KPHD 520-0 Workshop on Research Development (0.5 Unit)  

PhD students present new research ideas to faculty and students. Students must situate their ideas in a relevant literature, outline the type of results/analysis that the student expects to carry out, and most importantly, the potential contributions. Emphasis will be placed on the evaluating the viability of research ideas as job market papers.

KPHD 525-0 Data-Driven Theory (1 Unit)  

This course focuses on "data-driven" economic theory---that is, papers that take the theory seriously and in combination with data aim to make prescriptive recommendations; for example, how to design a performance pay plan given workers’ productivity data, or how to design an internal labor market. We will cover papers from several literatures including mechanism design and auctions, contract theory, market design, internal labor markets, taxation, and social insurance. Deliverables include several presentations (a central goal of this course is to hone your presenting skills), evaluations of peers’ presentations, and a paper project.

KPHD 530-0 Idea Incubator for Behavioral Science (1 Unit)  

The course challenges students to enhance their ability to generate, nurture and critique research ideas and relies heavily on group interaction, peer review, student presentations, and faculty coaching. Students will pick and then strengthen a publishable idea, and present their work to peers and faculty. By the end of the quarter students will have two refined research ideas. The course welcomes students in all years and programs who have an interest and emphasis in behavioral science (e.g., economics, management, marketing, psychology, sociology, etc.).

KPHD 540-0 Computational Social Science: Methods and Applications (1 Unit)  

This course is designed to prepare PhD students for computational social science (CSS) research. These skills include data acquisition, null model design and programming, and data mining for structured and unstructured data.

Prerequisites: Students must be proficient in basic Python programming. Students may either take NICO 101-0 and NICO 102-0 or complete lessons on Datacamp (python for data science, data science toolbox, pandas, and importing data lessons).