IDEAS home Printed from https://ideas.repec.org/a/sae/amerec/v56y2011i1p29-37.html
   My bibliography  Save this article

Does Calculus Help in Principles of Economics Courses? Estimates Using Matching Estimators

Author

Listed:
  • William Bosshardt
  • Neela Manage

Abstract

This paper estimates the impact of taking a calculus course on student performance in principles of economics. The analysis takes into account the role of observable student characteristics that are likely to influence the calculus choice and the outcome in the economics course. Propensity score matching provides estimates of the treatment effect of taking calculus when there is selection on observable factors. Matching estimation and OLS both suggest statistically significant and positive effects of taking calculus before principles. The estimates of the impact of taking calculus from matching techniques are, in this case, generally similar to those obtained by OLS. The matching estimation suggests that the largest benefit of calculus may be for those less likely – but not the least likely – to take it.

Suggested Citation

  • William Bosshardt & Neela Manage, 2011. "Does Calculus Help in Principles of Economics Courses? Estimates Using Matching Estimators," The American Economist, Sage Publications, vol. 56(1), pages 29-37, May.
    • Handle: RePEc:sae:amerec:v:56:y:2011:i:1:p:29-37
    DOI: 10.1177/056943451105600105
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/056943451105600105
    Download Restriction: no
    File URL: https://libkey.io/10.1177/056943451105600105?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. William Bosshardt, 2004. "Student Drops and Failure in Principles Courses," The Journal of Economic Education, Taylor & Francis Journals, vol. 35(2), pages 111-128, April.
    2. Kenneth G. Elzinga & Daniel O. Melaugh, 2009. "35,000 Principles of Economics Students: Some Lessons Learned," Southern Economic Journal, John Wiley & Sons, vol. 76(1), pages 32-46, July.
    3. Roberto Agodini & Mark Dynarski, 2004. "Are Experiments the Only Option? A Look at Dropout Prevention Programs," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 180-194, February.
    4. Charles Michalopoulos & Howard S. Bloom & Carolyn J. Hill, 2004. "Can Propensity-Score Methods Match the Findings from a Random Assignment Evaluation of Mandatory Welfare-to-Work Programs?," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 156-179, February.
    5. Charles L. Ballard & Marianne F. Johnson, 2004. "Basic Math Skills and Performance in an Introductory Economics Class," The Journal of Economic Education, Taylor & Francis Journals, vol. 35(1), pages 3-23, January.
    6. Jane S. Lopus & Paul W. Grimes & William E. Becker & Rodney A. Pearson, 2007. "Human Subjects Requirements and Economic Education Researchers," The American Economist, Sage Publications, vol. 51(2), pages 49-60, October.
    7. Roberto Agodini & Mark Dynarski, "undated". "Are Experiments the Only Option? A Look at Dropout Prevention Programs," Mathematica Policy Research Reports 51241adbf9fa4a26add6d54c5, Mathematica Policy Research.
    8. James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(2), pages 261-294.
    9. Sascha O. Becker & Andrea Ichino, 2002. "Estimation of average treatment effects based on propensity scores," Stata Journal, StataCorp LP, vol. 2(4), pages 358-377, November.
    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. Sam Allgood & William B. Walstad & John J. Siegfried, 2015. "Research on Teaching Economics to Undergraduates," Journal of Economic Literature, American Economic Association, vol. 53(2), pages 285-325, June.

    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. Colacelli, Mariana & Blackburn, David J.H., 2009. "Secondary currency: An empirical analysis," Journal of Monetary Economics, Elsevier, vol. 56(3), pages 295-308, April.
    2. Maciej Jakubowski, 2015. "Latent variables and propensity score matching: a simulation study with application to data from the Programme for International Student Assessment in Poland," Empirical Economics, Springer, vol. 48(3), pages 1287-1325, May.
    3. Sudhanshu Handa & John A. Maluccio, 2010. "Matching the Gold Standard: Comparing Experimental and Nonexperimental Evaluation Techniques for a Geographically Targeted Program," Economic Development and Cultural Change, University of Chicago Press, vol. 58(3), pages 415-447, April.
    4. Tommaso Nannicini, 2007. "Simulation-based sensitivity analysis for matching estimators," Stata Journal, StataCorp LP, vol. 7(3), pages 334-350, September.
    5. Ferraro, Paul J. & Miranda, Juan José, 2014. "The performance of non-experimental designs in the evaluation of environmental programs: A design-replication study using a large-scale randomized experiment as a benchmark," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PA), pages 344-365.
    6. Peter Z. Schochet & John Burghardt, 2007. "Using Propensity Scoring to Estimate Program-Related Subgroup Impacts in Experimental Program Evaluations," Evaluation Review, , vol. 31(2), pages 95-120, April.
    7. Fatih Unlu & Douglas Lee Lauen & Sarah Crittenden Fuller & Tiffany Berglund & Elc Estrera, 2021. "Can Quasi‐Experimental Evaluations That Rely On State Longitudinal Data Systems Replicate Experimental Results?," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 40(2), pages 572-613, March.
    8. Alberto Abadie & Guido W. Imbens, 2008. "On the Failure of the Bootstrap for Matching Estimators," Econometrica, Econometric Society, vol. 76(6), pages 1537-1557, November.
    9. Thomas D. Cook & William R. Shadish & Vivian C. Wong, 2008. "Three conditions under which experiments and observational studies produce comparable causal estimates: New findings from within-study comparisons," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 27(4), pages 724-750.
    10. Hämäläinen, Kari & Uusitalo, Roope & Vuori, Jukka, 2008. "Varying biases in matching estimates: Evidence from two randomised job search training experiments," Labour Economics, Elsevier, vol. 15(4), pages 604-618, August.
    11. Justine Burns & Malcolm Kewsell & Rebecca Thornton, 2009. "Evaluating the Impact of Health Programmes," SALDRU Working Papers 40, Southern Africa Labour and Development Research Unit, University of Cape Town.
    12. Jason K. Luellen & William R. Shadish & M. H. Clark, 2005. "Propensity Scores," Evaluation Review, , vol. 29(6), pages 530-558, December.
    13. Vivian C. Wong & Peter M. Steiner & Kylie L. Anglin, 2018. "What Can Be Learned From Empirical Evaluations of Nonexperimental Methods?," Evaluation Review, , vol. 42(2), pages 147-175, April.
    14. Andrew P. Jaciw, 2016. "Assessing the Accuracy of Generalized Inferences From Comparison Group Studies Using a Within-Study Comparison Approach," Evaluation Review, , vol. 40(3), pages 199-240, June.
    15. Andrea Pufahl & Christoph R. Weiss, 2009. "Evaluating the effects of farm programmes: results from propensity score matching," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 36(1), pages 79-101, March.
    16. Paolo Naticchioni & Silvia Loriga, 2011. "Short and Long Term Evaluations of Public Employment Services in Italy," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 57(3), pages 201-229.
    17. Dettmann, E. & Becker, C. & Schmeißer, C., 2011. "Distance functions for matching in small samples," Computational Statistics & Data Analysis, Elsevier, vol. 55(5), pages 1942-1960, May.
    18. Federico Biagi & Daniele Bondonio & Alberto Martini, 2015. "Counterfactual Impact Evaluation of Enterprise Support Programmes. Evidence from a Decade of Subsidies to Italian Firm," ERSA conference papers ersa15p1619, European Regional Science Association.
    19. Olivier Dagnelie & Philippe Lemay‐Boucher, 2012. "Rosca Participation in Benin: A Commitment Issue," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(2), pages 235-252, April.
    20. Francesco Serti & Chiara Tomasi, 2008. "Self-Selection and Post-Entry Effects of Exports: Evidence from Italian Manufacturing Firms," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 144(4), pages 660-694, December.

    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:sae:amerec:v:56:y:2011:i:1:p:29-37. 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: SAGE Publications (email available below). General contact details of provider: http://journals.sagepub.com/home/aex .

    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.