Quantitative Economics of Education - uni-leipzig.de · Quantitative Economics of Education ... Central drawbacks of this method ... -fun-factor, bandwagon (business admin fad), political

1

IEW Institute for Empirical Research in Economics 1lt

Quantitative Economics of Education

Winter 20102011

Instructor Prof Suumlssmuth Time 1115 ndash 1245

Location SR 7 Day Wed

MSc Economics

2

QEE Prof Bernd Suumlssmuth IEW Winter 20102011 2lt

Outline Part I

Introduction and motivation

I Investment in Human Capital

1 Investment decision and life-cycle model Theory

2 Investment decision and life-cycle model Empirics

3 Views on education besides classical HC Theory I

4 Views on education besides classical HC Theory II

Midterm Exam

3


I2 Investment decision and life-cycle model Empirics

or how to validate implications from HC-Theory models

The classic approach OLS specification of HC income function

hypotheses (Mincer 1974)

4


Estimates for 3 different countries

obviously

ldquoMincer Equationrdquo

Source Johnes (1993)

5



Source Mincer (1974)

original AEPs from Mincerrsquos seminal book

6


How to calculate the upper turning point of the income function

Differentiate with respect to years worked

In the Johnesrsquo example above it lies between 105 and 225 years that is

the peak is reached clearly before retirement age


7


Ad hoc 2 practical remarks

- If X is not available (but S is) help yourself with X = age ndash S ndash 6

- Itrsquos all conditional estimates example university degrees

estimating returns makes only sense in case of completing

= so called Heckman-Critique (James J Heckman Nobel 2000)


8


I21 Age-earnings profiles and Mincer-Regressions

2 principal methods to calculate rates of return on education

(a) Algebraic method

(b) Mincer-Regression

Starting point internal rate of return (IRR)

Algebraic method

9


Objective Calculation of ROI for educational investment of level x

Period of education starts now and takes S years

(working life ends in T years)

x = 1 eg primary education (completed typ compulsory school)

x = 2 eg secondary education (completed secondary school)

x = 3 eg tertiary education (university degree)

K-12

Algebraic method

10


Definition

The IRR is that value r that fulfills the following equation

where

Yx = income for an x-level of education

C = costs of education

t = time index (year)

Algebraic method

11


Special case

cost of education = foregone earnings (exclusively)

Algebraic method

12


private ROEs exclusively consider individual costs of education

social ROEs imply costs for the society as a whole

(financing education through taxes)

typically

social ROE lt private ROE

Note We can sharply discriminate private from social ROEs

Algebraic method

13


Central drawbacks of this method

Data intense

Information on AEPs for all levels of education = required

Query-based AEPs for individuals and small groups = often erratic

Smoothing of such AEPs = (frequently) required

ldquoTypicalrdquo (private) ROE based on algebraic calculation 10

Quantitatively returns on physical capital

Algebraic method

14


2-tier approach

1 Construct AEPs for specific groups of the population

2 Compute IRR on the base of these AEPs

A rare example of the use of the algebraic methods =

the works by Giora Hanoch (Jo Human Resources 1967)

Her seminal paper is entitled

ldquoAn Economic Analysis of Earnings and Schoolingrdquo

Algebraic method

15


Earnings by age and years of schooling (Hanoch 1967)

Whites North Whites South

Algebraic method

16


w

Yt = annual income for t years of education

Ct = total cost of investment in t-th year of education

rt = return

Assumption

Mincer-Regressions

A simple way to develop a testable Mincerian function

17


Back-tracing to period 0 (1st non-compulsory year of schooling) gives

Applying natural logs (ln) and the standard approximation

we get

Mincer-Regressions

18


For an identical return over all years of education this implies

Considering the impact of experience on income we finally end up w

the legendary Mincerian specification

Mincer-Regressions

19


Interpretation of (semi-log- or log-lin-specification)

Increasing S by 1 yr increases ln(Y) by

NB

therefore if ln(Y) increases by this = an increase of Y by

Mincer-Regressions

20


A slightly more sophisticated version of a Mincerian income function

Mincer-Regressions

w S1 S2 and S3 denoting dummy (01) variables for which

S1 = 1 for a level of education of at least first grade

S2 = 1 for a level of education of at least a high school grade

S3 = 1 for a level of education of at least a college degree

21


auf

Example

An individual who completed high school but not college is characterized by

S1 = 1 S2 = 1 and S3 = 0

Let Nx = yrs of education to attain level of education x

the private ROE on

primary education then is given by r1 = bN1

secondary education then is given by r2 = cN2

college education then is r3 = dN3

Mincer-Regressions

22


Advantages Mincerian vs algebraic method

less data-intense

Completely based on individual data

(instead of groupedaggregated data)

Disadvantages

Primarily suited to compute private ROEs



Mincer-Regressions

23


We should keep 3 caveats in mindhellip

1 Education = (partially) a consumption good

- fun-factor bandwagon (business admin fad) political motivation

- eg Angrist and Krueger (JASA 1992)

run for universities during Vietnam War

9 increase in students enrolled for 1965-69

lsquoVietnam Era Draft Lotteryrsquo

1970-73 Prob(study) 5 higher for small norsquos

Mincer-Regressions

24


and alsohellip

2 incomplete labor markets wages may not reflect productivity

3 lsquoSignallingrsquo and lsquoScreeningrsquo Mincerian approach

Mincer-Regressions

Returns to Investment in Education in global perspective

Psacharopoulos and Patrinos (EE 2004)

25


ROEs w increasing level of education

ROEs w increasing level of development

private ROE gt social ROE

MincerndashRegressions

3 major styilized facts (international perspective)

26



27


Overall women benefit more from education (in terms of returns) but


28


Major problems of global comparative studies

Sample selection and stratification

1 Developing countries bias towards cities major companies etc

2 Civil servants soldiers etc sample etc

(wages market determined)

Methodology

questionable really same estimation strategy for all countries


29


Some further critical aspects

Control variables = problematic in MincerndashRegressions (eg occupation)

Functional form linear quadratic in parts linear log

Sheepskin effects (lsquomilestonesrsquo after 12 and 16 yrs)

Selection models

(labor market activity = endogenous decision)


30


Some sample findings (German Labor Force Survey 2004)

Experience-Income profiles (university male)


31



Experience-Income profiles (university female)


32



High school graduates wo further vocational training (control group)


33





34





35





2


Outline Part I

Introduction and motivation

I Investment in Human Capital

1 Investment decision and life-cycle model Theory

2 Investment decision and life-cycle model Empirics

3 Views on education besides classical HC Theory I

4 Views on education besides classical HC Theory II

Midterm Exam

3






4



obviously



5





6







7








8







Algebraic method

9








K-12

Algebraic method

10


Definition


where




Algebraic method

11


Special case


Algebraic method

12





typically



Algebraic method

13



Data intense






Algebraic method

14


2-tier approach







Algebraic method

15




Algebraic method

16


w



rt = return

Assumption

Mincer-Regressions


17




we get

Mincer-Regressions

18





Mincer-Regressions

19




NB


Mincer-Regressions

20



Mincer-Regressions





21


auf

Example


S1 = 1 S2 = 1 and S3 = 0


the private ROE on




Mincer-Regressions

22



less data-intense



Disadvantages




Mincer-Regressions

23










Mincer-Regressions

24


and alsohellip



Mincer-Regressions



25







26



27




28







Methodology



29






Selection models



30





31





32





33





34





35





3






4



obviously



5





6







7








8







Algebraic method

9








K-12

Algebraic method

10


Definition


where




Algebraic method

11


Special case


Algebraic method

12





typically



Algebraic method

13



Data intense






Algebraic method

14


2-tier approach







Algebraic method

15




Algebraic method

16


w



rt = return

Assumption

Mincer-Regressions


17




we get

Mincer-Regressions

18





Mincer-Regressions

19




NB


Mincer-Regressions

20



Mincer-Regressions





21


auf

Example


S1 = 1 S2 = 1 and S3 = 0


the private ROE on




Mincer-Regressions

22



less data-intense



Disadvantages




Mincer-Regressions

23










Mincer-Regressions

24


and alsohellip



Mincer-Regressions



25







26



27




28







Methodology



29






Selection models



30





31





32





33





34





35





4



obviously



5





6







7








8







Algebraic method

9








K-12

Algebraic method

10


Definition


where




Algebraic method

11


Special case


Algebraic method

12





typically



Algebraic method

13



Data intense






Algebraic method

14


2-tier approach







Algebraic method

15




Algebraic method

16


w



rt = return

Assumption

Mincer-Regressions


17




we get

Mincer-Regressions

18





Mincer-Regressions

19




NB


Mincer-Regressions

20



Mincer-Regressions





21


auf

Example


S1 = 1 S2 = 1 and S3 = 0


the private ROE on




Mincer-Regressions

22



less data-intense



Disadvantages




Mincer-Regressions

23










Mincer-Regressions

24


and alsohellip



Mincer-Regressions



25







26



27




28







Methodology



29






Selection models



30





31





32





33





34





35





5





6







7








8







Algebraic method

9








K-12

Algebraic method

10


Definition


where




Algebraic method

11


Special case


Algebraic method

12





typically



Algebraic method

13



Data intense






Algebraic method

14


2-tier approach







Algebraic method

15




Algebraic method

16


w



rt = return

Assumption

Mincer-Regressions


17




we get

Mincer-Regressions

18





Mincer-Regressions

19




NB


Mincer-Regressions

20



Mincer-Regressions





21


auf

Example


S1 = 1 S2 = 1 and S3 = 0


the private ROE on




Mincer-Regressions

22



less data-intense



Disadvantages




Mincer-Regressions

23










Mincer-Regressions

24


and alsohellip



Mincer-Regressions



25







26



27




28







Methodology



29






Selection models



30





31





32





33





34





35





6







7








8







Algebraic method

9








K-12

Algebraic method

10


Definition


where




Algebraic method

11


Special case


Algebraic method

12





typically



Algebraic method

13



Data intense






Algebraic method

14


2-tier approach







Algebraic method

15




Algebraic method

16


w



rt = return

Assumption

Mincer-Regressions


17




we get

Mincer-Regressions

18





Mincer-Regressions

19




NB


Mincer-Regressions

20



Mincer-Regressions





21


auf

Example


S1 = 1 S2 = 1 and S3 = 0


the private ROE on




Mincer-Regressions

22



less data-intense



Disadvantages




Mincer-Regressions

23










Mincer-Regressions

24


and alsohellip



Mincer-Regressions



25







26



27




28







Methodology



29






Selection models



30





31





32





33





34





35





7








8







Algebraic method

9








K-12

Algebraic method

10


Definition


where




Algebraic method

11


Special case


Algebraic method

12





typically



Algebraic method

13



Data intense






Algebraic method

14


2-tier approach







Algebraic method

15




Algebraic method

16


w



rt = return

Assumption

Mincer-Regressions


17




we get

Mincer-Regressions

18





Mincer-Regressions

19




NB


Mincer-Regressions

20



Mincer-Regressions





21


auf

Example


S1 = 1 S2 = 1 and S3 = 0


the private ROE on




Mincer-Regressions

22



less data-intense



Disadvantages




Mincer-Regressions

23










Mincer-Regressions

24


and alsohellip



Mincer-Regressions



25







26



27




28







Methodology



29






Selection models



30





31





32





33





34





35





8







Algebraic method

9








K-12

Algebraic method

10


Definition


where




Algebraic method

11


Special case


Algebraic method

12





typically



Algebraic method

13



Data intense






Algebraic method

14


2-tier approach







Algebraic method

15




Algebraic method

16


w



rt = return

Assumption

Mincer-Regressions


17




we get

Mincer-Regressions

18





Mincer-Regressions

19




NB


Mincer-Regressions

20



Mincer-Regressions





21


auf

Example


S1 = 1 S2 = 1 and S3 = 0


the private ROE on




Mincer-Regressions

22



less data-intense



Disadvantages




Mincer-Regressions

23










Mincer-Regressions

24


and alsohellip



Mincer-Regressions



25







26



27




28







Methodology



29






Selection models



30





31





32





33





34





35





9








K-12

Algebraic method

10


Definition


where




Algebraic method

11


Special case


Algebraic method

12





typically



Algebraic method

13



Data intense






Algebraic method

14


2-tier approach







Algebraic method

15




Algebraic method

16


w



rt = return

Assumption

Mincer-Regressions


17




we get

Mincer-Regressions

18





Mincer-Regressions

19




NB


Mincer-Regressions

20



Mincer-Regressions





21


auf

Example


S1 = 1 S2 = 1 and S3 = 0


the private ROE on




Mincer-Regressions

22



less data-intense



Disadvantages




Mincer-Regressions

23










Mincer-Regressions

24


and alsohellip



Mincer-Regressions



25







26



27




28







Methodology



29






Selection models



30





31





32





33





34





35





10


Definition


where




Algebraic method

11


Special case


Algebraic method

12





typically



Algebraic method

13



Data intense






Algebraic method

14


2-tier approach







Algebraic method

15




Algebraic method

16


w



rt = return

Assumption

Mincer-Regressions


17




we get

Mincer-Regressions

18





Mincer-Regressions

19




NB


Mincer-Regressions

20



Mincer-Regressions





21


auf

Example


S1 = 1 S2 = 1 and S3 = 0


the private ROE on




Mincer-Regressions

22



less data-intense



Disadvantages




Mincer-Regressions

23










Mincer-Regressions

24


and alsohellip



Mincer-Regressions



25







26



27




28







Methodology



29






Selection models



30





31





32





33





34





35





11


Special case


Algebraic method

12





typically



Algebraic method

13



Data intense






Algebraic method

14


2-tier approach







Algebraic method

15




Algebraic method

16


w



rt = return

Assumption

Mincer-Regressions


17




we get

Mincer-Regressions

18





Mincer-Regressions

19




NB


Mincer-Regressions

20



Mincer-Regressions





21


auf

Example


S1 = 1 S2 = 1 and S3 = 0


the private ROE on




Mincer-Regressions

22



less data-intense



Disadvantages




Mincer-Regressions

23










Mincer-Regressions

24


and alsohellip



Mincer-Regressions



25







26



27




28







Methodology



29






Selection models



30





31





32





33





34





35





12





typically



Algebraic method

13



Data intense






Algebraic method

14


2-tier approach







Algebraic method

15




Algebraic method

16


w



rt = return

Assumption

Mincer-Regressions


17




we get

Mincer-Regressions

18





Mincer-Regressions

19




NB


Mincer-Regressions

20



Mincer-Regressions





21


auf

Example


S1 = 1 S2 = 1 and S3 = 0


the private ROE on




Mincer-Regressions

22



less data-intense



Disadvantages




Mincer-Regressions

23










Mincer-Regressions

24


and alsohellip



Mincer-Regressions



25







26



27




28







Methodology



29






Selection models



30





31





32





33





34





35





13



Data intense






Algebraic method

14


2-tier approach







Algebraic method

15




Algebraic method

16


w



rt = return

Assumption

Mincer-Regressions


17




we get

Mincer-Regressions

18





Mincer-Regressions

19




NB


Mincer-Regressions

20



Mincer-Regressions





21


auf

Example


S1 = 1 S2 = 1 and S3 = 0


the private ROE on




Mincer-Regressions

22



less data-intense



Disadvantages




Mincer-Regressions

23










Mincer-Regressions

24


and alsohellip



Mincer-Regressions



25







26



27




28







Methodology



29






Selection models



30





31





32





33





34





35





14


2-tier approach







Algebraic method

15




Algebraic method

16


w



rt = return

Assumption

Mincer-Regressions


17




we get

Mincer-Regressions

18





Mincer-Regressions

19




NB


Mincer-Regressions

20



Mincer-Regressions





21


auf

Example


S1 = 1 S2 = 1 and S3 = 0


the private ROE on




Mincer-Regressions

22



less data-intense



Disadvantages




Mincer-Regressions

23










Mincer-Regressions

24


and alsohellip



Mincer-Regressions



25







26



27




28







Methodology



29






Selection models



30





31





32





33





34





35





15




Algebraic method

16


w



rt = return

Assumption

Mincer-Regressions


17




we get

Mincer-Regressions

18





Mincer-Regressions

19




NB


Mincer-Regressions

20



Mincer-Regressions





21


auf

Example


S1 = 1 S2 = 1 and S3 = 0


the private ROE on




Mincer-Regressions

22



less data-intense



Disadvantages




Mincer-Regressions

23










Mincer-Regressions

24


and alsohellip



Mincer-Regressions



25







26



27




28







Methodology



29






Selection models



30





31





32





33





34





35





16


w



rt = return

Assumption

Mincer-Regressions


17




we get

Mincer-Regressions

18





Mincer-Regressions

19




NB


Mincer-Regressions

20



Mincer-Regressions





21


auf

Example


S1 = 1 S2 = 1 and S3 = 0


the private ROE on




Mincer-Regressions

22



less data-intense



Disadvantages




Mincer-Regressions

23










Mincer-Regressions

24


and alsohellip



Mincer-Regressions



25







26



27




28







Methodology



29






Selection models



30





31





32





33





34





35





17




we get

Mincer-Regressions

18





Mincer-Regressions

19




NB


Mincer-Regressions

20



Mincer-Regressions





21


auf

Example


S1 = 1 S2 = 1 and S3 = 0


the private ROE on




Mincer-Regressions

22



less data-intense



Disadvantages




Mincer-Regressions

23










Mincer-Regressions

24


and alsohellip



Mincer-Regressions



25







26



27




28







Methodology



29






Selection models



30





31





32





33





34





35





18





Mincer-Regressions

19




NB


Mincer-Regressions

20



Mincer-Regressions





21


auf

Example


S1 = 1 S2 = 1 and S3 = 0


the private ROE on




Mincer-Regressions

22



less data-intense



Disadvantages




Mincer-Regressions

23










Mincer-Regressions

24


and alsohellip



Mincer-Regressions



25







26



27




28







Methodology



29






Selection models



30





31





32





33





34





35





19




NB


Mincer-Regressions

20



Mincer-Regressions





21


auf

Example


S1 = 1 S2 = 1 and S3 = 0


the private ROE on




Mincer-Regressions

22



less data-intense



Disadvantages




Mincer-Regressions

23










Mincer-Regressions

24


and alsohellip



Mincer-Regressions



25







26



27




28







Methodology



29






Selection models



30





31





32





33





34





35





20



Mincer-Regressions





21


auf

Example


S1 = 1 S2 = 1 and S3 = 0


the private ROE on




Mincer-Regressions

22



less data-intense



Disadvantages




Mincer-Regressions

23










Mincer-Regressions

24


and alsohellip



Mincer-Regressions



25







26



27




28







Methodology



29






Selection models



30





31





32





33





34





35





21


auf

Example


S1 = 1 S2 = 1 and S3 = 0


the private ROE on




Mincer-Regressions

22



less data-intense



Disadvantages




Mincer-Regressions

23










Mincer-Regressions

24


and alsohellip



Mincer-Regressions



25







26



27




28







Methodology



29






Selection models



30





31





32





33





34





35





22



less data-intense



Disadvantages




Mincer-Regressions

23










Mincer-Regressions

24


and alsohellip



Mincer-Regressions



25







26



27




28







Methodology



29






Selection models



30





31





32





33





34





35





23










Mincer-Regressions

24


and alsohellip



Mincer-Regressions



25







26



27




28







Methodology



29






Selection models



30





31





32





33





34





35





24


and alsohellip



Mincer-Regressions



25







26



27




28







Methodology



29






Selection models



30





31





32





33





34





35





25







26



27




28







Methodology



29






Selection models



30





31





32





33





34





35





26



27




28







Methodology



29






Selection models



30





31





32





33





34





35





27




28







Methodology



29






Selection models



30





31





32





33





34





35





28







Methodology



29






Selection models



30





31





32





33





34





35





29






Selection models



30





31





32





33





34





35





30





31





32





33





34





35





31





32





33





34





35





32





33





34





35





33





34





35





34





35





35





Documents

Quantitative Economics of Education - uni-leipzig.de · Quantitative Economics of Education ... Central drawbacks of this method ... -fun-factor, bandwagon (business admin fad), political