PhD Courses in Denmark

Dates and time: 6 October 2025 – 10 October

Course overview
This course will cover several recent methodological innovations within economics, including designing information provision experiments, the collection and analysis of open-ended survey data, and modern AI tools.

Information provision experiments
Information provision experiments have become an increasingly common tool in economic research. One of the main goals of the course is to familiarize PhD students with best-practice methods for these types of experiments and provide an introduction to the research frontier. We will try to answer questions such as the following:

• What is the typical structure of a survey experiment in economics?
• How can I address concerns about demand effects, social desirability bias, and external validity?
• What makes a survey experiment publishable in top journals?
• How can recent advances in AI technology make survey experiments more powerful?

There is no good textbook on survey experiments in economics, but there are three complementary reviews that will inform our approach to designing survey experiments, namely Haaland et al. [2023], Stantcheva [2023], Fuster and Zafar [2023], Bursztyn et al. [2025]. ∗Department of Economics, NHH Norwegian School of Economics. E-mail: Ingar.Haaland@nhh.no

Open-ended survey data
In addition to the proliferation of information provision experiments, economists are increasingly using open-ended survey data to understand economic behavior [Haaland et al., 2024]. We will cover recent innovations within this topic, including questions such as:

• Best practices for collecting open-ended survey data
• Advantages and disadvantages compared to structured survey responses
• How to analyze open-ended survey data
• How to scale the collection and analysis of open-ended data using recent AI tools.

AI tools in economics research
The rapid rise of AI tools, such as ChatGPT, is not only transforming businesses and society [Mollick, 2024] but also revolutionizing the way we conduct economic research. This transformation is fundamentally changing the ‘research production function,” unlocking new opportunities to analyse and generate data in ways not possible just a few years ago [Korinek, 2023]. We will cover recent innovations at the intersection of AI and economics and answer questions such as:

• How can I integrate ChatGPT in my own research to become more productive?
• What are some current use cases for AI in economics?
• How can I contribute to the emerging research field at the intersection of AI and economics? While there is no textbook on AI and economics yet, Korinek [2023] provides a good starting point.

Selected research applications
In addition to a broad introduction to information provision experiments, open-ended survey data, and AI tools in economic research, we will cover selected research articles to illustrate many of the key concepts, including (but not limited to):

• Using open-ended survey data to better understand narratives and mental models [Andre et al., 2022]
• Using AI technology to collect qualitative data at scale, including qualitative interviews [Chopra and Haaland, 2023]
• Leveraging AI technology to understand news consumption decisions [Chopra et al., 2024, Braghieri et al., 2024]

Course lecturers: Ingar Haaland, Professor in the Department of Economics at the Norwegian School of Economics (NHH).

Course organizers: Center for Economic Behaviour and Inequality (CEBI), Ida Maria Hartmann and Simon Kyllebæk Andersen.

Language: English.

ECTS: 4.

Max. numbers of participants: 40.

Preparation: It is expected that the students read the references listed below, prior to attending the course.

Registration: Please register via the link in the box no later than 31 August 2025

Course fee: The course is free of charge for PhD students enrolled at the Faculty of Social Sciences, Copenhagen University, and for PhD students enrolled at one of the PhD schools participating in the DGPE research network. Other PhD students will be charged a course fee of DKK 5.000 kr. for participation in the course.

Further information: For more information about the PhD course, please contact the PhD Administration (phd@hrsc.ku.dk).

References
Peter Andre, Ingar Haaland, Christopher Roth, and Johannes Wohlfart. Narratives about the macroeconomy. Discussion Paper 17305, CEPR, 5 2022.

Luca Braghieri, Sarah Eichmeyer, Ro’ee Levy, Markus M. Mobius, Jacob Steinhardt, and Ruiqi Zhong. Article-level slant and polarization of news consumption on social media, 2024. Available at SSRN: https://ssrn.com/abstract=4932600.

Leonardo Bursztyn, Ingar Haaland, Nicolas Roever, and Christopher Roth. The social desirability atlas. Unpublished manuscript, March 2025.

Felix Chopra and Ingar Haaland. Conducting qualitative interviews with AI. Working Paper 10666, CESifo, 2023. Available at SSRN: https://ssrn.com/abstract=4583756 or http://dx.doi.org/10.2139/ssrn.4583756.

Felix Chopra, Ingar Haaland, Fabian Roeben, Christopher Roth, and Vanessa Sticher. Ai customization and the market for news, 2024. Mimeo.

Andreas Fuster and Basit Zafar. Survey experiments on economic expectations. In Handbook of Economic Expectations, chapter 4, pages 107–130. Elsevier, 2023. doi: 10.1016/B978-0-12-822927-9.00010-0.

Ingar Haaland, Christopher Roth, and Johannes Wohlfart. Designing information provision experiments. Journal of Economic Literature, 61(1):3–40, 3 2023. doi: 10.1257/jel. 20211658. URL https://www.aeaweb.org/articles?id=10.1257/jel.20211658.

Ingar K Haaland, Christopher Roth, Stefanie Stantcheva, and Johannes Wohlfart. Understanding economic behavior using open-ended survey data. Working Paper 32421, National Bureau of Economic Research, May 2024. URL http://www.nber.org/papers/w32421.

Anton Korinek. Generative ai for economic research: Use cases and implications for economists. Journal of Economic Literature, 61(4):1281–1317, January 2023. doi: 10.1257/jel.20231736. Ethan Mollick. Co-Intelligence: Living and Working with AI. Portfolio, New York, 1st edition, 2024. ISBN 9780593656656.

Stefanie Stantcheva. How to run surveys: A guide to creating your own identifying variation and revealing the invisible. Annual Review of Economics, 15:205–234, 2023. doi: 10.1146/ annurev-economics-091622-010157. First published online March 27, 202