IDEAS home Printed from https://ideas.repec.org/a/wly/jpamgt/v27y2008i3p640-669.html
   My bibliography  Save this article

Quantitative methods, economics, and or models

Author

Listed:
  • Anand Desai

    (The Ohio State University, Columbus, Ohio)

Abstract

Training in quantitative methods is seen as essential for policy analysts, public administrators, and public managers if they are to make cogent and informed data-based arguments. If our objective is to help students and future practitioners identify credible evidence, to make sense of that evidence, link it to their substantive knowledge, and thereby develop a defensible case for action, then this paper argues that our current approach to teaching methods is inappropriate. We need to take into consideration the learning styles and needs of our students in designing the delivery and content of our courses. Our current emphasis on teaching techniques needs to be replaced by an emphasis on teaching about the concepts underlying these tools and techniques. © 2008 by the Association for Public Policy Analysis and Management.

Suggested Citation

  • Anand Desai, 2008. "Quantitative methods, economics, and or models," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 27(3), pages 640-669.
    • Handle: RePEc:wly:jpamgt:v:27:y:2008:i:3:p:640-669
    DOI: 10.1002/pam.20345
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1002/pam.20345
    File Function: Link to full text; subscription required
    Download Restriction: no
    File URL: https://libkey.io/10.1002/pam.20345?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
    ---><---

    References listed on IDEAS

    as
    1. Marks R. Nester, 1996. "An Applied Statistician's Creed," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 45(4), pages 401-410, December.
    2. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, April.
    3. C. J. Wild & M. Pfannkuch, 1999. "Statistical Thinking in Empirical Enquiry," International Statistical Review, International Statistical Institute, vol. 67(3), pages 223-248, December.
    4. John D. Paulus & Robert S. Gay, 1987. "Analysis," Challenge, Taylor & Francis Journals, vol. 30(2), pages 54-57, March.
    5. Stephen E. Fienberg & Miron L. Straf, 1991. "Statistical Evidence in the US Courts: An Appraisal," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 154(1), pages 49-59, January.
    6. Deborah Hughes Hallett & John Boehrer, 2000. "Teaching quantitative methods to students of public affairs: Present and future," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 19(2), pages 335-341.
    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. Luís de Sousa & Alberto Rodrigues da Silva, 2015. "Showcasing a Domain Specific Language for Spatial Simulation Scenarios with case studies," ERSA conference papers ersa15p1044, European Regional Science Association.
    2. Eugenio Caverzasi & Antoine Godin, 2013. "Stock-flow Consistent Modeling through the Ages," Economics Working Paper Archive wp_745, Levy Economics Institute.
    3. Luca Riccetti & Alberto Russo & Mauro Gallegati, 2015. "An agent based decentralized matching macroeconomic model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 10(2), pages 305-332, October.
    4. Tomas Macak, 2021. "Stability of Dependencies of Contingent Subgroups with Merged Groups: Vaccination Case Study," Mathematics, MDPI, vol. 9(22), pages 1-12, November.
    5. Michael J. Radzicki, 2003. "Mr. Hamilton, Mr. Forrester, and a Foundation for Evolutionary Economics," Journal of Economic Issues, Taylor & Francis Journals, vol. 37(1), pages 133-173, March.
    6. Kazuya Yamamoto, 2015. "Mobilization, Flexibility of Identity, and Ethnic Cleavage," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(2), pages 1-8.
    7. Dirk Helbing & Thomas U. Grund, 2013. "Editorial: Agent-Based Modeling And Techno-Social Systems," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 16(04n05), pages 1-3.
    8. Ross Richardson & Matteo G. Richiardi & Michael Wolfson, 2015. "We ran one billion agents. Scaling in simulation models," LABORatorio R. Revelli Working Papers Series 142, LABORatorio R. Revelli, Centre for Employment Studies.
    9. Roberto Veneziani & Luca Zamparelli & Michalis Nikiforos & Gennaro Zezza, 2017. "Stock-Flow Consistent Macroeconomic Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 31(5), pages 1204-1239, December.
    10. Cincotti, Silvano & Raberto, Marco & Teglio, Andrea, 2010. "Credit money and macroeconomic instability in the agent-based model and simulator Eurace," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 4, pages 1-32.
    11. Khalil, Elias L., 2010. "The Bayesian fallacy: Distinguishing internal motivations and religious beliefs from other beliefs," Journal of Economic Behavior & Organization, Elsevier, vol. 75(2), pages 268-280, August.
    12. Jakub Bijak & Jason D. Hilton & Eric Silverman & Viet Dung Cao, 2013. "Reforging the Wedding Ring," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 29(27), pages 729-766.
    13. Juan Manuel Larrosa, 2016. "Agentes computacionales y análisis económico," Revista de Economía Institucional, Universidad Externado de Colombia - Facultad de Economía, vol. 18(34), pages 87-113, January-J.
    14. Joshua M. Epstein, 2007. "Agent-Based Computational Models and Generative Social Science," Introductory Chapters, in: Generative Social Science Studies in Agent-Based Computational Modeling, Princeton University Press.
    15. Rich, Karl M. & Ross, R. Brent & Baker, A. Derek & Negassa, Asfaw, 2011. "Quantifying value chain analysis in the context of livestock systems in developing countries," Food Policy, Elsevier, vol. 36(2), pages 214-222, April.
    16. Ugo Merlone & Daren Sandbank & Ferenc Szidarovszky, 2013. "Equilibria analysis in social dilemma games with Skinnerian agents," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 12(2), pages 219-233, November.
    17. Laobing Zhang & Gabriele Landucci & Genserik Reniers & Nima Khakzad & Jianfeng Zhou, 2018. "DAMS: A Model to Assess Domino Effects by Using Agent‐Based Modeling and Simulation," Risk Analysis, John Wiley & Sons, vol. 38(8), pages 1585-1600, August.
    18. Günter Küppers & Johannes Lenhard, 2005. "Validation of Simulation: Patterns in the Social and Natural Sciences," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 8(4), pages 1-3.
    19. Andrew W. Bausch, 2014. "Evolving intergroup cooperation," Computational and Mathematical Organization Theory, Springer, vol. 20(4), pages 369-393, December.
    20. David Kendrick & P. Mercado & Hans Amman, 2006. "Computational Economics: Help for the Underestimated Undergraduate," Computational Economics, Springer;Society for Computational Economics, vol. 27(2), pages 261-271, May.

    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:wly:jpamgt:v:27:y:2008:i:3:p:640-669. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www3.interscience.wiley.com/journal/34787/home .

    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.