- 78
- 198 770
Richard Gallenstein
Registrace 12. 09. 2017
Video
Lecture 13 - R Demo
zhlédnutí 601Před 3 lety
This video provides a demo for Lecture 13: Panel Data Models in R.
Lecture 12 - R Demo
zhlédnutí 449Před 3 lety
This video provides a demo for Lecture 12: Instrumental Variable Models in R.
Lecture 11 - R Demo
zhlédnutí 2KPřed 3 lety
This video provides a demo for Lecture 11: Propensity Score Matching in R.
Lecture 10 - R Demo
zhlédnutí 287Před 3 lety
This video provides a demo for Lecture 10: Randomization in R.
R Tutorial
zhlédnutí 1KPřed 3 lety
This video provides a very brief intro to how to use the R interface.
Lecture 8 - R Demo
zhlédnutí 286Před 3 lety
This video provides a demo for Lecture 8: Binary Dependent Variable Models in R.
Lecture 14 - R Demo
zhlédnutí 850Před 3 lety
This video provides a demo for Lecture 14: Difference in Differences Model in R.
Lecture 6 - R Demo
zhlédnutí 195Před 3 lety
This video provides a demo for Lecture 6: Multicolinearity and Goodness of Fit in R.
Lecture 7 - R Demo
zhlédnutí 198Před 3 lety
This video provides a demo for Lecture 7: Heteroskedasticity in R.
Lecture 15 - R Demo
zhlédnutí 697Před 3 lety
This video provides a demo for Lecture 15: Regression Discontinuity in R.
Lecture 4 - R Demo
zhlédnutí 348Před 3 lety
This video provides a demo for Lecture 4: Multivariate Regression in R.
Lecture 3 - R Demo
zhlédnutí 332Před 3 lety
This video provides a demo for Lecture 3: Simple Linear Regression in R.
Lecture 5 - R Demo
zhlédnutí 245Před 3 lety
This video provides a demo for Lecture 5: Omitted Variable Bias in R.
Lecture 1 - R Demo
zhlédnutí 841Před 3 lety
This video provides a demo for Lecture 1: Descriptive Statistics in R.
Lecture 8 Binary Dependent Variable Models
zhlédnutí 3,8KPřed 3 lety
Lecture 8 Binary Dependent Variable Models
Equilibrium and Efficiancy 4 Solving for an Equilibrium
zhlédnutí 200Před 5 lety
Equilibrium and Efficiancy 4 Solving for an Equilibrium
Equilibrium and Efficiancy 3 Welfare Theorems and Prices
zhlédnutí 333Před 5 lety
Equilibrium and Efficiancy 3 Welfare Theorems and Prices
really clear expression!!! Thank you so much:)
Brilliant class. This is one rare video, which made Panel Data Model understanding so clear. As a Econometrics student, i am tempted to view other previous videos to understand the subject better. Thanks
Hello Dr. Richard I have Questions, what's the best way to make analysis for panel Data is that R or Stata ?
Super clear. Thanks! The empirical example just showcases what makes a good and poor assumption. Also like the logics you demonstrated throughout your explanation.
I’m working on a project which we have proven to be Natural Experiment. Can you suggest some paper so we can strengthen the methodology?
May I request you to cover endogenous switching regression model.
Sir, why have you not taken all variables in validating assumption 2? Why you leave the variable - female?
Nice. Clear. Simple. But, dude, do you seriously think 'criteria' is in the singular?!? 😂
A great video with very clear explanation.
Thanks❤
Hi, your work is very helpful thank you.may you please make a video on quantile regression
Such a clear explanation. Thank you.
Where I can find that dataset wages_random? I want to replicate that code.
Sir, God bless you.
Thanks prof. Gallenstein for a very clear presentation
very well explanation, thankyou Richard.
Wow, really good lecture on DID, thank you very much!
Respect and Love
thank you very much for this beautiful video on randomization. you are really educational.
From what I have learned DiD is not limited to panel data.
I hope this is the the right video for calculating minimum detectable effect size if I see an observational study published in a paper and I am reviewing it for discussing in journal club? My main concern is not to jump to an erroneous conclusion of equivalence based on an underpowered observational study which did not even mention any power analysis. This misunderstanding has a potential for negatively impacting patient care. Is there an article and is there a calculator?
Is the B1 the probability or the change in probability due to a one unit change in X.
How to get the data sets?
What if the reason that the treatment group was given the treatment (i.e, not random assignment) is correlated with the treatment group's trend? In other words, what if assignment of treatment was done non-randomly precisely because a certain group in the population was identified to have a different trend than other groups? Is there any economic/statistical check for that?
Thanks a lot for your lectures! They are very clear and easy to understand! It helped me a lot.
Thank you for the great lecture Prof! It couldn't have come at a better time
Wonderful. This much clearer picture of RDD, I haven't received from anyone else. Keep posting. Love from NEPAL. 😊
Thank you very much. Should we try out some of the Placebo tests to validate the results ?
How can we get the data set in this example of Stata Professor ?
Thank you so much, very helpful! Regarding the subgroup analysis: if the interacton coefficient is not significant, would that mean that the subgroup are different in the sample at hand, but that there is no statistical significance for it? Thanks in advance for the clarification :)
So precise, so clear, easily understandable. This is the best DID video. Thank you!
Excellent explanation, thank you!
very clear thank you very much. Helped a great deal
Best explanation series in the CZcams I have watched so far. Thanks Professor for each video on this serie. Worth to note, the videos are really underrated.
Thank you professor for your nice and detailed presentations! If we are using Probit model and there will be a hetroskedasticity , can we report the marginal effect coefficients or totally leave the model use only the results of LPM? Thank you!
Very concise, thank you
Professor, thank you so much for a very clear explanation of DID. I was having a hard time to understand this method but through your video, it helps me to understand it clearly.
Great thanks
Thank you so much professor, it helps me a lot!
This is great !
Nice video. First part of video: one column. Use runiformint(0,1) Use it again in part two, within vaccess.
Can you also make demo video for coarsened exact matching with stata code?
Been looking for a playlist like this, love it!
Wow! What an elaborate way of explaining the DiD concept. This is the best lecture so far. Thanks so much sir, i have learnt alot. kindly help me understand, incase there are three groups (treated, control and pure control) in an RCT experiment, how do you estimate the DiD?
16:50 When you write L(x*,y*,lambda*) it isnt technically a function but a function value. It becomes a function when written as L(z, alpha, beta)
where can I find wage_fe.dta?
hello sir, can I get access of those lecture slided?
hello, does the balancing test result are one of the steps before running PSM? or just common support assumption?
Thank you!!! Can we have two stratification variables? In my case, I need to stratify my control and treatment groups based on gender and governorate to have equal representation of both. Is it doable?
Hello sir, These playlist are indeed of great help to me. Can you share those slides with me?