Panda-metrics-2024-25 - История изменений

Bdemeshev: /* Classes */

2024-12-15T12:52:08Z

Classes

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	2024-11-01, class 8: Calculation probabilities, expected values, variances and covariances for naive bootstrap.		2024-11-01, class 8: Calculation probabilities, expected values, variances and covariances for naive bootstrap.

			2024-11-08, class 9:

			2024-11-15, class 10:

			2024-11-22, class 11:

			2024-11-29, class 12:

			2024-12-06, class 13:

			2024-12-13, class 14: explicit formula for instrumental variables, equivalence of iv and 2-stage least squares estimator

	== Sources of Wisdom ==		== Sources of Wisdom ==

Bdemeshev в 17:52, 13 декабря 2024

2024-12-13T17:52:01Z

← Предыдущая версия		Версия от 17:52, 13 декабря 2024
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			2024-11-04, lecture 9:

	2024-12-02, lecture : Definition of conditional heteroskedasticity, example of a WLS for Var(u_i \| X) = sigma^2 / x_i^2, HC0 standard errors, HC3 standard errors from cross-validation, LM test for heterskedasticity as nR^2 in auxillary regression.		2024-11-11, lecture 10:

	2024-12-09, lecture White, Breusch-Pagan and Goldfeld-Quandt tests, proof that F-statistic is asympotically equivalent to nR^2.		2024-11-18, lecture 11: Definition of SVD decomposition, definition and properties of orthogonal matrices. Example: SVD decomposition of a column (2, 7). PCA as consequiutive sample variance maximization.

			2024-11-25, lecture 12:

			2024-12-02, lecture 13: Definition of conditional heteroskedasticity, example of a WLS for Var(u_i \| X) = sigma^2 / x_i^2, HC0 standard errors, HC3 standard errors from cross-validation, LM test for heterskedasticity as nR^2 in auxillary regression.

			2024-12-09, lecture 14: White, Breusch-Pagan and Goldfeld-Quandt tests, proof that F-statistic is asympotically equivalent to nR^2.
	Alternative way to calculate leave-one-out residuals in multivariate regression: divide ordinary residuals by 1-Hii (without proof).		Alternative way to calculate leave-one-out residuals in multivariate regression: divide ordinary residuals by 1-Hii (without proof).

			2024-12-16, lecture 15:

Bdemeshev в 17:41, 13 декабря 2024

2024-12-13T17:41:24Z

← Предыдущая версия		Версия от 17:41, 13 декабря 2024
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	* Russell Davidson, James G. MacKinnon, [http://qed.econ.queensu.ca/pub/faculty/mackinnon/rd-jgm-bootstrap-methods-2006.pdf Bootstrap] methods in Econometrics		* Russell Davidson, James G. MacKinnon, [http://qed.econ.queensu.ca/pub/faculty/mackinnon/rd-jgm-bootstrap-methods-2006.pdf Bootstrap] methods in Econometrics



			2024-12-02, lecture : Definition of conditional heteroskedasticity, example of a WLS for Var(u_i \| X) = sigma^2 / x_i^2, HC0 standard errors, HC3 standard errors from cross-validation, LM test for heterskedasticity as nR^2 in auxillary regression.

			2024-12-09, lecture White, Breusch-Pagan and Goldfeld-Quandt tests, proof that F-statistic is asympotically equivalent to nR^2.
			Alternative way to calculate leave-one-out residuals in multivariate regression: divide ordinary residuals by 1-Hii (without proof).

Bdemeshev в 21:16, 1 декабря 2024

2024-12-01T21:16:23Z

← Предыдущая версия		Версия от 21:16, 1 декабря 2024
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	'''Midterm 1: 12th November, 18:10.'''		'''Midterm 1: 12th November, 18:10.'''

			[https://docs.google.com/spreadsheets/d/13BcvqNW6-ITyoV-oJ_ePg8oatWDjVj75Wkovxbj0RC8/edit?usp=sharing Actual grades]

	=== Home assignments ===		=== Home assignments ===

Bdemeshev: /* Samurai diary */

2024-11-01T19:10:45Z

Samurai diary

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	* 3b1b [https://www.youtube.com/watch?v=cy8r7WSuT1I Herschel-Maxweel assumptions] and multivariate normal		* 3b1b [https://www.youtube.com/watch?v=cy8r7WSuT1I Herschel-Maxweel assumptions] and multivariate normal

			2024-10-21, lecture 8: Bootstrap before regression: naive bootstrap, t-statistic bootstrap. Regression with bootstrap: pair bootstrap, wild bootstrap (+1/-1 version).

			* Tim Hesterberg, [https://arxiv.org/abs/1411.5279 What Teachers Should Know about the Bootstrap]: fun and enjoyable introduction to bootstrap!

			* Russell Davidson, James G. MacKinnon, [http://qed.econ.queensu.ca/pub/faculty/mackinnon/rd-jgm-bootstrap-methods-2006.pdf Bootstrap] methods in Econometrics


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	2024-10-18, class 7: F-test. F-test for regression significance. Constructing restricted model. Chow test.		2024-10-18, class 7: F-test. F-test for regression significance. Constructing restricted model. Chow test.

			2024-11-01, class 8: Calculation probabilities, expected values, variances and covariances for naive bootstrap.

	== Sources of Wisdom ==		== Sources of Wisdom ==

Bdemeshev: /* Samurai diary */

2024-10-20T13:30:41Z

Samurai diary

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	== Samurai diary ==		== Samurai diary ==

	~~Class [https://github.com/bdemeshev/hse_panda_metrics_2024_2025/tree/main/course_notes notes]~~

	~~Maria Kirillova [https://disk.yandex.ru/d/b7XZwMnboHoF4Q notes]~~

	2024-09-02, lecture 1: Derivation of beta hat in the cases of a very simple regression and multiple regression.		2024-09-02, lecture 1: Derivation of beta hat in the cases of a very simple regression and multiple regression.
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	=== Classes ===		=== Classes ===

			Class [https://github.com/bdemeshev/hse_panda_metrics_2024_2025/tree/main/course_notes notes]

			Maria Kirillova [https://disk.yandex.ru/d/b7XZwMnboHoF4Q notes]

	2024-09-06, class 1: 1.1, 1.2 from [https://github.com/bdemeshev/metrics_pro/raw/master/metrics_pro_en.pdf MPro]		2024-09-06, class 1: 1.1, 1.2 from [https://github.com/bdemeshev/metrics_pro/raw/master/metrics_pro_en.pdf MPro]
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	2024-10-11, class 6: confidence interval for beta, hypothesis test for beta, test of equality of two betas, confidence interval for conditional expected value of forecast.		2024-10-11, class 6: confidence interval for beta, hypothesis test for beta, test of equality of two betas, confidence interval for conditional expected value of forecast.

			2024-10-18, class 7: F-test. F-test for regression significance. Constructing restricted model. Chow test.

	== Sources of Wisdom ==		== Sources of Wisdom ==

Bdemeshev в 13:29, 20 октября 2024

2024-10-20T13:29:21Z

← Предыдущая версия		Версия от 13:29, 20 октября 2024
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	Class [https://github.com/bdemeshev/hse_panda_metrics_2024_2025/tree/main/course_notes notes]		Class [https://github.com/bdemeshev/hse_panda_metrics_2024_2025/tree/main/course_notes notes]

			Maria Kirillova [https://disk.yandex.ru/d/b7XZwMnboHoF4Q notes]

	2024-09-02, lecture 1: Derivation of beta hat in the cases of a very simple regression and multiple regression.		2024-09-02, lecture 1: Derivation of beta hat in the cases of a very simple regression and multiple regression.

Bdemeshev: /* Grading */

2024-10-14T16:15:29Z

Grading

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	When necessary 0-100 grades are converted into 0-10 grades using division by 10 and standard rounding.		When necessary 0-100 grades are converted into 0-10 grades using division by 10 and standard rounding.

			'''Midterm 1: 12th November, 18:10.'''

	=== Home assignments ===		=== Home assignments ===

Bdemeshev: /* Samurai diary */

2024-10-14T16:14:48Z

Samurai diary

← Предыдущая версия		Версия от 16:14, 14 октября 2024
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	Hat matrix is proportional to conditional variance of forecasts. Proof of Gauss-Markov theorem through Pythagoras.		Hat matrix is proportional to conditional variance of forecasts. Proof of Gauss-Markov theorem through Pythagoras.

	~~More:~~ Geometry in [https://raw.githubusercontent.com/olyagnilova/gauss-markov-pythagoras/master/paper.pdf econometrics]		* Geometry in [https://raw.githubusercontent.com/olyagnilova/gauss-markov-pythagoras/master/paper.pdf econometrics]

	2024-09-30, lecture 5: Consistency of beta hat in matrix form. Inconsistency of beta hat in a simple regression with measurement error in regressor.		2024-09-30, lecture 5: Consistency of beta hat in matrix form. Inconsistency of beta hat in a simple regression with measurement error in regressor.
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	Proof that t-statistic in multivariate regression has t-distribution.		Proof that t-statistic in multivariate regression has t-distribution.

			* 3b1b [https://www.youtube.com/watch?v=cy8r7WSuT1I Herschel-Maxweel assumptions] and multivariate normal

Bdemeshev: /* Samurai diary */

2024-10-14T16:13:26Z

Samurai diary

← Предыдущая версия		Версия от 16:13, 14 октября 2024
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	2024-10-07, lecture 6: Estimating variance of random error: unbiasedness of SSRes / (n - k), consistency of SSRes / (n - k).		2024-10-07, lecture 6: Estimating variance of random error: unbiasedness of SSRes / (n - k), consistency of SSRes / (n - k).

			2024-10-14, lecture 7: Herschel-Maxwell assumptions give us normal distribution. Chi-squared distribution as squared length of projection of standard normal vector onto d-dimensional subspace.
			Proof that t-statistic in multivariate regression has t-distribution.


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	2024-09-20, class 3: 5.5 from [https://github.com/bdemeshev/metrics_pro/raw/master/metrics_pro_en.pdf MPro], derivation of variance of slope estimate for simple regression.		2024-09-20, class 3: 5.5 from [https://github.com/bdemeshev/metrics_pro/raw/master/metrics_pro_en.pdf MPro], derivation of variance of slope estimate for simple regression.

			2024-09-27, class 4:

			2024-10-04, class 5:

			2024-10-11, class 6: confidence interval for beta, hypothesis test for beta, test of equality of two betas, confidence interval for conditional expected value of forecast.

	== Sources of Wisdom ==		== Sources of Wisdom ==