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Barsha Saha
In this 1-hour long project-based course, you will learn how to conduct Panel Data (Regression) Analysis. You will receive step-by-step instructions to analyze the 'RENTAL' dataset from 'Introductory Econometrics: A Modern Approach' by Wooldridge using R Studio. In this project, we will discuss three models namely, Ordinary Least Square (OLS), Fixed effects (FE) and Random effects (RE) in brief and check which one fits the model best. You will also learn some additional diagnostic tests which were not required for this example but are useful for other panel datasets (especially, macro panels).
Read more
In this 1-hour long project-based course, you will learn how to conduct Panel Data (Regression) Analysis. You will receive step-by-step instructions to analyze the 'RENTAL' dataset from 'Introductory Econometrics: A Modern Approach' by Wooldridge using R Studio. In this project, we will discuss three models namely, Ordinary Least Square (OLS), Fixed effects (FE) and Random effects (RE) in brief and check which one fits the model best. You will also learn some additional diagnostic tests which were not required for this example but are useful for other panel datasets (especially, macro panels).
Read more
In this 1-hour long project-based course, you will learn how to conduct Panel Data (Regression) Analysis. You will receive step-by-step instructions to analyze the 'RENTAL' dataset from 'Introductory Econometrics: A Modern Approach' by Wooldridge using R Studio. In this project, we will discuss three models namely, Ordinary Least Square (OLS), Fixed effects (FE) and Random effects (RE) in brief and check which one fits the model best. You will also learn some additional diagnostic tests which were not required for this example but are useful for other panel datasets (especially, macro panels).
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Register for this course and see more details by visiting:
OpenCourser.com/course/ki0t4n/panel
What's inside
Syllabus
Project Overview
Welcome to Panel Data with R! In this guided project you will learn how to conduct Panel Data Regressions. You will receive step-by-step instructions to analyze a sample dataset in R Studio. We will work with 'RENTAL' dataset from 'Introductory Econometrics: A Modern Approach' by Wooldridge. In this project, we will discuss three models namely, Ordinary Least Square (OLS), Fixed effects (FE) and Random effects (RE) in brief and check which one fits the model best. You will also learn some additional diagnostic tests which were not required for this example but are useful for other panel datasets (especially, macro panels).
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Provides a step-by-step guide for conducting panel data regression analysis, making it suitable for beginners
Uses the 'RENTAL' dataset from the renowned textbook 'Introductory Econometrics: A Modern Approach' by Wooldridge, ensuring the relevance and credibility of the course material
Emphasizes practical application by including hands-on analysis of a real-world dataset, offering a valuable learning experience
Covers essential models for panel data analysis, including Ordinary Least Square (OLS), Fixed Effects (FE), and Random Effects (RE), providing a comprehensive understanding of the subject
Includes additional diagnostic tests that are commonly used in panel data analysis, enhancing the practical relevance of the course
May require learners to have some prior knowledge in econometrics or statistics, as it assumes a basic understanding of these concepts
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Reviews summary
Panel data analysis with r
Learners say this is a concise yet in-depth course on Panel Data Econometrics perfect for those who want to apply this kind of modeling. The instructor is knowledgeable and patient, and the course is easy to follow even for those who are new to R. While the course is entirely in English, learners say that it is easy to understand.
Projects create a fundamental understanding.
"creates no fundamental understanding of what fixed effets or random effects are."
Instructor is knowledgeable and patient.
"she just gives which functions are to be used in R."
"The lecturer explains everything so well I didn't even need additional info or help during the project."
Course is concise.
"Perfect concise minicourse in Panel Data Econometrics. "
Excellent content.
"Easy to follow and with great content :)"
"Perfect concise minicourse in Panel Data Econometrics. "
"I think it's very useful if you want to apply this kind of models. I recommend to do it. "
Course is clear and easy to understand.
"Es en ingles pero se entiende perfectamente y es muy claro"
"I used Python and prefered to stick with general OLS models for panel data with some correction for heteroscedasticity (to be honest most of the time I work with logit models). I wanted to extend my skills since panel data is the most popular format in banking and finance where I work. I am really new to R but the lecturer explains everything so well I didn't even need additional info or help during the project."
"creates no fundamental understanding of what fixed effets or random effects are."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Panel Data Analysis with R with these
activities:
Organize your course materials
Show steps
Organizing your course materials will help you stay on top of the material and prepare for assessments more effectively.
Show steps
-
Create a system for organizing your notes, assignments, and other course materials
-
File and label your materials regularly
-
Review your materials periodically to reinforce your understanding
Create a cheat sheet on panel data models
Show steps
Creating a cheat sheet will help you summarize the key concepts and formulas related to panel data models, which can be a valuable reference during the course.
Browse courses on
Econometrics
Show steps
-
Gather the necessary information from the course materials
-
Organize the information into a concise and easy-to-understand format
-
Create a digital or physical copy of the cheat sheet
Read 'Introductory Econometrics: A Modern Approach' by Wooldridge
Show steps
This book covers the fundamental concepts of econometrics such as ordinary least squares (OLS), fixed effects (FE), and random effects (RE) models, which are essential to understanding the course material.
View
Introductory Econometrics
on Amazon
Show steps
-
Acquire the book
-
Read through Chapter 10: Panel Data Models
-
Take notes on the key concepts and formulas
-
Complete the practice problems at the end of the chapter
Five other activities
Expand to see all activities and additional details
Show all eight activities
Form a study group with classmates
Show steps
Studying with classmates can help you reinforce your understanding of the course material and prepare for assessments.
Browse courses on
Panel Data Analysis
Show steps
-
Find a group of classmates who are interested in forming a study group
-
Meet regularly to discuss course material and work on problems together
-
Quiz each other and provide feedback on assignments
Solve practice problems on panel data models
Show steps
Solving practice problems will help reinforce your understanding of the different panel data models and how to apply them in practice.
Browse courses on
Econometrics
Show steps
-
Find a set of practice problems
-
Attempt to solve the problems independently
-
Check your answers against the provided solutions
Follow online tutorials on panel data analysis using R
Show steps
These tutorials will provide step-by-step guidance on how to use R to analyze panel data, which will be helpful for completing the course project.
Browse courses on
Panel Data Analysis
Show steps
-
Find a reputable online tutorial
-
Follow the tutorial and complete the exercises
-
Apply what you've learned to the course project
Apply panel data models to a real-world dataset
Show steps
Applying panel data models to a real-world dataset will give you hands-on experience with the techniques covered in the course.
Browse courses on
Econometrics
Show steps
-
Find a suitable dataset
-
Choose an appropriate panel data model
-
Estimate the model and interpret the results
-
Write a report summarizing your findings
Mentor a junior student in econometrics
Show steps
Mentoring a junior student can help you solidify your understanding of econometrics and develop your communication and leadership skills.
Browse courses on
Econometrics
Show steps
-
Identify a junior student who is interested in econometrics
-
Meet regularly to discuss course material and provide guidance
-
Help the student prepare for assessments
Organize your course materials
Show steps
Organizing your course materials will help you stay on top of the material and prepare for assessments more effectively.
Show steps
Show steps
Show steps
- Create a system for organizing your notes, assignments, and other course materials
- File and label your materials regularly
- Review your materials periodically to reinforce your understanding
Create a cheat sheet on panel data models
Show steps
Creating a cheat sheet will help you summarize the key concepts and formulas related to panel data models, which can be a valuable reference during the course.
Browse courses on
Econometrics
Show steps
Show steps
Show steps
- Gather the necessary information from the course materials
- Organize the information into a concise and easy-to-understand format
- Create a digital or physical copy of the cheat sheet
Read 'Introductory Econometrics: A Modern Approach' by Wooldridge
Show steps
This book covers the fundamental concepts of econometrics such as ordinary least squares (OLS), fixed effects (FE), and random effects (RE) models, which are essential to understanding the course material.
View
Introductory Econometrics
on Amazon
Show steps
Show steps
Show steps
- Acquire the book
- Read through Chapter 10: Panel Data Models
- Take notes on the key concepts and formulas
- Complete the practice problems at the end of the chapter
Five other activities
Expand to see all activities and additional details
Show all eight activities
Form a study group with classmates
Show steps
Studying with classmates can help you reinforce your understanding of the course material and prepare for assessments.
Browse courses on
Panel Data Analysis
Show steps
Show steps
Show steps
- Find a group of classmates who are interested in forming a study group
- Meet regularly to discuss course material and work on problems together
- Quiz each other and provide feedback on assignments
Solve practice problems on panel data models
Show steps
Solving practice problems will help reinforce your understanding of the different panel data models and how to apply them in practice.
Browse courses on
Econometrics
Show steps
Show steps
Show steps
- Find a set of practice problems
- Attempt to solve the problems independently
- Check your answers against the provided solutions
Follow online tutorials on panel data analysis using R
Show steps
These tutorials will provide step-by-step guidance on how to use R to analyze panel data, which will be helpful for completing the course project.
Browse courses on
Panel Data Analysis
Show steps
Show steps
Show steps
- Find a reputable online tutorial
- Follow the tutorial and complete the exercises
- Apply what you've learned to the course project
Apply panel data models to a real-world dataset
Show steps
Applying panel data models to a real-world dataset will give you hands-on experience with the techniques covered in the course.
Browse courses on
Econometrics
Show steps
Show steps
Show steps
- Find a suitable dataset
- Choose an appropriate panel data model
- Estimate the model and interpret the results
- Write a report summarizing your findings
Mentor a junior student in econometrics
Show steps
Mentoring a junior student can help you solidify your understanding of econometrics and develop your communication and leadership skills.
Browse courses on
Econometrics
Show steps
Show steps
Show steps
- Identify a junior student who is interested in econometrics
- Meet regularly to discuss course material and provide guidance
- Help the student prepare for assessments
Career center
Learners who complete Panel Data Analysis with R will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
A Data Analyst helps make use of the data by collecting, cleaning, analyzing, and presenting data. The course helps build a foundation for analyzing complex datasets with many variables over time, which is a skill commonly used by Data Analysts. Moreover, understanding different regression models and diagnostic tests for panel data analysis, as taught in the course, can be highly valuable for professionals in this subfield.
Econometrician
Econometrician
Econometricians provide statistical methods and models to help analyze economic data and the factors that influence economic outcomes. The course can provide useful insights into econometric techniques and models, including panel data analysis, which econometricians frequently employ to study economic phenomena over time and across different units.
Quantitative Researcher
Quantitative Researcher
Quantitative Researchers analyze financial data using statistical models and econometric techniques to inform investment decisions. The course introduces panel data analysis, a powerful tool for studying financial datasets with multiple observations over time. Understanding these techniques can enhance the capabilities of Quantitative Researchers in modeling and forecasting financial outcomes.
Market Researcher
Market Researcher
Market Researchers gather and analyze data about markets, customers, and competitors to inform marketing strategies. The course provides hands-on experience in analyzing panel data, which can be valuable for Market Researchers who need to analyze customer behavior and market trends over time to make informed decisions.
Actuary
Actuary
Actuaries assess and manage financial risks using mathematical and statistical techniques. The course introduces panel data analysis, which can be useful for actuaries in modeling and forecasting financial risks over time. Understanding these techniques can strengthen the analytical skills of actuaries in assessing and managing financial risks.
Statistician
Statistician
Statisticians collect, analyze, and interpret data to solve real-world problems. The course provides a foundation in panel data analysis, which is frequently used by statisticians to analyze longitudinal data. Understanding these techniques can enhance the ability of statisticians to analyze and draw meaningful conclusions from complex datasets.
Data Scientist
Data Scientist
Data Scientists use scientific methods, processes, algorithms, and systems to extract knowledge and insights from data. The course provides exposure to panel data analysis, a valuable technique for analyzing datasets with repeated measurements over time. This knowledge can complement the skills of Data Scientists in handling and analyzing complex data.
Research Analyst
Research Analyst
Research Analysts conduct research and provide insights on various subjects, including economics, finance, and marketing. The course offers a foundation in panel data analysis, a technique used to analyze longitudinal data. This knowledge can be beneficial for Research Analysts who need to analyze trends and patterns over time.
Consultant
Consultant
Consultants provide expert advice and solutions to organizations on various business issues. The course introduces panel data analysis, which can be useful for consultants who need to analyze data over time to identify trends, patterns, and potential areas for improvement.
Financial Analyst
Financial Analyst
Financial Analysts assess and evaluate the performance of companies and their financial health. The course may provide some knowledge of panel data analysis, which can be helpful for Financial Analysts in analyzing financial data over time to identify trends and patterns.
Risk Analyst
Risk Analyst
Risk Analysts identify, assess, and manage risks for organizations. The course may provide an overview of panel data analysis, which can be used to analyze risk factors and their impact over time. This knowledge may be helpful for Risk Analysts in evaluating and mitigating risks.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use advanced analytical techniques to solve complex problems in various industries. The course may offer some exposure to panel data analysis, which can be useful for Operations Research Analysts in modeling and analyzing data over time to find optimal solutions.
Marketing Manager
Marketing Manager
Marketing Managers plan and execute marketing strategies to promote products and services. While panel data analysis is not a core skill for Marketing Managers, the course may provide some insights into analyzing customer behavior over time, which can be helpful for understanding market trends and optimizing marketing campaigns.
Business Analyst
Business Analyst
Business Analysts identify and solve business problems using data analysis and modeling techniques. While panel data analysis may not be a common requirement for Business Analysts, the course may provide some exposure to analyzing data over time, which can be beneficial for understanding business trends and patterns.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. While panel data analysis is not a requirement for Software Engineers, the course may provide some exposure to data analysis and modeling, which can be beneficial for understanding software usage and user behavior over time.
For more career information including salaries, visit:
OpenCourser.com/course/ki0t4n/panel
Reading list
We've selected nine books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Panel Data Analysis with R.
Provides a comprehensive overview of the latest research on panel data econometrics. It valuable resource for students, researchers, and practitioners who want to learn about the latest advances in the field.
Provides a comprehensive introduction to panel data econometrics, covering both theoretical and practical aspects of the subject. It valuable resource for students, researchers, and practitioners who want to learn about panel data econometrics.
Classic textbook on econometric analysis of cross section and panel data. It provides a clear and concise introduction to the subject, and it valuable resource for students, researchers, and practitioners.
Textbook on econometrics. It is written in a clear and concise style, and it covers a wide range of topics, including regression analysis, time series analysis, and cross section analysis.
Provides a comprehensive treatment of the econometrics of panel data with limited dependent variables. It covers a wide range of topics, including binary choice models, ordered response models, and count data models. The book is written in a clear and concise style, and it valuable resource for students, researchers, and practitioners.
Provides a comprehensive treatment of the econometrics of panel data. It covers a wide range of topics, including fixed effects and random effects models, dynamic panel data models, and instrumental variables.
Provides a comprehensive treatment of panel data analysis. It covers a wide range of topics, including fixed effects and random effects models, dynamic panel data models, and instrumental variables.
Provides a clear and concise introduction to econometrics for panel data. It covers a wide range of topics, including fixed effects and random effects models, dynamic panel data models, and instrumental variables.
Save
Textbook on introductory econometrics. It is written in a clear and engaging style, and it covers a wide range of topics, including regression analysis, time series analysis, and cross section analysis.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/ki0t4n/panel
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Effort
2.5 hours
Level
Intermediate
Via
Coursera
Institution
Coursera Project Network
Instructor
Barsha Saha
Language
English
Good to know
Provides a step-by-step guide for conducting panel data regression analysis, making it suitable for beginners
Uses the 'RENTAL' dataset from the renowned textbook 'Introductory Econometrics: A Modern Approach' by Wooldridge, ensuring the relevance and credibility of the course material
Emphasizes practical application by including hands-on analysis of a real-world dataset, offering a valuable learning experience
Covers essential models for panel data analysis, including Ordinary Least Square (OLS), Fixed Effects (FE), and Random Effects (RE), providing a comprehensive understanding of the subject
Includes additional diagnostic tests that are commonly used in panel data analysis, enhancing the practical relevance of the course
May require learners to have some prior knowledge in econometrics or statistics, as it assumes a basic understanding of these concepts
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