Professor Christiaan Hogendorn
Spring 2015
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Course Policies and Grading Information
| Jan. 22 Th | 1. Introduction ● David Auerbach, "You Are What You Click: On Microtargeting: Why privacy and anonymity are being violated online by an unstoppable process of data profiling," The Nation, February 13, 2013. |
| Jan. 27 T | BLIZZARD |
| Jan. 29 Th | 2. Applications of Big Data ● Mayer-Schönberger, V., & Cukier, K. (2013). Big data: A revolution that will transform how we live, work, and think. Houghton Mifflin Harcourt, Chapters 1 and 6. Right-click this link to save pdf file ● Data Size Matters Berkeley Data Science infographic, 2013. |
| Feb. 3 T | 3. Data Science ● Robin Bloor, "A Data Science Rant," August 12, 2013. ● Chris Anderson, "The End of Theory: The Data Deluge Makes the Scientific Method Obsolete," WIRED MAGAZINE: 16.07, June 23, 2008. Assignment 1 due. |
| Feb. 5 Th | 4. Software for Big Data ● Will Stanton, "Becoming a data 'hacker,'" Will Stanton's Data Science Blog, June 29, 2014. ● Jeffrey Stanton, "Getting Started with R," Chapter 3 in An Introduction to Data Science, open source ebook. (Hereafter called "Stanton.") |
| Feb. 10 T | 5. Introduction to R and Data Frames ● Stanton, Chapter 5 "Rows and Columns." ● Stanton, beginning of Chapter 9 "Onward with R-Studio." Assignment 2 due. Data for assignment. |
| Feb. 12 Th | 6. Conditional Means ● Stanton, Chapter 6, "Beer, Farms, and Peas." ○ Joshua Anderson and Jorn-Steffen Pischke, appendix to Chapter 1 in Mastering 'Metrics, Princeton University Press, 2015. |
| Feb. 17 T | 7. Facebook ● Stanton, Chapter 8, "Big Data? Big Deal!" Assignment 3 due. Data for assignment. |
| Feb. 19 Th | 8. Regression ● Stanton, Chapter 16, "Line Up, Please" |
| Feb. 24 T | 9. Data Mining Fun spurious correlations Assignment 4 due. Optional Data for assignment. |
| Feb. 26 Th | 10. Machine Learning ● Stanton, Chapter 17, "Hi Ho, Hi Ho - Data Mining We Go" |
| March 3 T | 11. Google Flu Trends ● Lazer, D. M., Kennedy, R., King, G., and Vespignani, A. (2014), The parable of Google Flu: Traps in big data analysis. Science, 343(14 March). ● Bohannon, J. (2015). Credit card study blows holes in anonymity. Science, 347(6221), 468–468. |
| March 5 Th | 12. Big Data Business Models ● Product differentiation ● Need for intermediaries. INRIX case. |
| SPRING BREAK | |
| March 24 T | 13. Big Data and Economic Growth ● James Glanz, Is Big Data an Economic Big Dud? New York Times, August 17, 2013. ○ Carvalho, Vasco M. 2014. "From Micro to Macro via Production Networks." Journal of Economic Perspectives, 28(4): 23-48. |
| March 26 Th | 14. Price Discrimination ● Benjamin Shiller (2014). First Degree Price Discrimination Using Big Data, working paper no. 58, Brandeis University, Department of Economics and International Businesss School. ● Adam OzimekWill Big Data Bring More Price Discrimination, Forbes, September 2013. |
| March 31 T | 15. The FTC and Big Data ● Akiva Miller (2014). What Do We Worry About When We Worry About Price Discrimination? The Law and Ethics of Using Personal Information for Pricing. Journal of Technology Law & Policy, 19, 41. ● US Federal Trade Commission. (2014). Data brokers: A call for transparency and accountability. Midterm Assignment due. |
| April 2 Th | 16. Credit Cards and Big Data |
| April 7 T | 17. Marshall's Tides ● John Sutton (2002) "The Standard Paradigm, Chapter 1 in Marshall's Tendencies: what can economists know? MIT Press. |
| April 14 T | 18. The Experimental Ideal ● Joshua Anderson and Jorn-Steffen Pischke, Chapter 1 in Mastering 'Metrics, Princeton University Press, 2015. |
| April 16 Th | 20. Causality |
| April 21 T | 21. Media Slant ● Gentzkow, M. and Shapiro, J.M., 2010. What drives media slant? Evidence from US daily newspapers. Econometrica, 78(1), pp.35–71. |
| April 23 Th | 22. Long Tail of Google News ● Hengyi Zhu '15 An Examination of the Long-Tail Hypothesis in the Online News Market: The Case of Google News, Thesis, Wesleyan University. |
| April 28 T | 23. Nowcasting ● Steve Scott and Hal Varian "Bayesian Variable Selection for Nowcasting Economic Time Series ," Working paper 2014. Assignment 5 due. Data for assignment: group 1 group 2 group 3 group 4 |
| April 30 Th | 24. Machine Learning paper ● Peysakhovich, A., & Naecker, J. (2015). Machine learning and behavioral economics: Evaluating models of choice under risk and ambiguity. Available at SSRN 2548564. |
| May 5 T | 25. Conclusion |
| May 15 | Final Project and Midterm Revision due. |