IDEAS home Printed from https://ideas.repec.org/a/eee/respol/v53y2024i7s004873332400074x.html
   My bibliography  Save this article

What makes econometric ideas popular: The role of connectivity

Author

Listed:
  • Candelon, Bertrand
  • Joëts, Marc
  • Mignon, Valérie

Abstract

This paper aims to identify the factors contributing to the diffusion of ideas in econometrics by paying particular attention to connectivity in content and social networks. Considering a sample of 17,260 research papers in econometrics over the 1980-2020 period, we rely on Structural Topic Models to extract and categorize topics relevant to key domains in the discipline. Using a hurdle count model, we show that both content and social connectivity among the authors enhance the likelihood of non-zero citation counts and play a key role in shaping the diffusion of econometric ideas. We also find that high topic connectivity augmented by robust social connectivity among authors or authoring teams further enhances econometric ideas’ diffusion success. Finally, our findings unveil an inverted U-shaped relationship between connectivity and the success of idea diffusion; the latter initially escalates but starts to wane upon reaching a certain threshold.

Suggested Citation

  • Candelon, Bertrand & Joëts, Marc & Mignon, Valérie, 2024. "What makes econometric ideas popular: The role of connectivity," Research Policy, Elsevier, vol. 53(7).
    • Handle: RePEc:eee:respol:v:53:y:2024:i:7:s004873332400074x
    DOI: 10.1016/j.respol.2024.105025
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S004873332400074X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.respol.2024.105025?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Benjamin F. Jones, 2009. "The Burden of Knowledge and the "Death of the Renaissance Man": Is Innovation Getting Harder?," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(1), pages 283-317.
    2. Cameron,A. Colin & Trivedi,Pravin K., 2013. "Regression Analysis of Count Data," Cambridge Books, Cambridge University Press, number 9781107667273, September.
    3. Nicholas Bloom & Charles I. Jones & John Van Reenen & Michael Webb, 2020. "Are Ideas Getting Harder to Find?," American Economic Review, American Economic Association, vol. 110(4), pages 1104-1144, April.
    4. Stephen Hansen & Michael McMahon, 2016. "Shocking Language: Understanding the Macroeconomic Effects of Central Bank Communication," NBER Chapters, in: NBER International Seminar on Macroeconomics 2015, National Bureau of Economic Research, Inc.
    5. Hsieh, Chih-Sheng & König, Michael D. & Liu, Xiaodong & Zimmermann, Christian, 2018. "Superstar Economists: Coauthorship Networks and Research Output," IZA Discussion Papers 11916, Institute of Labor Economics (IZA).
    6. Chia-Lin Chang & Michael McAleer, 2013. "Ranking Leading Econometrics Journals Using Citations Data from ISI and RePEc," Econometrics, MDPI, vol. 1(3), pages 1-19, November.
    7. Dirk Deichmann & Michael Jensen, 2018. "I can do that alone…or not? How idea generators juggle between the pros and cons of teamwork," Strategic Management Journal, Wiley Blackwell, vol. 39(2), pages 458-475, February.
    8. Stephen Hansen & Michael McMahon & Andrea Prat, 2018. "Transparency and Deliberation Within the FOMC: A Computational Linguistics Approach," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(2), pages 801-870.
    9. Wang, Jian, 2016. "Knowledge creation in collaboration networks: Effects of tie configuration," Research Policy, Elsevier, vol. 45(1), pages 68-80.
    10. Magerman, Tom & Looy, Bart Van & Debackere, Koenraad, 2015. "Does involvement in patenting jeopardize one’s academic footprint? An analysis of patent-paper pairs in biotechnology," Research Policy, Elsevier, vol. 44(9), pages 1702-1713.
    11. Christian Kleiber & Achim Zeileis, 2016. "Visualizing Count Data Regressions Using Rootograms," The American Statistician, Taylor & Francis Journals, vol. 70(3), pages 296-303, July.
    12. Bertrand Candelon & Arnaud Dupuy, 2015. "Hierarchical Organization And Performance Inequality: Evidence From Professional Cycling," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56(4), pages 1207-1236, November.
    13. Deichmann, Dirk & Moser, Christine & Birkholz, Julie M. & Nerghes, Adina & Groenewegen, Peter & Wang, Shenghui, 2020. "Ideas with impact: How connectivity shapes idea diffusion," Research Policy, Elsevier, vol. 49(1).
    14. Seierstad, Cathrine & Opsahl, Tore, 2011. "For the few not the many? The effects of affirmative action on presence, prominence, and social capital of women directors in Norway," Scandinavian Journal of Management, Elsevier, vol. 27(1), pages 44-54, March.
    15. Nikias Sarafoglou & Jean Paelinck, 2008. "On diffusion of ideas in the academic world: the case of spatial econometrics," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 42(2), pages 487-500, June.
    16. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    17. Cameron, A. Colin & Trivedi, Pravin K., 1990. "Regression-based tests for overdispersion in the Poisson model," Journal of Econometrics, Elsevier, vol. 46(3), pages 347-364, December.
    18. James H. Stock & Mark W. Watson, 2017. "Twenty Years of Time Series Econometrics in Ten Pictures," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 59-86, Spring.
    19. Andrikopoulos, Andreas & Samitas, Aristeidis & Kostaris, Konstantinos, 2016. "Four decades of the Journal of Econometrics: Coauthorship patterns and networks," Journal of Econometrics, Elsevier, vol. 195(1), pages 23-32.
    20. Trapido, Denis, 2015. "How novelty in knowledge earns recognition: The role of consistent identities," Research Policy, Elsevier, vol. 44(8), pages 1488-1500.
    21. Wagner, Caroline S. & Whetsell, Travis A. & Mukherjee, Satyam, 2019. "International research collaboration: Novelty, conventionality, and atypicality in knowledge recombination," Research Policy, Elsevier, vol. 48(5), pages 1260-1270.
    22. Fragiskos Archontakis & Rocco Mosconi, 2021. "Søren Johansen and Katarina Juselius: A Bibliometric Analysis of Citations through Multivariate Bass Models," Econometrics, MDPI, vol. 9(3), pages 1-28, August.
    23. Sarah Kaplan & Keyvan Vakili, 2015. "The double-edged sword of recombination in breakthrough innovation," Strategic Management Journal, Wiley Blackwell, vol. 36(10), pages 1435-1457, October.
    24. Margaret E. Roberts & Brandon M. Stewart & Dustin Tingley & Christopher Lucas & Jetson Leder‐Luis & Shana Kushner Gadarian & Bethany Albertson & David G. Rand, 2014. "Structural Topic Models for Open‐Ended Survey Responses," American Journal of Political Science, John Wiley & Sons, vol. 58(4), pages 1064-1082, October.
    25. Cliff Nowell & Therese Grijalva, 2011. "Trends in co-authorship in economics since 1985," Applied Economics, Taylor & Francis Journals, vol. 43(28), pages 4369-4375.
    26. Lorenzo Ductor & Marcel Fafchamps & Sanjeev Goyal & Marco J. van der Leij, 2014. "Social Networks and Research Output," The Review of Economics and Statistics, MIT Press, vol. 96(5), pages 936-948, December.
    27. Mullahy, John, 1986. "Specification and testing of some modified count data models," Journal of Econometrics, Elsevier, vol. 33(3), pages 341-365, December.
    28. Ray Reagans & Ezra W. Zuckerman, 2001. "Networks, Diversity, and Productivity: The Social Capital of Corporate R&D Teams," Organization Science, INFORMS, vol. 12(4), pages 502-517, August.
    29. Benjamin F. Jones, 2021. "The Rise of Research Teams: Benefits and Costs in Economics," Journal of Economic Perspectives, American Economic Association, vol. 35(2), pages 191-216, Spring.
    30. repec:ipg:wpaper:2014-044 is not listed on IDEAS
    31. Lorenzo Ductor, 2015. "Does Co-authorship Lead to Higher Academic Productivity?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(3), pages 385-407, June.
    32. Larsen, Vegard H. & Thorsrud, Leif A., 2019. "The value of news for economic developments," Journal of Econometrics, Elsevier, vol. 210(1), pages 203-218.
    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. Deichmann, Dirk & Moser, Christine & Birkholz, Julie M. & Nerghes, Adina & Groenewegen, Peter & Wang, Shenghui, 2020. "Ideas with impact: How connectivity shapes idea diffusion," Research Policy, Elsevier, vol. 49(1).
    2. Celso Brunetti & Marc Joëts & Valérie Mignon, 2023. "Reasons Behind Words: OPEC Narratives and the Oil Market," Working Papers 2023-19, CEPII research center.
    3. Szymon Sacher & Laura Battaglia & Stephen Hansen, 2021. "Hamiltonian Monte Carlo for Regression with High-Dimensional Categorical Data," Papers 2107.08112, arXiv.org, revised Feb 2024.
    4. Andrikopoulos, Andreas & Trichas, Georgios, 2018. "Publication patterns and coauthorship in the Journal of Corporate Finance," Journal of Corporate Finance, Elsevier, vol. 51(C), pages 98-108.
    5. Luiz Paulo Fávero & Joseph F. Hair & Rafael de Freitas Souza & Matheus Albergaria & Talles V. Brugni, 2021. "Zero-Inflated Generalized Linear Mixed Models: A Better Way to Understand Data Relationships," Mathematics, MDPI, vol. 9(10), pages 1-28, May.
    6. Greene, William, 2007. "Functional Form and Heterogeneity in Models for Count Data," Foundations and Trends(R) in Econometrics, now publishers, vol. 1(2), pages 113-218, August.
    7. Christopher J. W. Zorn, 1998. "An Analytic and Empirical Examination of Zero-Inflated and Hurdle Poisson Specifications," Sociological Methods & Research, , vol. 26(3), pages 368-400, February.
    8. Stefano Bianchini & Moritz Müller & Pierre Pelletier, 2022. "Artificial intelligence in science: An emerging general method of invention," Post-Print hal-03958025, HAL.
    9. Christian Kleiber & Achim Zeileis, 2016. "Visualizing Count Data Regressions Using Rootograms," The American Statistician, Taylor & Francis Journals, vol. 70(3), pages 296-303, July.
    10. Larsen, Vegard H. & Thorsrud, Leif Anders & Zhulanova, Julia, 2021. "News-driven inflation expectations and information rigidities," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 507-520.
    11. Ulf‐ G. Gerdtham, 1997. "Equity in Health Care Utilization: Further Tests Based on Hurdle Models and Swedish Micro Data," Health Economics, John Wiley & Sons, Ltd., vol. 6(3), pages 303-319, May.
    12. Chiara Bocci & Laura Grassini & Emilia Rocco, 2021. "A multiple inflated negative binomial hurdle regression model: analysis of the Italians’ tourism behaviour during the Great Recession," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(4), pages 1109-1133, October.
    13. Leonardo N. Ferreira, 2021. "Forecasting with VAR-teXt and DFM-teXt Models:exploring the predictive power of central bank communication," Working Papers Series 559, Central Bank of Brazil, Research Department.
    14. Levy, Daniel & Mayer, Tamir & Raviv, Alon, 2022. "Economists in the 2008 financial crisis: Slow to see, fast to act," Journal of Financial Stability, Elsevier, vol. 60(C).
    15. Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "News Media vs. FRED-MD for Macroeconomic Forecasting," CESifo Working Paper Series 8639, CESifo.
    16. Gustavo Romero Cardoso & Marcio Issao Nakane, 2024. "What’s in a headline? News impact on the Brazilian economy," Working Papers, Department of Economics 2024_12, University of São Paulo (FEA-USP).
    17. Saskia Ter Ellen & Vegard H. Larsen & Leif Anders Thorsrud, 2022. "Narrative Monetary Policy Surprises and the Media," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(5), pages 1525-1549, August.
    18. Dongqing Lyu & Kaile Gong & Xuanmin Ruan & Ying Cheng & Jiang Li, 2021. "Does research collaboration influence the “disruption” of articles? Evidence from neurosciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 287-303, January.
    19. Laura Battaglia & Timothy Christensen & Stephen Hansen & Szymon Sacher, 2024. "Inference for Regression with Variables Generated from Unstructured Data," Papers 2402.15585, arXiv.org, revised May 2024.
    20. Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2022. "News media versus FRED‐MD for macroeconomic forecasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 63-81, January.

    More about this item

    Keywords

    Connectivity; Idea diffusion; Econometric publications; Citations; Structural Topic Model; Hurdle count model;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics

    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:eee:respol:v:53:y:2024:i:7:s004873332400074x. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/respol .

    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.