Below is the criteria I'd need you to obtain/ make. attached is my initial proposal however, I don't ...

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Below is the criteria I'd need you to obtain/ make. attached is my initial proposal however, I don't know how to gain the information needed to make it more like the sample paper (also attached). Keep in mind the sample is far more advanced but a good reference for things like the summary table and data format. If you were to accept, the main task would be to find the data that fulfills the requirements below and create a stata regression. Also all information needs to be cited so I can use the source. Please do not use bootstrapping or other data scrapping techniques unless absolutely needed. I sincerely appreciate your assistance if you do choose to accept. Below are the requirements: Discuss the sources of the data, explain all the variables, the sample used for estimation, the possible measurement errors etc. If you have done a lot of work developing a new or unusual data set, make sure you describe what you have done. Make a table of summary statistics. Model Specification Specify a multiple regression model to address your research question. In particular, your model should include as least four linear non dummy explanatory variables, one dummy variable and one nonlinear term. Make sure to present your model as an equation included in the text. You should Talk about the key variables, and explain why you include them Explain why the nonlinear terms might be necessary and what results can be expected. Set out any hypotheses to be tested, e.g. positive (or negative) effect of the key variables Estimation, Model Selection, and Diagnostics In this section, you will estimate both models in Stata, and then evaluate how well your model performs. You should check your model to see if it suffers from the following issues Multicollinearity, heteroscedasticity. Try to address them when present. 3 Omitted variable bias. Discuss what variable(s) might have been omitted and the possible consequences. Results Report the final results, test hypothesis on variables of interests, and interpret the coefficients. Make your own table to present the regression results.