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Economic Impact of Education: Micro and Macro Studies, Study notes of Development Economics

The theoretical and empirical impact of education on individuals and society, focusing on human capital theory and signalling theory. It presents micro studies' findings on the returns to schooling and addresses econometric problems such as reverse causality, omitted variable bias, and measurement error. Macro studies' problems, including reverse causality, omitted variable bias, and measurement error across countries, are also discussed.

Typology: Study notes

2017/2018

Uploaded on 10/16/2018

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Lecture 5: Education
Lecture
5:
Education
Readings:
Todaro, chapter 8
Roland, chapter 17
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Lecture 5: EducationLecture

5: Education

Readings: „

Todaro, chapter 8

„

Roland, chapter 17

Introduction „ Education for all = a key inclusive economic institution ‰ Levels the playing field ‰ People can develop ideas, start businesses „ A key source of creative destruction ‰ People can acquire political power „ Might be blocked by extractive political institutions (elite) „ Might explain the “educational gap” g p g p

Educational gap: secondary school

Today: 2 questions 1 Is education that important? 1

.^

Is education that important? ‰ The returns to education 2 If it is important then how to increase it?

If it is important, then how to increase it?

Theoretical impact of education „ Human capital theory „ Human capital theory ‰ Seems obvious that there are private returns toeducation ‰ Although it depends on the quality of education...

Signaling theory of education (Spence,1973) „ Schooling is a signal, not a way to acquire valuable skills „ Problem of information asymmetry between employer and jobcandidate: ‰ During the interview, the employer does not know the candidate’s productivity(only CV with age, gender, education , experience...) ‰ The employer hires the candidate (a bit of a lottery) ‰ The worker reveals its productivity ‰ At time t+1 the employer hires or not based on the same CV: statistical ‰ At time t+1, the employer hires or not based on the same CV: statisticaldiscrimination ( ≠ taste-based discrimination) ‰ For a candidate, certain characteristics cannot be changed, but education can be. ‰ Students choose to study or not if the costs to acquire this signal are less than thewage then earned. ‰ According to this theory, schooling is only a signal .

Empirical impact of education: microstudies „

Lots of micro studies (Krueger et al., 2001)

g

„

Estimate (for a bunch of individuals i): ‰

Log(Wage i^ )= a + b * School i^

  • c *Experience i^
  • d * Experience i 2

Results „ Log(Wage i^ )= a + b * School i^

  • c *Experience i^
  • d * Experience i 2 „ All studies find a b between 0.05, and 0.15, so: ‰ 1 more year of education brings between 5% and 15% moresalary y

Returns to schooling „

Psacharopoulos

„

Psacharopoulos

Returns to schooling „

Psacharopoulos

„

Psacharopoulos

Omitted variables bias

Education

Wage

Omitted Variable bias:Ability,...

Solutions? „ Control for other factors (but what is ability?) „ Control for other factors (but what is ability?) „ Use twins (to control for unobserved familycharacteristics)characteristics) ‰ But why did one study more than the other? „ Use randomized experiments „ Use randomized experiments... „ Use natural experiments: D fl (1998) h l t ti i I d i ‰ D uflo (1998): school construction in Indonesia

Building schools „

Indonesia: oil revenues: build 61,000 schools in 1973

‰ Schools built in priority where there are few schools to start with ‰ So 2 levels of program: High and Low

P i

h

l

t d

t

b t

d 12

ld

„

P

rimary schools: students between 7 and 12 years old

‰ Students aged 2 to 6 in 1974: full exposure ‰ Students aged 12 to 17 in 1974: no exposure ‰ Students aged 18 to 24 in 1974: no exposure

Results