ECON 328
国外经济作业代写 Assignment 6: IV estimation Complete this Assignment using Rmarkdown to produce a Word document (or PDF if you are a LaTeX user).
Assignment 6: IV estimation
Complete this Assignment using Rmarkdown to produce a Word document (or PDF if you are a LaTeX user). Imagine this markdown document is going to be presented to a committee that includes members who are not that familiar with R or statistics generally, so be sure all the fifigures are visually appealing and the axes are labeled in a way that makes them easy to understand. In this assignment we will be estimating a human capital model to explain variations in earnings using data drawn from the US National Longitudinal Survey of Young Men which begain in 1966 and continued with a series of follow-up surveys. These data, which are in a fifile called “Assign6data.csv” in the data folder, are based on the data from the original survey in 1966 and the follow-up in 1976.
The defifinitions of the relevant variables (you can ignore the other variables) are 国外经济作业代写
- nearcollge2: indicator for whether a subject grew up near a two-year college
- nearcollege4: indicator for whether a subject grew up near a four-year college
- education: subject’s years of education
- age: subject’s age at the time of the survey in 1976
- fatheduc: subject’s father’s years of education
- motheduc: subject’s mother’s years of education
- parents14: indicator for whether subject lived with both mother and father at age 14
- south66: indicator for whether subject lived in South in 1966
- ethnicity: indicator for whether subject’s race is African-American 国外经济作业代写
- smsa66: indicator for whether subject lived in SMSA (a geographical region with a relatively high population density at its core and close economic ties throughout the area) in 1966.
- south: indicator for whether subject lived in the South in 1976
- wage: subject’s wage in cents per hour in 1976
- enrolled: indicator for whether subject is enrolled in college in 1976
- kww: subject’s score on the Knowledge of the World of Work (KWW) test in 1966
- iq: IQ-type test score collected from the high school of the subject.
- married: indicator for whether the subject was married in 1976.
- librarycard14: indicator for whether subject had library card at age 14.
- experience: subject’s years of labor force experience in 1976
1. 国外经济作业代写
Plot a histogram of wage, and a second histogram of log(wage).
2.
Plot a scattergram of log(wages) and education with log(wage) on the vertical axis, identifying the different points by ethnicity, with a smoothing line (method=lm) for each ethnicity.
3. 国外经济作业代写
Plot a scattergram of log(wage) and education with log(wage) on the vertical axis, identifying the different points by south66, with a smoothing line (method=lm) for each value of south66 (yes and no).
4.
Run a standard wage equation model using OLS with the log of wage as dependent variable and experience, experience squared, education, smsa66, south66, and ethnicity as independent variables. You may add other variables if you think they improve the model. Print the output.
5. 国外经济作业代写
Use the ivreg command in the AER package to run the same model as the OLS you just performed, but correcting for the endogenaity of education. Print the output.
6.
Calculate the standard diagnostics for the 2SLS.
7. 国外经济作业代写
Finally, correct the 2SLS standard errors for heteroscedasticity, using the White approach, and print the new coeffificient matrix.
8.
You now have 2 histograms, two scattergrams, a set of diagnostics, and three different regression outputs with the log of wage as dependent variable. Explain what all this means, and how and why you have made the adjustments in the second and third regression. Remember, your reader is likely unaware of the endogenaity bias and what an instrumental variable estimator is, so be sure to explain all the terms and proceedures to make it clear what you have done, and why.
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