IDEAS home Printed from https://ideas.repec.org/a/eee/infome/v11y2017i1p63-79.html
   My bibliography  Save this article

Do patent citations indicate knowledge linkage? The evidence from text similarities between patents and their citations

Author

Listed:
  • Chen, Lixin

Abstract

Whether patent citations indicate knowledge linkage is still a controversial issue, which is very important for the widespread use of the patent citation analysis method. We hypothesize that there exists technological knowledge linkage between patents and their citations, and that the linkage can be detected through measuring text similarities between them. To test the hypothesis, we selected citing-cited patent pairs as the observation group and selected patent pairs without citing-cited relationship as the control group. Using the VSM with WF-IDF weighting method, we calculated text similarity values of the two groups. Through comparing text similarity values between the two groups, we validate that in the vast majority of cases text similarity values of citing-cited pairs are much higher than those of non-citing-cited pairs. The study in nano-technology field shows that the above results are the same, although patents in the same technological area are more relevant than in different technological areas. Furthermore, by comparing text similarities between applicant and examiner citing-cited pairs, the results show that in more cases examiner citations indicate knowledge linkage a bit better than applicant citations. Preferably, examiner citations can be regarded as not only the supplement of applicant citations but also the more important technological background and the prior art closely related to the patents. Compared to applicant citations, examiner citations are a good indicator of knowledge linkage rather than an incomplete and noisy indicator. In short, the results suggest that most certainly patent citations can indicate knowledge linkage, and more likely examiner citations can indicate knowledge linkage a bit better than applicant citations, especially for the component of patent claims. Therefore, we accept the hypothesis that patent citations can indicate knowledge linkage, which is the basic assumption of the patent citation analysis method.

Suggested Citation

  • Chen, Lixin, 2017. "Do patent citations indicate knowledge linkage? The evidence from text similarities between patents and their citations," Journal of Informetrics, Elsevier, vol. 11(1), pages 63-79.
    • Handle: RePEc:eee:infome:v:11:y:2017:i:1:p:63-79
    DOI: 10.1016/j.joi.2016.04.018
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1751157715301711
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.joi.2016.04.018?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Hegde, Deepak & Sampat, Bhaven, 2009. "Examiner citations, applicant citations, and the private value of patents," Economics Letters, Elsevier, vol. 105(3), pages 287-289, December.
    2. Juan Alcácer & Michelle Gittelman, 2006. "Patent Citations as a Measure of Knowledge Flows: The Influence of Examiner Citations," The Review of Economics and Statistics, MIT Press, vol. 88(4), pages 774-779, November.
    3. Chaomei Chen & Diana Hicks, 2004. "Tracing knowledge diffusion," Scientometrics, Springer;Akadémiai Kiadó, vol. 59(2), pages 199-211, February.
    4. Leonardo Costa Ribeiro & Ricardo Machado Ruiz & Américo Tristão Bernardes & Eduardo Motta Albuquerque, 2010. "Matrices of science and technology interactions and patterns of structured growth: implications for development," Scientometrics, Springer;Akadémiai Kiadó, vol. 83(1), pages 55-75, April.
    5. Julie Callaert & Joris Grouwels & Bart Looy, 2012. "Delineating the scientific footprint in technology: Identifying scientific publications within non-patent references," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(2), pages 383-398, May.
    6. Carpenter, Mark P. & Narin, Francis, 1983. "Validation study: Patent citations as indicators of science and foreign dependence," World Patent Information, Elsevier, vol. 5(3), pages 180-185.
    7. Bhaven N. Sampat, 2010. "When Do Applicants Search for Prior Art?," Journal of Law and Economics, University of Chicago Press, vol. 53(2), pages 399-416, May.
    8. Criscuolo, Paola & Verspagen, Bart, 2008. "Does it matter where patent citations come from? Inventor vs. examiner citations in European patents," Research Policy, Elsevier, vol. 37(10), pages 1892-1908, December.
    9. Ryan Lampe, 2012. "Strategic Citation," The Review of Economics and Statistics, MIT Press, vol. 94(1), pages 320-333, February.
    10. Epicoco, Marianna, 2013. "Knowledge patterns and sources of leadership: Mapping the semiconductor miniaturization trajectory," Research Policy, Elsevier, vol. 42(1), pages 180-195.
    11. Hu, Albert G. Z. & Jaffe, Adam B., 2003. "Patent citations and international knowledge flow: the cases of Korea and Taiwan," International Journal of Industrial Organization, Elsevier, vol. 21(6), pages 849-880, June.
    12. Arnold Verbeek & Koenraad Debackere & Marc Luwel & Petra Andries & Edwin Zimmermann & Filip Deleus, 2002. "Linking science to technology: Using bibliographic references in patents to build linkage schemes," Scientometrics, Springer;Akadémiai Kiadó, vol. 54(3), pages 399-420, July.
    13. Martin Meyer, 2000. "What is Special about Patent Citations? Differences between Scientific and Patent Citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 49(1), pages 93-123, August.
    14. Xianwen Wang & Xi Zhang & Shenmeng Xu, 2011. "Patent co-citation networks of Fortune 500 companies," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(3), pages 761-770, September.
    15. Narin, Francis & Olivastro, Dominic, 1992. "Status report: Linkage between technology and science," Research Policy, Elsevier, vol. 21(3), pages 237-249, June.
    16. Alcácer, Juan & Gittelman, Michelle & Sampat, Bhaven, 2009. "Applicant and examiner citations in U.S. patents: An overview and analysis," Research Policy, Elsevier, vol. 38(2), pages 415-427, March.
    17. Rui Li & Tamy Chambers & Ying Ding & Guo Zhang & Liansheng Meng, 2014. "Patent citation analysis: Calculating science linkage based on citing motivation," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(5), pages 1007-1017, May.
    18. Edward Cureton, 1956. "Rank-biserial correlation," Psychometrika, Springer;The Psychometric Society, vol. 21(3), pages 287-290, September.
    19. András Vargha & Harold D. Delaney, 2000. "A Critique and Improvement of the CL Common Language Effect Size Statistics of McGraw and Wong," Journal of Educational and Behavioral Statistics, , vol. 25(2), pages 101-132, June.
    20. Fattori, Michele & Pedrazzi, Giorgio & Turra, Roberta, 2003. "Text mining applied to patent mapping: a practical business case," World Patent Information, Elsevier, vol. 25(4), pages 335-342, December.
    21. Nelson, Andrew J., 2009. "Measuring knowledge spillovers: What patents, licenses and publications reveal about innovation diffusion," Research Policy, Elsevier, vol. 38(6), pages 994-1005, July.
    22. Hsi-Yin Yeh & Yi-Shan Sung & Hsiao-Wen Yang & Wan-Chu Tsai & Dar-Zen Chen, 2013. "The bibliographic coupling approach to filter the cited and uncited patent citations: a case of electric vehicle technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(1), pages 75-93, January.
    23. Martin S. Meyer, 2001. "Patent citation analysis in a novel field of technology:An exploration of nano-science and nano-technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 51(1), pages 163-183, April.
    24. Engelsman, E. C. & van Raan, A. F. J., 1994. "A patent-based cartography of technology," Research Policy, Elsevier, vol. 23(1), pages 1-26, January.
    25. Jacques Michel & Bernd Bettels, 2001. "Patent citation analysis.A closer look at the basic input data from patent search reports," Scientometrics, Springer;Akadémiai Kiadó, vol. 51(1), pages 185-201, April.
    26. Péter Érdi & Kinga Makovi & Zoltán Somogyvári & Katherine Strandburg & Jan Tobochnik & Péter Volf & László Zalányi, 2013. "Prediction of emerging technologies based on analysis of the US patent citation network," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(1), pages 225-242, April.
    27. Han Woo Park & Loet Leydesdorff, 2009. "Knowledge linkage structures in communication studies using citation analysis among communication journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(1), pages 157-175, October.
    28. Albert, M. B. & Avery, D. & Narin, F. & McAllister, P., 1991. "Direct validation of citation counts as indicators of industrially important patents," Research Policy, Elsevier, vol. 20(3), pages 251-259, June.
    29. Marianna Epicoco, 2013. "Knowledge patterns and sources of leadership: Mapping the semiconductor miniaturization trajectory," Post-Print hal-03381305, HAL.
    30. Guo Zhang & Ying Ding & Staša Milojević, 2013. "Citation content analysis (CCA): A framework for syntactic and semantic analysis of citation content," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 64(7), pages 1490-1503, July.
    31. von Wartburg, Iwan & Teichert, Thorsten & Rost, Katja, 2005. "Inventive progress measured by multi-stage patent citation analysis," Research Policy, Elsevier, vol. 34(10), pages 1591-1607, December.
    32. Tom Magerman & Bart Looy & Xiaoyan Song, 2010. "Exploring the feasibility and accuracy of Latent Semantic Analysis based text mining techniques to detect similarity between patent documents and scientific publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(2), pages 289-306, February.
    33. Guo Zhang & Ying Ding & Staša Milojević, 2013. "Citation content analysis (CCA): A framework for syntactic and semantic analysis of citation content," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(7), pages 1490-1503, July.
    34. Cotropia, Christopher A. & Lemley, Mark A. & Sampat, Bhaven, 2013. "Do applicant patent citations matter?," Research Policy, Elsevier, vol. 42(4), pages 844-854.
    35. Mina, A. & Ramlogan, R. & Tampubolon, G. & Metcalfe, J.S., 2007. "Mapping evolutionary trajectories: Applications to the growth and transformation of medical knowledge," Research Policy, Elsevier, vol. 36(5), pages 789-806, June.
    36. Calvin Weng & Tugrul Daim, 2012. "Structural Differentiation and Its Implications—Core/Periphery Structure of the Technological Network," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 3(4), pages 327-342, December.
    37. Manuel Trajtenberg & Adam B. Jaffe & Michael S. Fogarty, 2000. "Knowledge Spillovers and Patent Citations: Evidence from a Survey of Inventors," American Economic Review, American Economic Association, vol. 90(2), pages 215-218, May.
    38. Ying Ding & Guo Zhang & Tamy Chambers & Min Song & Xiaolong Wang & Chengxiang Zhai, 2014. "Content-based citation analysis: The next generation of citation analysis," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(9), pages 1820-1833, September.
    39. Martinelli, Arianna, 2012. "An emerging paradigm or just another trajectory? Understanding the nature of technological changes using engineering heuristics in the telecommunications switching industry," Research Policy, Elsevier, vol. 41(2), pages 414-429.
    40. Loet Leydesdorff & Ismael Rafols, 2009. "A global map of science based on the ISI subject categories," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(2), pages 348-362, February.
    41. Szu-chia S. Lo, 2010. "Scientific linkage of science research and technology development: a case of genetic engineering research," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(1), pages 109-120, January.
    42. Yuxian Liu & Ronald Rousseau, 2010. "Knowledge diffusion through publications and citations: A case study using ESI-fields as unit of diffusion," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(2), pages 340-351, February.
    43. Ahlgren, Per & Colliander, Cristian, 2009. "Document–document similarity approaches and science mapping: Experimental comparison of five approaches," Journal of Informetrics, Elsevier, vol. 3(1), pages 49-63.
    44. Hyunseok Park & Janghyeok Yoon & Kwangsoo Kim, 2012. "Identifying patent infringement using SAO based semantic technological similarities," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(2), pages 515-529, February.
    45. Bart Verspagen, 2000. "The Role of Large Multinationals in the Dutch Technology Infrastructure. A Patent Citation Analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 47(2), pages 427-448, February.
    46. Leo Egghe & Loet Leydesdorff, 2009. "The relation between Pearson's correlation coefficient r and Salton's cosine measure," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(5), pages 1027-1036, May.
    47. Yuxian Liu & Ronald Rousseau, 2010. "Knowledge diffusion through publications and citations: A case study using ESI‐fields as unit of diffusion," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(2), pages 340-351, February.
    48. Francis Narin & Kimberly S Hamilton & Dominic Olivastro, 1995. "Linkage between agency-supported research and patented industrial technology," Research Evaluation, Oxford University Press, vol. 5(3), pages 183-187, December.
    49. Jean O. Lanjouw & Mark Schankerman, 2004. "Patent Quality and Research Productivity: Measuring Innovation with Multiple Indicators," Economic Journal, Royal Economic Society, vol. 114(495), pages 441-465, April.
    50. Narin, Francis & Hamilton, Kimberly S. & Olivastro, Dominic, 1997. "The increasing linkage between U.S. technology and public science," Research Policy, Elsevier, vol. 26(3), pages 317-330, October.
    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. Ali Gazni & Zahra Ghaseminik, 2019. "The increasing dominance of science in the economy: Which nations are successful?," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(3), pages 1411-1426, September.
    2. Lai, Kuei-Kuei & Bhatt, Priyanka C. & Kumar, Vimal & Chen, Hsueh-Chen & Chang, Yu-Hsin & Su, Fang-Pei, 2021. "Identifying the impact of patent family on the patent trajectory: A case of thin film solar cells technological trajectories," Journal of Informetrics, Elsevier, vol. 15(2).
    3. Choi, Seokkyu & Lee, Hyeonju & Park, Eunjeong & Choi, Sungchul, 2022. "Deep learning for patent landscaping using transformer and graph embedding," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    4. Song, Haoyang & Hou, Jianhua & Zhang, Yang, 2023. "The measurements and determinants of patent technological value: Lifetime, strength, breadth, and dispersion from the technology diffusion perspective," Journal of Informetrics, Elsevier, vol. 17(1).
    5. Raminta Pranckutė, 2021. "Web of Science (WoS) and Scopus: The Titans of Bibliographic Information in Today’s Academic World," Publications, MDPI, vol. 9(1), pages 1-59, March.
    6. Matthew Clancy & Paul Heisey & Yongjie Ji & GianCarlo Moschini, 2020. "The Roots of Agricultural Innovation: Patent Evidence of Knowledge Spillovers," NBER Chapters, in: Economics of Research and Innovation in Agriculture, pages 21-75, National Bureau of Economic Research, Inc.
    7. Appio, Francesco Paolo & Martini, Antonella & Fantoni, Gualtiero, 2017. "The light and shade of knowledge recombination: Insights from a general-purpose technology," Technological Forecasting and Social Change, Elsevier, vol. 125(C), pages 154-165.
    8. Wang, Jean J. & Ye, Fred Y., 2021. "Probing into the interactions between papers and patents of new CRISPR/CAS9 technology: A citation comparison," Journal of Informetrics, Elsevier, vol. 15(4).
    9. Wei Cheng & Dejun Zheng & Shaoxiong Fu & Jingfeng Cui, 2024. "Closer in time and higher correlation: disclosing the relationship between citation similarity and citation interval," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(7), pages 4495-4512, July.
    10. Guijie Zhang & Luning Liu & Fangfang Wei, 2019. "Key nodes mining in the inventor–author knowledge diffusion network," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(3), pages 721-735, March.
    11. Jie Chen & Jialin Chen & Shu Zhao & Yanping Zhang & Jie Tang, 2020. "Exploiting word embedding for heterogeneous topic model towards patent recommendation," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2091-2108, December.
    12. Jee, Su Jung & Kwon, Minji & Ha, Jung Moon & Sohn, So Young, 2019. "Exploring the forward citation patterns of patents based on the evolution of technology fields," Journal of Informetrics, Elsevier, vol. 13(4).
    13. Fernández, Ana María & Ferrándiz, Esther & Medina, Jennifer, 2022. "The diffusion of energy technologies. Evidence from renewable, fossil, and nuclear energy patents," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    14. Aaldering, Lukas Jan & Song, Chie Hoon, 2021. "Of leaders and laggards - Towards digitalization of the process industries," Technovation, Elsevier, vol. 105(C).
    15. Wu, Yingwen & Ji, Yangjian, 2023. "Identifying firm-specific technology opportunities from the perspective of competitors by using association rule mining," Journal of Informetrics, Elsevier, vol. 17(2).
    16. Jie Liu & Arnulf Grubler & Tieju Ma & Dieter F. Kogler, 2021. "Identifying the technological knowledge depreciation rate using patent citation data: a case study of the solar photovoltaic industry," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 93-115, January.
    17. Hou, Jianhua & Tang, Shiqi & Zhang, Yang & Song, Haoyang, 2023. "Does prior knowledge affect patent technology diffusion? A semantic-based patent citation contribution analysis," Journal of Informetrics, Elsevier, vol. 17(2).

    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. Huang, Ying & Chen, Lixin & Zhang, Lin, 2020. "Patent citation inflation: The phenomenon, its measurement, and relative indicators to temper its effects," Journal of Informetrics, Elsevier, vol. 14(2).
    2. Adam B. Jaffe & Gaétan de Rassenfosse, 2017. "Patent citation data in social science research: Overview and best practices," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(6), pages 1360-1374, June.
    3. Fernández, Ana María & Ferrándiz, Esther & Medina, Jennifer, 2022. "The diffusion of energy technologies. Evidence from renewable, fossil, and nuclear energy patents," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    4. Satoshi Yasukawa & Shingo Kano, 2014. "Validating the usefulness of examiners’ forward citations from the viewpoint of applicants’ self-selection during the patent application procedure," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(3), pages 895-909, June.
    5. Wang, Jean J. & Ye, Fred Y., 2021. "Probing into the interactions between papers and patents of new CRISPR/CAS9 technology: A citation comparison," Journal of Informetrics, Elsevier, vol. 15(4).
    6. Inchae Park & Yujin Jeong & Byungun Yoon, 2017. "Analyzing the value of technology based on the differences of patent citations between applicants and examiners," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 665-691, May.
    7. Jyun-Cheng Wang & Cheng-hsin Chiang & Shu-Wei Lin, 2010. "Network structure of innovation: can brokerage or closure predict patent quality?," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(3), pages 735-748, September.
    8. Julie Callaert & Maikel Pellens & Bart Looy, 2014. "Sources of inspiration? Making sense of scientific references in patents," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 1617-1629, March.
    9. Sung, Hui-Yun & Wang, Chun-Chieh & Huang, Mu-Hsuan & Chen, Dar-Zen, 2015. "Measuring science-based science linkage and non-science-based linkage of patents through non-patent references," Journal of Informetrics, Elsevier, vol. 9(3), pages 488-498.
    10. Appio, Francesco Paolo & Martini, Antonella & Fantoni, Gualtiero, 2017. "The light and shade of knowledge recombination: Insights from a general-purpose technology," Technological Forecasting and Social Change, Elsevier, vol. 125(C), pages 154-165.
    11. Hur, Wonchang & Oh, Junbyoung, 2021. "A man is known by the company he keeps?: A structural relationship between backward citation and forward citation of patents," Research Policy, Elsevier, vol. 50(1).
    12. Huang, Mu-Hsuan & Yang, Hsiao-Wen & Chen, Dar-Zen, 2015. "Increasing science and technology linkage in fuel cells: A cross citation analysis of papers and patents," Journal of Informetrics, Elsevier, vol. 9(2), pages 237-249.
    13. Hsi-Yin Yeh & Yi-Shan Sung & Hsiao-Wen Yang & Wan-Chu Tsai & Dar-Zen Chen, 2013. "The bibliographic coupling approach to filter the cited and uncited patent citations: a case of electric vehicle technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(1), pages 75-93, January.
    14. Hain, Daniel S. & Jurowetzki, Roman & Buchmann, Tobias & Wolf, Patrick, 2022. "A text-embedding-based approach to measuring patent-to-patent technological similarity," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    15. Petra Moser & Joerg Ohmstedt & Paul W. Rhode, 2018. "Patent Citations—An Analysis of Quality Differences and Citing Practices in Hybrid Corn," Management Science, INFORMS, vol. 64(4), pages 1926-1940, April.
    16. Su, Hsin-Ning & Moaniba, Igam M., 2017. "Investigating the dynamics of interdisciplinary evolution in technology developments," Technological Forecasting and Social Change, Elsevier, vol. 122(C), pages 12-23.
    17. Kenneth Zahringer & Christos Kolympiris & Nicholas Kalaitzandonakes, 2017. "Academic knowledge quality differentials and the quality of firm innovation," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 26(5), pages 821-844.
    18. Barirani, Ahmad & Beaudry, Catherine & Agard, Bruno, 2017. "Can universities profit from general purpose inventions? The case of Canadian nanotechnology patents," Technological Forecasting and Social Change, Elsevier, vol. 120(C), pages 271-283.
    19. Dechezlepretre, Antoine & Martin, Ralf & Mohnen, Myra, 2014. "Knowledge spillovers from clean and dirty technologies," LSE Research Online Documents on Economics 60501, London School of Economics and Political Science, LSE Library.
    20. Ashtor, Jonathan H., 2022. "Modeling patent clarity," Research Policy, Elsevier, vol. 51(2).

    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:infome:v:11:y:2017:i:1:p:63-79. 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/joi .

    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.