Panel Data Analysis in Stata Full tutorial 2024 Practical Part 1 of 3

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Panel datasets are common in various fields, particularly econometrics. For example, we can examine factors influencing unemployment rates in various US states from 1970 to 1986 . Or, in clinical trials, factors influencing the prevalence of Covid-19 in different cities across the country. To do a scientific analysis of a panel dataset, follow these steps: • 1. Set dataset as a panel. • 2- Describe variables using tables and charts. • 3. Choose a suitable model (pooled, panel, fixed or random). • 4. Check model assumptions. • 5. Modify any assumptions that were violated. • 6. Interpret outputs. • 7- Write reports. • In this video, I attempted to cover most of the above topics practically. For that, the tutorial is divided into three parts. Each section includes: • ** Part 1 of 3: Introduction ** • 1. What is a panel dataset and which characters does it contain? 01:33 • 2. Introduce the dataset used in the tutorial and provide a download link. 02:05 • 3- Setting data as a panel format and the challenges to do that. 04:30 • 4- Describe variables in data using plots and tables. 06:49 • 🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈 • (Part 2 of 3: Assumptions. • 1. How to assess long-term (stable) relationships (Kao, Pedroni, Westerland). 00:43 • 2. How to check stationary in mean and correct violations (Levin-Lin-Chu). 02:24 • 3- How to check for stationary in variance. 07:46 • 4- How to correct and manage variance violations. 10:14 • Part 3 of 3: Fit Model • 1. How to choose between pooled and panel analysis. 01:08 • 2- How to choose between fixed and random effect analysis. 02:52 • 3- How to check for heteroscedasticity in residual variance using the Leven or Breusch-Pagan tests. 06:18 • 4. How to analyze residuals for serial correlation, also known as autocorrelation. 07:32 • 5- Modified heteroscedasticity and serial correlation in residuals. 08:55 • 6- Use Generalized Least Squares (GLS) and Driscoll-Kraay standard errors. 11:12) • 🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈🌈 • *** Final Note: • As a researcher or student, you might order a similar project. Then, send a message via the Whatsapp (+98 933 856 9801 or +60 1364 30 178).

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