The Growth of Firms and Industry Dynamics

We are all in admiration of so-called unicorns that experience high growth to reach $1 billion or more in value. But how common are these firms? Can they be predicted in advance? While the popular press often gives a distorted view by focusing on success stories, this course offers a balanced view of the overall structure and dynamics of the population. A “big picture” view is presented first, showing the huge dispersion that persists within business populations in terms of growth rates, age, productivity, and the firm size distribution. Models of industry dynamics (Gibrat's Law, Gamblers' Ruin Theory) are simple and powerful ways of explaining the emergence of the observed distributions. We then summarize economic studies in the area to uncover the characteristics and determinants of firm growth, to enhance our ability to predict which firms will grow. Various firm-level and industry-level theories have been put forward to explain why some firms grow faster than others, and these theories will be discussed, highlighting their strengths as well as their limitations. The course welcomes students who want to pursue their studies and their career in the business world, such as economists and business analysts, investors, financial sector professionals, public policy professionals, and also aspiring entrepreneurs. The student will watch videos, read background materials, participate in discussion fora, and take polls and quizzes as they strengthen their understanding and critical analysis of the modern industry landscape. 3b:T

• Explain the distributions of firm size, firm age, firm-level productivity, and firm growth
• Apply a class of useful models that includes Gibrat's Law and Gambler's Ruin Theory
• Develop an aerial view of the determinants of firm growth that have been reliably identified by researchers
• Conduct a comparison and critical evaluation of various theories of firm growth, that each provide an internally-coherent depiction of certain aspects of firm growth

• No particular prerequisites. The content may include specialist terminology (e.g. business, mathematics) but this will be explained in the course.