Technology Economics

Technology firms use large-scale experimentation and empirical analysis to make decisions. Microsoft alone runs tens of thousands of A/B tests a year, and many tested changes, often 70 to 90 percent, do not improve their target metric. Without systematic measurement, firms may adopt ineffective features, set suboptimal prices, or scale decisions that do not work.

The course covers the main methods economists use to answer causal questions and solve empirical business problems: randomized experiments, quasi-experimental methods, and demand estimation. Each method is introduced through its formal framework, the academic literature, and a series of case studies.

The course has two complementary goals. The first is to build a foundation of a practical empirical skill set that economists might use working in the technology sector. The second is to introduce the business context of technology companies: how firms such as Nvidia, Microsoft, Google, and Netflix operate, how to read financial statements, and what incentives arise in two-sided markets such as Uber’s or Airbnb’s.

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