Related lectures (32)
Generalized Method of Moments (GMM)
Introduces the Generalized Method of Moments (GMM) in econometrics, focusing on its application in instrumental variable estimation and asset pricing models.
Stochastic Simulations: Ergodicity and Estimators
Explores geometric ergodicity in Markov chains and estimators' bias and variance, highlighting efficiency loss quantification.
Estimation and Analysis of Deviance
Covers estimation of unknown parameters, analyzing model fit, bird prey response, and model diagnostics.
Point Estimation Methods: MOM and MLE
Explores point estimation methods like MOM and MLE, discussing bias, variance, and examples.
Statistical Models and Parameter Estimation
Explores statistical models, parameter estimation, and sampling distributions in probability and statistics.
Estimators and Bias
Explores estimators, bias, and efficiency in statistics, emphasizing the trade-off between bias and variability.
Instrumental Variables: Intuition and Estimation
Covers instrumental variables, addressing endogeneity issues in regression analysis through estimation techniques and practical examples.
Linear Regression Basics
Covers the basics of linear regression, instrumental variables, heteroskedasticity, autocorrelation, and Maximum Likelihood Estimation.
Robust Regression: Methods and Applications
Explores robust and resistant methods in linear models, emphasizing the importance of handling extreme observations and the implications of robustness in regression models.
Statistical Theory: Maximum Likelihood Estimation
Explores the consistency and asymptotic properties of the Maximum Likelihood Estimator, including challenges in proving its consistency and constructing MLE-like estimators.

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