Behavioral economics uses the concepts and tools of economics to build an understanding of human behavior that is grounded in relatively realistic assumptions. It combines the empirical and theoretical rigor that characterize modern economics with insights from psychology and sociology about hidden drivers of human behavior. Environmental economics, on the other hand, is a broad set of approaches to understanding how people interact with the environment and natural resources – the things we get from the natural world (everything from minerals to fresh air to the pleasure we get from experiencing nature) and the things we put into it (such as pollution). Many environmental problems are modeled and understood using core behavioral models. In this course, we will study the intersection of the two fields, focusing on environmental applications of behavioral topics. We will start by understanding approaches to research in these fields through theory, experiments, observational data and surveys. Next, we will explore rational unselfishness, including altruism and reciprocity, which can give rise to voluntary pro-environment behavior. We’ll introduce the behavioral economics of choice under risk and of intertemporal choice, which are crucial to environmental problems like climate change. And, time permitting, we’ll study various biases and ways in which people can be nudged, intentionally or unintentionally, including to protect the environment.

Data-driven decision-making and analytical thinking are essential skills for success in today’s business environment. The demand for analytics expertise continues to grow, and in many cases, it has become a core requirement for business professionals. The rise of digital technologies — such as personal electronic devices, social media and e-commerce — has led to an exponential increase in the volume of data generated and collected every day. Organizations are eager to extract insights from this data to gain a competitive edge. To effectively work with large volumes of structured and unstructured data, coding skills are increasingly necessary. This introductory course offers a foundation in analytics, with a focus on using Python for data analysis. Students will explore real-world applications and gain hands-on experience with Python tools and techniques.

One or both of the following research seminars will be offered, each demonstrating how financial and economic research can support the global transition to a sustainable and low-carbon economy. Together, these seminars highlight the role of economic research in addressing climate change and promoting an energy-sustainable future.

• The climate finance seminar focuses on how public and private investment can drive low-carbon development and climate adaptation.
• The environmental and energy economics seminar examines how market forces and policy tools shape energy use, emissions and the adoption of renewable technologies.

Step into the role of a decision-maker in a global industry. In this hands-on, simulation-based course, you and your teammates will run your own company, making real business choices about product design, pricing, advertising, promotions and sales. Over 12 rounds of play, you’ll see how your decisions shape the company’s performance, using market reports and analysis tools to guide your strategy. By the end, you’ll have a taste of what it’s like to think like a business leader — analyzing data, collaborating with a team,and competing to succeed in a fast-paced market.