IDEAS home Printed from https://ideas.repec.org/p/ecl/stabus/3735.html
   My bibliography  Save this paper

Economists (and Economics) in Tech Companies

Author

Listed:
  • Athey, Susan

    (Stanford Graduate School of Business)

  • Luca, Michael

    (Harvard Business School)

Abstract

As technology platforms have created new markets and new ways of acquiring information, economists have come to play an increasingly central role in tech companies--tackling problems such as platform design, strategy, pricing, and policy. Over the past five years, hundreds of PhD economists have accepted positions in the technology sector. In this paper, we explore the skills that PhD economists apply in tech companies, the companies that hire them, the types of problems that economists are currently working on, and the areas of academic research that have emerged in relation to these problems.

Suggested Citation

  • Athey, Susan & Luca, Michael, 2018. "Economists (and Economics) in Tech Companies," Research Papers 3735, Stanford University, Graduate School of Business.
    • Handle: RePEc:ecl:stabus:3735
    as

    Download full text from publisher

    File URL: https://www.gsb.stanford.edu/gsb-cmis/gsb-cmis-download-auth/470336
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. M. Keith Chen & Judith A. Chevalier & Peter E. Rossi & Emily Oehlsen, 2019. "The Value of Flexible Work: Evidence from Uber Drivers," Journal of Political Economy, University of Chicago Press, vol. 127(6), pages 2735-2794.
    2. Susan Athey & Glenn Ellison, 2011. "Position Auctions with Consumer Search," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 126(3), pages 1213-1270.
    3. Dina Mayzlin & Yaniv Dover & Judith Chevalier, 2014. "Promotional Reviews: An Empirical Investigation of Online Review Manipulation," American Economic Review, American Economic Association, vol. 104(8), pages 2421-2455, August.
    4. Edward L. Glaeser & Andrew Hillis & Scott Duke Kominers & Michael Luca, 2016. "Crowdsourcing City Government: Using Tournaments to Improve Inspection Accuracy," American Economic Review, American Economic Association, vol. 106(5), pages 114-118, May.
    5. Michael Dinerstein & Liran Einav & Jonathan Levin & Neel Sundaresan, 2018. "Consumer Price Search and Platform Design in Internet Commerce," American Economic Review, American Economic Association, vol. 108(7), pages 1820-1859, July.
    6. Susan Athey & Dean Eckles & Guido W. Imbens, 2018. "Exact p-Values for Network Interference," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(521), pages 230-240, January.
    7. Robin S. Lee, 2013. "Vertical Integration and Exclusivity in Platform and Two-Sided Markets," American Economic Review, American Economic Association, vol. 103(7), pages 2960-3000, December.
    8. Benjamin Edelman & Michael Luca & Dan Svirsky, 2017. "Racial Discrimination in the Sharing Economy: Evidence from a Field Experiment," American Economic Journal: Applied Economics, American Economic Association, vol. 9(2), pages 1-22, April.
    9. Michael Anderson & Jeremy Magruder, 2012. "Learning from the Crowd: Regression Discontinuity Estimates of the Effects of an Online Review Database," Economic Journal, Royal Economic Society, vol. 122(563), pages 957-989, September.
    10. Benjamin Edelman & Michael Ostrovsky & Michael Schwarz, 2007. "Internet Advertising and the Generalized Second-Price Auction: Selling Billions of Dollars Worth of Keywords," American Economic Review, American Economic Association, vol. 97(1), pages 242-259, March.
    11. Monic Sun, 2012. "How Does the Variance of Product Ratings Matter?," Management Science, INFORMS, vol. 58(4), pages 696-707, April.
    12. Cody Cook & Rebecca Diamond & Jonathan V Hall & John A List & Paul Oyer, 2021. "The Gender Earnings Gap in the Gig Economy: Evidence from over a Million Rideshare Drivers [Measuring the Gig Economy: Current Knowledge and Open Issues]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 88(5), pages 2210-2238.
    13. Thomas Blake & Chris Nosko & Steven Tadelis, 2015. "Consumer Heterogeneity and Paid Search Effectiveness: A Large‐Scale Field Experiment," Econometrica, Econometric Society, vol. 83, pages 155-174, January.
    14. Lynn Wu & Erik Brynjolfsson, 2015. "The Future of Prediction: How Google Searches Foreshadow Housing Prices and Sales," NBER Chapters, in: Economic Analysis of the Digital Economy, pages 89-118, National Bureau of Economic Research, Inc.
    15. Hyunyoung Choi & Hal Varian, 2012. "Predicting the Present with Google Trends," The Economic Record, The Economic Society of Australia, vol. 88(s1), pages 2-9, June.
    16. Joshua D. Angrist & Jörn-Steffen Pischke, 2009. "Mostly Harmless Econometrics: An Empiricist's Companion," Economics Books, Princeton University Press, edition 1, number 8769.
    17. Thomas Blake & Chris Nosko & Steven Tadelis, 2016. "Returns to Consumer Search: Evidence from eBay," NBER Working Papers 22302, National Bureau of Economic Research, Inc.
    18. Varian, Hal R., 2007. "Position auctions," International Journal of Industrial Organization, Elsevier, vol. 25(6), pages 1163-1178, December.
    19. Gary Bolton & Ben Greiner & Axel Ockenfels, 2013. "Engineering Trust: Reciprocity in the Production of Reputation Information," Management Science, INFORMS, vol. 59(2), pages 265-285, January.
    20. Edward L. Glaeser & Hyunjin Kim & Michael Luca, 2019. "Nowcasting the Local Economy: Using Yelp Data to Measure Economic Activity," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 249-273, National Bureau of Economic Research, Inc.
    21. Anindya Ghose & Panagiotis G. Ipeirotis & Beibei Li, 2012. "Designing Ranking Systems for Hotels on Travel Search Engines by Mining User-Generated and Crowdsourced Content," Marketing Science, INFORMS, vol. 31(3), pages 493-520, May.
    22. Nikhil Agarwal & Susan Athey & David Yang, 2009. "Skewed Bidding in Pay-per-Action Auctions for Online Advertising," American Economic Review, American Economic Association, vol. 99(2), pages 441-447, May.
    23. Edward L. Glaeser & Hyunjin Kim & Michael Luca, 2018. "Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change," AEA Papers and Proceedings, American Economic Association, vol. 108, pages 77-82, May.
    24. Peter Cohen & Robert Hahn & Jonathan Hall & Steven Levitt & Robert Metcalfe, 2016. "Using Big Data to Estimate Consumer Surplus: The Case of Uber," NBER Working Papers 22627, National Bureau of Economic Research, Inc.
    25. Michael Luca & Georgios Zervas, 2016. "Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud," Management Science, INFORMS, vol. 62(12), pages 3412-3427, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gružauskas Valentas & Čalnerytė Dalia & Fyleris Tautvydas & Kriščiūnas Andrius, 2021. "Application of Multivariate Time Series Cluster Analysis to Regional Socioeconomic Indicators of Municipalities," Real Estate Management and Valuation, Sciendo, vol. 29(3), pages 39-51, September.
    2. Apostolos Filippas & John J. Horton & Richard J. Zeckhauser, 2020. "Owning, Using, and Renting: Some Simple Economics of the “Sharing Economy”," Management Science, INFORMS, vol. 66(9), pages 4152-4172, September.
    3. Stefan Wager & Kuang Xu, 2019. "Experimenting in Equilibrium," Papers 1903.02124, arXiv.org, revised Jun 2020.
    4. Thomas V Maher & Charles Seguin & Yongjun Zhang & Andrew P Davis, 2020. "Social scientists’ testimony before Congress in the United States between 1946-2016, trends from a new dataset," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-13, March.
    5. Gary Charness & Brian Jabarian & John A. List, 2023. "Generation Next: Experimentation with AI," NBER Working Papers 31679, National Bureau of Economic Research, Inc.
    6. Greiff, Matthias & Paetzel, Fabian, 2020. "Information about average evaluations spurs cooperation: An experiment on noisy reputation systems," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 334-356.
    7. Kuroki, Masanori, 2021. "Using Python and Google Colab to teach undergraduate microeconomic theory," International Review of Economics Education, Elsevier, vol. 38(C).
    8. Rickard Nyman & Paul Ormerod, 2020. "Understanding the Great Recession Using Machine Learning Algorithms," Papers 2001.02115, arXiv.org.
    9. Larin, Sergey & Khrustalev, Evgeny & Ermakova, Yasmina, 2023. "Characteristics of markets for the creation of innovative products and their impact on the mechanisms of interaction between the subjects of the innovation infrastructure," MPRA Paper 119340, University Library of Munich, Germany, revised 28 Apr 2023.
    10. Abraham K. Song, 2019. "The Digital Entrepreneurial Ecosystem—a critique and reconfiguration," Small Business Economics, Springer, vol. 53(3), pages 569-590, October.
    11. Stefan Wager & Kuang Xu, 2021. "Experimenting in Equilibrium," Management Science, INFORMS, vol. 67(11), pages 6694-6715, November.
    12. Gallin, Joshua & Molloy, Raven & Nielsen, Eric & Smith, Paul & Sommer, Kamila, 2021. "Measuring aggregate housing wealth: New insights from machine learning ☆," Journal of Housing Economics, Elsevier, vol. 51(C).
    13. Deshpande, Advait, 2020. "The potential influence of machine learning and data science on the future of economics: Overview of highly-cited research," SocArXiv 9nh8g, Center for Open Science.
    14. Brett R Gordon & Kinshuk Jerath & Zsolt Katona & Sridhar Narayanan & Jiwoong Shin & Kenneth C Wilbur, 2019. "Inefficiencies in Digital Advertising Markets," Papers 1912.09012, arXiv.org, revised Feb 2020.
    15. Yuting Xiao & Buwajian Abula, 2024. "Examining the Impact of Digital Economy on Agricultural Trade Efficiency in RCEP Region: A Perspective Based on Spatial Spillover Effects," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(3), pages 9907-9934, September.
    16. Nicolas Petit & David J Teece, 2021. "Innovating Big Tech firms and competition policy: favoring dynamic over static competition [Patterns of industrial innovation]," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 30(5), pages 1168-1198.
    17. Valentiny, Pál, 2024. "Mennyire innovatívak a Big Tech vállalatok? [How innovative are Big Tech companies?]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(1), pages 22-56.
    18. Bessen, James & Impink, Stephen Michael & Reichensperger, Lydia & Seamans, Robert, 2022. "The role of data for AI startup growth," Research Policy, Elsevier, vol. 51(5).
    19. Krügel, Jan Philipp & Paetzel, Fabian, 2024. "The impact of fraud on reputation systems," Games and Economic Behavior, Elsevier, vol. 144(C), pages 329-354.
    20. Michael Lechner, 2023. "Causal Machine Learning and its use for public policy," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 159(1), pages 1-15, December.
    21. Michael G Jacobides & Ioannis Lianos, 2021. "Regulating platforms and ecosystems: an introduction [Ecosystem as structure: an actionable construct for strategy]," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 30(5), pages 1131-1142.
    22. Krügel, Jan Philipp & Paetzel, Fabian, 2021. "The Impact of Fake Reviews on Reputation Systems and Efficiency," VfS Annual Conference 2021 (Virtual Conference): Climate Economics 242415, Verein für Socialpolitik / German Economic Association.
    23. Jacobides, Michael G. & Cennamo, Carmelo & Gawer, Annabelle, 2024. "Externalities and complementarities in platforms and ecosystems: From structural solutions to endogenous failures," Research Policy, Elsevier, vol. 53(1).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dominik Gutt & Jürgen Neumann & Steffen Zimmermann & Dennis Kundisch & Jianqing Chen, 2018. "Design of Review Systems - A Strategic Instrument to shape Online Review Behavior and Economic Outcomes," Working Papers Dissertations 42, Paderborn University, Faculty of Business Administration and Economics.
    2. Scott Duke Kominers & Alexander Teytelboym & Vincent P Crawford, 2017. "An invitation to market design," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 33(4), pages 541-571.
    3. Hana Choi & Carl F. Mela, 2019. "Monetizing Online Marketplaces," Marketing Science, INFORMS, vol. 38(6), pages 948-972, November.
    4. Avi Goldfarb, 2014. "What is Different About Online Advertising?," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 44(2), pages 115-129, March.
    5. Gesche, Tobias, 2018. "Reference Price Shifts and Customer Antagonism: Evidence from Reviews for Online Auctions," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181650, Verein für Socialpolitik / German Economic Association.
    6. Dominik Gutt & Philipp Herrmann & Mohammad S. Rahman, 2018. "Crowd-Driven Competitive Intelligence: Understanding the Relationship Between Local Market Competition and Online Rating Distributions," Working Papers Dissertations 41, Paderborn University, Faculty of Business Administration and Economics.
    7. Apostolos Filippas & John J. Horton & Richard J. Zeckhauser, 2020. "Owning, Using, and Renting: Some Simple Economics of the “Sharing Economy”," Management Science, INFORMS, vol. 66(9), pages 4152-4172, September.
    8. Yongwook Paik & Christos A. Makridis, 2023. "The social value of a ridesharing platform: a hedonic pricing approach," Empirical Economics, Springer, vol. 64(5), pages 2125-2150, May.
    9. Jens Foerderer & Nele Lueker & Armin Heinzl, 2021. "And the Winner Is …? The Desirable and Undesirable Effects of Platform Awards," Information Systems Research, INFORMS, vol. 32(4), pages 1155-1172, December.
    10. Brett Hollenbeck & Sridhar Moorthy & Davide Proserpio, 2019. "Advertising Strategy in the Presence of Reviews: An Empirical Analysis," Marketing Science, INFORMS, vol. 38(5), pages 793-811, September.
    11. Burguet, Roberto & Caminal, Ramon & Ellman, Matthew, 2015. "In Google we trust?," International Journal of Industrial Organization, Elsevier, vol. 39(C), pages 44-55.
    12. Piolatto, A. & Schuett, Florian, 2022. "Information vs Competition : How Platform Design Affects Profits and Surplus," Discussion Paper 2022-002, Tilburg University, Tilburg Law and Economic Center.
    13. Paul Belleflamme & Martin Peitz, 2018. "Inside the Engine Room of Digital Platforms: Reviews, Ratings, and Recommendations," Working Papers halshs-01714549, HAL.
    14. Kaplan, Todd R. & Zamir, Shmuel, 2015. "Advances in Auctions," Handbook of Game Theory with Economic Applications,, Elsevier.
    15. Yan Chen & Peter Cramton & John A. List & Axel Ockenfels, 2021. "Market Design, Human Behavior, and Management," Management Science, INFORMS, vol. 67(9), pages 5317-5348, September.
    16. Yu (Jeffrey) Hu & Jiwoong Shin & Zhulei Tang, 2016. "Incentive Problems in Performance-Based Online Advertising Pricing: Cost per Click vs. Cost per Action," Management Science, INFORMS, vol. 62(7), pages 2022-2038, July.
    17. Dominik Gutt & Philipp Herrmann & Mohammad S. Rahman, 2019. "Crowd-Driven Competitive Intelligence: Understanding the Relationship Between Local Market Competition and Online Rating Distributions," Information Systems Research, INFORMS, vol. 30(3), pages 980-994, September.
    18. Greiff, Matthias & Paetzel, Fabian, 2020. "Information about average evaluations spurs cooperation: An experiment on noisy reputation systems," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 334-356.
    19. Chen Jin & Luyi Yang & Kartik Hosanagar, 2023. "To Brush or Not to Brush: Product Rankings, Consumer Search, and Fake Orders," Information Systems Research, INFORMS, vol. 34(2), pages 532-552, June.
    20. Federico Etro, 2012. "Leadership in Multi-sided Markets and Dominance in Online Advertising," Chapters, in: Joseph E. Harrington Jr & Yannis Katsoulacos (ed.), Recent Advances in the Analysis of Competition Policy and Regulation, chapter 11, Edward Elgar Publishing.

    More about this item

    JEL classification:

    • A11 - General Economics and Teaching - - General Economics - - - Role of Economics; Role of Economists
    • D4 - Microeconomics - - Market Structure, Pricing, and Design
    • L0 - Industrial Organization - - General
    • M2 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ecl:stabus:3735. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/gsstaus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.