Welcome to my on 2-Stage Least Squares (2SLS). This course is carefully designed for students/researchers who are learning 2SLS for the first time and who are not quantitatively inclined.
In fact, this course is entirely NON-MATHEMATICAL!
This course is perfect for learning the intuition and logic of 2SLS and its corresponding diagnostic tests before formally learning the derivation and mathematics from an econometrics course or textbook.
Moreover, this course covers the application of 2SLS and its diagnostic tests using two of the most popular econometrics software packages, Stata and EViews.
At the end of this course, the student will have a clear understanding of why 2SLS is used and how it is implemented, and be able to estimate a 2SLS model using empirical data.
A quick introduction to this Section and how to use the material in this course.
Fundamental to the understanding of 2SLS is the difference between causation and correlation. The purpose of OLS and 2SLS regressions is to examine causality, not correlation. So let's make sure we understand the difference!
The assumption of exogeneity is vital for OLS regressions. In this Lecture, we will understand exactly what exogeneity is and why it is important for OLS regressions.
In this Lecture, the endogeneity bias is presented in an intuitive and completely non-technical manner. Using a simple and relate-able example, the endogeneity bias is clearly illustrated and its impact on OLS regression coefficient estimates is discussed.
The instrumental variable (IV): The magic bullet that will eliminate the endogeneity bias. What makes it so special? How do we identify a possible IV?
Let's find out!
Lets walk through the logic of the famous 2-Stage Least Squares model, and discuss exactly how it eliminates the endogeneity bias. Its so simple yet elegant!
In this Lecture, we discuss the thought process of finding a potential instrument. We uncover a possible instrument variable for the classic Wages and Education relationship, and walk you through the theory of justifying a potential instrument.
What is a strong instrument? In this Lecture, we discuss how you can formally test the strength of an instrument to ensure that is gets the job done!
This Lecture discusses the Test for Overidentifying Restrictions and why it is vital in checking the validity of the instrumental variable. If an instrument is invalid, then your 2-Stage Least Squares estimates will be incorrect! This test is crucial for your rseearch!
The Durbin and Wu-Hausman test is the classic test of endogeneity in a regression model. That is, do we even need 2-Stage Least Squares at all? When should we use 2SLS or a simple OLS regression? The results of this test will inform us which type of regression model is needed.
This test is important and should be conducted in all research projects employing instrumental variables.
In this Lecture, I walk you through the process of importing empirical data from Excel to Stata. We do this for the Wages and Education example.
We first conduct an OLS regression that assumes strict exogeneity. We will use these results to compare to our 2SLS results to observe any differences once endogeneity is accounted for. This is a neat way to showcase the power of the 2SLS model.
Lets estimate the 2-Stage Least Squares model in Stata and interpret its coefficients. Have they changed much form the OLS model? What does this mean?
In this Lecture, I will walk you through the process of testing for the strength and validity of the instruments, and the test for endogeneity. These diagnostic tests are crucial for any research project using 2SLS, so don't forget them!
This Lecture walks you through another 2SLS example: passenger demand and airfares. Again, we will walk through the process of estimating an OLS regression, a 2SLS regression, then testing for the strength and validity of the instrument and, finally, testing for endogeneity. I'll also show you how to create dummy variables in Stata.
After this example, you'll be an expert at conducting 2SLS in Stata!
How to import the Wages and Education data from Excel to EViews. It's a walk in the park!
We walk through the process of estimating an OLS regression model in EViews. We do this so we can compare the estimates with the 2SLS model in the following Lecture. Any differences observed is likely to be due to the endogeneity bias and the breakdown of the strict exogeneity assumption.
Lets estimate the 2-Stage Least Squares model and compare the results to our OLS regression. EViews is such a simple program to use and the steps are easy to follow. Never has it been so easy to implement such an elegant model!
In this Lecture, I'll show you, step-by-step, how to test for the strength and validity of an instrument along with the formal test for endogeneity. The tests conducted in EViews are slightly different from those of Stata, so be careful.
We go through a second example using passenger demand and airfares data. Again, we estimate an OLS regression, 2SLS regression, and conduct the tests for a strong and valid instrument and endogeneity. I'll also show you how to create dummy variables in EViews.
Estimating a 2SLS model will be a piece of cake after this example!
In this Section, I'll discuss the best way to move ahead with your studies after completing this course. By now, you will have a solid understanding of the intuition and logic of 2SLS. You're now ready to learn it formally from your course notes or textbook. I have a whole system of how I learn new econometric methods through textbooks that I will discuss here.
Moreover, this can be applied to all types of econometric models, not just 2SLS.
I've added an article I've written discussing the different forms of endogeneity and appropriate instruments.
Review of the material
This Section covers the notion of statistical significance, economic significance, dependent vs independent variables, R-Square statistic, interpreting the regression coefficients, and much more!
Hi everyone! My name is David, and I'm a Udemy instructor for Statistics and Econometrics. I hold a PhD in Finance from the University of New South Wales, Australia, and am currently a Lecturer in Aviation Finance. I absolutely love teaching! I like to break down complex concepts into little bite-sized pieces using simple and often silly stories for my students. The look on their faces from clueless to "ah ha!" is priceless, and means a lot to me.
In particular, I love teaching Statistics and I currently have a Youtube channel ("Quant Concepts") devoted to teaching statistics to newbies and those struggling with the subject. My channel has over 320,000 views and 1,600 subscribers, and is growing rapidly! I also run a Facebook page "freestatshelp" where I assist students with statistics from around the world for free. Come and check it out!
Yup, I'm a nerd.
Apart from teaching, I'm also an active researcher at the university and research in all sorts of stuff. I'm particularly passionate about my following research projects:
* Using microeconomics to improve the way funds are raised for charitable causes,
* Using agent-based modelling to observe how information goes viral on social media, and
* How exposure to technology and the Internet affects children's ability to concentrate.
Once a year, I go to a village in Phang Nga, Thailand, to volunteer and teach English at a disadvantaged (poorly funded) primary school for Burmese students. I would have to say one of the best times of my life is when I was staying in a small village in Thailand (Thai Mueang), teaching English to the Burmese kids, riding my scooter, working out of ym lap top, and just living a simple life.
Beauty lies in simplicity.