Return from schooling refers to the monetary or non-monetary benefits that individuals receive from investing in education, such as higher earnings, better job opportunities, improved health, and increased social status. The concept of return from schooling has been extensively studied by economists, and one of the most influential approaches in this field is Mincer's human capital theory.
Mincer's equation is a mathematical model that estimates the rate of return to education in terms of the percentage increase in earnings associated with an additional year of schooling. According to Mincer, the important variables that explain the return from schooling are the level and quality of education, work experience, and personal characteristics such as age, gender, and race.
The Mincer equation is expressed as follows:
ln(W) = α + β1Ed + β2Exp + β3Exp^2 + β4X + ε
Where W is the logarithm of earnings, Ed is the years of education, Exp is the years of work experience, Exp^2 is the squared value of years of experience, X represents personal characteristics such as age, gender, and race, and ε is the error term.
The variable Ed (years of education) is the most important variable in the Mincer equation, as it captures the effect of education on earnings. The coefficient β1 represents the percentage increase in earnings associated with an additional year of schooling, ceteris paribus (i.e., holding all other variables constant). This coefficient is often used as a measure of the return to education.
The variable Exp (years of work experience) is also an important variable in the Mincer equation, as it captures the effect of on-the-job training and learning by doing. Mincer argued that work experience enhances the productivity of workers, and thus increases their earnings. The coefficient β2 represents the percentage increase in earnings associated with an additional year of work experience, ceteris paribus. However, Mincer also included the squared term of Exp (β3*Exp^2) to account for the diminishing returns of experience on earnings.
In addition to the variables Mincer mentioned, other variables that could be important in explaining return from schooling include occupation, industry, geographic location, and family background. For example, the type of occupation or industry a person works in can significantly affect their earnings, even after controlling for years of education and work experience. Similarly, geographic location can influence earnings through differences in cost of living, labor market conditions, and industry structure. Family background can also affect earnings through factors such as inherited wealth, social connections, and cultural capital.
One limitation of using Mincer's equation to estimate return to schooling is that it assumes a linear relationship between education and earnings. However, this assumption may not hold in reality, as the marginal returns to education may vary across different levels of education, fields of study, and labor market contexts. Moreover, the Mincer equation does not account for unobserved factors that may affect both education and earnings, such as innate ability, personality traits, and motivation. Finally, the Mincer equation is based on cross-sectional data, which may not capture the full range of variation in the returns to education over time and across different cohorts of workers.