Causal Inference Part I kickstarts a new 4-day series on design-based causal inference series. It covers the foundations of causal inference grounded in a counterfactual theory of causality built on the Neyman-Rubin model of potential outcomes. It will also cover randomization inference, independence, matching, regression discontinuity and instrumental variables. We will review the theory behind each of these designs in detail with the aim being comprehension, competency and confidence. Each day is 8 hours with 15 minute breaks on the hour plus an hour for lunch. To help accomplish this, we will hold ongoing discussions via Discourse, work through assignments and exercises together, and have detailed walk-throughs of code in R and Stata. This is the prequel to the Part II course that covers difference-in-differences and synthetic control.

Causal inference Part II is a 4-day workshop in design based causal inference series. It will cover three contemporary research designs in causal inference -- difference-in-differences, synthetic control and matching/weighting methods -- as well as introduce participants to causal graphs developed by Judea Pearl and others. Each day is 8 hours with 15 minute breaks on the hour plus an hour for lunch. We will review the theory behind each design, go into detail on the intuition of the estimation strategies and identification itself, as well as explore code in R and Stata and applications using these methods. The goal as always is that participants leave the workshop with competency and confidence. This class will be a sequel to the 4-day workshop on Causal Inference Part I.

This course is intended to be a practical guide for early career economists doing applied research. The nuts and bolts of writing, publishing, and service to the profession are covered in two half-day sessions, each lasting roughly four hours (including short breaks). We begin by providing tips on selecting a research topic, doing a comprehensive literature search, and “pitching” your results. Next, we go through the publication process from choosing a journal to effectively responding to the comments of editors and reviewers. We wrap up by discussing networking, refereeing for economics journals, and getting the most out of conferences and departmental seminars. Each half-day session ends with an optional 30-minute Q&A about the academic job market.

Shift-Share Instrumental Variables (SSIV) are used to address endogeneity and selection challenges in many economic settings. This half-day workshop will introduce the basics of SSIV and cover the recent literature on its econometric foundations. Special focus will be paid on the different assumptions underlying the "exogenous shares" and "exogenous shocks" approaches to SSIV identification, and their practical implications. We will also cover a more general class of instrumental variable strategies combining exogenous shocks and non-random exposure. Group programming exercises will be used to illustrate various theoretical concepts in real-world applications.

Instrumental variables (IV) is a powerful tool for leveraging external ("exogenous") variation to estimate the causal effects of otherwise confounded ("endogenous") variables. This two-day workshop will introduce the basics of IV through different practical examples, formalize the requirements of a valid and powerful IV, and discuss the mechanics of the two-stage least squares (2SLS) estimator. Special focus will be paid on interpreting linear IV under heterogeneous treatment effects and recent advances in judge leniency designs. The course will include substantial group programming exercises, where different IV techniques will be illustrated in real-world applications.

This one-day workshop will cover advanced topics from the recent difference-in-differences literature. One question of particular focus will be, "what should I do if I'm not 100% sure about the validity of the parallel trends assumption?" We will cover a variety of relaxations to the parallel trends assumption, and new tools for power calculations and sensitivity analysis. The workshop will focus not just on the theory, but also on practical implementation in statistical software such as R and Stata.