n this exam you will work with a simulated housing dataset to test whether rural house prices went up faster than non$-$rural house prices after $2020,$ due to the pandemic. You will be using a diff$-$in$-$diff analysis while at the same time discovering how factors like square footage and number of bedrooms affect house price.

There are two datasets:

sales.csv: A dataset where each row is a house sale. The variables are:

sale$\_$id: A unique identifier for the sale

sale$\_$price: The price at which the house was sold

sale$\_$year: The year in which the house was sold

zipcode: The zipcode of the house

sq$\_$ft: The square footage of the house

lot$\_$sq$\_$ft: The square footage of the lot

num$\_$bedrooms: The number of bedrooms in the house

num$\_$bathrooms: The number of bathrooms in the house

built$\_$before$\_1977$: Whether the house was built before $1977$

has$\_$garage: Whether the house has a garage

has$\_$view: Whether the house has a nice view

zips.csv: A dataset where each row is a zipcode. The variables are:

zipcode: The zipcode

is$\_$rural: Whether or not the zipcode is rural

There are four tasks.

Task $1$

Read both data files into R and merge them. Name the resulting dataframe df$.$

Task $2$

Create three new variables in df:

treated: A boolean variable which is True if the house is in a rural zipcode

post: A boolean variable which is True if the sale year is $>=2020$

treatedXpost: Equal to treated$*$post

Task $3$

Make a diff$-$in$-$diff plot showing the average log sale price by year for the treated $($rural$)$ and untreated $($non$-$rural$)$ groups.

The plot title should be "Average Log Sale Price by Year, Rural vs$.$ Non$-$Rural"

The X axis should be labeled "Year"

The Y axis should be labeled "Avg Log Sale Price"

Task $4$

Run one regression with log$($sale$\_$price$)$ as the dependent variable. Include the following variables as covariates:

log$($sq$\_$ft$)$

log$($lot$\_$sq$\_$ft$)$

num$\_$bedrooms

num$\_$bathrooms

built$\_$before$\_1977$

has$\_$garage

has$\_$view

treatedXpost

Additionally, include sale$\_$year and zipcode as dummy variables

Report the regression results using Stargazer. $($The table should only have one column$).$

Interpret the results

In addition, you must answer a question asking you to interpret the results $(3$ pts$)$