An Cao
An Cao
  • Видео 75
  • Просмотров 30 956

Видео

Tobit-2 model - motivation, formulation, estimation
Просмотров 1683 года назад
Tobit-2 model - motivation, formulation, estimation
Tobit I introduction & marginal effects
Просмотров 7253 года назад
Tobit I introduction & marginal effects
Maximum Likelihood Estimation - Linear regression
Просмотров 3,1 тыс.3 года назад
Maximum Likelihood Estimation - Linear regression
Maximum Likelihood - Introduction
Просмотров 1113 года назад
Maximum Likelihood - Introduction
Heteroskedasticity tests
Просмотров 1093 года назад
Heteroskedasticity tests
From GLS to heteroskedasticity
Просмотров 883 года назад
From GLS to heteroskedasticity
GLS estimator
Просмотров 4203 года назад
GLS estimator
Multicollinearity & Dummy variables
Просмотров 2983 года назад
Multicollinearity & Dummy variables
Goodness of fit
Просмотров 613 года назад
Goodness of fit
Sampling properties - Variance estimate
Просмотров 873 года назад
Sampling properties - Variance estimate
part 3 - Gauss Markov & OLS estimator
Просмотров 1113 года назад
part 3 - Gauss Markov & OLS estimator
GLM in matrix notation
Просмотров 3713 года назад
GLM in matrix notation
Intro - GLM example
Просмотров 953 года назад
Intro - GLM example
Statistic reviews - part 4
Просмотров 603 года назад
Statistic reviews - part 4
Statistics review - part 3
Просмотров 1023 года назад
Statistics review - part 3
Statistics review - part 2
Просмотров 833 года назад
Statistics review - part 2
Statistics review - part 1
Просмотров 1463 года назад
Statistics review - part 1
AAE commented syllabus 21
Просмотров 2633 года назад
AAE commented syllabus 21
3. Long-run producer's surplus (Markets week 5)
Просмотров 2133 года назад
3. Long-run producer's surplus (Markets week 5)
1.2. Long run analysis - part 2 (Markets week 5)
Просмотров 1523 года назад
1.2. Long run analysis - part 2 (Markets week 5)
1.1. Long run analysis - part 1 (Markets week 5)
Просмотров 1863 года назад
1.1. Long run analysis - part 1 (Markets week 5)
3.2. Comparative statics (Markets week 4)
Просмотров 2133 года назад
3.2. Comparative statics (Markets week 4)
3.1. Demand and supply shifts (Markets week 4)
Просмотров 1483 года назад
3.1. Demand and supply shifts (Markets week 4)
2. Short-run equilibrium (Markets week 4)
Просмотров 2053 года назад
2. Short-run equilibrium (Markets week 4)
1. Very short-run and short-run supply (Markets week 4)
Просмотров 1713 года назад
1. Very short-run and short-run supply (Markets week 4)
2. Market demand (Markets week 3)
Просмотров 1923 года назад
2. Market demand (Markets week 3)
1.3. Bayesian games with continuum of action (Markets week 3)
Просмотров 2233 года назад
1.3. Bayesian games with continuum of action (Markets week 3)
1.2. Bayesian-Nash equilibrium (Markets week 3)
Просмотров 4843 года назад
1.2. Bayesian-Nash equilibrium (Markets week 3)
1.1. Bayesian games (Market week 3)
Просмотров 2153 года назад
1.1. Bayesian games (Market week 3)

Комментарии

  • @jaime9927
    @jaime9927 2 месяца назад

    You explained it so clearly, thanks!

  • @tareqalmahmud621
    @tareqalmahmud621 2 месяца назад

    Thank you so much, wish you the best as well.

  • @kenyoon2769
    @kenyoon2769 8 месяцев назад

    Thank you!

  • @LenaWenzel-d1x
    @LenaWenzel-d1x 9 месяцев назад

    Nice !

  • @SophiaMirrashidi
    @SophiaMirrashidi 9 месяцев назад

    super helpful, thank you!

  • @secarl
    @secarl 9 месяцев назад

    It seems P(yi>0|hi=1) measures something like intention, which would be hard to support with behavioral data. I can measure the probability of the action, and the magnitude, but intention would be difficult. Good and important topic.

  • @khawlaqirmane8675
    @khawlaqirmane8675 10 месяцев назад

    Thank you so much ❤

  • @tszngonglam
    @tszngonglam Год назад

    very clear and easy to follow, got the point, thanks so much!!

  • @TÔMTIÊNYÊN
    @TÔMTIÊNYÊN Год назад

    E cảm ơn a

  • @AthumanAhmed
    @AthumanAhmed Год назад

    Thank you so much madam, may God bless you.

  • @gokulsampath9345
    @gokulsampath9345 2 года назад

    This is by far and away the best explanation of the vast breadth of limited dependent variable models I have ever found. I have been working on a paper where the outcome is a limited dependent variable for almost a year. While my choice of running both Heckman and 2PM models was correct all along, this is the most thorough explanation of when to use what model I have ever seen. Even getting into the likelihood functions. I will recommend everyone I know struggling with this. Well done!

  • @areebazafar9548
    @areebazafar9548 2 года назад

    THANK YOU 🙂 YOURVIDEOS HELPS ME TO UNDERSTAND THE BASICS WHICH I'M NOT ABLE TO UNDERSTAND THANKS

  • @philipaklorbortu6192
    @philipaklorbortu6192 2 года назад

    Very good 👍

  • @ameleworkbiresaw275
    @ameleworkbiresaw275 2 года назад

    Thank You!!!

  • @quean0101
    @quean0101 3 года назад

    23:39 typo: the last term on the right-hand side should be +p2c2, not p2c1

  • @moh.irzatchoirunnawaz4387
    @moh.irzatchoirunnawaz4387 3 года назад

    Thank you so much for detail explanation, wish u all the best

  • @dhanarmajhi395
    @dhanarmajhi395 3 года назад

    Thanks Ma'am, I really appreciate to your teaching 🥰🥰 From Odisha, India

  • @abc-vd1id
    @abc-vd1id 3 года назад

    ❤️❤️ beautiful

  • @kashiisshhhh
    @kashiisshhhh 3 года назад

    Great

  • @mathetabenson9464
    @mathetabenson9464 3 года назад

    Hello Ms. An Cao, I enjoyed your presentation above. As a beginner on this topic, I find it quite insightful. Could you please share the slides you keep referring to in this lecture? Again thank you for your good work

    • @quean0101
      @quean0101 3 года назад

      Hi there, here is the link to the slides: uni-bonn.sciebo.de/s/Pkeq6MT6jcdvLsv

    • @mathetabenson9464
      @mathetabenson9464 3 года назад

      @@quean0101 Thank you. I really appreciate

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  • @joguns8257
    @joguns8257 3 года назад

    Very educative and enlightening. I had been looking for something like this....Please upload more.

  • @rex-wn2td
    @rex-wn2td 3 года назад

    Good teacher but no views. I feel bad.

  • @quean0101
    @quean0101 3 года назад

    30:46 should be 70 percent (the average score so far), so that it makes sense that when then next assignment you get 80 percent, your average score will be improved!

  • @quean0101
    @quean0101 3 года назад

    7:20 I goofed. So it's actually "eq" in the textbook. That was just my typo. Sorry!

  • @quean0101
    @quean0101 4 года назад

    Mistake: from 26:31 til 30:15, the maximized MP should be 1,2000,000 and not 120k. I missed one zero at the end. Similar mistake for the maximized AP, and the MP when l = 30 8 (from 31:54 till end). They are both 900k, not 90k. However, the nature of the relationship among productivities remain unaffected.

  • @ngonluu4574
    @ngonluu4574 4 года назад

    Well done, An! Miss you here!!! Keep up...

  • @lebronjamesuit
    @lebronjamesuit 4 года назад

    great work !!! An