Lasha Chochua

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Bachelor's course · ISET · 2026

Econometrics 2

This undergraduate course develops multiple regression analysis, statistical inference, nonlinear specifications, causal assessment, instrumental variables, panel data, binary response models, and experimental methods. Lecture slides, problem sets, solutions, and computational materials are available below.

Lecture Slides

01Review of Probability and StatisticsProbability, random variables, sampling, and statistical foundations.PDF 02Multiple RegressionLinear regression with multiple regressors.PDF 03OLS in Matrix NotationThe linear regression model and OLS using matrix algebra.PDF 04AOLS Properties and Hypothesis TestingSmall- and large-sample properties and statistical tests.PDF 04BThe Delta MethodNonlinear transformations and asymptotic inference.PDF 05AHeteroskedasticityHeteroskedastic errors, inference, and robust methods.PDF 05BNonlinear Regression FunctionsNonlinear specifications and interpretation.PDF 06Assessing Multiple Regression StudiesInternal validity, causal effects, and threats to identification.PDF 07AInstrumental Variables, Part IEndogeneity, instruments, and two-stage least squares.PDF 07BInstrumental Variables, Part IIInstrument validity and further IV analysis.PDF 08Regression with Panel DataLongitudinal data, fixed effects, and panel regression.PDF 09Binary Dependent VariablesRegression models for binary outcomes.PDF 10Experiments and Quasi-ExperimentsExperimental designs and quasi-experimental evidence.PDF 11Course SummaryA review of causal interpretation, threats to validity, IV, panel methods, difference-in-differences, and regression discontinuity.PDF

Recitations and Solutions

Problem sets and their corresponding solutions.

01Problem Set 1 Problem Set Solutions

02Problem Set 2 Problem Set Solutions

03Problem Set 3 Problem Set Solutions

04Problem Set 4 Problem Set Solutions

05Problem Set 5 Problem Set Solutions

06Problem Set 6 Problem Set Solutions

07Problem Set 7 Problem Set Solutions

08Problem Set 8 Problem Set Solutions

09Problem Set 9 Problem Set Solutions

10Problem Set 10 Problem Set Solutions

11Problem Set 11 Problem Set Solutions

Computing and Supplementary Materials

Probability in RSelf-study notebook on probability distributions and simulation.IPYNB LLN, CLT, and BootstrappingComputational illustrations of sampling and asymptotic ideas.IPYNB OLS versus GLSNotebook comparing ordinary and generalized least squares.IPYNB Heteroskedasticity TestingApplied testing and robust inference exercises.IPYNB Birthweight and Smoking ExerciseAn applied regression exercise in R.IPYNB OLS: Full DerivationA worked derivation of the OLS estimator.PDF VS Code Setup for WindowsInstallation and setup instructions for the course.PDF VS Code Setup for macOSInstallation and setup instructions for the course.PDF