Thomas A. DiPrete - School-Work Linkages and the Distribution of Wages

School-Work Linkages and the Distribution of Wages Thijs Bol, Christina Ciocca, Herman van de Werfhorst, and Thomas A. DiPrete University of Amsterdam and Columbia University

June 14, 2017

Thijs Bol, Christina Ciocca, Herman van School-Work de Werfhorst,Linkages and Thomas and the A. DiPrete Distribution (University of Wages of Amsterdam June 14, 2017 and Columbia 1 / 30Un

How Does Education Affect the Wage Distribution?

Partly through the combination of the distribution of educational attainment and the rate of return to education.

The rate of return depends in part on the structure of demand for education, and on its supply.

Other educational features also may play a role, but these are less-well studied.

T. Bol, C. Ciocca, H. van de Werfhorst, and T. DiPrete School-Work (UvA and Linkages Columbia)

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Institutional Features and Fields of Study Allmendinger, Kerckhoff, Shavit & Müller et al studied how standardization, selectivity, vocational specificity – treated as aggregate, country-level features – affect the school to work transition.

Other scholars have estimated rates of return to fields of study.

Both important, but the above approaches leave out two important questions: Are the returns to education partly a function of the occupational destinations that school-leavers with specific credentials wind up in?

National educational systems differ in the extent to which they create weak or strong linkages between school-leaving credentials and occupations. Do these institutional differences affect the structure of inequality?

T. Bol, C. Ciocca, H. van de Werfhorst, and T. DiPrete School-Work (UvA and Linkages Columbia)

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“Training Regimes� vs. The Structure of Linkage

Much important work has addressed national differences in educational systems.

This work (notably by Shavit and Mueller) identified important macro-level differences. ...and demonstrated that these macro-characteristics mattered for the school-to-work transition (e.g., the time to first job or unemployment rate)

Addressed only implicitly the relational character of educational systems, i.e., the ways educational outcomes connect to occupational destinations and the differences both within and between countries, as well as over time.

T. Bol, C. Ciocca, H. van de Werfhorst, and T. DiPrete School-Work (UvA and Linkages Columbia)

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Theory of How Linkage Structure Relates to Wage Structure DiPrete et al. (2017)1 showed that countries differ in their linkage structure and also that these differences themselves differ depending on the specific educational outcome under study.

They showed that distinctions such as “organizational space” (often identified with France) or “credential space” (often identified as Germany) oversimplify both in the cross-section and historically.

While organizational spaces ostensibly have weak links between educational outcomes and the occupational structure, France actually has stronger linkages between education and occupation than does Germany for many educational outcomes.

Moreover, the differences between Germany and France have themselves been changing since 1970 (Elbers, Bol, and DiPrete 2016).

1 DiPrete, Bol, Ciocca, and van de Werfhorst (2017, AJS). “School-to-Work Linkages in the United States, Germany, and France.”

T. Bol, C. Ciocca, H. van de Werfhorst, and T. DiPrete School-Work (UvA and Linkages Columbia)

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Why does this matter for wage outcomes and inequality?

Stronger linkage, we conjecture, may raise productivity and therefore wages through more efficient matching of workers to jobs they are trained for.

Stronger linkage, we conjecture, may create solidarity, raises bargaining strength, and therefore wages.

Stronger linkage, we predict, should reduce within-occupation skill heterogeneity.

This, in conjunction with greater solidarity, should reduce within-occupation wage variance, which is a component of wage inequality.

T. Bol, C. Ciocca, H. van de Werfhorst, and T. DiPrete School-Work (UvA and Linkages Columbia)

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Linkage Strength Total linkage strength (M, the Mutual Information Index): The average reduction in occupational (educational) entropy (En(· )) between its overall value and its value for workers with a specific educational (occupational) level and field of study, averaged over all educational (occupational) categories.

G X M= pg (En(Pj ) − En(Pj|g )) g =1

Local linkage strength (Mg ): The extent to which the occupational (educational) distribution of workers in educational (occupational) category g differs from the overall occupational (educational) distribution.

Mg =

X

pj|g ln

j

M=

X

pj|g pj

=

X

pj αgj ln(αgj ) where αgj =

j

pjg pj pg

pg M g

g T. Bol, C. Ciocca, H. van de Werfhorst, and T. DiPrete School-Work (UvA and Linkages Columbia)

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Data for Three Countries

United States: 2009 American Community Survey & SIPP data (2004 & 2008 panels).

Germany: 2006 Mikrozensus.

France: 2005-2012 EnquĂŞte Emploi (one wave of data from 37 rotation groups).

T. Bol, C. Ciocca, H. van de Werfhorst, and T. DiPrete School-Work (UvA and Linkages Columbia)

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Data, continued Gross earnings for full-time employed individuals, converted to a monthly measure (Hard to measure wages for part-time employees in all countries).

For Mikrozensus, we predicted gross earnings from personal income interacted with age and household status plus other variables using the SOEP (R 2 = 0.95), and used the imputed score as the German gross income measure.

We used about 90 harmonized ISCO categories & about 80 harmonized educational categories (levels + fields) for France, Germany, US . each cell with at least 100 respondents.

(in other analyses, we use native occupational codes and native fields and educational levels (200+ in both France and Germany).

T. Bol, C. Ciocca, H. van de Werfhorst, and T. DiPrete School-Work (UvA and Linkages Columbia)

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Local Linkage of Educational Levels and Fields France

Germany

United States

NA ● ● ●

Other ● ● ●●

Sec Environ

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Pers serv Social serv

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Eng

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Teach ●

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Arts

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Law Buss&admin

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Lifesci

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Physsci

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Comput

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Manuf

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Archit

Socsci

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Human.

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Agri

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Transport

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Local segregation ●

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Local Linkage: Heuristic With harmonized categories, proportion of workers with a given educational outcome in the three most common occupations âˆź = one fifth of the linkage score plus 0.2.

So if the local linkage score is 0.4, roughly .2 + .2*.4 = .28, i.e., 28% of the workers with that educational outcome are predicted to be in one of the three most common occupational destinations for that educational outcome.

If the local linkage score is 2.0, roughly .2 + .2*2 = .6, i.e., 60% of the workers that the educational outcome are predicted to be in one of the three most common occupational outcomes for that educational category.

A similar calculation can be done if we are focusing on occupational linkage scores instead of educational linkage scores.

Total linkage has similar interpretation (weighted average of local linkage).

T. Bol, C. Ciocca, H. van de Werfhorst, and T. DiPrete School-Work (UvA and Linkages Columbia)

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Local Linkage: Illustration Figure: The Proportion of Workers in the Three Most Common Occupational Destinations, for Three Illustrative Educational Outcomes in Germany.

Health (ISCED 5AB/6)

Math and statistics (ISCED 5AB/6) Local linkage: 2.07

Local linkage: 3.42

Health professionals (86.1%)

Health associate professionals (3.2%)

Nursing and midwifery (1.2%)

Mathematicians and statisticians (41.4%)

Computer associate professionals (16.0%)

Architects and engineers (7.2%)

Health (ISCED 3ABC) Local linkage: 1.49

Personal care workers (27.2%)

Nursing and midwifery (25.1%)

Social work associate prof.

(9.6%)

Note: The percentages for each of the three educational outcomes sum to less than 100% because some workers with each of these educational outcomes are working in occupations other than the three occupations shown. The occupations shown are the three most common occupational destinations for workers with the indicated educational outcome.

T. Bol, C. Ciocca, H. van de Werfhorst, and T. DiPrete School-Work (UvA and Linkages Columbia)

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Variation across Level-Fields and across Countries

Categories that correspond well to specific occupational licensing requirements and categories at the upper tertiary level generally have rather strong linkage scores.

Computing, engineering, law, architecture, business and administration, health, mathematics and statistics, and the physical sciences are all examples of fields that correspond to various professional occupations and that in almost every case have stronger linkage at the upper tertiary than at lower tertiary educational level in all three countries.

At the same time, the relative linkage strength of these and other fields clearly varies across France, Germany, and the U.S.

T. Bol, C. Ciocca, H. van de Werfhorst, and T. DiPrete School-Work (UvA and Linkages Columbia)

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Total Linkage Strength in France, Germany, and the U.S. 1.00

0.50

0.25

US

Germany

0.00 France

Total linkage strength

0.75

A. Between major occupations, by level B. Between minor occupations within major occupations, by level C. Between major occupations, by field within level D. Between minor occupations within major occupations, by field within level

Variance Decomposition of Wages by Educational Levels and Fields 0.20

Between levels Between fields, within levels

0.10

0.05

US

Germany

0.00

France

Explained variance in ln gross earnings

0.15

Importance of Fields (in words)

In France, the relative contribution of fields is 16.9 percent.

In Germany the relative contribution is 15.5 percent.

In the United States the relative contribution is much lower (8.7 percent).

Secondary school education in the U.S. is not differentiated by field of study, in contrast to France and Germany.

T. Bol, C. Ciocca, H. van de Werfhorst, and T. DiPrete School-Work (UvA and Linkages Columbia)

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Effect of Linkage on Individual-Level Wages

Within-country analysis (separately by gender): Regress: log of wages = f(age, age-squared, education level, and the local linkage score for the specific combination of educational level and field of study).

Between-country analysis: Stack country datasets.

Regress: log of wages = f(age, age-squared, gender, country fixed effects,2 fixed effects for the specific combination of educational level and field of study, and the difference in the local linkage score for the education-field category across two or three countries).

2

The country effect captures currency and price differences along with differences in the average level of real wages in the country.

Is Linkage Associated with Earnings?

In France and Germany, linkage strength is negatively related to gross monthly earnings at the secondary level.

An increase of .25 in local linkage (roughly the average difference in local linkage strength between France and Germany and about a standard deviation increase in France across fields at the secondary education level) is associated with a 0.5% decrease in earnings in Germany and a 0.8% decrease in earnings in France.

At the upper tertiary level, in contrast, stronger linkage is associated with about 1% higher earnings in the U.S. and 2% higher earnings in France.

But these results do not differentiate whether a worker is or is not in a linking occupation.

This matters.

T. Bol, C. Ciocca, H. van de Werfhorst, and T. DiPrete School-Work (UvA and Linkages Columbia)

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Between-Education Within-Country Analysis

France Germany US <=4A >=5B <=4A >=5B >=5B Local seg.

-0.053** 0.023** -0.060** -0.099** 0.0048 (-7.47) (4.65) (-11.70) (-10.95) (1.07) In linking occ.

0.0072 0.047** 0.044** -0.0031 0.0056 (1.54) (6.40) (10.35) (-0.23) (0.57) Link * localseg 0.083** 0.080** 0.13** 0.18** 0.064** (7.35) (10.92) (13.75) (10.12) (10.75) Observations 60774 41987 81782 41670 366301 R-squared 0.24 0.33 0.15 0.20 0.20 Note: Models include gender and age. t statistics in parentheses

Interpretation (between-field, within-country) Being educated in a strongly linking secondary-level educational field produces an expected negative outcome only if the worker himself is not in a closely-linked occupation.

At the mean linkage for ISCED level 3B in France (0.79), a worker in a closely linked occupation enjoys an earnings premium of 7.3%.

If he works in a field whose linkage strength is about one standard deviation (0.25) above the mean, the earnings advantage rises to 9.3%.

In Germany, the gap between being in a linked occupation vs an unlinked occupation is even greater.

At the local linkage mean, the gain for being in a linked occupation is 15%.

If educated in a educational field that has linkage strength about one French standard deviation (.25) above the mean, the advantage is 19%. At one German standard deviation (.4) above the mean, the advantage is 21%.

T. Bol, C. Ciocca, H. van de Werfhorst, and T. DiPrete School-Work (UvA and Linkages Columbia)

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Interpretation, continued

Also an advantage at tertiary level of being in a linking occupation: France: 15% advantage at mean local linkage (~1.3), grows to 17% when local linkage is mean + 1SD. Germany: 10% advantage at mean local linkage, grows to 12% at mean + 1SD. U.S.: 9% advantage at mean local linkage, grows to 11% at mean + 1SD.

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Within-Education, Between-Country Analysis (Males < 45yrs)

Fr-D 0.11** (8.93) 0.028** (6.52) 0.0041 (0.40) 0.32**

Fr-D, excl Tert 0.12** (6.03) 0.023** (4.29) -0.023 (-1.24) 0.32**

Fr-D, Tert 0.078** (4.94) 0.0092 (0.92) 0.036* (2.38) 0.29**

Fr_D_US, Tert Local seg.

0.12** (2.70) In linking occ.

0.034 (1.36) s Link * localseg 0.053** (3.19) Germany 0.30** US 0.43** R-squared 0.39 0.29 0.34 0.23 Note: Models include gender and age. t statistics in parentheses

Within Education Between-Country Analysis Not in linked occ.

Young men, FR-DE, high

.1

.2

.3

.4

.5

0 .05 .1 .15 .2

.2

.4

.6

.8

1

.2

.3

.4

.5

.2

.4

.6

.8

1

.3

.4

.5

.4

.6

.8

.3

.2

1

.2

Old women, FR-DE, high

.4

.5

.4

.6

.8

1

.4

.6

.8

1

Old women, FR-DE-US, high

.1 .2 .3 .4

-.05 0 .05 .1 .15

.2

1

0 .1 .2 .3 .4

.2

Old women, FR-DE, low

.1

.8

Young women, FR-DE-US, high

0 .05 .1 .15 .2

.2

.6

Old men, FR-DE-US, high

Young women, FR-DE, high

0 .02.04.06.08

Young women, FR-DE, low

.1

.4

0 .05 .1 .15 .2

-.05 0 .05 .1

.1

.2

Old men, FR-DE, high

.02.04.06.08.1.12

Old men, FR-DE, low

0 .01.02.03.04

Predicted effect on earnings

Young men, FR-DE-US, high

.02.04.06.08.1.12

.01.02.03.04.05.06

Young men, FR-DE, low

In linked occ.

.2

.4

.6

Local linkage

.8

1

.2

.4

.6

.8

1

Interpretation (within-education, between-country â&#x20AC;&#x201C; secondary level) Comparing France and Germany at the secondary level: An increase of 0.25 in linkage strength (0.3 is IQR) yields additional earnings of between 1 and 4% for workers who are not in a linking occupation.

At young ages, workers gain more from being in a field with stronger local linkage if they themselves are in a linking occupation; the young men in linking occupations have an earnings premium of 3.8% while young women have a premium of 6.3% for a 0.25 increase in linkage strength. which is larger than the 2.9% and 1.0% gains from a .25 increase in linkage strength for young men and women who are not themselves in a linking occupation.

Older workers, in contrast do not benefit as much if they are in one of the linking occupations.

Gains later in the career are often in other occupations that represent career advancement from the linking occupations themselves, e.g., to a managerial occupation.

(Now including managers as a covariate, men < 45 yrs)

Fr-D Fr-D, excl Tert Fr-D, Tert Fr_D_US, Tert Local seg.

0.116** 0.154** 0.490** 0.503** (2.70) (3.60) (13.57) (14.17) In linking occ.

0.034 0.101** -0.071* 0.024 (1.36) (3.99) (-2.57) (0.86) Link * localseg 0.053** 0.059** 0.104** 0.132** (3.19) (3.59) (5.84) (7.49) Germany 0.301** 0.321** 0.336** 0.367** US 0.431** 0.395** 0.089** 0.073** R-squared 0.23 0.25 0.15 0.18 Note: Models include gender, age and whether in a managerial occupation. t statistics in parentheses

Interpretation (within-education/between-country - tertiary level) The effect sizes depend on whether the U.S. is included or excluded, but in either case, the general pattern is similar (and the IQR is around .75 in either case).

Between France and Germany, a 0.25 increase in linkage implies a 2% increase in earnings for young men and women if they are not in a linking occupation, and a larger 3.7% and 7.2% increase respectively if they are in a linking occupation.

When the U.S. is included, a 0.25 increase in linkage implies a 2.9% increase in earnings for young men and a 6.9% increase for young women if they are not in a linking occupation, and a larger 7.6% and 11.1% increase respectively if they are in a linking occupation.

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The Effects of Linkage on Within-Education Wage Inequality

Local seg.

Germany US Age Age sq female Observations R-squared

Fr-D, excl Tert -0.078** (-12.56) 0.105** -0.014** 0.017** 0.043** 130659 0.01

Note: t-statistics in parentheses.

Fr-D-US, only Tert -0.038** (-5.01) 0.088** 0.294** -0.024** 0.036** -0.098** 445854 0.01

Interpretation, Within-Education Wage Inequality

Secondary-level: Mean residual-squared is 0.17.

A 0.25 increase in local linkage reduces expected squared residual by -.010 (6% of the mean).

Tertiary-level: Mean residual-squared is 0.47.

A 0.25 increase in local linkage reduces expected squared residual by -.020 (4% of the mean).

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Conclusions Occupations shape the wage distribution, and differently in these countries.

The strength of linkage matters.

A worker generally earns more with a school leaving credential if s/he is in a linking occupation ...with the gain being stronger when local linkage is stronger.

Within-education (i.e., educational level and field) inequality is lower when local linkage is stronger.

Within-country variation in the strength of linkage across educational outcomes therefore affects wage inequality.

Between-country variation in the strength of linkage across educational outcomes produces differences in wage inequality across countries.

T. Bol, C. Ciocca, H. van de Werfhorst, and T. DiPrete School-Work (UvA and Linkages Columbia)

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Extensions

These conclusions apply to the full-time work force.

Overall inequality is also a function of the distribution across part-time, full-time, and the unemployed and not-employed.

Linkage strength probably also plays a role in the probability of working full-time and the probability of being unemployed.

These are topics for next time.

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