2026 UK Stata Conference Workshop Using Stata for the New Difference-in-Differences with Panel Data

2026 UK Stata Conference Workshop Using Stata for the New Difference-in-Differences with Panel Data

Este completo curso introductorio de matemáticas está diseñado para dotar a los estudiantes de los conocimientos y habilidades fundamentales necesarios para destacar en cursos de econometría, incluyendo cálculo y álgebra lineal. Mediante una instrucción rigurosa, los estudiantes desarrollarán una comprensión profunda de los conceptos matemáticos y sus aplicaciones.

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150,00 €
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2 días
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Overview

This comprehensive two-day introductory mathematics course equips students with essential mathematical tools required for success in econometrics. With a focus on both linear algebra and calculus, students will gain the theoretical grounding and problem-solving skills needed to confidently tackle statistical modelling and data analysis.

Course Aims & Objectives
  • Provide foundational knowledge in key mathematical areas including calculus and linear algebra.
  • Prepare students to engage with advanced econometric techniques such as regression analysis and maximum likelihood estimation.
  • Develop mathematical reasoning skills applicable across economics, statistics, and quantitative research.
Key Skills Acquired

By the end of the course, students will understand:

  • Systems of linear equations and solution methods.

  • Matrix operations, transposition, determinants, and inverses.

  • Vector spaces, eigenvalues, and quadratic forms.

  • Calculus basics: derivatives, differentials, concavity/convexity.

  • Techniques in unconstrained optimisation for functions of a single variable.

Learning Outcomes
  • Mathematical Foundations: Gain essential knowledge in algebra and calculus to support the study of econometrics.
  • Proficiency in Mathematical Techniques: Understand and apply key mathematical tools used in econometric analysis.
  • Quantitative Skills: Develop skills in handling data, constructing models, and interpreting mathematical results.
  • Critical Thinking: Apply logical reasoning and structured problem-solving approaches to real-world economic problems.
Course Structure

Delivery Format: Two-Day Intensive

  • Lectures: 4 sessions (2 hours each)
  • Tutorials/Workshops: 2 sessions (1 hours each)

Agenda

Day 1:

Lecture 1: Linear Systems, Matrices & Operations
  • Systems of linear equations
  • Solving systems: substitution, elimination
  • Matrix notation & basic operations
  • Transposition
Tutorial 1: Hands-on applications
  • Solving economic models using matrix equations (e.g., input-output analysis)
  • Real-time problem-solving using short exercises

 

Lecture 2: Determinants, Inverses & Eigenvalues
  • Determinants and properties
  • Inverse of 2.2 and 3.3 matrices
  • Cramer’s Rule
  • Intro to eigenvalues & diagonalisation (essential conceptual grounding)
Tutorial 2: Applications
  • Working with matrix inversion in economic models
  • Identifying stability via eigenvalues in simple dynamic systems
Day 2:

Lecture 3: Calculus Basics and Differentiation
  • Derivatives and differentials
  • Rules of differentiation
  • Concavity, convexity, inflection points
  • Taylor expansion and Mean Value Theorem
Tutorial 3: Applications
  • Marginal analysis
  • Cost, revenue and profit functions
  • Approximating functions with Taylor Series
Lecture 4: Optimisation Techniques
  • First and second-order conditions
  • Unconstrained optimisation
  • Optimisation over closed intervals
Tutorial 4: Applications of Optimisation
  • Maximising/minimising utiity and profit functions
  • Economic interpretation of first and second-order conditions
  • Real-world problems using optimisation (e.g cost minimisation, revenue maximisation)
  • Introduction to interpreting mathematical results in the context of econometric models (e.g. MLE intuition via univariate log-likelihoods)

Course Timetable

Subject to minor changes
Day Morning Session Afternoon Session
Day One 10am-1pm (London time) 2pm-5pm (London time)
Day Two 10am-1pm (London time) 2pm-5pm (London time)

Reading List

Surveys for Background Reading:

  • de Chaisemartin, C., and X. D'Haultfœuille (2023), “Two-Way Fixed Effects and Differences-in-Differences with Heterogeneous Treatment Effects: A Survey,” Econometrics Journal 26, C1-C30
  • Roth, J., P.H.C. Sant’Anna, A. Bilinksi, and J. Poe (2023), “What’s Trending in Difference-in-Differences: A Synthesis of the Recent Econometrics Literature,” Journal of Econometrics 234, 2218-2244.
  • Baker, A., B. Callaway, S. Cunningham, A. Goodman-Bacon, P.H.C. Sant’Anna (2026), “Difference-in-Differencs: A Practitioner’s Guide,” Journal of Economic Literature 64, 498-557.
  • Wooldridge, J.M (2026), “Recent Advances in Difference-in-Differences with Panel Data,” manuscript.

 

Journal Articles

  • Borusyak, K., X. Jaravel, and J. Spiess (2024), “Revisiting Event Study Designs: Robust and Efficient Estimation,” Review of Economic Studies 91, 3253-3285.
  • Callaway, B. and P.H.C. Sant'Anna (2021), “Difference-in-Differences with Multiple Time Periods,” Journal of Econometrics 225, 200-230.
  • Goodman-Bacon, A. (2021), “Difference-in-Differences with Variation in Treatment Timing,” Journal of Econometrics 225, 254-277.
  • Lee, S.J., and J.M. Wooldridge (2026), “A Simple Transformation Approach to Difference-in-Differences Estimation for Panel Data,” forthcoming, Journal of Business and Economic Statistics.
  • Lee, S.J., and J.M. Wooldridge (2026), “Simple Approaches to Inference with Difference-in-Differences Estimators with Small Cross-Sectional Sample Sizes,” working paper. https://papers.ssrn.com/sol3/Delivery.cfm?abstractid=5325686
  • Roth, J. (2022), “Pre-test with Caution: Event-study Estimates After Testing for Parallel Trends,” American Economic Review: Insights 4, 305-322.
  • Sun, L. and S. Abraham (2021), “Estimating Dynamic Treatment Effects in Event Studies with Heterogeneous Treatment Effects,” Journal of Econometrics 225, 175-199.
  • Wooldridge, J.M. (2023), “Simple Approaches to Nonlinear Difference-in-Differences with Panel Data,” Econometrics Journal 26, C31-C66.
  • Wooldridge, J.M. (2025), “Two-Way Fixed Effects, the Two-Way Mundlak Regression, and Difference-in-Differences Estimators,” Empirical Economics Volume 69, 2545–2587.

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