Consider the dataset (wage2) in the Wooldridge package embedded in R for this assignment. The dataset...
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Consider the dataset (wage2) in the Wooldridge package embedded in R for this assignment. The dataset contains numerous variables, but for the purpose of this assignment, consider the variables described in Table 1. Table 1: Definition of variables in wage2 dataset Variable Wage Hours IQ KWW Educ Exper Tenure Age sibs Meduc Feduc Definition Monthly earnings Average weekly hours IQ score Knowledge of world work score Years of education Years of work experience Years with current employer Age in years Number of Siblings Mother's education Father's education The objective of the study for which the data was collected was to establish the effects the given variables on monthly wages in the United States of America. 1. Install the appropriate package in to R, then call the relevant dataset. 2. Use the data described to determine the effects of the different variables on wage. Discuss the significance of the coefficients and the model fit. (15) 3. Perform pre-estimation model diagnostic tests (autocorrelation, multicollinearity, heteroscedasticity and omitted variable bias). Note: State the Null hypothesis for each test and give the appropriate interpretation. (15) 4. If you find any violators of the OLS from the above mentioned diagnostic tests, run the appropriate tests to correct for them. (10) Consider the dataset (wage2) in the Wooldridge package embedded in R for this assignment. The dataset contains numerous variables, but for the purpose of this assignment, consider the variables described in Table 1. Table 1: Definition of variables in wage2 dataset Variable Wage Hours IQ KWW Educ Exper Tenure Age sibs Meduc Feduc Definition Monthly earnings Average weekly hours IQ score Knowledge of world work score Years of education Years of work experience Years with current employer Age in years Number of Siblings Mother's education Father's education The objective of the study for which the data was collected was to establish the effects the given variables on monthly wages in the United States of America. 1. Install the appropriate package in to R, then call the relevant dataset. 2. Use the data described to determine the effects of the different variables on wage. Discuss the significance of the coefficients and the model fit. (15) 3. Perform pre-estimation model diagnostic tests (autocorrelation, multicollinearity, heteroscedasticity and omitted variable bias). Note: State the Null hypothesis for each test and give the appropriate interpretation. (15) 4. If you find any violators of the OLS from the above mentioned diagnostic tests, run the appropriate tests to correct for them. (10)
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Use packagenamemydata Dataset is in a data folder with for exa... View the full answer
Related Book For
Statistics Unlocking The Power Of Data
ISBN: 9780470601877
1st Edition
Authors: Robin H. Lock, Patti Frazer Lock, Kari Lock Morgan, Eric F. Lock, Dennis F. Lock
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