I have taught a range of courses from strategic management to corporate governance to quantitative methods and econometrics. Examples include:
This is a survey course on corporate governance. It studies the relationship between the firm and its owners. Managing owners and other external stakeholders is a core part of senior leaders’ job. On the other side, the firm’s owners need to be able to effectively control the behavior of management if they are to protect their investments. This course aims to train students to deal with corporate governance issues from both sides of the table.
The course objectives are:
To prepare students for leadership roles in firms as CEOs, entrepreneurs or senior managers. We will learn about the core issues that leaders face in managing investors and other stakeholders, and the strategies that they can pursue to manage them.
To understand and learn the about the tools that are available to investors to control companies, and the problems that they can face.
To educate students in the responsibilities they might face as directors of companies, and how they can be effective in these roles.
To give students an overview of how business activities fit into broader society, by discussing who should control the firm, and the goals they should pursue.
To provide a solid understanding of core corporate governance issues that routinely affect global businesses. These include: the board of directors, executive compensation, mergers and acquisitions, ownership and control of firms, and regulatory compliance.
I teach courses in quantitative methods with application to business and social sciences. My courses cover the general linear model (GLM) and estimation by OLS. The course moves on to evaluate contemporary methods in quantitative research including:
Panel data econometrics (static and dynamic). The course discusses the advantages of panel data techniques and what problems it does and does not resolve.
Endogenous variables and instrumental variables. A central problem when trying to claim causal effects in social sciences is that most variables of interest are not exogenous. Instrumental variable estimation is one solution to this. The importance of identification is discussed.
Contemporary methods for identifying causal effects in social science research. This includes a discussion of average treatment effects (ATE), difference-in-difference methods (DiD), propensity score matching, regression discontinuity design (RD), quasi and random experiments and so on. The goal is to show how increasingly sophisticated research design and empirical methods can be helpful to researchers to isolate causal effects.