Economics of Culture – Applied Methods

Course content

Purpose. The purpose of the course is two-fold: One purpose relates to the topic of the course; to give students an understanding of how cultural values may influence society. The idea of the literature is that our cultural values influence how we act, including how we act as economic agents. When working with the topic, we will go through the literature, including both theoretical and empirical models to further our understanding of how cultural values impact society. The second purpose relates to the method; to teach students the application and intuitive interpretation of microeconometric methods in micro- and macroeconomic research. When working with the method, we will also focus on how to conduct independent research, relevant for master theses, seminars, and the later real-world problems.

Topic. The broad questions asked is “Why are some societies richer, more educated, more democratic, less prone to conflict, or happier than others?” Some proximate answers is that some societies have obtained higher productivity and investment rates in human- and physical capital. We go deeper to ask why some societies then are so much more productive and invest more than others, experience less conflict, and are more likely to be democratic? The answers to this deeper question can be grouped into three categories: culture, institutions, and geography. This course will focus on the role of culture, which means for instance the role of trust, religion, or individualism in society. We will pay extra attention to religion, which may influence both the cultural values of the inhabitants of a society and the institutions that surround them. For instance, religions often have different rules that get ingrained into the culture of a society, thus influencing peoples’ actions.

Method. The course includes a hands-on introduction to relevant methods that are common in several economics fields. Empirical research in macroeconomics has seen a great leap forward with the emergence of Big Data, which has been used in microeconomic research for some time. During the course, the students will work with the data behind some of the main papers themselves, learning the intuition behind the micro-econometric analysis, and learn how to make sound choices and arguments, how to construct variables useful for micro-econometric analysis, and how to present results in an intuitive way. The main part of the course will focus on the intuition behind econometric techniques that students have already learnt in other courses. In addition, we will introduce one method that may be new to some; handling spatial data. Spatial data includes all data that can be visualized on a map. With fairly easy techniques, students will be able to calculate different variables based on these maps.

 

The course will start with two broad lectures on the economics of culture field. The remaining lectures will focus on the following three topics. Each topic introduces a question and a method and will commence with a lecture by Jeanet introducing the topic, followed by an exercise session, where students work with the method and data themselves, instructed by Jeanet. While the topics spans various research, the concrete datasets consist mainly of data from Jeanet’s own research, but the datasets are broad enough for the students to employ them to investigate other cultural dimensions and other economic outcomes.

Topic 1. What determines democracy? We will explore answers to this questions based on differences in cultural values. For instance, what role does the cultural dimensions individualism / collectivism play in the emergence of democracies. We will also explore how religion influences the transition from autocracy to democracy. For instance, we will work with empirical research documenting that so-called divine legitimacy, which is the use of religion for power purposes, may have prevented some economies from democratizing. Exercises: Students will work with datasets spanning 1265 historic societies spanning the globe and cross-country data. The students will learn how to calculate variables from points on a map and combine them with other spatial data.

 

Topic 2. What determines differences in cultural values across the globe? When attempting to determine the impact of cultural values for society, we will have to also think about where these differences in cultural values came from. We will discuss why this is important. Some questions that we will address is why is it that the inhabitants of some societies trust eachother much more than the inhabitants of other societies? And why are some societies more religious than others? Exercises: When working with cultural values, some of the most relevant datasets are the World Values Survey and the European Values Study. We will work with both and learn how to deal with large survey datasets that span the globe.

Topic 3. How did cultural values determine the emergence of science and modern growth? What role did psychology play? For instance, how did individualism or religion matter? Some historical anecdotes suggest that religion was good for the emergence of science. Others suggest that religion hampered the development of science. To settle the dispute, we will work with theoretical and empirical research. Exercises: When working with cultural values such as religion, individualism or trust, we often need to be quite creative when trying to measure these variables, especially when we go back in history. Students will be introduced to these issues, how to deal with them, and get ideas for some of these creative get-arounds. For instance, we will work with novel research that that uses peoples’ names to infer cultural values of their parents. The students will then work with these data to estimate the impact of religiosity and individualism on modern economic growth. The students will learn how to work with individual-level data that spans Europe and to work with panel data of European cities.

After each topic, the students will get time to formulate their own research questions based on the dataset used for the particular topic. These questions will form the basis for synopses that enter the 3-4 assignments handed in throughout the course. The synopses should include the students’ own research questions, arguments for why the particular question is relevant for economists, which model should be used to examine the question, and how to deal with potential endogeneity problems. It is not the intention of this course that the students estimate their models econometrically. That could potentially be done in future master theses.

Learning outcome

The Learning Outcome:

Knowledge:

After completing the course, the student is expected to be able to:

  • Discuss and theorize about the impacts of cultural values on society.
  • Discuss and reflect on problems concerned with empirical analysis across societies. What makes for a sound econometric analysis? What does the parameter estimates indicate? Does the data really support the hypothesis or not?
  • Account for how to deal with these problems.
  • Critize econometric analysis; Can it really be generalized? Are the estimates of an important size?

 

Skills:

After completing the course, the student is expected to be able to:

  • Structure an econometric analysis of the impact of cultural values on societal values.
  • Analyze these impacts using econometric methods.
  • Construct variables based on spatial data.
  • Construct measures of factors that are hard to measure, such as cultural values, based on either surveys or more creative methods using Google Trends, first names, or other methods.
  • Evaluate whether the impact is economically sizable and important.
  • Present and communicate econometric results in an intuitive and illustrative way.
  • Formulate good research questions, and argue for why a topic is important and relevant to study.

 

Competences:

After completing the course, the student is expected to be able to:

  • Engage and appreciate dicussions about the meaning and impact of cultural or religious differences, potentially evaluating their policy implications.
  • Engage in discussion about when an econometric analysis is useful and what it is not.
  • Plan and implement analyses of factors that are  otherwise not so standard for economists, such as values and beliefs.

 

The course will be taught using

i) lectures, which provide an overview of particular research areas and give the intuition behind the method of specific papers.

ii) exercise classes, where students get time to work with the data behind the main papers, learn the necessary tools to replicate the main results, and generate ideas for how to use the data in new ways. Throughout the exercises, Jeanet will be available for questions and will give mini-lectures on selected topics.

iii) 3-4 homework assignments based on the exercises done in class. The assignments consist of synopses, where the students formulate a new question based on the dataset worked on in the particular exercise, motivate the question based on relevant literature, and argue for which econometric model to use. The assignments can be handed in in groups. Some times in class will be given for these homework assignments.

The course uses journal articles, such as:

Bénabou, R., Ticchi, D., & Vindigni, A. (2022). Forbidden fruits: the political economy of science, religion, and growth, The Review of Economic Studies, 89(4).

Bryan, G. T, Choi, J. J, & Karlan, D. (2021). Randomizing Religion: The Impact of Protestant Evangelism on Economic Outcomes. The Quarterly Journal of Economics 1(136), 293-380.

Campante, Filipe, & Yanagizawa-Drott, David. (2015). Does religion affect economic growth and happiness? Evidence from Ramadan. The Quarterly Journal of Economics, 130(2), 615-658.

Gächter, Simon, and Jonathan F. Schulz. "Intrinsic honesty and the prevalence of rule violations across societies." Nature 531.7595 (2016): 496-499.

Haushofer, Johannes, and Ernst Fehr. "On the psychology of poverty." Science 344.6186 (2014): 862-867.

Henrich, Joseph, et al. "In search of homo economicus: behavioral experiments in 15 small-scale societies." American Economic Review 91.2 (2001): 73-78.

Herrmann, Benedikt, Christian Thoni, and Simon Gachter. "Antisocial punishment across societies." Science 319.5868 (2008): 1362-1367.

Iyer, S. (2016). The new economics of religion. Journal of Economic Literature, 54(2), 395-441.

Norenzayan, A., Shariff, A. F., Gervais, W. M., Willard, A. K., McNamara, R. A., Slingerland, E., & Henrich, J. (2016). The cultural evolution of prosocial religions. Behavioral and brain sciences, 39.

Squicciarini, M. P. (2020). Devotion and Development: Religiosity, Education, and Economic Progress in Nineteenth-Century France. American Economic Review, 110(11), 3454-91.

Data for exercise classes is described in:

Bentzen, J (2019) Acts of God? Religiosity and Natural Disasters Across Subnational World Districts, The Economic Journal, 129(622).

Bentzen, J, G Gokmen (2022) The Power of Religion, Journal of Economic Growth.

Andersen, L H and Bentzen, J S (2022) In the Name of God! Religiosity and the Emergence of Science and Modern Growth, CEPR Discussion paper.

• It is strongly recommended to have a basic knowledge of long-run macro from “Macroeconomics I” and simple regression analysis from “Econometrics I” from the Bachelor of Economics, University of Copenhagen or similar courses.
• Students will benefit from having followed courses in "Applied Econometric Policy Evaluation" at the Bachelor and Master of Economics, University of Copenhagen, "Economic History" at the Bachelor of Economics, University of Copenhagen or similar courses.

Oral
Individual
Collective
Continuous feedback during the course of the semester
Peer feedback (Students give each other feedback)
  • The students receive feedback during exercise classes, both individually and collectively.
  • Students will give and receive peer feedback, orally in groups and written.
  • In addition, office hours are offered.
ECTS
7,5 ECTS
Type of assessment
Written examination, 48 hours
Exam registration requirements
  • 80% of the assigments must be approved to be able to sit the exam.
Aid

Use of AI tools is permitted. You must explain how you have used the tools. When text is solely or mainly generated by an AI tool, the tool used must be quoted as a source.

Marking scale
7-point grading scale
Censorship form
No external censorship
Re-exam
  • Oral examination with without preparation time. 
  • The questions cover the entire curriculum and are based on the written mandatory assignments.

 

80% of the assigments must be approved to be able to sit the reexam.

Criteria for exam assessment

•    Portfolio, 48 hours.
•    The exam is a written assignment consisting of two parts:
- Part 1: The first part is based on one of the mandatory assignments worked on during the course. The student can use the feedback received during the course to improve the assignment. This can be done before the exam period begins. The repeat assignment is chosen at random and reveals with the release of the exam.
- Part 2: The second part is a new assignment. It takes approximately 24 hours to answer the new assignment.
Part 1 weighs 25% and Part 2 weighs 75% of final grade.
•    The new assignments can be written individually or by groups of maximum three students.
•    The groups and the students, that hand in an individual assignment, are not allowed to communicate with each other about the given problem-set for the new assignment.
•    The plagiarism rules and the rules for co-written assignments must be complied.
•    All parts must be answered in English.
•    All parts must be uploaded to Digital Exam in one file.

Single subject courses (day)

  • Category
  • Hours
  • Lectures
  • 42
  • Preparation
  • 152
  • English
  • 194

Kursusinformation

Language
English
Course number
AØKA08244U
ECTS
7,5 ECTS
Programme level
Full Degree Master
Ph.D.
Duration

1 semester

Placement
Autumn
Studyboard
Department of Economics, Study Council
Contracting department
  • Department of Economics
Contracting faculty
  • Faculty of Social Sciences
Course Coordinator
  • Jeanet Sinding Bentzen   (14-75706c79707f396d70797f8570794b706e7a79397680396f76)
Saved on the 07-02-2024

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