Course Information
Course title
The Digital Economy 
Designated for
Curriculum Number
Curriculum Identity Number
Wednesday 6,7,8(13:20~16:20) 
Restriction: juniors and beyond OR Restriction: MA students and beyond OR Restriction: Ph. D students
The upper limit of the number of students: 40. 
Course introduction video
Table of Core Capabilities and Curriculum Planning
Table of Core Capabilities and Curriculum Planning
Course Syllabus
Please respect the intellectual property rights of others and do not copy any of the course information without permission
Course Description

Digitization and the internet lowers the cost to collect, disseminate and analyse data. This
course explores how digitization affects interactions between people, firms and governments. We examine how institutions and regulations can and do respond. Topics include privacy, social networks, network effects, online platforms, recommendation algorithms, reputation mechanisms, search, matching and digital payment systems. Advanced economic theory, especially tools from information economics, will be used to explain features of the digital economy and suggest policy recommendations. 

Course Objective
Course Objective:
Upon completion of the course, students should be able to:
1. Describe how the digital age changes interactions.
2. Apply advanced economic theories to analyse implications of different features of the digital economy.
3. Evaluate the impact of different policy recommendations.
4. Articulate questions and formalise conjectures about phenomena in the digital economy.
5. Support made claims with solid economic arguments.

Course outline (Course Schedule of 18 weeks)
Week 1: Privacy --- Collection of Personal Information and Price Discrimination Shota (2020a), Shota (2020b)

Week 2: Privacy --- Other Use of Personal Information
Liang and Madsen (2020), Tirole (2021)

Week 3: Privacy --- Markets of Personal Information
Acquisti et al (2016), Bonatti and Bergemann (2018), Bonatti, Bergemann and Gan (2021),

Week 4: Algorithm and Prediction
Kim et al (2019), Eliaz and Spiegler (2020)

Week 5: Recommendation Systems
Che and Horner (2018)

Week 6: Big Data and Competition
De Corniere and Taylor (2020), Hagiu and Wright (2020)

Week 7: Social Learning
Bikhchandani, Hersheleifer and Welch (1998)

Week 8:Student Presentation?

Week 9: Mid-term

?Week 10: Understanding Network Economy?Edelman and Wright (2015), Katz, Michael L. and Carl Shapiro (1985)

Week 11The Economics of Platforms
Rochet and tirole (2006)

Week 12: The Economics of Search
Ellison and Ellison (2009), Bergemann, Brooks and Morris (2021)

Week 13: The Economics of Search Engines
Eliaz and Spiegler (2020)

Week 14: The Economics of Digital Currencies
Nakamoto (2008), Budish (2018)

Week 15: The Economics of Digital Currencies
Chiu and Koeppl (2018), Cong and He (2018)

Week 16: The Economics of Open Source Production
Tesoriere and Balletta (2017)

Week 17: Student Presentation

Week 18: Final 
Course Requirement
Student Presentations and Term paper (40%)
Examinations (40%)
Assignments and Participation (20%) 
Student Workload (expected study time outside of class per week)
Office Hours
1. Acquisti et al (2016), “The Economics of Privacy,” Journal of Economic Literature, 54(2): 442-92.

2. Bergemann, Dirk and Alessandro Bonatti (2018), “Markets for Information,” working paper.

3. Bergemann, Dirk, Alessandro Bonatti and Tan Gan (2021), “The Economics of Social Data,” working paper.

4. Bergemann, Dirk, Benjamin Brooks and Stephen morris (2021), “Search, Information, and Prices,” Journal of Political Economy, forthcoming.

5. Bikhchandani, Sushil, David Hirsheleifer and Ivo Welch (1998), “Learning from the Behavior of Others: Conformity, Fads and Informational Cascades,” Journal of Economic Perspectives, 12(3): 151-70.

6. Brynjolfsson, Erik and Brian Kahin (Eds.) (2000), Understanding the Digital Economy, MIT Press.

7. Budish, Eric (2018), “The Economic Limits of Bitcoin and the blockchain,” working paper.

8. Che, Yeon-koo and Johannes Horner (2018), “Recommender Systems as Mechanisms for Social Learning,” Quarterly Journal of Economics, 133(2): 871–925.

9. Che, Yeon-koo, Kyungmin Kim, and Weijie Zhong (2019), “Statistical Discrimination in Ratings-Guided Markets,” working paper

10. Chiu, Jonathan and Thorsten V. Koeppl (2018), “The Economics of Cryptocurrencies – Bitcoin and Beyond,” working paper.

11. Cong, Lin William and Zhiguo He (2018), “Blockchain Disruption and Smart Contracts,” Review of Financial Studies.

12. De Corniere, Alexandre and Greg Taylor (2020), “Data and Competition: a General Framework with Applications to Mergers, Market Structure, and Privacy Policy,” working paper.

13. Dinerstein, Michael, Liran Einav, Jonathan Levin, and Neel Sundaresan (2018), “Consumer Price Search and Platform Design in Internet Commerce,” American Economic Review, 108(7): 1820-59.

14. Edelman, Benjamin and Julian Wright (2015), “Price Coherence and Excessive Intermediation,” Quarterly Journal of Economics, 130(3): 1283–1328.

15. Eliaz, Kfir and Ran Spiegler (2011), “A Simple Model of Search Engine Pricing,” Economic Journal, 121(556): 329-39.

16. Eliaz, Kfir and Ran Spiegler (2020), “A Model of Competing Narratives,” American Economic Review, 110(12): 3786-816

17. Ellison, Glenn and Sara Fisher Ellison (2009), “Search, Obfuscation, and Price Elasticities on the Internet,” Econometrica, 77(2): 427-52.

18. Goldfarb, Avi, Shane M. Greenstein, and Catgerine Tucker (Eds.) (2015), Economic Analysis of the Digital Economy, Chicago Press.

19. Hagiu, Andrei and Julian Wright (2020), “Data-enabled learning, network effects and competitive advantage,” working paper.

20. Hendershoot, Terence (Ed.) (2006), Handbook of Economics and Information Systems, Elsevier Publishing.

21. Ichihashi, Shota (2020), “Online Privacy and Information Disclosure,” American Economic Review, 110(2): 569-95.

22. Ichihashi, Shota (2020), “Dynamic Privacy Choices,” working paper.

23. Liang, Annie and Erik Madsen (2020), “Data and Incentives,” working paper.

24. Katz, Michael L. and Carl Shapiro (1985), “Network Externalities, Competition, and Compatibility,” American Economic Review, 75(3): 424-40.

25. Peitz, Martin and Joel Waldfogel (Eds.) (2012), Handbook of Digital Economics, Oxford University Press, New York, NY.

26. Rochet, Jean-Charles and Jean Tirole (2006), “Two?Sided Markets: A Progress Report,” Rand Journal of Economics, 37(3): 645-667.

27. Rysman, Marc (2009), “The Economics of Two-Sided Markets,” Journal of Economic Perspectives, 23(3): 125-43.

28. Tesoriere, Antonio and Luigi Balletta (2017), “A dynamic model of open source vs proprietary R&D,” European Economic Review, 94: 221-39.

29. Tirole, Jean (2021), “Digital Dystopia,” American Economic Review, forthcoming 
Designated reading
No data