You will be working on a project where you use multivariate regression analysis to analyze economic data. You will be responsible for determining the research question, formulating the regression model, finding the relevant data and papers, performing the analysis and discussing the results. Chapter 19 in Wooldridge’s “Introductory Econometrics” has many useful examples and suggestions for carrying out an empirical project.

Econ3338.01: Introduction to Econometrics IProject InstructionsYou will beworking on a project where you use multivariate regression analysis to analyze economic data.You will be responsible fordetermining the research question, formulating the regression model, finding the relevant dataand papers, performing the analysis and discussing the results.Chapter 19 in Wooldridge’s “Introductory Econometrics” has many useful examples and suggestions for carrying out an empirical project.Technical Details-Formats Your final projectmust be submitted uploaded to a designated folder onBrightspacebyDecember15, 2020. Please submit an electronic copy of your first draft for a format check byDecember6, 2020. If any important part of the paper is missing or is not properly presented, you will receive an emailwithin 3-4days.1.Cover page.Thecover page should be structured as follows:NameB00#DateProject TitlePrepared for ECON 3338.01: Introduction to Econometrics2.Length.The maximum length, including figures,tablesand references, should not exceed 12pages.3.Font size and space. The text should be double-spaced, with size 12 font.4.Equations. Use an equation editor (built-in in MS Word) to specifyyour model(s), and number all equations in your text sequentially (1, 2, etc).Proposed Outline1. IntroductionIn this section, describe the research question and explain why it is important. Focus on the dependent variable.Providea brief description of what you will do in your project(in each section),without gettinginto detail.

2. Literature reviewProvide a short review of journal articles and/or booksthat are closely related to your project.Include the complete reference for each reviewed study in the reference section. 3. MethodologyThis section must discuss in detail what you will do in this project. You should mention the questions that you willanswer and how you plan todo so. For example, you write that you will investigatethe effectof education and experienceon wages. This will be done by considering a multivariate linear model, to be estimatedby OLS. Ifthere is a similar paper in the literature,you must explainthe difference between your work and thecited paper. Is it in the methodology? Do you include more independent variables in your analysis? Do you use a different estimation technique? Do you have a different data set? Remember to write the regression that you plan to runusing thefollowing format:=++Focus on the independent variables. For each independent variable, explain why you have included it in the model and whether you expect it to have a positive or negative impact on the dependent variable. 4. Description of the dataIn thissection, you describe your data set in detail: thevariables, their nature (continuous, categorical,or binary0/1), time period that they span, the number of observations, and thesourceof the data. Summary statistics should be provided either in tables or figures, depending on thetype of data. The full range of summary statistics (mean/variance/min/max/skewness/kurtosis) can be provided for continuous variables. Binaryor categoricalvariablescan be reported using frequency tables orpie charts. Provide some discussion of the descriptive statistics of the dependent and independent variables. If you notice some patterns in your data,interesting or strange, mentionthemhere. You can also includesome preliminary analysis about the relationship between variables of interestusing scatterplotsbetween pairs of variables.5. ResultsIn section 3you haveexplainedyour methodology. In this section, you shouldestimate the models based on your data and reportthe results.The regression outputs and specification tests must be provided and discussed. In the classyou will learn how to estimate the models and how to do inference for the models (i.e.,testing hypotheses about the values of the parameters of your model based on OLS estimates). You are asked to use what you have learned to estimate your models

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