Economics of Culture – Empirical Approaches (tidl. 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. 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 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 micro-econometric 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 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 involve 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 these deeper questions can be grouped into three categories: culture, institutions, and geography. This course will focus on the role of culture, encompassing for instance the role of trust, religion, or individualism in a 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 features applications of econometrics methods that are familiar to the students and 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, learning the intuition behind the micro-econometric analysis, 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 known econometric techniques.

 

The course will start with two broad lectures on the economics of culture field. The remaining lectures will focus on three broad topics. Each topic introduces a question and a method and 

will commence with a lecture by Jeanet motivating the topic and methods involved, followed by an exercise session, where students work with the method and data themselves, instructed by Jeanet. While the topics span 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 question 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. Exercises: Students will work with datasets spanning 1265 historic societies spanning the globe and cross-country data. The students will learn what types of figures are convincing and illustrative of a particular hypothesis and learn how to calculate variables from points on a map and combine them with other data.

 

Topic 2. What determines differences in cultural values across the globe? When attempting to determine the impact of cultural values for society, we need to 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 inhabitants of some societies trust each other 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, religion or risk preferences matter? Exercises: When working with cultural values such as 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 individualism on modern economic growth. The students will learn how to work with individual-level data that spans Europe and 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 2-3 assignments handed in during the course. The synopses 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 seminars or master theses.

Education

Students enrolled at the Master programme

  • PhD-students can complete a phd-research module: yes
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 synopsis assignments (of which 2 are mandatory), where the students formulate a 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.

iv) 12 small pre-lecture hand-ins (of which 9 are mandatory), which consist of sending a question or a theory that will become part of your synopses.

The course uses journal articles, such as:

Alesina, Alberto, and Paola Giuliano. "Culture and institutions." Journal of economic literature 53.4 (2015): 898-944.

Bénabou, R., Ticchi, D., & Vindigni, A. (2022). Forbidden fruits: The political economy of science, religion, and growth. The Review of Economic Studies, 89(4), 1785-1795.

Bentzen, Jeanet Sinding. "Religiosity and development." Oxford Research Encyclopedia of Economics and Finance. 2021.

Dohmen, T., Falk, A., Huffman, D., Sunde, U., Schupp, J., & Wagner, G. G. (2011). Individual risk attitudes: Measurement, determinants, and behavioral consequences. Journal of the European Economic Association, 9(3), 522-550.

Fernández, Raquel. "Does culture matter?." Handbook of social economics 1 (2011): 481-497

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

Giuliano, P., & Nunn, N. (2021). Understanding cultural persistence and change. The Review of Economic Studies, 88(4), 1541-1581.

Guiso, L., Sapienza, P., & Zingales, L. (2006). Does culture affect economic outcomes?. Journal of Economic Perspectives, 20(2), 23-48.

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.

Huntington, Samuel. "The clash of civilizations." Foreign affairs 72, no. 3 (1993): 22-29.

Nunn, Nathan. "Culture and the historical process." Economic History of Developing Regions 27 (2012): 108-118.

Nunn, N., & Wantchekon, L. (2011). The slave trade and the origins of mistrust in Africa. American Economic Review, 101(7), 3221-3252.

Spolaore, Enrico, and Romain Wacziarg. "How deep are the roots of economic development?" Journal of economic literature 51.2 (2013)

Squicciarini, M. P. (2020). Devotion and development: religiosity, education, and economic progress in nineteenth-century France. American Economic Review, 110(11), 3454-3491.

Tabellini, G. (2008). The scope of cooperation: Values and incentives. The Quarterly Journal of Economics, 123(3), 905-950.

Voigtländer, N., & Voth, H. J. (2012). Persecution perpetuated: the medieval origins of anti-Semitic violence in Nazi Germany. The Quarterly Journal of Economics, 127(3), 1339-1392.

• It is strongly recommended to possess basic knowledge of simple regression analysis from “Econometrics I” from the Bachelor of Economics, University of Copenhagen or similar courses and to be able to work with Stata (or similar programming tools for econometric analysis).
• Students will benefit greatly from having followed courses on applied econometrics, similar to "Applied Econometric Policy Evaluation" at the Bachelor and Master of Economics, University of Copenhagen.
• Students will benefit some from having taken the courses ”Advanced Development Economics – Macro Aspects”, ”Economic History”, and long-run macro from “Macroeconomics I”, or similar courses.
• Students who have followed the course ”Advanced Development Economics – Macro Aspects” will be familiar with some of the contents in Topic 3. To a lesser extent, also students who followed the course ”Economic Growth”.

Personal data processed as a compulsory part of the seminar: We will work with two types of individual-data: 1) current surveys where individuals are anonymous and 2) publicly available historic data of individuals born in Europe born between 1300 and 1940, where individuals are not anonymous.

Schedule:
• We will meet for three hours each week during weeks 36-50 (except week 42).
• The course will alternate between 2-3 hours lectures followed by 1 hour exercises, interrupted by short lectures on topics that need extra attention. The exercises consist of a) hands-on data work, where we run regressions and produce nice figures and b) idea development where students develop ideas and econometric models based on the data.

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
Portfolio, 36 hours
Exam registration requirements
  • 80% of the assignments 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
The oral re-examination may be with external assessment
Re-exam

Re-exam:

  • The re-exam is a 20 min. oral exam oral exam without prepartion

     

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

Criteria for exam assessment

Written take-home exam without invigilation:

  • Portfolio, 36 hours.
  • The exam is a written assignment consisting of two parts:
    - Part 1: The first part is based on one of the synopses handed in during the course. The student can use the feedback received during the course to improve the synopsis. 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, which consists partly of discussion questions and partly of a task involving analysing data. It takes approximately 24 hours to answer the new assignment.
    Part 1 weighs approximately 25% and Part 2 weighs 75% of the 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.
  • Chatgpt is allowed and the exam is constructed so that a response purely based on chatgpt will obtain the grade 0.
  • 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   (14-76716d7a71803a6e717a8086717a4c716f7b7a3a77813a7077)
Saved on the 17-05-2024

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