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Finite-sample instrumental variables inference using an asymptotically pivotal statistic

Author

Listed:
  • Bekker, Paul A.
  • Kleibergen, Frank

    (Groningen University)

Abstract

This paper is concerned with investigating the role of accounting practices in radical change processes. The institutional framework has been taken as a starting point in investigating these processes. The research has been carried out at the Dutch Railways. This company was forced by the Dutch government to change from a public company into a private company. This decision by the Dutch Government has had radical consequences for Dutch Railways’ position in the (rail) transport market and for the way of managing the company. The research focuses on the processes in which the company has changed its template as a public company into a profit-oriented template. This paper examines the interaction of accounting practices with the environmental and organisational context. Emphasis is placed on how these mutual processes of interaction change internal and external positioning, create new visibilities, transform perspectives on organisational activities and performance and modify conditions for organisational change. Existing institutional concepts regarding change processes are evaluated in the light of the case findings and building blocks are developed for a comprehensive change framework.

Suggested Citation

  • Bekker, Paul A. & Kleibergen, Frank, 2001. "Finite-sample instrumental variables inference using an asymptotically pivotal statistic," Research Report 01F38, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    • Handle: RePEc:gro:rugsom:01f38
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    File URL: http://irs.ub.rug.nl/ppn/228125065
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    Cited by:

    1. Phillips, Peter C.B. & Gao, Wayne Yuan, 2017. "Structural inference from reduced forms with many instruments," Journal of Econometrics, Elsevier, vol. 199(2), pages 96-116.
    2. Dufour, Jean-Marie & Taamouti, Mohamed, 2007. "Further results on projection-based inference in IV regressions with weak, collinear or missing instruments," Journal of Econometrics, Elsevier, vol. 139(1), pages 133-153, July.
    3. D.S. Poskitt & C.L. Skeels, 2005. "Small Concentration Asymptotics and Instrumental Variables Inference," Department of Economics - Working Papers Series 948, The University of Melbourne.
    4. Whitney K. Newey & Frank Windmeijer, 2005. "GMM with many weak moment conditions," CeMMAP working papers CWP18/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Frank Kleibergen, 2004. "Expansions of GMM statistics that indicate their properties under weak and/or many instruments and the bootstrap," Econometric Society 2004 North American Summer Meetings 408, Econometric Society.
    6. Tom Boot & Johannes W. Ligtenberg, 2023. "Identification- and many moment-robust inference via invariant moment conditions," Papers 2303.07822, arXiv.org, revised Oct 2025.
    7. Johannes W. Ligtenberg, 2023. "Inference in clustered IV models with many and weak instruments," Papers 2306.08559, arXiv.org, revised Oct 2025.
    8. Tom Boot & Didier Nibbering, 2024. "Inference on LATEs with covariates," Papers 2402.12607, arXiv.org, revised Nov 2024.
    9. Frank Kleibergen & Lingwei Kong & Zhaoguo Zhan, 2023. "Identification Robust Testing of Risk Premia in Finite Samples," Journal of Financial Econometrics, Oxford University Press, vol. 21(2), pages 263-297.
    10. Elise Coudin & Jean-Marie Dufour, 2010. "Finite and Large Sample Distribution-Free Inference in Median Regressions with Instrumental Variables," Working Papers 2010-56, Center for Research in Economics and Statistics.
    11. Jean-Marie Dufour, 2003. "Identification, weak instruments, and statistical inference in econometrics," Canadian Journal of Economics, Canadian Economics Association, vol. 36(4), pages 767-808, November.
    12. Jean‐Marie Dufour, 2003. "Identification, weak instruments, and statistical inference in econometrics," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 36(4), pages 767-808, November.
    13. Bekker, Paul A. & Lawford, Steve, 2008. "Symmetry-based inference in an instrumental variable setting," Journal of Econometrics, Elsevier, vol. 142(1), pages 28-49, January.

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