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Applying Random Coefficient Models to Strategy Research: Testing for Firm Heterogeneity, Predicting Firm-Specific Coefficients, and Estimating Strategy Trade-Offs

Author

Listed:
  • Juan Alcacer
  • Wilbur Chung
  • Ashton Hawk

    (Fisher College of Business - OSU - The Ohio State University [Columbus])

  • Gonnalo Pacheco-De-Almeida

Abstract

Although Strategy research aims to understand how firm actions have differential effects on performance, most empirical research estimates the average effects of these actions across firms. This paper promotes Random Coefficients Models (RCMs) as an ideal empirical methodology to study firm heterogeneity in Strategy research. Specifically, we highlight and illustrate three main benefits that RCMs offer to Strategy researchers — testing firm heterogeneity, predicting firm-specific effects, and estimating trade-offs in strategy — using both synthetic and actual data-sets. These examples showcase the potential uses of RCMs to test and build theory in Strategy, as well as to perform exploratory and definitive analyses of firm

Suggested Citation

  • Juan Alcacer & Wilbur Chung & Ashton Hawk & Gonnalo Pacheco-De-Almeida, 2013. "Applying Random Coefficient Models to Strategy Research: Testing for Firm Heterogeneity, Predicting Firm-Specific Coefficients, and Estimating Strategy Trade-Offs," Working Papers hal-01970729, HAL.
    • Handle: RePEc:hal:wpaper:hal-01970729
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    Citations

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    Cited by:

    1. Anna Ferragina & Fernanda Mazzotta, 2015. "Agglomeration economies in Italy: impact on heterogeneous firms’ exit in a multilevel framework," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 42(4), pages 395-440, December.
    2. Aziza GARSAA & Nadine LEVRATTO, 2017. "Les disparités d’évolution de l’emploi sont-elles dues à la nature des entreprises ou à leur localisation ? Une analyse multiniveaux sur les zones d’emploi françaises," Region et Developpement, Region et Developpement, LEAD, Universite du Sud - Toulon Var, vol. 45, pages 31-58.
    3. Abonazel, Mohamed R., 2016. "Generalized Random Coefficient Estimators of Panel Data Models: Asymptotic and Small Sample Properties," MPRA Paper 72586, University Library of Munich, Germany.
    4. Marco Sanfilippo & Adnan Seric, 2016. "Spillovers from agglomerations and inward FDI: a multilevel analysis on sub-Saharan African firms," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 152(1), pages 147-176, February.
    5. Emannuel Dhyne & Joep Konings & Joep Konings & Stijn Vanormelingen,, 2018. "IT and productivity: A firm level analysis," Working Paper Research 346, National Bank of Belgium.
    6. Cassiman, Bruno & ,, 2013. "Profiting from Innovation: Firm Level Evidence on Markups," CEPR Discussion Papers 9703, C.E.P.R. Discussion Papers.
    7. Muellner, Jakob & Klopf, Patricia & Nell, Phillip C., 2017. "Trojan Horses or Local Allies: Host-country National Managers in Developing Market Subsidiaries," Journal of International Management, Elsevier, vol. 23(3), pages 306-325.
    8. Konings, Jozef & Dhyne, Emmanuel & Van den bosch, Jeroen & ,, 2018. "The Return on Information Technology: Who Benefits Most?," CEPR Discussion Papers 13246, C.E.P.R. Discussion Papers.
    9. Vijaya Sunder M & Anupama Prashar, 2023. "State and citizen responsiveness in fighting a pandemic crisis: A systems thinking perspective," Systems Research and Behavioral Science, Wiley Blackwell, vol. 40(1), pages 170-193, January.

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