TAILIEUCHUNG - Lecture Advanced Econometrics (Part II) - Chapter 5: Limited dependent variable models - Truncation, censoring (tobit) and sample selection

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. | Advanced Econometrics - Part II Chapter 5 Limited - Dependent Variable Models Chapter 5 LIMITED - DEPENDENT VARIABLE MODELS TRUNCATION CENSORING TOBIT AND SAMPLE SELECTION. I. TRUNCATION The effect of truncation occurs when sample data are drawn from a subset of a larger population of interest. 1. Truncated distributions Is the part of an untruncated distribution that is above or below some specified value Density of a truncated random variable If a continuous random variable x has pdf f x and a is a constant then f x x a f x Prob x a If x N ơ2 P x a 1 - ol a I 1 - o a a I l Ơ J l Ơ - x- 2 1 -2 ____-_e 2Ơ f xlx a fL 1 -O a 1 -O a 1 . x - p p ơ l Ơ c o 1 - o a o Truncated standard normal distribution 2. Moments of truncated distributions C x x a J xf x x a dx a V J a x - Nam T. Hoang UNE Business School 1 University of New England Advanced Econometrics - Part II Chapter 5 Limited - Dependent Variable Models o Truncated mean and truncated variance If x N ơ2 and a is a constant E x x a ơẰ a 1 Var xlx a cr2 1 - ổ a Where a I a I . is this standard normal density c 7 J And Ằ a a 1 - h a if x a A a -ộ a ỊO a if x a And ổ a A a A a -a 0 ổ a 1 for all values of a 2 _2 7 J 7 truncated 3. The truncated regression model Assume now ị XB Yị s. Where e X. N 0 ơ2 So that Y X. N A W We are interested in the distribution of Yi given that Yi is greater than the truncation point a E Y Y a X p 7 ộ a - Xl B ơ 1 -O a - XtB ơ dE Yi Yi a _ da ------------- B o d . da r dX. 1 1 õXị B a A - aiẰị - B7 B 1 - A a A B 1 - ỗt Where a. a XịBi Ảị Ả at Sị ổ aị 1 -ổt is between zero and 1 for every element of Xi the marginal effect is less than the corresponding coefficient Nam T. Hoang UNE Business School 2 University of New England Advanced Econometrics - Part II Chapter 5 Limited - Dependent Variable Models Var Y Y a a 1 - S o Estimate Y Y a E Y Y a u XI p ơẢt ui Var Uị ơ2 1 - ỗị If we use OLS on Yi Xi we omit Ảị -Ạ all the biases that arise because of an omitted variable can be expected. o .

• Kinh tế học
• Advanced Econometrics
• Lecture Advanced Econometrics
• Limited dependent variable models
• Some issues in specification
• Sample selection model
• Regression analysis of treatment effects
• Review of least squares
• Likelihood methods
• Least quares methods
• Maximum likelihood estimation
• Greneralized linear regression model
• Properties of ols estimators
• Whites heteroscedascity consistent estimator
• Greneralized least squares estimation
• Lecture Heteroskedasticity
• Proterties of ols in rpesence
• Teesting for heteroskedasticity
• Treatment for heteroskedasticity
• Properties of ols estimator under autocorrelation
• Disturnabce rprocess
• Estimation under autocorrelation
• Estimator under autocorrelation
• General framework for panel data
• Pooled regression
• Fixed effects
• Random effects model
• Choosing between fixed
• Seemingly unrelated regressions
• Generalized least squares estimation
• Kronecker product
• Two case when sur provides
• Eficiency gain over
• Hypothesis testing
• Simultaneous equations models
• Order conditions for identification
• Estimation of a simultaneous equation system
• Lecture Simultaneous equations models
• Lecture Hypothesis testing
• Maximum likelihood estimators
• Likelihood ratio test
• Lagrange multiplier test
• Hausman specification test
• Discrete choice analysis
• Binary outcome models
• Discrete choice model
• Basic types of discrete values
• The probability models
• Multinomial models
• The multinomial logit model
• Conditional logit model
• Mixed logit mode
• Dummy varialable
• Intercept dummies with interactions
• Seasonal efects
• Test for structure break
• Differences in differences
• Models for count data
• Poisson regression model
• Goodness of fit
• Negative binomial regression model
• Too many zeros data
• Generalized method of moments
• Orthogonality condition
• Method of moments
• The advantages of GMM estimator
• Financial econometrics
• Advanced modeling techniques
• Regression analysis
• Selected topics
• Regression applications
• Regression applications in finance
• Stepwise regression
• Autoregressive conditional heteroskedastic models
• Vector autoregressive models
• Robust estimation
• Principal components analysis
• Factor analysis
• bank
• stock
• Stochastic Volatility
• Efficient Method of Moments
• econometrics
• Managerial economics
• Multiple regression analysis
• Qualitative information
• Data issues
• Advanced panel data methods
• Pooling cross sections across
• Speculative Prices
• Finite Variance
• Security Prices
• Random Variables
• Nonstationary Variance
• Stochastic Volatilities