Applied Microeconometrics

A rigorous, cutting-edge overview of the range of methods used to conduct causal inference in the social sciences.

This textbook provides a lucid, rigorous, and cutting-edge overview of the methods used to conduct causal inference in the social sciences, covering all the core techniques and latest advances. Offering a detailed survey of the current state of microeconometric theory, Damian Clarke delves deeply into machine learning applications and presents developments in difference-in-difference methods, instrumental variables, multiple hypothesis testing, and other advanced topics. With a diverse range of examples and exercises offering hands-on experience, Applied Microeconometrics equips graduate students and researchers to apply state-of-the art scholarship to actionable problems.

• Integrates a rich array of machine learning methods into causal modeling frameworks
• Covers recent advances in difference-in-differences and dynamic research designs, formal discussions of challenges related to inference and hypothesis testing, and heterogeneity analysis
• Features a breadth of real-world examples from recent papers
• Includes coding implementation in Python, R, and Stata

• Publication date: 9 June 2026
• Page count: 384
• Dimensions: Height 203 mm; Width 229 mm; Thickness 27 mm
• Publisher: MIT Press Ltd
• Format: Paperback
• ISBN-13: 9780262053648