代做Econometrics Project 2024 Summer帮做Python语言

日期：2024-06-24 05:14

Econometrics

Project

2024 Summer

Individual Project

1. Topic：any topic related with Economics

2. Software：Stata or any other statistical software

3. Submission deadline：

Ÿ Please send an electronic copy of your project to TA on the due date. Please put your name on the cover page of your report. The empirical project must be handed in before/on the due date. Any late submission will not be accepted.

Ÿ Full Credits of project is 100 points.

Requirements

（I）Introduction（10 points）

(a)  Goal of project：state what question you are interested in and explain the meaning of the topic you choose;

(b)  Describe the objective of your interests, define dependent variables and independent variables, and make pre-judgements on the relationship between all independent variables and dependent variable.

（II）Data collection（10 points）

    Require to collect a panel data with n × T ≥ 100 or a cross-sectional data set with n ≥ 100，and the number of variables must be no less than 3. Please indicate the data resources.

（III）Descriptive Analysis（10 points）

Scatter plots dependent variable and independent variables, and summarize descriptive statistics on all variables including number of observations, mean, standard deviation, minimum, maximum, skewness and kurtosis. Explain the properties of your data.

（IV）Regression Analysis and Hypothesis Testing（50 points）

Conduct multiple regression analysis or panel regression analysis, and discuss the following questions:

(a) Should you apply linear model or nonlinear model on your data? Should you apply Random or Fixed effect model?

(b) Does the model suffer multicollinearity problem? How to solve the issue if exists?

(c) Conduct some hypothesis tests to support your opinions.

You may consider various models. Please summarize all regression estimation results in one table as the lecture notes show.

（V）Conclusion（20 points）

Base on all regression estimation results and hypothesis testing, please choose the best model and explain the reason of your choice. Interpret your best model results and the underlying economic meaning, and make a conclusion.