Skill allocation in North American economies

Liliana Meza González, Ph.D.Universidad Iberoamericana

Presentation for NAALC meetingCIDE, November 13th, 2006

Dimensions of skill (from the Human Capital Theory)

Years of formal education Years of experience (learning by doing) On the job training Age Health Type of occupation

North American Population pyramids, 2005

North American Population pyramids, 2040

Mechanisms of skill allocation between countries

Trade Inter-industry trade Intra-industry trade

Outsourcing Foreign Direct Investment Labor Migration

Table 1

Mexico United States Canada

Gross domestic product 1 046 100.0 11 679 200.0 1 003 000.0GDP per capita 10 059 39 732 31 395Real GDP growth 4.4 4.2 2.9 Inflation 6.1 2.6 3.1GDP per hour worked 0.90 3.16 0.84Consumer price indices 122.3 109.7 109.7Employment rates: total 60.8 71.2 72.6Employment rates: men 82.5 77.2 76.7Employment rates: women 41.3 65.4 68.4Employment rates for age group 15-24 45.2 53.9 58.1Employment rates for age group 25-54 69.6 79.0 81.4Employment rates for age group 55-64 55.0 59.9 54.0Hours per year per person in employment 1 848 1 824 1 751Education - outcomes - tertiary attainment for age group 25-64 15.4 38.4 44.0Total population 104 000 293 655 31 946Life expectancy at birth: total 74.9 77.2 79.7Infant mortality 20.1 7.0 5.4Trade in goods and services 31.0 12.7 36.5Import penetration for goods and services 33.7 15.2 40.7Imports of goods 196.8 1 525.3 273.4Exports of goods 188.0 817.9 316.9Imports of services 18.6 296.1 57.3Exports of services 13.9 343.9 47.5Inflows of foreign direct investment 16 602 106 832 6 292Outlows of foreign direct investment 3 490 252 012 47 446Outward direct investment stocks 17 185 2 069 013 312 185Inward direct investment stocks 154 344 1 553 955 274 286Source: OECD Statistics

2004COMPARATIVE STATISTICS

Table 2 COMPARATIVE STATISTICS, 2003

México United States CanadaValue added in agriculture, hunting, forestry and fishing

3.79 1.189 2.206Value added in industry, including energy 20.339 17.414 26.59Value added in construction 5.163 4.854 5.308Value added in transport, trade, hotels and restaurants

30.316 19.591 20.743Value added in banks, insurance, real estate and other business services 13.046 32.044 25.636Value added in government, health, education and other and personal services 27.346 24.907 19.518Relative unit labour costs in manufacturing 99.747 91.899 113.106Employment rates: total 59.615 71.223 72.155Employment rates: men 81.981 76.949 76.369Employment rates: women 39.443 65.679 67.927Part-time employment rates 13.449 13.225 18.933Self-employment rates: total 37.135 7.566 9.779Self-employment rates: men 37.083 8.823 10.991Self-employment rates: women 37.233 6.136 8.395Actual hours worked 1857.114 1821.7 1732.7Long term unemployment 1.028 11.809 10.023Exports of I CT equipment 35905.819 136637.095 12018.2Telephone access 48.17 116.847 106.716

Source: OCDE Statistics

Table 3 COMPARATIVE STATISTICS, 2003

México United States CanadaMean scores on the reading scale in PISA 399.722 495.182 527.914Mean scores on the reading scale in PISA, standard errors 4.092 3.221 1.747

Mean scores on the science scale in PISA 404.896 491.263 518.745Mean scores on the science scale in PISA, standard errors

3.488 3.079 2.016Computer usage by 15-year-old students at school: percentage 54.283 42.896 40.379Computer usage by 15-year-old students at school: standard error 1.854 1.382 0.89Computer usage by 15-year-old students at home: percentage 48.238 83.027 89.639Computer usage by 15-year-old students at home: standard error 1.767 0.708 0.291Percentage of 15-year-old students using computers less than one year: percentage 38.82 3.302 1.594Percentage of 15-year-old students using computers less than one year: standard error 1.787 0.338 0.136Percentage of 15-year-old students using computers one to three years: percentage 33.167 12.598 9.97Percentage of 15-year-old students using computers one to three years: standard error 1.015 0.529 0.303Percentage of 15-year-old students using computers three to five years: percentage 13.644 21.994 22.207Percentage of 15-year-old students using computers three to five years: standard error 0.776 0.616 0.439Percentage of 15-year-old students using computers more than five years: percentage 14.369 62.106 66.229Percentage of 15-year-old students using computers more than five years: standard error 1.794 0.955 0.505Tertiary attainment for age group 25-64 15.41 38.422 43.993Tertiary attainment for age group 25-34 18.715 38.653 52.848Tertiary attainment for age group 55-64 7.635 34.744 33.755

Source: OCDE Statistics

Skill allocation in NA due to trade (manufacturing sector)

Graph 1

Thousa

nds

of w

ork

ers

Total Manufacturing employment in North Americayear

1994 1995 1996 1997 1998 1999 2000 2001 2002

18000

19000

20000

21000

22000

Graph 2

(-) USA ( )̂ Mexico (o) Canada

Manufacturing employment indices in North America1994=100

1994 1995 1996 1997 1998 1999 2000 2001 2002

80

90

100

110

120

130

Graph 3

Lo

g U

S M

an

uf.

Ou

tpu

t

Year

Lo

g R

ea

l Ma

qu

ila V

alu

e A

dd

ed

Log US Manuf. Output Log Real Maquila Value Added

1980 1985 1990 1995 2000 2003

4

4.2

4.4

4.6

4.8

8

9

10

11

Graph 4

Production Worker Emp ShareYear

Mexico United States

1991 1993 1995 1997 1999 2001 2003 2005

.67

.69

.71

Graph 5(m

ean)

pro

duct

ion_

shar

e

Production employment share of manufacturing for CanadaPeriod 1994-2002

1994 2002

.745857

.791998

Table 2

Shares of production workers and manufacturing employment

15 most production worker intensive 1995 2001 2004Share of production workers 0.86 0.83 0.83Share of manufacturing employment (percent) 23% 19% 19%

15 least production worker intensiveShare of production workers 0.56 0.54 0.54Share of manufacturing employment (percent) 27% 29% 27%

United States

15 most production worker intensive 1994 1997 2001Share of production workers 0.86 0.87 0.88Share of manufacturing employment (percent) 25% 26% 28%

15 least production worker intensiveShare of production workers 0.57 0.62 0.65Share of manufacturing employment (percent) 15% 14% 13%

Canada

15 most production worker intensive 1994 1997 2001 2004Share of production workers 0.80 0.81 0.81 0.81Share of manufacturing employment (percent) 26% 27% 25% 24%

15 least production worker intensiveShare of production workers 0.50 0.52 0.50 0.50Share of manufacturing employment (percent) 18% 17% 17% 17%

Mexico

Source: Authors´calculations based on different data sources.

Decomposition analysis

This is done to test whether the changes in the share of employment of production workers come from movements within industries or from movements between industries.

i

iii

ii ellel

between within

Table 3 Decomposition analysis

1994 1997 2001

Change 1997-2001

Change 1994-2001

Ratio of production workers to total 0.759 0.781 0.810 0.029 0.051Decompostion of change in skill ratio

Changes between industries 0.004 0.006Changes within industries 0.025 0.045

1994 1997 2001 2004Change

1994-1997

Change 1997-2001

Change 2001-2004

Ratio of production workers to total 0.690 0.696 0.683 0.676 0.0066 -0.013 -0.0076Decompostion of change in skill ratio

Changes between industries 0.0033 -0.006 -0.0027Changes within industries 0.0033 -0.007 -0.0036

1990 1995 2001 2004Change

1990-1995

Change 1995-2001

Change 2001-2004

Change 1990-2004

Ratio of production workers to total 0.714 0.724 0.700 0.697 0.010 -0.024 -0.003 -0.017Decompostion of change in skill ratio

Changes between industries 0.003 -0.008 0.005 -0.002Changes within industries 0.007 -0.017 -0.008 -0.025

Source: Authors´ calculations

Canada

Mexico

United States

Regression Analysis

To obtain correlations between employment and wage bill shares of certain kind of workers and different industry characteristics (including economic integration with other NA countries)

ln Lijt= o + 1 Xt + 2 Zjt + 3 Tjt + jt …………………………………………….. (1a)

ln Wijt = o + 1 Xt + 2 Zjt + 3 Tjt + jt .….……………………………………….. (1b)

where Lijt is j´s industry employment of worker type i in period t; Wijt is j´s

industry earnings or wages of worker type i in period t; is the first difference

operator (e.g. Yjt = Yjt– Yjt- 1); Xt is a vector of time varying regressors common

to all industries; Zjt is a time varying vector of industry regressors; T jt is a time

varying industry vector containing the variables of interest such as trade flows,

and jt and jt are random disturbances assumed to be i.i.d. normal. Lijt and Wijt

are expressed as proportions.

Proportion of workers: USA MEXICO CANADAcoef p coef p coef p

Non-educated -6.754511 0.000 0.4522 0.247 0.0670 0.364Highly educated 6.545438 0.000 -0.6793 0.079 -0.0670 0.364Young(<30) -2.949868 0.000 2.2179 0.000 0.1055 0.764Old(>50) 0.263006 0.735 -1.2237 0.000 -0.1907 0.587White collar 3.145483 0.035 -1.2582 0.008 0.4667 0.005Blue collar -4.676038 0.002 1.3899 0.004 -0.3968 0.078Source: Authors´ calculations

Proportion of workers: USA MEXICO CANADAcoef p coef p coef p

Non-educated 0.4580 0.677 -0.0763 0.831 -0.0080 0.898Highly educated -0.5825 0.584 -0.0204 0.954 0.0080 0.898Young(<30) 1.7081 0.014 2.2493 0.000 0.6685 0.025Old(>50) 0.6544 0.311 -1.0359 0.000 0.9131 0.002White collar 0.2632 0.833 0.9404 0.030 -0.8543 0.000Blue collar 0.1589 0.904 -0.9385 0.031 0.7768 0.000Source: Authors´ calculations

Proportion of workers: USA MEXICO CANADAcoef p coef p coef p

Non-educated -7.4059 0.000 -0.4033149 0.424 1.7789 0.836Highly educated 6.4344 0.000 0.0191231 0.975 930.7880 0.000Young(<30) -2.1138 0.002 1.368867 0.002 147.4700 0.094Old(>50) 0.3035 0.709 -0.71198 0.014 76.6205 0.377White collar 4.2660 0.005 -1.563907 0.011 0.4789 0.066Blue collar -5.7041 0.001 1.0653 0.051 -0.4788 0.067Source: Authors´ calculations

Proportion of workers: USA MEXICO CANADAcoef p coef p coef p

Non-educated 0.9130 0.466 -0.734538 0.113 0.3173 0.966Highly educated -0.0936 0.936 0.725736 0.190 -657.0815 0.001Young(<30) 1.2995 0.032 1.09771 0.007 49.6976 0.510Old(>50) 0.2896 0.679 -0.852578 0.001 53.0014 0.471White collar -0.0064 0.996 1.055148 0.064 0.1085 0.626Blue collar 1.0975 0.461 -1.1062 0.027 -0.1039 0.643Source: Authors´ calculations

Table 4Correlations between exports and worker group proportions, by industries

Correlations between imports & payroll proportions, by worker groups

Table 5

Table 6Correlations between exports & payroll proportions, by worker groups

Table 7

Correlations between imports and worker group proportions, by industries

Labor demand analysis

This helps us figure out if US and Mexican populations in the manufacturing sectors have been complements or substitutes.

_ _ _ _0 1 2 3 4

_ _ _ _0 1 2 3 4

_ _ _ _0 1 2 3 4

us u us u mx s mx u mxit it it it it it

mx s us u mx s mx u mxit it it it it it

mx u us u mx s mx u mxit it it it it it

L w w w y

L w w w y

L w w w y

(1) (2) (3)

Constant Output

Constant Output

Constant Output

US Blue Collar

Employment

MX White Collar Employment

MX Blue Collar

Employment

US Hourly Wage Blue -1.072 0.110 -0.171

(0.032)** (0.008)** (0.009)**

MX Hourly Wage White 0.110 -0.042 0.059

(0.008)** (0.006)** (0.005)**

MX Hourly Wage Blue -0.171 0.059 -0.077

(0.009)** (0.005)** (0.006)**

Production Value 0.165 0.298 0.397

(0.005)** (0.005)** (0.005)**

Constant 5.274 -2.025 -1.505

(0.101)** (0.075)** (0.075)**

Observations 9900 9900 9900

Standard errors in parentheses

* significant at 5%; ** significant at 1%

Table 5

Evidence

The manufacturing sector produces less than 25% of GDP in the three economies.

The agricultural sector produces less than 4% of GDP in the three countries. The tradables sector represents around 30% of GDP in the three countries. Around 70% of GDP in each country is subject to skill allocation through other

means than inter-industry trade: Intra-industry trade, outsourcing, FDI and migration.

There is evidence [Feenstra and Hanson ( )] that outsourcing , FDI and intra-industry trade increases the demand for skill labor in the source and the receiving countries.

Most of the skill allocation among the three countries is happening through migration of low skill labor to the largest economy in the region.

Annual Average Mexico-US Migration and US Employment Rates

0

100

200

300

400

500

600

1992 1994 1996 1998 2000 2002 2004

Source: Passel and Suro 2005

Tho

usan

ds o

f Mig

rant

s

91.0

92.0

93.0

94.0

95.0

96.0

97.0

US

Em

ploy

men

t Rat

e

Annual Mexico-US Migration

US Employment Rate

Concluding remarks

The main mechanism for skill allocation in the region has been migration of the low skil population.

Canada has taken advantage of the skill composition created by the strong attraction forces of the region, but the US manufacturing sector has been decreasing and employing more skilled labor, maybe due to an increasing productivity and the competition from other regions of the world (especially Asia)

Outsourcing, FDI and intra-industry trade seem to be causing an increasing demand for skilled labor in Mexico and the US, creating both supply and demand forces for migration of the unskilled labor to the service sector of the largest economy.

It would be advisable to give Mexico a special treatment as a source country of unskilled labor (highly needed in the American and Canadian service sector) and to try to enforce labor laws in the three countries to protect labor rights of North-American population.

More and better education for the Mexican population should be a main labor policy in the region, so Mexico stops being the main source of unskilled labor to the region.