Design Based Causal Inference in Collaborative Governance Research

Course: PAD 6025 Theoretical Perspectives in Public Policy

  • Fall 2022
  • Level: Doctoral

Introduction: This lecture underscores the importance of causal inference in public administration research, particularly within the realm of collaborative governance. It elucidates the application of both experimental and observational data to examine collaborative behaviors and outcomes in policy implementation processes. The methodologies discussed in this lecture encompass survey and field experiments, as well as natural experiments, which include difference-in-differences, regression discontinuity, synthetic control, and instrumental variable methods. The lecture presents three empirical examples drawn from my recent work in environmental policy and management. These topics include watershed management, air pollution control, and sustainable development.

Open Science in Public Management

Course: PAD 6707 Logics of Inquiry

  • Fall 2021
  • Level: Doctoral

Introduction: This lecture promotes the concept of open science within the realm of public management research, highlighting the detrimental effects of unethical practices such as p-hacking and data manipulation. It also discusses the recent publication crisis spanning several social and natural science disciplines. Building on this context, I articulate why open science is essential for public management research. Finally, I share my experiences of applying open science principles into my own research, covering the entire process from pre-registration and data collection to publication, complete with open data and open code.

Conjoint Analysis in Social Science

Course: PAD 6025 Theoretical Perspectives in Public Policy

  • Fall 2020
  • Level: Doctoral

Introduction: This lecture introduces the conjoint analysis method. Conjoint analysis is an experimental technique commonly used in social sciences to understand how individuals make decisions based on multiple attributes simultaneously. This method can efficiently test and compare multiple theories in a single experiment and derive their causal quantities within an integrated model. The lecture provides a detailed explanation of the theoretical basis of this method, as well as an empirical example from my recent research. Furthermore, it offers a hands-on tutorial for students to implement this method.

Behavioral Science and Sustainability

Course: PAD 5935 Governing Sustainable Communities

  • Fall 2019
  • Level: Doctoral & Master

Introduction: This lecture introduces how to “nudge” people’s conservation behaviors. The lecture also discusses employing experimental methods for conducting behavioral research in the field of sustainable development.

Experimental Methods in Social Science

Course: PAD 5701 Research Methods

  • Fall 2018
  • Level: Master

Introduction: This lecture provides a comprehensive overview of experimental methods widely employed in social science research. It delves into various techniques, highlighting their practical application in generating reliable, causal insights. The importance of randomized control trials and other experimental designs, including field, lab, and survey experiments, is discussed. Real-world examples and hands-on activities further enhance the understanding of these methods, emphasizing their essential role in answering complex social science questions.