Empirical Papers/Data:
Labour Market Trends (OECD):
-Average returns to education across OECD is $250k for men, $227k for women.
-Approximately 60% of individuals invest in a higher education degree.
-Educational attainment significantly reduces unemployment – 6% for 18-24 year olds, but
less amongst 25-29 year olds.
The Returns to Education:
-Private returns to education:
-Grossman (2006): greater education = increased life satisfaction and lower probability of
divorce.
-Oreopoulos & Salvanes (2011): school may affect individual preferences, so as to make
individuals more patient, goal oriented and less likely to take risks.
-Social returns to education:
-Helliwell & Putnam (2007): education one of most important factors in social engagement.
-Lochner & Moretti (2004): education has negative impact on criminality; this is estimated to
be 40-60% of private returns to education.
-Machin et al (2011): greater length of compulsory education has significant benefits on
those with the lowest levels of attainment.
-Currie & Moretti (2003) – positive spillover effects of education on children.
-Rauch (1993): knowledge externalities increase RtE by 3-5% points in social returns.
Returns to Education – Estimation:
-Mincer estimates the IRR, , and finds linear relationship relating to years of schooling. Doe not
include experience – we underestimate the effect of schooling on wages when excluding experience.
BUT estimator is ability biased and selection biased – IV approach required where IV must be
relevant and meet exclusion requirement.
-Angruist & Krueger (1991) use birth date and compulsory schooling laws, running a 2SLS –
find those born earlier in calendar year have shoer durations of schooling. They find that OLS
slightly over-estimates the impact of education on wages.
-Lochner & Monge-Naranjo (2011): use US AFQT scores to understand link between college
attendance and borrowing patterns.
-Find positive ability-schooling relationship for students from low-income families.
-Note the borrowing constraint that stops individuals going to college but the scale of the
investment.
-College attendance increasing with AQFT score – positive ability-schooling effect is equally
strong for youth from high/low-income families.
, -Oreopoulos & Salvanes (2011): look at siblings and twins in Norway in 1920s to remove any
heterogeneity.
-Positive correlation uncovered b/w duration of studies + future earnings. On average,
siblings with additional year schooling earn 5.2% more than less educated.
-Experience and skills generate further nonpecuniary returns.
-Card (1995) uses college proximity as exogenous determinant of schooling to avoid ability bias.
-Men growing up in labour markets w/ 4-year college (approx. 70%) have significantly higher
education levels and earnings that others, even after controls implemented.
-Effect greatest for those with low predicted schooling levels – hence local college lowers
costs/raises perceived benefits of education.
-Suggests downward bias in OLS estimates of returns to education by 25-60%; 10-15% of this
is however potential measurement error in schooling.
-Although instrument is very sensitive and he runs too many regressions = overcomplicated.
The Unitary Model:
-Adopts income pooling hypothesis – distribution of income within a household does not matter.
-Rejected by most papers though, with exception of couples with pre-school children.
-Fortin & Lacroix (1197): pre-school children act as a public good in household, thus ensuring
pooling restriction is not violated.
The Collective Model:
-Now household choices arise from maximising subject to individual preferences.
-Chiappori (1992): show that efficient allocations are also the solutions of the individual
problems where each person is endowed with specific amount.
-Lundberg et al (1997): this fact (violation of pooling) helps when examining the effect of
public policies. They test this by giving non-wage income to females only.
-Find strong evidence that husband shifts expenditure to things like women and child
clothing as opposed to male clothing – by giving income allowance to women, this generates
different kinds of expenditure (thus income pooling does not hold).
Labour Supply – Empirical Aspects:
-Blundell et al (1992): investigate the form of labour supply – differentiate between those with non-
earned income above and below median.
-Find individual supply takes hump-shaped curve, thus leisure is normal good. Labour supply
greater for those above median wage than those below (incentives). Find potential local
maximum in labour supply, with demand for leisure then increasing in R.
-Bloom et al (2009): effect of fertility on female LFP – by removing legal restrictions on abortions etc,
fertility falls significantly.
-Birth reduces labour supply by two years; availability of childcare can make this greater.
Labour Market Trends (OECD):
-Average returns to education across OECD is $250k for men, $227k for women.
-Approximately 60% of individuals invest in a higher education degree.
-Educational attainment significantly reduces unemployment – 6% for 18-24 year olds, but
less amongst 25-29 year olds.
The Returns to Education:
-Private returns to education:
-Grossman (2006): greater education = increased life satisfaction and lower probability of
divorce.
-Oreopoulos & Salvanes (2011): school may affect individual preferences, so as to make
individuals more patient, goal oriented and less likely to take risks.
-Social returns to education:
-Helliwell & Putnam (2007): education one of most important factors in social engagement.
-Lochner & Moretti (2004): education has negative impact on criminality; this is estimated to
be 40-60% of private returns to education.
-Machin et al (2011): greater length of compulsory education has significant benefits on
those with the lowest levels of attainment.
-Currie & Moretti (2003) – positive spillover effects of education on children.
-Rauch (1993): knowledge externalities increase RtE by 3-5% points in social returns.
Returns to Education – Estimation:
-Mincer estimates the IRR, , and finds linear relationship relating to years of schooling. Doe not
include experience – we underestimate the effect of schooling on wages when excluding experience.
BUT estimator is ability biased and selection biased – IV approach required where IV must be
relevant and meet exclusion requirement.
-Angruist & Krueger (1991) use birth date and compulsory schooling laws, running a 2SLS –
find those born earlier in calendar year have shoer durations of schooling. They find that OLS
slightly over-estimates the impact of education on wages.
-Lochner & Monge-Naranjo (2011): use US AFQT scores to understand link between college
attendance and borrowing patterns.
-Find positive ability-schooling relationship for students from low-income families.
-Note the borrowing constraint that stops individuals going to college but the scale of the
investment.
-College attendance increasing with AQFT score – positive ability-schooling effect is equally
strong for youth from high/low-income families.
, -Oreopoulos & Salvanes (2011): look at siblings and twins in Norway in 1920s to remove any
heterogeneity.
-Positive correlation uncovered b/w duration of studies + future earnings. On average,
siblings with additional year schooling earn 5.2% more than less educated.
-Experience and skills generate further nonpecuniary returns.
-Card (1995) uses college proximity as exogenous determinant of schooling to avoid ability bias.
-Men growing up in labour markets w/ 4-year college (approx. 70%) have significantly higher
education levels and earnings that others, even after controls implemented.
-Effect greatest for those with low predicted schooling levels – hence local college lowers
costs/raises perceived benefits of education.
-Suggests downward bias in OLS estimates of returns to education by 25-60%; 10-15% of this
is however potential measurement error in schooling.
-Although instrument is very sensitive and he runs too many regressions = overcomplicated.
The Unitary Model:
-Adopts income pooling hypothesis – distribution of income within a household does not matter.
-Rejected by most papers though, with exception of couples with pre-school children.
-Fortin & Lacroix (1197): pre-school children act as a public good in household, thus ensuring
pooling restriction is not violated.
The Collective Model:
-Now household choices arise from maximising subject to individual preferences.
-Chiappori (1992): show that efficient allocations are also the solutions of the individual
problems where each person is endowed with specific amount.
-Lundberg et al (1997): this fact (violation of pooling) helps when examining the effect of
public policies. They test this by giving non-wage income to females only.
-Find strong evidence that husband shifts expenditure to things like women and child
clothing as opposed to male clothing – by giving income allowance to women, this generates
different kinds of expenditure (thus income pooling does not hold).
Labour Supply – Empirical Aspects:
-Blundell et al (1992): investigate the form of labour supply – differentiate between those with non-
earned income above and below median.
-Find individual supply takes hump-shaped curve, thus leisure is normal good. Labour supply
greater for those above median wage than those below (incentives). Find potential local
maximum in labour supply, with demand for leisure then increasing in R.
-Bloom et al (2009): effect of fertility on female LFP – by removing legal restrictions on abortions etc,
fertility falls significantly.
-Birth reduces labour supply by two years; availability of childcare can make this greater.
