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Education & the labor market. Josep-Oriol Escardíbul Public Finance I Master in Economics (UB)

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Education & the labor market

Josep-Oriol Escardíbul

Public Finance I

Master in Economics (UB) - 2013

(2)

Index

1. Education, employment, and salaries

2. The returns to education

3. Critics to the rate of return to education

4. Rate of return: Empirical evidence

5. HRM, training & business results

(3)

1. Education & Employment (I)

USA: Unemployment rates individuals ages 25 and older. 2006

0 2 4 6 8 10 12 14

Bachelor's degree or higher Associate degree Some college, no degree High school graduate Not a high school graduate

Black White

(4)

1. Education & Employment (II)

100000 79400

61300 50900

40600 37100 31500 23400

0 20000 40000 60000 80000 100000

Professional degree Doctoral degree Master's degree Bachelor's degree Associate degree Some college, no degree High school graduate Not a high school graduate

USA: Median earnings and tax payments of full-time year-round workers ages

25 and older (2005)

(5)

1. Education & Employment (III): Spain

Rate of unemployment: > 16 years old

Rate of unemployment: > 25-29 years old

52,3

31,9

27,3

21,6

12,8

3,9 21,7

10,5 11,1

8,8 6,9

1,7 0,0

10,0 20,0 30,0 40,0 50,0 60,0

No studies Primary Lower secondaryUpper secondary Higher Phd

2011 2005

46,4 43,8

32,6

25,1

20,2 18,9

22,2

15,5

12,0 9,8 10,8

2,7 0,0

5,0 10,0 15,0 20,0 25,0 30,0 35,0 40,0 45,0 50,0

No studies Primary Lower

secondary

Upper secondary

Higher Phd

2011 2005

(6)

1. Education & Employment (IV): Spain

Employed. Net monthly income from main job

0,0 20,0 40,0 60,0 80,0 100,0

No studies Primary Lower secondary Vocational Upper secondary University

> 3000 euros 2101-3000 euros 1601-2100 euros 1201-1600 euros 1001-1200 euros 600-1000 euros Up to 600 euros

(7)

2. Rate of return (I): Mincer - Overtaking

• Overtaking means that individuals who join the workforce later because they decide to increase their educational level, or those joining at the same time opting for jobs with less pay but with a high degree of training, overtake those who entered the labor market in standard conditions (previous incorporation in jobs of higher starting salary but with less chance of promotion).

• Empirical analyses conducted by Mincer concluded that the

point of overtaking occurs approximately 7-9 years of

joining the labor market.

(8)

2. Rate of return (II): private & social

• Rates of return are typically estimated in two ways:

• Early studies used a discounted cash flow, accounting framework.

• Recently researchers have adopted an earnings function approach.

• The effects on employment, productivity and earnings can be expressed in terms of the rate of return on education and training. Rates of return are computed for various qualifications or for the length of time spent in education or on training courses. The rate of return expresses the value of an additional year of education (or the value of a particular qualification) in terms of the associated increase in earnings or income.

Private: the benefits and costs refer to the individual undertaking the investment.

Social: relates the social benefits and costs of an educational activity. Benefits include income tax or positive externalities.

Costs include public costs of education.

(9)

2. Rate of return (III): private & social

(10)

2. Rate of return (IV): formula

I n = Σ (1+r n ) -t

t=tn

T R n (t) - R n-1 (t)

CA

n

= Σ (1+r n ) -t

t=tn-1

tn C n (t) + R n-1 (t)

B n = Σ (1+r n ) -t

t=tn

T R n (t) - R n-1 (t) - Σ (1+r n ) -t

t=tn-1

tn C n (t) + R n-1 (t) = 0

- Present additional income of educational level “n” (In):

- Present additional costs of educational level “n” (CAn):

- Present additional net benefits of educational level (Bn):

R

n

= Remuneration for educational level “n”

R

n-1

= Remuneration for educational level “n-1”

C

n

= Cost of educational level “n”

r

n

= Rate of return

(11)

2. Rate of return (V): Mincer (wage equation)

- The model: W= f(S,Exp,Sen):

• W (wages)

• S (schooling)

• Exp (experience-general training)

• Sen (seniority-specific training)

2 i i 2 i

1 i

i α βS γ EX γ EX other variables ε

lnW = + + + + +

2 i 2 i i

1 3

1 2

i

i PRIM SEC UNIV EX EX

Y

ln = α + β + β + β + γ + γ + ε

-To avoid sample selection bias (Heckman, 1979):

- Probit estimates of employment status

- Inverse Mills ratio included in wage equation as

independent variable

(12)

3. Criticism (I)

• The ability debate: How much of the earnings differential (Rn-Rn-1) is really due to the extra education the individual has received)?

• ROR: Traditionally (rule of thumb) = 60%

• Regressions:

• Include variables related to capacity: tests results, exams results…

• Sample of twins

• Instrumental variables

• Education = f(IV): parents’ education/occupation, season of birth, proximity to school center, school reforms….

• W = f( , exp, exp2)

(13)

3. Criticism (II)

• Labor force participation/unemployment: one graduate from a given educational level might not be in the LF or might be unemployed.

• Real costs: some are more years than expected, some become drop outs…

• Positive externalities of education (and NMBE) are not included as benefits

• Social intervention is needed since financial markets are not perfect and not all individuals have the same risk aversion. Thus, some people would be excluded from education

• The way salaries are established (collective bargaining; social convention)

• Quality of education

• Overeducation

• Information is cross-section (time dimension of salaries)

(14)

4. Empirical evidence (I)

Rate of growth GDP:

I Y r = I H

Y * r H + I M

Y * r M I H

Y * r H = I p

Y * r p + I s

Y * r s + I h

Y * r h

Author Analysis Results

R. SOLOW Regression 87,5% of per capita GDP growth = technical progress (1957) USA, 1909-1949

T.W. SCHULTZ Rate of return Education is 16.5-20% of GNP (1968) USA, 1929-1957

Shultz (income growth accounting)

(15)

4. Empirical evidence (II)

(Dickson & Harmon, 2011)

• Estimates vary significantly depending on:

• Data set

• Assumption made & the estimation techniques

• Attempts at estimating a single rate of return may be not very

informative if returns to education differ by education level, or differ across populations (including by social strata)

• Economists fail to take into account the risk associated with education investment decisions (socially sub-optimal level of education investment)

• There are non-monetary benefits of education (it increases the social

rate of return).

(16)

4. Empirical evidence (III)

Author Sample Results

Mincer (1974) USA 7% Men (Non agricultural white men)

Psacharopoulos World RoR primary > secondary > Higher

(1985 & 1994) 1970s/1980s Private RoR > Social RoR

Psach. & Patrinos (2004) 1980s/1990s RoR Women> RoR Men

(overall 10%) RoR General education > RoR Vocational education RoR developing countries > RoR developed countries

Angrist & Krueger (1991) USA, Census 1970, 1980 OLS 6,3%; IV 8,1%

Butcher & Case (1993) USA, PSID 1985 OLS 5,9%; IV 6,6%

Kane & Rose (1993) USA, NLS Class of 1972 OLS 9,1%; IV 18,5%

Card (1993) USA, NLS young men OLS 7,3%; IV 13,2%; IV 9,7%

Cohn & Addison OECD countries 8,76%

(1998) 1980s/1990s RoR Women> RoR Men; RoR Higher > secondary

Ahenfelter et al Meta-analysis Average returns: 6-7%

(1999) 27 studies; 9 countries Average returns IV-twins: 9%

Arias & McMahon USA, Current Pop. Survey High school Men: from 12,5% to 9,5%

(2001) Cohorts 1967-75, 1980, 85, 90, 95 High school Women: from 9,8% to 11,3%

University Men: from 5,7% to 6,6%

University Women: from 10,3% to 7,9%

Trostel et al OECD 28 countries 5,0% Men; 6,0% Women (OLS)

(2002) & developing. 1985-1995 At least 1 percentual point more with IV (20%) Different instruments: ex: USA (8,4-10,6% men; 11,6-13,6% women)

Davereux & Fan (2011) UK ROR = 6% (Men & Women)

Henderson et al (2011) USA 8,4% (1950); 9,1% (60s); 8,3% (70s); 8% (80s); 10,7% (90s); 12,3% (2005) Data 1940-2005 Blacks > Whites (bigger gap than other studies)

(several cohorts) Natives > Immigrants (smaller gap than other studies) Younger workers > older workers

(17)

4. Empirical evidence (IV)

Author Year/country OLS / IV

Behrman et al. 1994 / USA 5,0% / 9,4%

Ashenfelter & Krueger 1994 / USA 8,4% / 12,9%

Miller et al 1995 / Australia 6,4% / 4,5%

Ashenfelter & Rouse 1998/ USA 10,2% / 8,8%

Rouse 1999/ USA 11,1% / 11,0%

Behrman & Rosenzweig 1999/ USA 11,8% / 10,4%

Literature Twins

(18)

4. Empirical evidence (V)

Harmon & Walker (2001) review:

• Basic specifications suggest a return for a year of schooling of between 7 and 9%. Social return: 6-12%.

• Women gain more from additional education than men.

• Those in the top part of the income distribution gain higher returns per year of education than those in the bottom part.

• Return on schooling vary significantly across countries, but are generally

positive and large.

(19)

4. Rates of return: Europe. Psacharopoulos

• Negative (although weak) inverse relationship between the returns to education and the country’s per capita income.

• The returns to higher education have been rising. Such trend means that the demand for higher skills outpaces the increased supply of graduates in the market place.

Country Year Private Social

Spain 2004 8,2 5,8

33 European countries 1993-2005 10,2 7,9

15 European comparable countries 2000s 12,3 7,9

Time trend Year Private

Spain 1981 7,5

1991 13,5

Earnings premium of tertiary/secondary Year Secondary Tertiary

Spain 2004 100 132

27 European countries 2002-2006 100 161

(20)

4. Rates of return: Spain

Author Year Sample Method Results

Alba & San Segundo 1995 Pilot Earnings Survey Mincerian eq. All (8,3% OLS; 9% corrected s.selection bias), Men (7,7%), Women (9,7%)

1990 Wage earners (8,1%); Self-employed (8,1%);

Vila & Mora 1996 Pilot Earnings Survey (1990) Mincerian eq. 5,30%

San Segundo 1996 Household Budget Survey Mincerian eq. All (9,3%), Men (8,4%), Women (11,4%) 1990-1991

Barceinas et al 2000 PHOGUE, 1994 Mincerian eq. 7,5% Men ; 8,3% Women

IV 9,0% Men

Wage Salary Survey, 1994 Mincerian eq. 8,2% Men ; 8,3% Women

IV 8,0% Men

Barceinas et al 2001 Household Budget S. 19990-91 Mincerian eq. Wage earners (7,0%); Self-employed (3,2%);

PHOGUE, 1994 Mincerian eq. Wage earners (8,2%); Self-employed (3,6%);

Arrazola y Hevia 2001 PHOGUE, 1994 Mincerian eq. 6,4% Men ; 7,4% Women

Workers full time Women corrected self-selection: 8,2%

16-65y IV 8,1% Men ; 14,2% Women

Gonzalo y Pons 2001 PHOGUE, 1994 Mincer (endog.) 6,4% Men

Workers full time IV 10,0% Men

Caparrós et al. 2001 PHOGUE, 1996 Mincerian eq. (endog.) 8,1% Men ; 9,5% Women PHOGUE, 1994 Mincerian eq. (endog.) 6,6% Men ; 9,1% Women

Arrazola et al 2003 PHOGUE, 1994 Mincer variation 8,0% Men

Workers full time (16-65y) Mincer variation IV 8,7% Men

García_Mainar & 2005 PHOGUE Self employed / Wage earners

Montuenga-Gómez 1994-2000 Mincer 1,3% / 1,3%

IV 4,9% / 8,8%

Arrazola & Hevia 2008 PHOGUE, 2000 Mincer variation 5,8% / 8,1%

Workers full time Mincer (endog.) 9,8% / 10,9%

(21)

4. Rates of return: Spain

Author Year Sample Method Results

Oliver et al. 1998 Household Burdget Survey Primary ROR: Private (14,2%); Social (12,5%). Mincer: 11,2%

1990-1991 Secondary ROR: Private (15,9%); Social (14,1%). Mincer: 9,7%

Higher ROR: Private (14,2%); Social (12,2%). Mincer: 11,0%

Vila & Mora 1998 Family Expenditure Survey Mincerian eq. Men / Women/Total

Primary 4,1%/ 6,6%/ 4,2%

1990-991 Secondary 6,1%/ 6,2%/ 6,0%

Vocational T. 5,1%/ 3,7%/ 4,8%

Higher (diplomatura) 7,6%/ 8,2%/ 7,3%

Higher (licenciatura) 8,5%/ 11,0%/ 9,3%

Lassibille & Navarro 1998 Household Burdget Survey Mincerian eq. Total

1990-1991 Primary 7,4%

Upper secondary 8,5%

Higher 15,7%

Blanco y Pons 2000 Class Survey, 1991 Ability & self-selection Men / Women

Employees 16-65y Primary 9,2% / 6,3%

EGB 11,5% / 5,6%

Secondary 23,1% / 20,1%

Upper secondary 53,4% / 47,3%

University 68,4% / 46,4%

Barceinas et al 2000 PHOGUE, 1994 Primary/ no educ. Mincer (2,4%); self-selection bias (14,5%) Workers full time Lowe sec./Primary Mincer (3,0%); self-selection bias (6,9%)

Upper sec/lower sec. Mincer (12,0%); self-selection bias (13,8%) University/upper sec. Mincer (10,6%); self-selection bias (13,0%)

Arrazola et al. 2003 PHOGUE Mincer variation Private / Social

1993-1994 Lower secondary 10,3% / 7,9%

Upper secondary 9,7% / 7,2%

University 8,9% / 6,7%

Arrazola & Hevia 2008 PHOGUE Mincer (endog.) Men / Women

2000 Primary 10,4% / 20,7%

Base = no studies Lower secondary 20,4% / 34,0%

Vocat. Lower sec. 81,4% / 60,3%

Vocat. Upper sec. 46,2% / 87,4%

Upper secondary 54,8% / 75,9%

University (diplomatura) 96,6% / 168,0%

University (licenciatura) 116,8% / 205,0%

Levels of education

(22)

4. Rates of return: adjustments

• Adjustment of measurement error in the educational variable:

raises the rate of return (10%)

• Adjustment of quality of education: raises the rate of return (30%)

• Adjustment of ability: reduces the rate of return (25-30%)

• Adjustment for time trend: 10% in 1980s (Carnoy, 1997)

• Adjustment for IV: raises the rate of return (30%). Although IV

estimates may not be good enough and different instruments

provide different estimates of the RoR

(23)

5. HRM, training & business results

Training and profit

Bassi et al., (2002): positive relationship between investment in training and the total returns to shareholders (US).

• Molina & Ortega (2003): A high incidence of training positive effect on company profits, through employee satisfaction and client loyalty (US).

Myers et al. (2004): company profit is related to employee’s education as well as individual’s skills.

• Chu (2005): if workers receive additional external training profits increase by 2% in Shanghai (China).

Training and productivity

• Tan and Batra (1995): training increases productivity (developing countr.).

• Black and Lynch (1996): 10% increase in training 8.5% in productivity.

• Bartel (2000): training outside increases productivity (US).

• Cooke (2001): trained employees are more efficient (UK).

Training and competitive advantage

• Lynch (1998): training allows the adoption of advanced technology (US).

Ottersten et al., (1999): 1% raise in training increased quality of work by 0.1%.

• Papalexandris & Nikandrou (2000): Training is crucial for the acceptance and management of change, which itself leads to the improvements in client services that well-organized companies achieve (Greece).

• Johannessen and Olsen (2003): training allows to incorporate knowledge.

References

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