### Explanation of Regression Function Parameters**Question:**What is/are the parameter(s) in the regression function below that capture(s) the unexplained portion of the black-white wage gap?**Regression Function:**\[ \text{Wage} = \beta_1 \times \text{state} + \beta_2 \times \text{education} + \beta_3 \times \text{part-time} + \beta_4 \times \text{industry/occupation} + \beta_5 \times \text{age} + \beta_6 \times \text{black} \]**Answer Options:**- [ ] beta3- [ ] beta1- [ ] beta4- [ ] beta5- [ ] beta2- [ ] beta6- [ ] alpha**Explanation:**In this context, the parameter that captures the unexplained portion of the black-white wage gap is typically associated with the variable related to race or ethnicity, which in this case is \(\beta_6 \times \text{black}\). This parameter represents the estimated effect of being black on wages, after controlling for all other factors. Therefore, the correct parameter is \(\beta_6\).

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MATLAB: An Introduction with Applications

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Data on 220 reported crimes is collected from district X in 2016. Suppose CS denotes the total cost to the state of offering crime protection services to this district (in thousand dollars), LEOP denotes the number of law enforcement officers on patrol, DTP denotes the damage to public and private property (in thousand dollars), CCTV denotes the number of CCTV cameras installed in the district, and Prison denotes the number of prison inmates The following table shows the results of a few regressions of the total cost to the state. Dependent variable: total cost to the state (in thousand dollars) Regressor (1) (2) (3) (4) 12.32 17.99 14.55 18.1 LEOP (0.52) (0.84) (2.25) (0.82) 0.73 0.59 0.75 DTP (0 12) (0.04) 0.73 (0.06) CCTV (0.13) 2.11 2.12 (0.39) 288.5 (4 14) Prison (0.5) 182.5 191.6 219.95 Intercept (11.52) (6.68) (5.26) 0.64 0.75 0.12 0.75 R 220 220 220 220 Heteroskedasticity-robust standard errors are given in parentheses under coefficients. Which of the following statements…
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What is/are the parameter(s) in the regression function below that capture(s) the unexplained portion of the black-white wage gap. Wage = beta1*state + beta2*education + beta3*part-time + beta4*industry/occupation + beta5*age + beta6*black beta3

What is/are the parameter(s) in the regression function below that capture(s) the unexplained portion of the black-white wage gap. Wage = beta1state + beta2education + beta3part-time + beta4industry/occupation + beta5age + beta6black beta3