What You Will Learn!
- Types of Data in Econometrics
- How to download Data from World Development Indicators (WDI)
- Importing Time Series Data in Eviews
- Importing Cross Sectional Data in Eviews
- Importing Panel Data in Eviews
- Estimation and Interpretation of Ordinary Least Squares (OLS)
- Some Assumptions of CLRM
- How to Detect and Remove Auto-Correlation (Serial Correlation)
- Heteroskedasticity (Detection and Removal)
- Normality (Jorque Bera test)
- Students should expect some quizzes and an Assignment at the end of course
- Data Sources
Description
In this course, you will learn:
Types of Data in Economics
Downloading data from World Development Indicators (WDI)
Importing Time series, Cross-sectional and Panel Data into Eviews
Estimating and Interpreting OLS
Assumptions of Classical Linear Regression Model (CLRM)
Detection and Removal of Autocorrelation
Detection and Removal of Heteroskedasticity
Normality using Jorque Bera test
I have created this course in such a manner that if you follow the videos in a sequential manner and then connect the quizzes and assignment with the videos, you will have a great benefit in your professional career.
There are many types of data in economics, but in this course, I have only mentioned and discussed those data types which are mostly used for estimation and prediction when it comes to economics.
When it comes to downloading data, it is an easy yet very difficult task because most of the students don’t know from where and how they should download data. Therefore it is also discussed how and from where you can download data.
In this course, each and every step is discussed, not only discussed, but I have shown them practically. So it will be beneficial for the learners to apply them in future life.'
In the assumption of classical linear regression model, I have just discussed the assumptions and have given reference books for more understandings.
Who Should Attend!
- Students studying any of the above mentioned subjects at any grade level
- Anyone wants to learn Estimating Data
