IDEAS home Printed from https://ideas.repec.org/p/sgo/wpaper/1005.html
   My bibliography  Save this paper

The Effects of Management Practices on Productivity: Evidence from Baseball Team Production

Author

Listed:
  • Young Hoon Lee

    (Department of Economics, Sogang University, Seoul)

Abstract

This paper studies the effects of various management practices on production efficiency by using panel data set of baseball teams. Particularly, we are interested in the effects of work force characteristics (age of workers, age variations, roster stability, and worker's talent disparity) on team production, since construction of roster (the player distribution decision) is a major part of team management every off-season. It finds that efficiency differences caused from management are considerably larger than those from coaching ability. Additionally, neither positive nor negative peer effects are found since the playing talent disparity does not influence statistically significantly on team efficiency. Another empirical finding is the negative correlation between the intrinsic ability of manager and hitter's age. It is implied that either an efficient manager tends to prefer young workers, or young workers makes their manager more efficient. That is, excellent leadership operates better when working forces are young.

Suggested Citation

  • Young Hoon Lee, 2010. "The Effects of Management Practices on Productivity: Evidence from Baseball Team Production," Working Papers 1005, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy), revised 2010.
    • Handle: RePEc:sgo:wpaper:1005
    as

    Download full text from publisher

    File URL: https://tinyurl.com/yk8dx23j
    File Function: First version, 2010
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Nicholas Bloom & John Van Reenen, 2007. "Measuring and Explaining Management Practices Across Firms and Countries," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(4), pages 1351-1408.
    2. Yair Mundlak, 1961. "Empirical Production Function Free of Management Bias," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 43(1), pages 44-56.
    3. Fried, Harold O. & Lovell, C. A. Knox & Schmidt, Shelton S. (ed.), 1993. "The Measurement of Productive Efficiency: Techniques and Applications," OUP Catalogue, Oxford University Press, number 9780195072181.
    4. Bernd Frick & Robert Simmons, 2008. "The impact of managerial quality on organizational performance: evidence from German soccer," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 29(7), pages 593-600.
    5. Ann P. Bartel & Casey Ichniowski & Kathryn L. Shaw, 2005. "How Does Information Technology Really Affect Productivity? Plant-Level Comparisons of Product Innovation, Process Improvement and Worker Skills," NBER Working Papers 11773, National Bureau of Economic Research, Inc.
    6. Nicholas Bloom & Christos Genakos & Raffaella Sadun & John Van Reenen, 2011. "Management Practices Across Firms and Countries," CEP Discussion Papers dp1109, Centre for Economic Performance, LSE.
    7. Kumbhakar, Subal C & Ghosh, Soumendra & McGuckin, J Thomas, 1991. "A Generalized Production Frontier Approach for Estimating Determinants of Inefficiency in U.S. Dairy Farms," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(3), pages 279-286, July.
    8. Young Hoon Lee & David Berri, 2008. "A Re‐Examination Of Production Functions And Efficiency Estimates For The National Basketball Association," Scottish Journal of Political Economy, Scottish Economic Society, vol. 55(1), pages 51-66, February.
    9. Reifschneider, David & Stevenson, Rodney, 1991. "Systematic Departures from the Frontier: A Framework for the Analysis of Firm Inefficiency," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 32(3), pages 715-723, August.
    10. Peter Dawson & Stephen Dobson & Bill Gerrard, 2000. "Stochastic Frontiers and the Temporal Structure of Managerial Efficiency in English Soccer," Journal of Sports Economics, , vol. 1(4), pages 341-362, November.
    11. Sandra E. Black & Lisa M. Lynch, 2001. "How To Compete: The Impact Of Workplace Practices And Information Technology On Productivity," The Review of Economics and Statistics, MIT Press, vol. 83(3), pages 434-445, August.
    12. Antonio Alvarez & Christine Amsler & Luis Orea & Peter Schmidt, 2006. "Interpreting and Testing the Scaling Property in Models where Inefficiency Depends on Firm Characteristics," Journal of Productivity Analysis, Springer, vol. 25(3), pages 201-212, June.
    13. Cornwell, Christopher & Schmidt, Peter & Sickles, Robin C., 1990. "Production frontiers with cross-sectional and time-series variation in efficiency levels," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 185-200.
    14. Caudill, Steven B. & Ford, Jon M., 1993. "Biases in frontier estimation due to heteroscedasticity," Economics Letters, Elsevier, vol. 41(1), pages 17-20.
    15. Scully, Gerald W, 1974. "Pay and Performance in Major League Baseball," American Economic Review, American Economic Association, vol. 64(6), pages 915-930, December.
    16. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-374, October.
    17. Lee, Young Hoon, 2006. "A stochastic production frontier model with group-specific temporal variation in technical efficiency," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1616-1630, November.
    18. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    19. Seung Ahn & Young Lee & Peter Schmidt, 2007. "Stochastic frontier models with multiple time-varying individual effects," Journal of Productivity Analysis, Springer, vol. 27(1), pages 1-12, February.
    20. Leo Kahane, 2005. "Production Efficiency and Discriminatory Hiring Practices in the National Hockey League: A Stochastic Frontier Approach," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 27(1), pages 47-71, August.
    21. Caudill, Steven B & Ford, Jon M & Gropper, Daniel M, 1995. "Frontier Estimation and Firm-Specific Inefficiency Measures in the Presence of Heteroscedasticity," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 105-111, January.
    22. Lawrence M. Kahn, 2000. "The Sports Business as a Labor Market Laboratory," Journal of Economic Perspectives, American Economic Association, vol. 14(3), pages 75-94, Summer.
    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. Young Hoon Lee, 2009. "Frontier Models and their Application to the Sports Industry," Working Papers 0903, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy), revised 2009.
    2. Antonio Alvarez & Carlos Arias, 2014. "A selection of relevant issues in applied stochastic frontier analysis," Economics and Business Letters, Oviedo University Press, vol. 3(1), pages 3-11.
    3. Antti Saastamoinen, 2015. "Heteroscedasticity Or Production Risk? A Synthetic View," Journal of Economic Surveys, Wiley Blackwell, vol. 29(3), pages 459-478, July.
    4. Satya Paul & Sriram Shankar, 2020. "Estimating efficiency effects in a panel data stochastic frontier model," Journal of Productivity Analysis, Springer, vol. 53(2), pages 163-180, April.
    5. Subal C. Kumbhakar & Christopher F. Parmeter & Valentin Zelenyuk, 2022. "Stochastic Frontier Analysis: Foundations and Advances I," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 8, pages 331-370, Springer.
    6. Christopher F. Parmeter & Hung-Jen Wang & Subal C. Kumbhakar, 2017. "Nonparametric estimation of the determinants of inefficiency," Journal of Productivity Analysis, Springer, vol. 47(3), pages 205-221, June.
    7. Shamsuzzoha & Makoto Tanaka, 2021. "The role of human capital on the performance of manufacturing firms in Bangladesh," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(1), pages 21-33, January.
    8. Jorge Galán & Helena Veiga & Michael Wiper, 2014. "Bayesian estimation of inefficiency heterogeneity in stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 42(1), pages 85-101, August.
    9. Sickles, Robin C. & Hao, Jiaqi & Shang, Chenjun, 2015. "Panel Data and Productivity Measurement," Working Papers 15-018, Rice University, Department of Economics.
    10. Seunghwa Rho & Peter Schmidt, 2015. "Are all firms inefficient?," Journal of Productivity Analysis, Springer, vol. 43(3), pages 327-349, June.
    11. Christine Amsler & Peter Schmidt & Wen-Jen Tsay, 2015. "A post-truncation parameterization of truncated normal technical inefficiency," Journal of Productivity Analysis, Springer, vol. 44(2), pages 209-220, October.
    12. Kashiwagi, Kenichi & Mtimet, Nadhem & Zaibet, Lokman & Nagaki, Masakazu, 2010. "Technical efficiency of olive oil manufacturing and efficacy of modernization programme in Tunisia," 2010 AAAE Third Conference/AEASA 48th Conference, September 19-23, 2010, Cape Town, South Africa 96195, African Association of Agricultural Economists (AAAE).
    13. Ali M. Oumer & Amin Mugera & Michael Burton & Atakelty Hailu, 2022. "Technical efficiency and firm heterogeneity in stochastic frontier models: application to smallholder maize farms in Ethiopia," Journal of Productivity Analysis, Springer, vol. 57(2), pages 213-241, April.
    14. Ajayi, V. & Weyman-Jones, T., 2021. "State-Level Electricity Generation Efficiency: Do Restructuring and Regulatory Institutions Matter in the US?," Cambridge Working Papers in Economics 2166, Faculty of Economics, University of Cambridge.
    15. Paul, Satya & Shankar, Sriram, 2018. "Modelling Efficiency Effects in a True Fixed Effects Stochastic Frontier," MPRA Paper 87437, University Library of Munich, Germany.
    16. Julio del Corral & Andrés Maroto & Andrés Gallardo, 2017. "Are Former Professional Athletes and Native Better Coaches? Evidence From Spanish Basketball," Journal of Sports Economics, , vol. 18(7), pages 698-719, October.
    17. T S Mkhabela, 2009. "Measuring Managerial Efficiency in South African Soccer," Studies in Economics and Econometrics, Taylor & Francis Journals, vol. 33(3), pages 1-18, December.
    18. Julio Peña-Torres & Michael Basch & Sebastian Vergara, "undated". "EFICIENCIA TÉCNICA Y ESCALAS DE OPERACIÓN EN PESCA PELÁGICA: UN ANÁLISIS DE FRONTERAS ESTOCÁSTICAS (Pesquería Centro-Sur en Chile)," ILADES-UAH Working Papers inv137, Universidad Alberto Hurtado/School of Economics and Business.
    19. Cliff Huang & Hung-pin Lai, 2012. "Estimation of stochastic frontier models based on multimodel inference," Journal of Productivity Analysis, Springer, vol. 38(3), pages 273-284, December.
    20. Chen, Yueh H. & Lin, Winston T., 2009. "Analyzing the relationships between information technology, inputs substitution and national characteristics based on CES stochastic frontier production models," International Journal of Production Economics, Elsevier, vol. 120(2), pages 552-569, August.

    More about this item

    Keywords

    management practice; production efficiency; baseball team; productivity disparity;
    All these keywords.

    JEL classification:

    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism
    • M12 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Personnel Management; Executives; Executive Compensation

    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:sgo:wpaper:1005. 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: Jung Hur (email available below). General contact details of provider: https://edirc.repec.org/data/risogkr.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.