Microeconometrics 2400-ICU1MIR
Introduction[1]
- Ceteris paribus assumption and control variables
- Random vs. fixed regressors assumption
- Random sample assumption and its role in econometrics
- Model defined in conditional expectations
- Properties of conditional expectations
- Partial effects, elasticities and semielasticities
- Average partial effects
- Basic asymptotics
Ordinary least squares and instrumental variable estimation [2,3]
- Omitted variable bias
- Properties of OLS with omitted variables
- Proxy variable solution
- Instrumental variable solution (IV and 2SLS)
- Assumptions of IV
- Asymptotics of IV
- Endogeneity testing
- Generated regressors and instruments
- Pooled cross sections
- Clustered samples
Unobserved effects and panel analysis [4-6]
- Linear unobserved effects model - assumptions
- Random effects estimator
- Fixed effects estimator
- First difference estimator
- Panel estimators - comparison (Hausman test)
- Panel estimation of dynamic models - sequential exogeneity
- Individual specific slopes
- Panel models with endogenous explanatory variables
- Hausman and Taylor type estimators
Nonlinear models [7,8]
- M estimators - assumptions and properties
- Hypothesis testing
- Optimization
- Simulation and bootstrapping
- Maximum and quasi maximum likelihood estimators (ML) - asymptotic properties
- Least absolute distance (LAD) estimators and Generalized Methods of Moments (GMM) - assumptions and properties
- Efficiency of estimators
Count data models [9]
- Poisson model - assumptions
- Negative binominal models - assumptions
- Advanced models for count data (ZIP)
Discrete dependent variable [10,11,12]
- Latent dependent variable problem
- Index models for binary data (linear, probit and logit)
- Dynamic models for binary data - initial condition problem
- Multinomial choice models - extreme value type I distribution
- Multinomial logit - independence of irrelevant alternatives (IIA) assumption
- Conditional logit and hierarchical logit
- Ordered choice models - ordered logit and probit
- Censored data models - tobit, 2 stage model
- Advanced topics
Nonrandom sample selection, attrition and stratified samples [13]
- Sample selection problem
- OLS and sample selection bias
- Truncated samples and II type tobit (Heckman model)
- Binary choice models with sample selection (Heckman probit)
- Panel data models for rotated panels and attrition problem
- Stratified samples - sampling schemes and weighted estimators
Policy response analysis [14]
- Regression methods
- Methods based on probability of response
- Instrumental variable methods
Type of course
Course coordinators
Mode
Learning outcomes
KW01, KW02, KW03, KW04, KW05, KU01, KU02, KU03, KU04, KU05, KU06, KU07, KK01, KK02, KK03
Bibliography
Required readings:
- Wooldrige, Jeffrey M, Econometric analysis of cross section and panel data, The MIT Press, Cambridge 2002
Suggested readings:
- William Greene, Econometric Analysis, Prentice Hall 2003
- Maddala, Limited Dependent and Qualitative Variables in Econometrics, OUP 1983
Additional information
Information on level of this course, year of study and semester when the course unit is delivered, types and amount of class hours - can be found in course structure diagrams of apropriate study programmes. This course is related to the following study programmes:
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