Introduction

Chapter 1 — Introduction Experimentation is the sharpest tool available for solving the causal inference problem. This chapter frames the book around two Experimental Problems: EP1—quantifying economic fundamentals, measuring treatment effects, and identifying key mediators and moderators in an ethically responsible manner—and EP2—predicting whether the causal impacts of treatments from one environment transfer to spatially, temporally, scale-, or population-differentiated environments. The chapter introduces the general potential outcomes framework, the role of internal and external validity, and lays out the book’s game plan for building from foundations to practice.

1. Causal inference is challenging because the same unit cannot be observed in more than one state of the world simultaneously.
2. Experimentation is a vital tool used to solve the causal inference problem, allowing us to lend insights into two Experimental Problems.
3. Experimental Problem 1 (EP1) pertains to quantifying economic fundamentals, measuring treatment effects, and identifying key mediators and moderators in an ethically responsible manner.
4. Experimental Problem 2 (EP2) relates to predicting whether the causal impacts of treatments from one environment transfer to spatially, temporally, scale-, or population-differentiated environments.