Code & Data
Teaching code, notebooks, and data
Find course supports, exercises, datasets, programs, notebooks and simulators, organized by course and session. The Homogeneity teaching note has its own Python and R replication code and practical instructions.
CY Cergy Paris Université · 2026/2027
Econometrics — L3
Chapter-based exercises, teaching datasets, and previous continuous assessments with supplied answer keys.
Chapter exercises
Exercise sheets
- Chapter I — Introduction and simple regressionPDF · Open resource
- Chapter II — Simple regression applicationsPDF · Open resource
- Chapter III — Probability and random variablesPDF · Open resource
- Chapter IV — Inference in simple regressionPDF · Open resource
- Chapter V — Estimator propertiesPDF · Open resource
- Chapter VI — Multiple regression applicationsPDF · Open resource
- Chapter VII — Hypothesis tests and specificationPDF · Open resource
- Chapter VIII — Functional form and model comparisonPDF · Open resource
Previous continuous assessments (CC)
Course supports
- CC 2017-18 — Question paperPDF · Open resource
- CC 2018-19 — Question paperPDF · Open resource
- CC 2019-20 — Question paperPDF · Open resource
- CC 2021-22 — Question paperPDF · Open resource
- CC 2022-23 — Question paperPDF · Open resource
- CC 2022-23 — Answer keyPDF · Open resource
- CC 2023-24 — Question paperPDF · Open resource
- CC 2024-25 — Question paperPDF · Open resource
- CC 2024-25 — Answer keyPDF · Open resource
Teaching datasets
Data
- BWGHTCSV · bwght.csvDES · BWGHT.DESRAW · BWGHT.rawSAS7BDAT · bwght.sas7bdatXLS · bwght.xls
- CAMPUSDES · campus.desRAW · campus.rawXLS · campus.xls
- CEOSAL1DES · CEOSAL1.DESRAW · CEOSAL1.rawXLS · ceosal1.xls
- GPA1DES · GPA1.DESRAW · GPA1.rawXLS · gpa1.xls
- GPA2CSV · gpa2.csvDES · GPA2.DESRAW · gpa2.rawSAS7BDAT · gpa2.sas7bdatXLS · gpa2.xls
- HPRICE1CSV · hprice1.csvDES · HPRICE1.DESRAW · hprice1.rawSAS7BDAT · hprice1.sas7bdatXLS · hprice1.xls
- HPRICE2CSV · hprice2.csvDES · HPRICE2.DESRAW · HPRICE2.rawSAS7BDAT · hprice2.sas7bdatXLS · hprice2.xls
- HTVCSV · htv.csvDES · htv.desRAW · htv.rawSAS7BDAT · htv.sas7bdatXLS · htv.xls
- JTRAINDES · JTRAIN.DESRAW · JTRAIN.rawXLS · jtrain.xls
- MEAP93DES · meap01.desRAW · meap01.rawXLS · meap01.xlsDES · MEAP93.DESRAW · MEAP93.rawXLS · meap93.xls
- NBASALCSV · nbasal.csvDES · nbasal.desRAW · nbasal.rawSAS7BDAT · nbasal.sas7bdatXLS · nbasal.xls
- RDCHEMCSV · rdchem.csvDES · RDCHEM.DESRAW · RDCHEM.rawSAS7BDAT · rdchem.sas7bdatXLS · rdchem.xls
- RENTALCSV · rental.csvDES · RENTAL.DESRAW · RENTAL.rawSAS7BDAT · rental.sas7bdatXLS · rental.xls
- TWOYEARDES · twoyear.desRAW · twoyear.rawXLS · twoyear.xls
- WAGE1DES · WAGE1.DESRAW · WAGE1.rawXLS · wage1.xls
Complete downloads
- Teaching dataset collection — original formats and dictionariesZIP · Open resource
CY Cergy Paris Université · 2026/2027
Econometrics — M1
An exercise collection covering regression foundations, matrix formulation, inference, heteroskedasticity, nonlinear least squares, and instrumental variables.
Course materials
Exercise sheets
- Econometrics exercisesPDF · Open resource
Mock exam 2
Mock exams
- Mock exam 2 — Question paperPDF · Open resource
- Mock exam 2 — SolutionsPDF · Open resource
Mock exam 3
Mock exams
- Mock exam 3 — Question paperPDF · Open resource
- Mock exam 3 — SolutionsPDF · Open resource
Mock exams — Complete download
Complete downloads
- Mock exams 2 and 3 — Question papers and solutionsZIP · Open resource
CY Cergy Paris Université · 2026/2027
Econometrics — M2 & PhD
An advanced exercise collection on linear models, inference, instrumental variables, maximum likelihood, and generalized method of moments.
Course materials
Exercise sheets
- Advanced econometrics exercisesPDF · Open resource
Mock exam 2
Mock exams
- Mock exam 2 — Question paperPDF · Open resource
- Mock exam 2 — SolutionsPDF · Open resource
Mock exam 4
Mock exams
- Mock exam 4 — Question paperPDF · Open resource
- Mock exam 4 — SolutionsPDF · Open resource
Mock exams — Complete download
Complete downloads
- Mock exams — Available question papers and solutionsZIP · Open resource
Sciences Po Saint-Germain-en-Laye · 2026/2027
Microeconomics — L1
Session 1 introduces consumers, producers, price elasticity, market efficiency, transfers, and deadweight loss.
Course materials
Course supports
- Session 1 — Consumers, producers, and market efficiencyPDF · Open resource
Supplements & readings
- Session 1 — Accompanying readingsZIP · Open resource
Université Catholique de l’Ouest · 2026/2027
Microeconomics III — L3
Microeconomic foundations, strategic decisions and Nash equilibrium, followed by risk, insurance, portfolio choice and private information, with exercises, Python/R programs and interactive simulators.
Part I — Foundations
Course supports
- Séance 1 — Introduction généralePDF · Open resource
Part II — Strategic decisions and games
Course supports
- Séances II à IV — Théorie des jeux : décisions stratégiques et équilibre de NashPDF · Open resource
Exercise sheets
- Exercise series 1 — Game theory and competitive strategiesPDF · Open resource
Simulators
- Simulateur — Jeux répétésInteractive HTML · Open resource
- Simulateur — Pile ou faceInteractive HTML · Open resource
Part III — Risk and information
Course supports
- Part III — Course support (sessions V–VIII)PDF · Open resource
Exercise sheets
- Exercise series 5PDF · Open resource
- Exercise series 6PDF · Open resource
- Exercise series 7PDF · Open resource
- Exercise series 8PDF · Open resource
Supplements & readings
- Supplement — Pindyck & RubinfeldPDF · Open resource
- Supplement — VarianPDF · Open resource
Code
- Annex-generation utilityPython · Open resource
- Course figures and calculationsPython · partie3.pyR · partie3.R
Simulators
- Information cascade simulatorInteractive HTML · Open resource
- Portfolio choice simulatorInteractive HTML · Open resource
- Diversification and correlation simulatorInteractive HTML · Open resource
- Risk pooling simulatorInteractive HTML · Open resource
Practical instructions
- Practical READMEHTML · Open resource
Complete downloads
- Complete folder — supports, code, data and supporting checksZIP · Open resource
Self-assessment — Game theory and risk
Self-assessment
- Online practice quiz (QCM) — Game theory and riskInteractive HTML · Open resource
Complete downloads
- Practice quiz — Complete downloadZIP · Open resource
Université Catholique de l’Ouest · 2026/2027
Econometrics — L3
Session 1 introduces covariance, correlation, descriptive evidence, and simple regression. Session 2 develops sampling, probability, estimator distributions and inference, with course and exercise code in Python, R and Stata, notebooks, data and interactive simulators.
Practical instructions
Practical instructions
- Practical READMEHTML · Open resource
Session 1 — Covariance, correlation and regression
Course supports
- Course supportPDF · Open resource
Exercise sheets
- Exercise sheetPDF · Open resource
Notebooks
Code
- Annex-generation utilityPython · Open resource
- Data export utilityPython · Open resource
- CourseStata · seance01.doPython · seance01.pyR · seance01.R
- ExercisesStata · td01.doPython · td01.pyR · td01.R
Data
- Dataset — attendStata data · Open resource
- Dataset — cps78_85Stata data · Open resource
- Dataset — econmathStata data · Open resource
- Dataset — jtrain2Stata data · Open resource
- Dataset — phillipsStata data · Open resource
- Dataset — wagepanStata data · Open resource
- Dataset — wineStata data · Open resource
Simulators
- Interactive covariance simulatorInteractive HTML · Open resource
Complete downloads
- Complete folder — supports, code, data and supporting checksZIP · Open resource
Session 2 — Sampling, probability and inference
Course supports
- Course supportPDF · Open resource
Exercise sheets
- Exercise sheetPDF · Open resource
Notebooks
Code
- Annex-generation utilityPython · Open resource
- Data export utilityPython · Open resource
- CourseStata · seance02.doPython · seance02.pyR · seance02.R
- ExercisesStata · td02.doPython · td02.pyR · td02.R
Data
- Dataset — attendStata data · Open resource
- Dataset — cps78_85Stata data · Open resource
- Dataset — econmathStata data · Open resource
- Dataset — htvStata data · Open resource
- Dataset — jtrain2Stata data · Open resource
- Dataset — nbasalStata data · Open resource
- Dataset — phillipsStata data · Open resource
- Dataset — wagepanStata data · Open resource
- Dataset — wineStata data · Open resource
Simulators
- Interactive sampling simulatorInteractive HTML · Open resource
Complete downloads
- Complete folder — supports, code, data and supporting checksZIP · Open resource
Self-assessment — Sessions 1 and 2
Self-assessment
- Online practice quiz (QCM) — Simple regression and OLS propertiesInteractive HTML · Open resource
Complete downloads
- Practice quiz — Complete downloadZIP · Open resource
CY Cergy Paris Université · 2026/2027
Data Analysis with Python — L3
Five applied sessions on price indices, unemployment, data cleaning, dataset merges, and income distributions, with source data and reproducible Python notebooks.
TD01
Exercise sheets
- TD01 — Price indices: instructionsPDF · Open resource
Notebooks
- TD01 — Price indices: notebookJupyter notebook · Open resource
Complete downloads
- Complete folder — supports, code, data and supporting checksZIP · Open resource
TD02
Course supports
- TD02 — Presentation slidesPDF · Open resource
Exercise sheets
- TD02 — Unemployment: instructionsPDF · Open resource
Notebooks
- TD02 — Unemployment: notebookJupyter notebook · Open resource
Complete downloads
- Complete folder — supports, code, data and supporting checksZIP · Open resource
TD03
Course supports
- TD03 — Presentation slidesPDF · Open resource
Exercise sheets
- TD03 — Wage data: instructionsPDF · Open resource
Supplements & readings
- TD03 — Wage data: dictionaryPDF · Open resource
Notebooks
- TD03 — Wage data: notebookJupyter notebook · Open resource
Data
- TD03 — Wage data: CSVCSV · Open resource
Complete downloads
- Complete folder — supports, code, data and supporting checksZIP · Open resource
TD04
Course supports
- TD04 — Presentation slidesPDF · Open resource
Exercise sheets
- TD04 — Dataset merges: instructionsPDF · Open resource
Supplements & readings
- Additional course notesPDF · Open resource
Notebooks
- TD04 — Dataset merges: notebookJupyter notebook · Open resource
Complete downloads
- Complete folder — supports, code, data and supporting checksZIP · Open resource
TD05
Course supports
- TD05 — Presentation slidesPDF · Open resource
Exercise sheets
- TD05 — Income distributions: instructionsPDF · Open resource
Notebooks
- TD05 — Income distributions: notebookJupyter notebook · Open resource
Data
- cm03-salaires.csvCSV · Open resource
Practical instructions
- Session instructions — HTMLInteractive HTML · Open resource
Complete downloads
- Complete folder — supports, code, data and supporting checksZIP · Open resource
Teaching Note · October 2021
Homogeneity — Teaching Note replication code
Python and R programs derive the restrictions, generate the figures, run the simulations and compare the estimates. The supplied simulation data and output tables accompany the code.