Date Topic Handout (including data and do-files) Homework (if any) Week 1 An Assortment of Useful Information: Replication, do-files, and log files. LaTeX and presentation issues. CLARIFY and simulation..
Do-files, Simulation and CLARIFY, notes on LaTeX, LaTeX example, OLS in matrix form.
Week 2 Maximum Likelihood Estimation: Theory and mechanics.
Maximum likelihood estimation
MLE exercise Weeks 3-4 Binary Dependent Variables: Logit, probit, scobit, heteroskedastic probit, rare events logit.
Binary dependent variables
Binary dependent variables exercise Weeks 5-6 Discrete Choice Models: A general framework for discrete chioce models. Multinomial logit, conditional logit, nested logit, multinomial probit, and mixed logit. Simulated maximum likelihood. Week 7 Ordered response models: Ordered probit and logit, generalized ordered logit, heteroskedastic ordered probit.
Ordered response models
Ordered response models exercise Week 8 Event Count Models: Poisson model, negative binomial model, generalized event count model, hurdle model, zero-inflated model.
Event count models
Event count models exercise Week 9 Continuous Time Duration Models: Basic components of duration analysis. Nonparametric models. Parametric models: exponential, weibull, log-logistic, generalized gamma etc.. Semi-parametric models: Cox model. Basic components of duration analysis
Week 10 Discrete Time Duration Models: Logit, probit, cloglog.
Discrete time duration models
Discrete time duration model exercise Week 11 Advanced Duration Models: Frailty models, competing risks models, repeated events models, split population models, duration models with selection. Duration models with selection
Other notes:
Brad Jones notes 1, Brad Jones' notes 2, Brad Jones' notes 3, Chris Zorn's notes 1, Chris Zorn's notes 2, Neal Beck's notes, Steven Jenkin's notes
Week 12 Tobit Models: Truncated and censored data.
Tobit Model
Tobit models exercise Week 13 Selection Models: Heckman model (two-step and MLE). Bivariate probit, bivariate probit with partial observability, and bivariate probit with sample selection. Selection Models Selection models exercise Weeks 14-15 Time Series: Stationary and non-stationary data. Durbin-Watson and LM tests for serial correlation. Cochrane-Orcutt and Prais-Winsten procedures. Lags - finite distributed, ADL etc. Error correction models. Impulse and unit response functions. AR and MA error processes. Tests for stationarity and unit roots. Drifts and trends. Cointegration. Structural stability. Spurious regression. Time series exercise Weeks 16 Longitudinal Data: Panel vs TSCS data. Heterogeneity - fixed vs random effects. GLS, FGLS, Parks Methods, PCSEs etc. Lags. Hurwicz bias.