IDEAS home Printed from https://ideas.repec.org/p/fpr/impass/5.html
   My bibliography  Save this paper

Some useful methods for measuring the benefits of social science research

Author

Listed:
  • Kilpatrick, Henry E., Jr.

Abstract

What are the “returns” to policy-oriented research in the social sciences? One presumes that the positive net benefits to society, or at least a certain segment of society, would be treated as returns, but how does one determine what these benefits are? Clearly benefits to some social science research are available because society continued to fund it, albeit at different levels in different locations and times. This paper cannot fully answer the questions of what it is we seek to measure in any empirical sense, although it will discuss this issue. The returns in the marketplace for social science research are those that exist in the eye of the customer who bears the cost of the research. This paper's primary goal is to offer the client some ways of measuring these returns. It does this with particular emphasis on methods that are often overlooked, even though some of them have been available to the analyst for decades. It also explains some of the costs and benefits of each method and explains how some of them may be used together in order to achieve a higher level of efficacy in measurement.

Suggested Citation

  • Kilpatrick, Henry E., Jr., 1998. "Some useful methods for measuring the benefits of social science research," Impact assessments 5, International Food Policy Research Institute (IFPRI).
    • Handle: RePEc:fpr:impass:5
    as

    Download full text from publisher

    File URL: https://www.ifpri.org/cdmref/p15738coll2/id/125709/filename/125740.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Eugene Garfield, 1963. "Citation indexes in sociological and historical research," American Documentation, Wiley Blackwell, vol. 14(4), pages 289-291, October.
    2. A. Charnes & W. W. Cooper & R. O. Ferguson, 1955. "Optimal Estimation of Executive Compensation by Linear Programming," Management Science, INFORMS, vol. 1(2), pages 138-151, January.
    3. Denton, Frank T, 1985. "Data Mining as an Industry," The Review of Economics and Statistics, MIT Press, vol. 67(1), pages 124-127, February.
    4. Colin B. Begg & Jesse A. Berlin, 1988. "Publication Bias: A Problem in Interpreting Medical Data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 151(3), pages 419-445, May.
    5. Stephan, Paula E., 2010. "The Economics of Science," Handbook of the Economics of Innovation, in: Bronwyn H. Hall & Nathan Rosenberg (ed.), Handbook of the Economics of Innovation, edition 1, volume 1, chapter 0, pages 217-273, Elsevier.
    6. Levy, David M. & Feigenbaum, Susan, 1990. "Testing the replication hypothesis : When the data set is subject to gross error," Economics Letters, Elsevier, vol. 34(1), pages 49-53, September.
    7. Nikias Sarafoglou & Kingsley E. Haynes, 1996. "University productivity in Sweden: a demonstration and explanatory analysis for economics and business programs," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 30(3), pages 285-304.
    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. Kuyvenhoven, Arie, 2014. "Impact assessment of IFPRI’s capacity-strengthening work, 1985–2010," Impact assessments 38, International Food Policy Research Institute (IFPRI).
    2. Paarlberg, Robert L., 2014. "Impact assessment: IFPRI 2020 conference on building resilience on food and nutrition security," Impact assessments 37, International Food Policy Research Institute (IFPRI).
    3. Kutschukian, Jean-Marc, 2008. "A Framework For The Economic Evaluation Of Environmental Science," 2008 Conference (52nd), February 5-8, 2008, Canberra, Australia 6026, Australian Agricultural and Resource Economics Society.
    4. Ryan, James G., 2003. "Evaluating the impact of agricultural projection modeling using the "IMPACT” framework," Impact assessments 17, International Food Policy Research Institute (IFPRI).

    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. Auspurg Katrin & Hinz Thomas, 2011. "What Fuels Publication Bias?: Theoretical and Empirical Analyses of Risk Factors Using the Caliper Test," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(5-6), pages 636-660, October.
    2. Susan Feigenbaum & David M. Levy, 1996. "The Technological Obsolescence Of Scientific Fraud," Rationality and Society, , vol. 8(3), pages 261-276, August.
    3. Paula E. Stephan, 2004. "Robert K. Merton's perspective on priority and the provision of the public good knowledge," Scientometrics, Springer;Akadémiai Kiadó, vol. 60(1), pages 81-87, May.
    4. Jarle Moen, 2005. "Is Mobility of Technical Personnel a Source of R&D Spillovers?," Journal of Labor Economics, University of Chicago Press, vol. 23(1), pages 81-114, January.
    5. Roberto Iorio & Sandrine Labory & Francesco Rentocchini, 2014. "Academics’ Motivations and Depth and Breadth of Knowledge Transfer Activities," Working Papers 1401, c.MET-05 - Centro Interuniversitario di Economia Applicata alle Politiche per L'industria, lo Sviluppo locale e l'Internazionalizzazione.
    6. David, Paul A. & Hall, Bronwyn H., 2000. "Heart of darkness: modeling public-private funding interactions inside the R&D black box," Research Policy, Elsevier, vol. 29(9), pages 1165-1183, December.
    7. Wojtek Michalowski & Włodzimierz Ogryczak, 2001. "Extending the MAD portfolio optimization model to incorporate downside risk aversion," Naval Research Logistics (NRL), John Wiley & Sons, vol. 48(3), pages 185-200, April.
    8. Petersen, Alexander M. & Rotolo, Daniele & Leydesdorff, Loet, 2016. "A triple helix model of medical innovation: Supply, demand, and technological capabilities in terms of Medical Subject Headings," Research Policy, Elsevier, vol. 45(3), pages 666-681.
    9. Matteo Migheli & Giovanni B. Ramello, 2014. "Open Access Journals & Academics’ Behaviour," ICER Working Papers 03-2014, ICER - International Centre for Economic Research.
    10. Kadziński, MiŁosz & Greco, Salvatore & SŁowiński, Roman, 2012. "Extreme ranking analysis in robust ordinal regression," Omega, Elsevier, vol. 40(4), pages 488-501.
    11. Catalina Martínez & Valerio Sterzi, 2021. "The impact of the abolishment of the professor’s privilege on European university-owned patents," Industry and Innovation, Taylor & Francis Journals, vol. 28(3), pages 247-282, March.
    12. Thomas L. Saaty, 2013. "The Modern Science of Multicriteria Decision Making and Its Practical Applications: The AHP/ANP Approach," Operations Research, INFORMS, vol. 61(5), pages 1101-1118, October.
    13. Mohammadi, Ali & Broström, Anders & Franzoni, Chiara, 2015. "Work Force Composition and Innovation: How Diversity in Employees’ Ethnical and Disciplinary Backgrounds Facilitates Knowledge Re-combination," Working Paper Series in Economics and Institutions of Innovation 413, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.
    14. Yanagida, John F. & Book, Don N., 1984. "Application of the Least Absolute Value Technique as a Data Filter for Detecting Structural Change in the Demand for Meat," Northeastern Journal of Agricultural and Resource Economics, Northeastern Agricultural and Resource Economics Association, vol. 0(Number 1), pages 1-5, April.
    15. Carayol, Nicolas & Dalle, Jean-Michel, 2007. "Sequential problem choice and the reward system in Open Science," Structural Change and Economic Dynamics, Elsevier, vol. 18(2), pages 167-191, June.
    16. Stan J. Liebowitz, 2014. "Willful Blindness: The Inefficient Reward Structure In Academic Research," Economic Inquiry, Western Economic Association International, vol. 52(4), pages 1267-1283, October.
    17. David Grosse Kathoefer & Jens Leker, 2012. "Knowledge transfer in academia: an exploratory study on the Not-Invented-Here Syndrome," The Journal of Technology Transfer, Springer, vol. 37(5), pages 658-675, October.
    18. Dima, Bogdan & Dincă, Marius Sorin & Spulbăr, Cristi, 2014. "Financial nexus: Efficiency and soundness in banking and capital markets," Journal of International Money and Finance, Elsevier, vol. 47(C), pages 100-124.
    19. Stanley, T.D. & Doucouliagos, Chris & Jarrell, Stephen B., 2008. "Meta-regression analysis as the socio-economics of economics research," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 37(1), pages 276-292, February.
    20. Mueller-Langer, Frank & Andreoli-Versbach, Patrick, 2018. "Open access to research data: Strategic delay and the ambiguous welfare effects of mandatory data disclosure," Information Economics and Policy, Elsevier, vol. 42(C), pages 20-34.

    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:fpr:impass:5. 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/ifprius.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.