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E- Views- Econometrics Course

person icon Nasir Munir

4.2

E- Views- Econometrics Course

Elevate your econometric skills with EViews expertise

updated on icon Updated on May, 2024

language icon Language - English

person icon Nasir Munir

category icon Construction Estimation

Lectures -13

Duration -2.5 hours

4.2

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Course Description

In this course, you will learn:

  • Types of Data

  • What are the different sites for data citations

  • How to import data in E-views

  • checking the stationarity of the data

  • converting time series data into panel data

  • 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

  • Johansen cointegration test

  • Estimation and interpretation of ARDL model

The purpose for creating this course is that all of you can able to estimate and run the different models for estimation using Eviews. All the lectures are designed 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 discussed them through mathematically as well as using EVeiws.

You will learn also about ARCH and GARCH family in this course.


Goals

What will you learn in this course:

This course  will able you to learn about the regression models, and you will learn that how to create dummy variables, and how to make panel data.

Prerequisites

What are the prerequisites for this course?

Basic information about computers.

E- Views- Econometrics Course

Curriculum

Check out the detailed breakdown of what’s inside the course

Data downloading
13 Lectures
  • play icon How to download data 05:46 05:46
  • play icon Types of data 09:56 09:56
  • play icon Importing Data into Eviews 06:50 06:50
  • play icon Checking the Stationarity of Time series Data 10:38 10:38
  • play icon Checking the Stationarity of Panel Data 19:37 19:37
  • play icon Detection of Auto correlation 14:33 14:33
  • play icon Detection of Multicollinearity 10:38 10:38
  • play icon Detection of Heteroskedastic 08:46 08:46
  • play icon Granger Causality Test 08:56 08:56
  • play icon Johansen cointegration Test 13:22 13:22
  • play icon VAR Model 17:58 17:58
  • play icon VECM Model 14:52 14:52
  • play icon ARDL 10:46 10:46

Instructor Details

Nasir Munir

Nasir Munir

"PhD Economist with 12 years of teaching experience, guiding students towards mastery in economics, one lesson at a time."

Dr. Nasir, a highly skilled and experienced educator, has been teaching at various universities for over a decade. With a PhD in Economics, Dr. Nasir brings a wealth of knowledge and expertise to the classroom and is dedicated to fostering a passion for learning in his students. Currently, Dr. Nasir is serving as a faculty member at SZABIST Islamabad, one of the leading universities in Pakistan.

Throughout his career, Dr. Nasir had the opportunity to work at a number of different universities, gaining valuable experience and insights along the way. In addition to their academic pursuits, Dr. Nasir has also worked with PLAN Pakistan, a leading non-governmental organization, further expanding their knowledge and understanding of the field. With a deep commitment to teaching and a passion for helping others succeed, Dr. Nasir is a valuable asset to any educational institution.

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