This is a final project worth 15% of my grade, please DO NOT take this question if you do not know how to do it or will not finish on time. Please review what is necessary for the final project in the attachment below before taking this question.

Please, I beg you, do not take this question if you are not capable of doing it, PLEASE review the attachment first.

https://www.kaggle.com

https://finance.yahoo.com

Some useful links for the project.

1. The first step is to identify a question of interest, in particular a Y (dependent) variable that you would like to describe and some (independent) variables X that you use to explain Y . It is important that you are able to discuss what economic theory (or common sense) would suggest the relationship between Y and the Xs should be. This will give you a framework to interpret the regression results. Remember that:
   • cross-sectional data consists of different units observed at the same point in time (eg, a sample of workers in 2019); in this case your goal is to explain why Y is different across units
   • time series data is when we track one variable over time (eg, GDP from 1950 to 2019 at the quarterly frequency); here the goal is to explain the fluctuations over time of the variable
2. The following step is to find a suitable dataset that provides a sample for the variables you want to observe. There are lots of open datasets that can be freely downloaded on the internet. Make sure that you quickly identify a dataset, otherwise it is advisable that you change to a different project idea for which you can find data.
3. Once you have the idea and the data, it is time to apply the LRM. Some issues you should inves- tigate and discuss are:
   • Are the variables that you thought could be important statistically significant (at 5%)?
   • Are there variables that you would have liked to include in the regression but could not find data for? Discuss whether you expect these omitted variables to introduce bias in your OLS estimates.
   • Are the estimated effects (betas) of the expected sign?
   • Interpret the estimated effects
   • Are there one or more variables that you would like to exclude from the regression because they are irrelevant? Use the F-test
   • Include at least one type of nonlinearity in the LRM and interpret its effect 4. Prepare a presentation with the following slides:
   • Slide 1: title of the project, author
   • Slide 2: Describe the question you are trying to answer and why it is relevant
   • Slide 3: Describe the empirical LRM in terms of the dependent variable, independent variables, and formulate an expectation of the sign of their relationship; include at least one nonlinearity in the LRM that you are considering
   • Slide 4: Discuss data sources
   • Slide 5: Discuss the estimation results in terms of the finding on the relation between the Xs and Y (and their significance), the goodness-of-fit of the regression, the relevance of the nonlinearity included in the model, and the questions discussed earlier
   • Slide 6: draw some conclusions from your analysis, in particular discussing the answer to your initial question

We Will discuss more in the chat.

In the upload file, I will make the presentation and the 5-10 minute video, but I need the questions answered to make it.

All parts must be completed, thank you guys so much! I will tip VERY WELL if I am happy with the work, please try your best, it is worth a lot of my grade.