The assignment have to be done on R studio ,making a code R and HTML document--- title: "Assignment...

Question

The assignment have to be done on R studio ,making a code R and HTML document--- title: "Assignment 2" subtitle: "Econ 3210, Fall 2020" author: "Your name here" output: html_document --- ```{r setup, include=FALSE} knitr::opts_chunk$set( 	echo = TRUE, 	message = FALSE, 	warning = FALSE ) # Set the graphical theme ggplot2::theme_set(ggplot2::theme_light()) library(AER) library(wooldridge) library(tidyverse) ``` ## Question 1. This data is based on the following paper: K. Graddy (1997), "Do Fast-Food Chains Price Discriminate on the Race and Income Characteristics of an Area?" Journal of Business and Economic Statistics 15, 391-401. In the paper, the authors argue that fast food chains employ discriminatory pricing practices by charging higher amounts for common items in areas that have a higher proportion of African Americans (the variable **prpblck**). a. What are the names of the variables in the **discrim** data? ```{r} # Your code here. discrim  answer here 3. Estimate the relationship in (2). Interpret both the of the estimates of $\hat\beta_0$ and $\hat \beta_1$. ```{r} # code here ``` > answer here 4. Do beatiful people earn more than less beautiful people? (ie, is the coeffient $\hat \beta_1$ statistically significant)? 5. Now use the variable `belavg` instead `abvavg` in a regress.  Is there a penalty for being below average looking (`belavg` is below average looking). ## Question 3. Suppose we wanted to predict a CEO's salary based on the firms return on equity over the previous 2 years.  The data set `ceosal` contains the variables `salary` (annual salary in thousands) and `roe`, the return on equity in percent (ie, return * 100).  Consider the following equation: $$ salary_i = \beta_0 + \beta_1 roe_i + u_i $$ ```{r} ceosal  answer here 2. In the following code chunck, I change the units of measurment. In particular, $roe\_decimal_i$ is $roe_i/100$ or measured as the return in decimals.  The variable $salary\_dollars_i$ is salary measured in dollars rather than a thousands of dollars. ```{r} ceosal %    mutate(roe_decimal = roe / 100,          salary_dollars = salary * 1000) ``` Estimate $$ salary\_dollars_i = \alpha_0 + \alpha_1 roe_i + u_i $$ and  $$ salary_i = \gamma_0 + \gamma_1 roe\_decimal_i + u_i $$ in the code chunk below and interpret both the intercept and the slope coefficient. What is the relationship between $\beta_1$ and $\gamma_1$ and $\alpha_1$, and $\beta_0$ and $\gamma_0$ and $\alpha_0$ ```{r} # your code here ``` > answer here 3. Investigate the following hypothesis: $$ H_0: \gamma_1 = 0 \ H_1: \gamma_1 
eq 1 $$ Do our conclusions change from part 1?

Naveen · Accepted Answer

---
title: "Assignment 2"
subtitle: "Econ 3210, Fall 2020"
author: "Alain"
output: html_document
---
  
```{r setup, include=FALSE}
knitr::opts_chunk$set(
  echo = TRUE,
  message = FALSE,
  warning = FALSE
)
# Set the graphical theme
ggplot2::theme_set(ggplot2::theme_light())
library(AER)
library(wooldridge)
library(tidyverse)
library(dplyr)
```
## Question 1.
This data is based on the following paper:
  
  K. Graddy (1997), "Do Fast-Food Chains Price Discriminate on the Race and Income Characteristics of an Area?" Journal of Business and Economic Statistics 15, 391-401.
In the paper, the authors argue that fast food chains employ discriminatory pricing practices by charging higher amounts for common items in areas that have a higher proportion of African Americans (the variable **prpblck**).
a. What are the names of the variables in the **discrim** data?
  
```{r}
# Your code here.
discrim Ans: There is no significant correlation between the variables and above given correlation is represents the casual relationship.
d. Construct a 95 percent confidence interval for the coefficient on `prpblck`.  What is the interpretation of a confidence interval?
  
```{r}
# Your code here
confint(model.lm, "prpblck", level = .95)
```
>Ans: The coefficient of prpblck variable will take the values in between 0.017829 and 0.112024.
## Question 2.

--- title: "Assignment 2" subtitle: "Econ 3210, Fall 2020" author: "Your name here" output: html_document --- ```{r setup, include=FALSE} knitr::opts_chunk$set( echo = TRUE, message = FALSE, warning =...

Answer To: --- title: "Assignment 2" subtitle: "Econ 3210, Fall 2020" author: "Your name here" output:...

Answer To This Question Is Available To Download

Related Questions & Answers

Submit New Assignment