

0.011 (0.035)

0.038 (0.039)

-0.074** (0.046)

itratioln *8288 0.005 (0.005)

0.035 (0.031)

0.032 (0.031)

-0.061* (0.026)

-0.003 (0.024)

itratioln *8900 0.025 (0.024)

0.004 (0.022)

0.019 (0.020)

0.044 (0.031)

-0.045 (0.034)

ConclusionsNature of skill bias changes across time

New technology increased wage premiums for highly skilled workers more in 1980s than 1990s in the US.

Evidence that this technology is moving more towards increasing wage premiums for those with intermediate skills over time.

Adoption effect highly significant in the US - consistent with findings by Chun (2003)

Evidence for the UK is more mixed but there is some suggestion of increasing skill bias for intermediate skill levels.

Conclusions

In contrast, in France only one intermediate category shows any positive impact from ICT and the lowest intermediate category shows a negative impact in the 1990s.

Probably reflects the differences in the labour market institutions in France

High supply of educated workers and their relatively low wage