Advanced Applied Econometrics

Fall 2024/2025


Office hours: MS Teams, by appointment via email.
E-mail: jmuck[at]sgh.waw.pl.

Homework #1 [.pdf]

Exercises [.pdf]
Datasets: AcemogluEtAl2001[.dta] , Anscombe[.dta] , Angrist_Krueger_1992[.dta] , birthweight[.dta] , chilean[.dta] , cig85_95[.dta] (SW), cps[.dta] (POE) , ConsumptionUS[.dta] , COVID2020[.dta] , EAInflation[.dta] , EKC[.dta] , Gravity[.dta] , GermanInflation[.dta] , hicp[.dta] , ice creams (UCLA) [.dta] , InternationalTradePoland[.dta] , USPhillipsCurve[.dta], mroz[.dta] (POE) , njmin3[.dta] (POE) , nkpc[.dta] , patents[.dta] (Woldridge) , SEM[.dta] , star[.dta] (POE) , utown[.dta] (POE), USMacro[.dta], VAR2[.dta] , VAR1[.dta] , VAR_UK[.dta] , WorldTradeCPB[.dta] .
Probability distribution and cumulative distribution in Stata: [link]
Useful Stata commands: [link]
Codes:

Course materials

  1. Linear regression. Least squares estimator. Asymptotic properties. Gauss-Markov theorem
    Presentation: [.pdf]
  2. Testing economic hypotheses. Multiple hypothesis testing. Linear and non-linear hypotheses. Confidence intervals. Delta method.
    Presentation: [.pdf]
  3. Verifying key assumptions: normality, colinearity and functional form. Goodness-of-fit.
    Presentation: [.pdf]
  4. Heteroskedasticity and serial correlation. Generalized least squares estimator. Weighted least squares. Robust and clustered standard errors.
    Presentation: [.pdf]
  5. Endogeneity. Instrumental variables estimation. Properties of instrumental variables.
    Presentation: [.pdf]
  6. Simultaneous equations model, Parameter identification problem, Estimation method for SEM
    Presentation: [.pdf]
  7. Time series. Stationarity, spurious regression and cointegration
    Presentation: [.pdf]
  8. Autoregressive distributed lags models. Vector Autoregression (VAR) models. Structural VAR.
    Presentation: [.pdf]
  9. Panel data. Between and within variation. Random and fixed effects models. Between regression. Hausman-Taylor estimator.
    Presentation: [.pdf]
  10. Limited dependent variable. Models for binary and multinomial outcome variable. Count data models. Tobit regression. Panel data and limited dependent variable.
    Presentation: [.pdf]
  11. Generalized method of moments. Selected applications
    Presentation: [.pdf]
  12. Dynamic panel data models. Nickell's Bias. Anderson-Hsiao estimator. Arellano-Bond estimator. System GMM estimator.
    Presentation: [.pdf]
  13. Estimating treatment effects. Difference-in-differences.
    Presentation: [.pdf]