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Endogenous network production functions with selectivity

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  • Horrace, William C.
  • Liu, Xiaodong
  • Patacchini, Eleonora

Abstract

We consider a production function that transforms inputs into outputs through peer effect networks. The distinguishing features of this model are that the network is formal and observable through worker scheduling, and selection into the network is done by a manager. We discuss identification and suggest several estimation techniques. We tackle endogeneity arising from selection into groups and exposure to common group factors by employing a polychotomous Heckman-type selection correction. We illustrate our method using data from the Syracuse University Men’s Basketball team, where at any time the coach selects a lineup and players interact strategically to win games.

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  • Horrace, William C. & Liu, Xiaodong & Patacchini, Eleonora, 2016. "Endogenous network production functions with selectivity," Journal of Econometrics, Elsevier, vol. 190(2), pages 222-232.
    • Handle: RePEc:eee:econom:v:190:y:2016:i:2:p:222-232
    DOI: 10.1016/j.jeconom.2015.06.005
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    1. Awudu Abdulai, 2023. "Information acquisition and the adoption of improved crop varieties," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(4), pages 1049-1062, August.
    2. Luisa Corrado & Salvatore Di Novo, 2018. "Estimating Models with Dynamic Network Interactions and Unobserved Heterogeneity," CEIS Research Paper 439, Tor Vergata University, CEIS, revised 06 Nov 2018.
    3. Presler, Jonathan L., 2022. "You are who you eat with: Academic peer effects from school lunch lines," Journal of Economic Behavior & Organization, Elsevier, vol. 203(C), pages 43-58.
    4. Liu, Xiaodong, 2017. "Identification of peer effects via a root estimator," Economics Letters, Elsevier, vol. 156(C), pages 168-171.
    5. AJ A. Bostian & Moriah B. Bostian & Marita Laukkanen & Antti Simola, 2020. "Assessing the productivity consequences of agri-environmental practices when adoption is endogenous," Journal of Productivity Analysis, Springer, vol. 53(2), pages 141-162, April.
    6. Zenou, Yves & Lindquist, Matthew & Sauermann, Jan, 2015. "Network Effects on Worker Productivity," CEPR Discussion Papers 10928, C.E.P.R. Discussion Papers.
    7. Arun Advani & Bansi Malde, 2018. "Credibly Identifying Social Effects: Accounting For Network Formation And Measurement Error," Journal of Economic Surveys, Wiley Blackwell, vol. 32(4), pages 1016-1044, September.
    8. Sida Peng, 2019. "Heterogeneous Endogenous Effects in Networks," Papers 1908.00663, arXiv.org.
    9. William C. Horrace & Hyunseok Jung & Shane Sanders, 2022. "Network Competition and Team Chemistry in the NBA," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 35-49, January.
    10. Tiziano Arduini & Eleonora Patacchini & Edoardo Rainone, 2015. "Parametric and Semiparametric IV Estimation of Network Models with Selectivity," EIEF Working Papers Series 1509, Einaudi Institute for Economics and Finance (EIEF), revised Oct 2015.
    11. Shankar Ghimire & Justin A Ehrlich & Shane D Sanders, 2020. "Measuring individual worker output in a complementary team setting: Does regularized adjusted plus minus isolate individual NBA player contributions?," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-11, August.
    12. William C. Horrace & Hyunseok Jung, 2018. "Stochastic frontier models with network selectivity," Journal of Productivity Analysis, Springer, vol. 50(3), pages 101-116, December.
    13. William C. Horrace & Hyunseok Jung & Jonathan L. Pressler & Amy Ellen Schwartz, 2021. "What Makes a Classmate a Peer? Examining Which Peers Matter in NYC Elementary Schools," Center for Policy Research Working Papers 241, Center for Policy Research, Maxwell School, Syracuse University.
    14. Orea, Luis & Álvarez, Inmaculada C., 2019. "Spatial Production Economics," Efficiency Series Papers 2019/06, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    15. A. G. Billé & C. Salvioni & R. Benedetti, 2018. "Modelling spatial regimes in farms technologies," Journal of Productivity Analysis, Springer, vol. 49(2), pages 173-185, June.
    16. Patacchini, Eleonora & Hsieh, Chih-Sheng & Lin, Xu, 2019. "Social Interaction Methods," CEPR Discussion Papers 14141, C.E.P.R. Discussion Papers.
    17. Saghafian, Soroush & Imanirad, Raha & Traub, Stephen J., 2019. "Do Physicians Influence Each Other’s Performance? Evidence from the Emergency Department," Working Paper Series rwp19-018, Harvard University, John F. Kennedy School of Government.

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    More about this item

    Keywords

    Stochastic frontier model; Spatial autoregressive model; Peer effects; Endogenous network formation; Selectivity;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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