IDEAS home Printed from https://ideas.repec.org/a/red/ecodyn/v21y2020i1agenda.html

The Research Agenda: Laura Veldkamp on Modeling and Measuring the Data Economy

Author

Listed:
  • Laura Veldkamp

    (Columbia University)

Abstract

Laura Veldkamp is a Professor of Finance and Economics at Columbia University’s Graduate School of Business and a former co-editor of the Journal of Economic Theory. Her research research focuses on how individuals, investors and firms get their information, how that information affects the decisions they make, and how those decisions affect the macroeconomy and asset prices.

Suggested Citation

  • Laura Veldkamp, 2020. "The Research Agenda: Laura Veldkamp on Modeling and Measuring the Data Economy," EconomicDynamics Newsletter, Review of Economic Dynamics, vol. 21(1), April.
    • Handle: RePEc:red:ecodyn:v:21:y:2020:i:1:agenda
    as

    Download full text from publisher

    File URL: https://www.economicdynamics.org/newsletter-apr-2020/#unique-identifierVeldkamp
    Download Restriction: None
    ---><---

    References listed on IDEAS

    as
    1. Juliane Begenau & Maryam Farboodi & Laura Veldkamp, 2018. "Big Data in Finance and the Growth of Large Firms," Working Papers 18-08, New York University, Leonard N. Stern School of Business, Department of Economics.
    2. Juliane Begenau & Maryam Farboodi & Laura Veldkamp, 2018. "Big Data in Finance and the Growth of Large Firms," NBER Working Papers 24550, National Bureau of Economic Research, Inc.
    3. Juliane Begenau & Laura Veldkamp & Maryam Farboodi, 2018. "Big Data in Finance and the Growth of Large Firms," 2018 Meeting Papers 155, Society for Economic Dynamics.
    4. Bai, Jennie & Philippon, Thomas & Savov, Alexi, 2016. "Have financial markets become more informative?," Journal of Financial Economics, Elsevier, vol. 122(3), pages 625-654.
    5. Steven J. Davis & John Haltiwanger, 2024. "Dynamism Diminished: The Role of Housing Markets and Credit Conditions," American Economic Journal: Macroeconomics, American Economic Association, vol. 16(2), pages 29-61, April.
    6. Begenau, Juliane & Farboodi, Maryam & Veldkamp, Laura, 2018. "Big data in finance and the growth of large firms," Journal of Monetary Economics, Elsevier, vol. 97(C), pages 71-87.
    Full references (including those not matched with items on IDEAS)

    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. Shiyang Huang & Yan Xiong & Liyan Yang, 2022. "Skill Acquisition and Data Sales," Management Science, INFORMS, vol. 68(8), pages 6116-6144, August.
    2. Peress, Joel & Schmidt, Daniel, 2021. "Noise traders incarnate: Describing a realistic noise trading process," Journal of Financial Markets, Elsevier, vol. 54(C).
    3. Andrei, Daniel & Mann, William & Moyen, Nathalie, 2019. "Why did the q theory of investment start working?," Journal of Financial Economics, Elsevier, vol. 133(2), pages 251-272.
    4. Tadas Limba & Andrejus Novikovas & Andrius Stankevičius & Antanas Andrulevičius & Manuela Tvaronavičienė, 2020. "Big Data Manifestation in Municipal Waste Management and Cryptocurrency Sectors: Positive and Negative Implementation Factors," Sustainability, MDPI, vol. 12(7), pages 1-14, April.
    5. Jennie Bai & Massimo Massa, 2021. "Is Human-Interaction-based Information Substitutable? Evidence from Lockdown," NBER Working Papers 29513, National Bureau of Economic Research, Inc.
    6. Khan, Habib Hussain & Qureshi, Fiza & Jamali, Dima, 2025. "Digital disruption in financing: Are fintech and bigtech credit reshaping corporate access to capital?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 103(C).
    7. Zheng, Liyuan & Zhang, Sheng & Gao, Di & Liu, Jingwei, 2025. "How does digital investment drive real-sector engagement? Theoretical and empirical evidence," International Review of Financial Analysis, Elsevier, vol. 108(PB).
    8. Alexandre Kohlhas & Vladimir Asriyan, 2025. "The Macroeconomics of Data: Scale, Product Choice, and Pricing in the Information Age," Economics Series Working Papers 1073, University of Oxford, Department of Economics.
    9. Zhou, Zhongsheng & Li, Zhuo, 2023. "Corporate digital transformation and trade credit financing," Journal of Business Research, Elsevier, vol. 160(C).
    10. Chen, Xian & Liu, Yang & Wen, Fenghua, 2024. "Air pollution and the digital transformation," International Review of Economics & Finance, Elsevier, vol. 96(PC).
    11. Hong, Liu & Nikbakht, Ehsan & Zhou, Tianpeng, 2023. "Does product market competition affect the adoption of FinTech by non-financial firms?," Finance Research Letters, Elsevier, vol. 54(C).
    12. Breuer, Matthias & Leuz, Christian & Vanhaverbeke, Steven, 2025. "Reporting regulation and corporate innovation," Journal of Accounting and Economics, Elsevier, vol. 80(1).
    13. Ehsan Valavi & Joel Hestness & Newsha Ardalani & Marco Iansiti, 2022. "Time and the Value of Data," Papers 2203.09118, arXiv.org.
    14. Zhou, Xi & Chen, Shou, 2021. "FinTech innovation regulation based on reputation theory with the participation of new media," Pacific-Basin Finance Journal, Elsevier, vol. 67(C).
    15. Youngjin Yoo & Ola Henfridsson & Jannis Kallinikos & Robert Gregory & Gordon Burtch & Sutirtha Chatterjee & Suprateek Sarker, 2024. "The Next Frontiers of Digital Innovation Research," Information Systems Research, INFORMS, vol. 35(4), pages 1507-1523, December.
    16. Yali Li & Gaobin Du & Yilun Lu, 2025. "Management incentives, governance, and digital transformation: effects on financial disclosure integrity," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 49(4), pages 1115-1145, December.
    17. Xu, Heng & Pan, Shiyuan, 2025. "Policy combinations, high-quality population development, and China's economic growth: An endogenous fertility model," Economic Modelling, Elsevier, vol. 151(C).
    18. Surabhi R & Shiva Kumar, 2024. "Evolution of FinTech: A Systematic Literature Review," Nowoczesne Systemy Zarządzania. Modern Management Systems, Military University of Technology, Faculty of Security, Logistics and Management, Institute of Organization and Management, issue 2, pages 49-62.
    19. Ufuk Akcigit & Sina T. Ates, 2021. "Ten Facts on Declining Business Dynamism and Lessons from Endogenous Growth Theory," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(1), pages 257-298, January.
    20. Bianco, Timothy & Herrera, Ana María, 2025. "Monetary policy and credit flows: A tale of two effective lower bounds," Journal of Economic Dynamics and Control, Elsevier, vol. 175(C).

    More about this item

    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:red:ecodyn:v:21:y:2020:i:1:agenda. 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: Christian Zimmermann (email available below). General contact details of provider: https://edirc.repec.org/data/sedddea.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.