(a) Let's say we are interested in the effect of education on wage. wage = a + Beduc; + u , where iis individual, wage, is wage of i, educ, is the years of education of i. u, is an error term. It is often challenging to study the effect of education on wages. Discuss any potential issues estimating the model. (b) to solve the potential issue, let's think about the instrumental variables method. State two condi- tions to be a valid instument and briefly explain. (e) To test one of the conditions, let's assume you estimate the following regression model:
(a) Let's say we are interested in the effect of education on wage. wage = a + Beduc; + u , where iis individual, wage, is wage of i, educ, is the years of education of i. u, is an error term. It is often challenging to study the effect of education on wages. Discuss any potential issues estimating the model. (b) to solve the potential issue, let's think about the instrumental variables method. State two condi- tions to be a valid instument and briefly explain. (e) To test one of the conditions, let's assume you estimate the following regression model:
MATLAB: An Introduction with Applications
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Author:Amos Gilat
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Transcribed Image Text:4. Wage and Education
(a) Let's say we are interested in the effect of education on wage.
wage; = a + Beduc; + u¡
, where i is individual, wage, is wage of i, educ, is the years of education of i. u, is an error term.
It is often chanllenging to study the effect of education on wages. Discuss any potential issues
estimating the model.
(b) To solve the potential issue, let's think about the instrumental variables method. State two condi-
tions to be a valid instument and briefly explain.
(c) To test one of the conditions, let's assume you estimate the following regression model:
educ; = y +8feduc; + vi
where it is individual, educ, is the years of education of i. feduc, is the i's father's education
level, v, is an error term. Table 2 shows the result of the regression analysis:
Table 2: Regression results of equation (4)
OLS estimates
Father's education
F-stat
R²
0.29***
(0.02)
164.72
0.18
Notes: Number in parenthesis is standard error. *** p<0.01, ** p<0.05, *: p<0.1
Discuss why father's education is valid or invalid based on the numbers in the table.
(d) Table 3 shows the regression results when using simple OLS estimation and instrumental variables
method:
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