According to human capital theory, a person’s earning is linked to her level of education – there is a relationship between workers income and years of education. Using data from the Labour Force Survey, a researcher found the following regression results for earnings on intercept, years of education, experience, and experience squared: Earnings = 5.24 + 0.035 educ + 0.165 exper – 0.003 exper2 (2.45) (0.012) (0.031) (0.001) Construct a 95% confidence interval for the effect of years of education on earnings ? 2. Consider an individual with 8 years of experience. What would you expect to be the return to two (2) additional years of experience (the effect on earnings)?
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
According to human capital theory, a person’s earning is linked to her level of education – there is a relationship between workers income and years of education. Using data from the Labour Force Survey, a researcher found the following regression results for earnings on intercept, years of education, experience, and experience squared:
Earnings = 5.24 + 0.035 educ + 0.165 exper – 0.003 exper2
(2.45) (0.012) (0.031) (0.001)
- Construct a 95% confidence interval for the effect of years of education on earnings ?
2. Consider an individual with 8 years of experience. What would you expect to be the return to two (2) additional years of experience (the effect on earnings)?
3. According to economic theory, individuals have different abilities. Taking this into consideration, the correct specification of the regression
log(earnings) = β0 + β1 educ + β2 exper + β3 exper2 + β4 ability + ε
4.In the above regression, what is your expectation of the sign of the ability coefficient β4? Explain
5.What do you think is the sign of the
6. Estimating the regression function with ability included, would the estimated value of β1 be greater or less than its value in the regression without ability? Explain
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