Advanced Econometrics

Lecture "Advanced Econometrics (Part II) - Chapter 13: Generalized method of moments (GMM)" presentation of content: Orthogonality condition, method of moments, generalized method of moments, GMM and other estimators in the linear models, the advantages of GMM estimator, GMM estimation procedure.

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Lecture "Advanced Econometrics (Part II) - Chapter 10: Models for panel data" presentation of content: General framework for panel data, pooled regression, fixed effects, random effects model, choosing between fixed and random effects models, finding big.

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Lecture "Advanced Econometrics (Part II) - Chapter 11: Seemingly unrelated regressions" presentation of content: Model, generalized least squares estimation of sur model, kronecker product, two case when sur provides no eficiency gain over, hypothesis testing.

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Lecture "Advanced Econometrics (Part II) - Chapter 12: Simultaneous equations models" presentation of content: Model, rank and order conditions for identification, estimation of a simultaneous equation system.

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Lecture "Advanced Econometrics (Part II) - Chapter 7: Greneralized linear regression model" presentation of content: Model, properties of ols estimators, white's heteroscedascity consistent estimator, greneralized least squares estimation.

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Lecture "Advanced Econometrics (Part II) - Chapter 8: Heteroskedasticity" presentation of content: Proterties of ols in rpesence of heteroskedasticity, teesting for heteroskedasticity, treatment for heteroskedasticity.

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Lecture "Advanced Econometrics (Part II) - Chapter 9: Autocorrelation" presentation of content: Properties of ols estimator under autocorrelation, disturnabce rprocess, estimation under autocorrelation.

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Lecture "Advanced Econometrics (Part II) - Chapter 3: Discrete choice analysis - Binary outcome models" presentation of content: Discrete choice model, basic types of discrete values, the probability models, estimation and inference in binary choice model, binary choice models for panel data.

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Lecture "Advanced Econometrics (Part II) - Chapter 1: Review of least squares & likelihood methods" presentation of content: Least quares methods, maximum likelihood estimation.

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Lecture "Advanced Econometrics (Part II) - Chapter 2: Hypothesis testing" presentation of content: Maximum likelihood estimators, wald test, likelihood ratio test, lagrange multiplier test, application of tests procedures to linear models, hausman specification test, power and size of tests.

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Lecture "Advanced Econometrics (Part II) - Chapter 5: Limited dependent variable models - Truncation, censoring (tobit) and sample selection" presentation of content: Truncation, censored data, some issues in specification, sample selection model, regression analysis of treatment effects.

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Lecture "Advanced Econometrics (Part II) - Chapter 4: Discrete choice analysis - Multinomial models" presentation of content: The multinomial logit model, conditional logit model, mixed logit mode, independence of irrelevant alternatives, nested logit model, multinomial probit model.

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Lecture "Advanced Econometrics (Part II) - Chapter 6: Dummy varialable" presentation of content: Intercept dummy, intercept dummies with interactions, seasonal efects, pooled data, test for structure break, differences in differences.

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Lecture "Advanced Econometrics (Part II) - Chapter 6: Models for count data" presentation of content: Poisson regression model, goodness of fit, overdispersion, negative binomial regression model, too many zeros data.

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Unemployment (or joblessness), as defined by the International Labour Organization, occurs when people are without jobs and they have actively sought work within the past four weeks.[1] The unemployment rate is a measure of the prevalence of unemployment and it is calculated as a percentage by dividing the number of unemployed individuals by all individuals currently in the labor force. During periods of recession, an economy usually experiences a relatively high unemployment rate.

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