Lesson 7: Education I Flashcards
Explain what the mechanism behind education and development is.
- Macro-perspective: often modelled as contributor to economic growth
- Micro-perspective: increases productivity & income, signal of ability, intrinsic values (consumption good)
- Returns are not only private: productivity spillovers, better functioning democracy, improves health (including of children), lowers fertility
Explain the intuition behind The human side of structural transformation by Porzio et al. (2022)
- half of global decline in agricultural employment was driven by new cohorts entering the labor market -> interpretation as human capital
- human capital growth led to a sharp decline in the agricultural labor supply (40% of agricultural employment)
- effect of shocks (policy reforms) on more educated labor (increase) and decline in agricultural employment
Describe the global status around SDG 4 (Education).
- tremendous progress since 1960, but large setbacks due to Covid
- most out-of-school children live in SSA or South Asia
- world’s poorest countries have the lowest completion rates (SSA)
- there are large disparities in quality of schooling (average learning outcome vs GDP per capita)
Explain a simple model of parental investments in education.
Education as investment decision on part of the parents. Determinants: price of schooling, returns to cognitive skills in labor market, potential home production, parents’ discount rates, transfer from children to parents in adulthood, child’s learning efficiency, quality of schooling
Model
* parents make schooling decisions for their child
* parents’ utility is a function of schooling (S) and the child’s income (y)
U(y,S) = m ln (y) - h(S)
ln (y) = a + bS
h’(S) = r + ΦS
Optimal schooling level
S° = (mb - r)/Φ
Interpretation:
r: constant added to cost of schooling
Φ: multiple added to cost of schooling
m: parental share
b: returns to education -> imperfect information
What shapes the returns to education b?
- demand for different types of skills in the labor market
- barriers to accessing high-return jobs
- length of time over which people are expected to reap the benefits of their education
- effectiveness of schooling in improving cognitive and non-cognitive skills
- health & nutrition
- peer effects
Explain the findings on returns to female education in the paper by Jayachandran et al.
examination of a sudden drop in maternal mortality in Sri Lanka -> increase in life expectancy for girls -> returns to schooling increase -> years of education increase
Explain how the perceived returns to schooling interact with the demand for schooling in Jensen.
- perceived returns to secondary schooling are extremely low
- after giving more information about returns to schooling, higher years of school completion
Explain the motivation and research question behind Singh (2020) on learning outcomes.
**Motivation: **
* quality of human capital crucial for economic development
* quality of schooling lags behind in many countries
* cross-country gaps are large
**Research Questions: **
* How do gaps evolve in early schooling?
* How much does schooling productivity explain these gaps?
Explain the setup in Singh (2020) on quality of schooling.
- Countries: Ethiopia, India, Peru, Vietnam
- Data: child-level panel data at age 5 and 8 (Young Lives Study)
- Compare identical tests of achievement across countries
- Causally identify differential productivity of schooling: value-added models and RDD estimates based on enrolment guidelines and date of birth (only in Peru & Vietnam)
What are the results in Singh (2020) on quality of schooling?
**Summary: **
* gaps emerge early and widen rapidly
* by age 8: approx. 2 SD gap with Ethiopia, 1 SD with India
* Vietnamese school year 0.3SD more productive
* equalizing to Vietnam explains most cross-country haps
Details
* gaps in test score distribution exist for both age groups, but widen quite a lot (highest score for ethiopia at 8 is lowest score in vietnam)
* RDD evidence: an additional year of schooling in Vietnam helps a lor more than in Peru (larger jump)
* value added and RDD-estimates align closely
* implies that productivity & not just enrolment drives the gaps
Give a quick overview of the Young Lives Study as used in Singh (2020)
- 2000 children/ country born 2001-02
- Ages: 5yo in 2006, 8yo in 2009
- Use data from 2006 & 2009 on quantitative proficiency: 1) pre-school level quantitative skills test for 5 year olds, 2) mathematical tests for 8 year olds
- tests are comparable across countries within each age group
Explain the RDD used in Singh (2020).
- school entry cut-offs: July 31st in Peru, Dec 31 in Vietnam
- creates discontinuity in grades completed at age 8
- compares children just above/ below school entry age
-> tries different functional forms
-> runs a balance test
-> checks for manipulation
What are identifying assumption for RDD?
- homogeneity around the cut-off (without the cutoff you should see comparable trends)
- covariate balance (balance on observables)
Why is Vietnam more productive in terms of education?
- not explained by more spending - Peru spends more per student
- Vietnam: more after-schooling tuition, higher teacher accountability
- fewer problems with absenteeism, stronger classroom practices
What are the policy implications of Singh (2020) on productivity of education.
- expanding access is insufficient
- need to improve effectivesness of each school year
- early divergence matters - interventions should begin early
- What specific reforms drive productivity?
What policy interventions work to improve learning?
Overview
* pedagocial interventions»_space; input-based approaches
* most effective: targeting instruction to student level, improving teaching practices, teacher incentives, tracking
* inputs generally ineffective on their own
Interventions that work:
* Pedagogy-focussed: teaching at the Right Level, mindspark (adaptive, rech-aided learning, especially effective for weaker students)
* incentives and accountability: teacher attendance incentives -> lower absenteeism, better outcomes, performance pay -> higher rest scores than input grants
**Interventions with no impact: **
* Inputs: textbooks or flipcharts
* School Quality Assessment program
Explain the latest evidence from Tanzania on complementaries to improve schooling productivity (Mbiti, 2016).
- RCT from Tanzania
- School grants alone had no effect
- Grants + performance-based teacher incentives led to large gains in test scores
- effects of both treatment together was significantly greater than the sum of parts
What are the three most effective and cost-effective approaches to improve schooling quality? (Angrist et al. 2024)
- targeted information campaigns on benefits, cost and quality
- interventions to target teaching instructions b learning level rather than grade
- improved pedagogy in from of strucutred lesson plany with linked student materials, teacher professional development & monitoring
What are the key take-aways from the lecture on schooling productivity?
- expanding access to schooling is not enough - improving learning within each school year is key
- early gaps in learning emerge and widen quickly, highlighting the importance of early interventions
- interventions targeting pedagogy or accountability are consistently more effective than input-based solutions
