Microeconometrics (4EK664)
Mikroekonometrie (4EK464)
Taught by:
Tomas Formanek
Department of Econometrics
Faculty of Informatics and Statistics
University of Economics, Prague
Requirements and classification
Block 1: Overview of estimation methods for microeconometric tasks
- Linear and generalized linear models
- Instrumental variable regression & diagnostic tests
- Local regression, regression splines
- Generalized addtive models (GAMs)
- Simulation methods in microeconometrics, bootstrap, cross-validation
Case studies and applications
Block 2: Treatment effects analysis
- Treatment effects analysis: introduction to the topic, assumptions, self-selection problem
- Average treatment effect (ATE), average treatment effect of the treated (ATET)
- Differences in differences (DiD) estimator
- Propensity score matching: propensity score, matching methods, diagnostic tests
- Regression discontinuity desig: with deterministic and fuzzy thresholds
Case studies and applications
Block 3: LDVs - Models for binary and count dependent variables
- Binary dependent variable: logit, probit, marginal effects, diagnostic tests
- Binary dependent variable: confusion matrix, ROC curve, separated variable problem, marginal effects for models with interaction terms
- Count-data models: Poisson and NB distributions, estimation, diagnostics, controlling for exposure/offset
- Zero-inflated and hurdle models
Block 4: LDVs - Models for multinomial dependent variables
- Unordered dependent variables: conditional, multinomial, and mixed logit models, models with hierarchical structure
- Ordered dependent variables: estimation methods, marginal effects, interpretation
- Discrete choice experiments (DCEs): stated and revealed preferences (basic steps for designing and evaluating DCEs)
Case studies and applications
Block 5: LDVs - Other types of limited dependent variables
- Censored and truncated data, Tobit model
- Heckit (sample selection models)
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