Education Flashcards
What are some of the reasons that parents may decide to send their children to school?
a. Education can increase future earnings potential
b. Education can lead to better health outcomes
c. Education provides a better overall understanding of the world
Which of the following is meant by the “sheepskin” effect in the context of education?
“Sheepskin” refers to the pure signaling effect of education, where aside from any knowledge or skills learned, having completed a certain level of education enables someone to earn a higher wage.
In which ways might additional education benefit girls?
- Improving how much they can earn in the labor market
- Improving standing in the marriage market
- Increasing future bargaining power within the household
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What are some possible spillovers or externalities from education?
- Positive: Having more educated people in an area might lead to better labor market opportunities
- Positive: Having more educated people in an area might lead to more political activism and pressure on the government to develop more effective institutions
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True or false: Many people in the developing world earn income from agriculture. For these people, the benefits of a traditional classroom education are almost surely near zero.
False.
The graph above shows years of schooling on the x-axis and log income on the y-axis. Call the slope of this line β. How do we interpret the slope of this log-linear relationship?
The slope at any given point represents the proportional increase in income associated with a 1-year increase in schooling.
The graph above is of the form ln(y)=Bx + ε (where ε represents the error term). The mathematical interpretation of the slope is it represents the proportional change in income associated with a one-year increase in schooling attainment. To see this, differentiate the equation with respect to x (1/y)(dy/dx) = B
Discretizing the derivatives, you can see that when dx=1, B = (delta y)/y
As shown in the same graph above, each additional year of schooling:
Is correlated with higher income in the future. The graph shows a clear positive association between years of schooling and future earnings. However, we cannot say that this relationship is causal, as in A, since there could be any number of other factors that would explain why children who are more likely to stay in school longer are also more likely to have higher income in the future. In other words, when we compare outcomes for someone who has 4 years of schooling to someone who has 10 years of schooling, we could be looking at very different people. Since there is a clear relationship between the two, the most we can say just from observing this relationship is that years of schooling are positively correlated with greater future income, as in B.
What other factors could be driving the observed relationship between additional years of schooling and earning potential?
- Children who are more motivated or driven stay in school longer, and these same children are the ones that would earn more in the future anyways.
- Children with rich parents can afford to stay in school longer, and these are the same children that would earn more in the future anyways
- Smart children stay in school longer, and these are the same children that would earn more in the future anyways
Using the table provided above, how does the probability of ever enrolling in senior high school differ between boys in the treatment group (assigned to scholarship) and boys in the control group (not assigned to scholarship)?
57% of the control group enrolls, 93% of the treatment group enrolls, and the difference is statistically significant.
Let Yi denote cognitive test scores, Ai denote years of schooling, and Zi denote assignment to the scholarship. Use the following expressions to answer the next questions.
The effect of assignment to the scholarship on school participation, which can be interpreted as a causal relationship.
Equation (2) describes which of the following?
The effect of assignment to the scholarship on cognitive test scores, which can be interpreted as a causal relationship.
Equation (3) describes which of the following?
The instrumental variables estimate of the effect of years of schooling on cognitive test scores. Equation (3) describes the instrumental variables estimate of the effect of years of schooling on cognitive test scores, as in B. This is what is known as the “Wald Estimate,” which is the ratio of the effect of the scholarship program on cognitive test scores to the effect of the scholarship program on school attendance (or the reduced form estimate divided by the first stage estimate).
Which of the following assumptions is needed for beta to be a valid estimate of the effect of years of schooling on cognitive test scores?
- Random assignment to the scholarship program is correlated with school attendance decisions
- Random assignment to the scholarship program impacts cognitive test scores ONLY through its impact on years of schooling
Which of the following would make assignment to the scholarship an invalid instrument?
- The scholarship was not randomly assigned
- The scholarship came along with a study guide only available to scholarship winners, and this study guide gave them an advantage in the test compared to non-scholarship winning classmates
According to the results presented in class, what is the causal effect of assignment to the scholarship group on ever enrolled in secondary high school for males?
36 percentage points.