IDEAS home Printed from https://ideas.repec.org/a/spr/eurase/v7y2017i3d10.1007_s40822-017-0080-2.html
   My bibliography  Save this article

Efficiency-solvency linkage of Indian general insurance companies: a robust non-parametric approach

Author

Listed:
  • Ram Pratap Sinha

    (Government College of Engineering and Leather Technology)

Abstract

The present study explored the efficiency-solvency linkage in the context of the Indian general insurance sector through a two stage analysis. In the first stage, a robust bootstrap approach is followed for the estimation of technical efficiency scores of 16 in-sample public and private sector general insurance companies. In the second stage, the impact of solvency on the efficiency of the insurers has been considered via truncated regression. The results point out a statistically significant relationship between input/output oriented efficiency and solvency ratio.

Suggested Citation

  • Ram Pratap Sinha, 2017. "Efficiency-solvency linkage of Indian general insurance companies: a robust non-parametric approach," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 7(3), pages 353-370, December.
    • Handle: RePEc:spr:eurase:v:7:y:2017:i:3:d:10.1007_s40822-017-0080-2
    DOI: 10.1007/s40822-017-0080-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40822-017-0080-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s40822-017-0080-2?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Leverty, J. Tyler & Grace, Martin F., 2010. "The robustness of output measures in property-liability insurance efficiency studies," Journal of Banking & Finance, Elsevier, vol. 34(7), pages 1510-1524, July.
    2. Alois Kneip & Léopold Simar & Paul Wilson, 2011. "A Computationally Efficient, Consistent Bootstrap for Inference with Non-parametric DEA Estimators," Computational Economics, Springer;Society for Computational Economics, vol. 38(4), pages 483-515, November.
    3. Byeongyong Paul Choi & Mary A. Weiss, 2005. "An Empirical Investigation of Market Structure, Efficiency, and Performance in Property‐Liability Insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 72(4), pages 635-673, December.
    4. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    5. Kao, Chiang & Hwang, Shiuh-Nan, 2008. "Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan," European Journal of Operational Research, Elsevier, vol. 185(1), pages 418-429, February.
    6. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    7. Dieter Gstach, 1998. "Another Approach to Data Envelopment Analysis in Noisy Environments: DEA+," Journal of Productivity Analysis, Springer, vol. 9(2), pages 161-176, March.
    8. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
    9. Barros, Carlos Pestana & Nektarios, Milton & Assaf, A., 2010. "Efficiency in the Greek insurance industry," European Journal of Operational Research, Elsevier, vol. 205(2), pages 431-436, September.
    10. Cummins, J. David & Xie, Xiaoying, 2008. "Mergers and acquisitions in the US property-liability insurance industry: Productivity and efficiency effects," Journal of Banking & Finance, Elsevier, vol. 32(1), pages 30-55, January.
    11. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    12. Rajiv D. Banker, 1993. "Maximum Likelihood, Consistency and Data Envelopment Analysis: A Statistical Foundation," Management Science, INFORMS, vol. 39(10), pages 1265-1273, October.
    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. Kaffash, Sepideh & Azizi, Roza & Huang, Ying & Zhu, Joe, 2020. "A survey of data envelopment analysis applications in the insurance industry 1993–2018," European Journal of Operational Research, Elsevier, vol. 284(3), pages 801-813.

    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. Kaffash, Sepideh & Azizi, Roza & Huang, Ying & Zhu, Joe, 2020. "A survey of data envelopment analysis applications in the insurance industry 1993–2018," European Journal of Operational Research, Elsevier, vol. 284(3), pages 801-813.
    2. Ram Pratap Sinha, 2017. "Dynamic Performance Benchmarking of Indian General Insurers," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 15(3), pages 543-564, September.
    3. Huang, Wei & Eling, Martin, 2013. "An efficiency comparison of the non-life insurance industry in the BRIC countries," European Journal of Operational Research, Elsevier, vol. 226(3), pages 577-591.
    4. Ibrahim Alnafrah, 2021. "Efficiency evaluation of BRICS’s national innovation systems based on bias-corrected network data envelopment analysis," Journal of Innovation and Entrepreneurship, Springer, vol. 10(1), pages 1-28, December.
    5. Kuan-Chen Chen & Chung-I Lin, 2020. "Studies on the Determinants of Efficiency in Taiwanese Life Insurance Industry - Application of Bootstrapped Truncated Model," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 10(1), pages 1-4.
    6. Kao, Chiang & Liu, Shiang-Tai, 2014. "Measuring performance improvement of Taiwanese commercial banks under uncertainty," European Journal of Operational Research, Elsevier, vol. 235(3), pages 755-764.
    7. Aggelopoulos, Eleftherios & Georgopoulos, Antonios, 2017. "Bank branch efficiency under environmental change: A bootstrap DEA on monthly profit and loss accounting statements of Greek retail branches," European Journal of Operational Research, Elsevier, vol. 261(3), pages 1170-1188.
    8. Davtalab-Olyaie, Mostafa & Asgharian, Masoud & Nia, Vahid Partovi, 2019. "Stochastic ranking and dominance in DEA," International Journal of Production Economics, Elsevier, vol. 214(C), pages 125-138.
    9. Lampe, Hannes W. & Hilgers, Dennis, 2015. "Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA," European Journal of Operational Research, Elsevier, vol. 240(1), pages 1-21.
    10. Michali, Maria & Emrouznejad, Ali & Dehnokhalaji, Akram & Clegg, Ben, 2023. "Subsampling bootstrap in network DEA," European Journal of Operational Research, Elsevier, vol. 305(2), pages 766-780.
    11. George Halkos & Roman Matousek & Nickolaos Tzeremes, 2016. "Pre-evaluating technical efficiency gains from possible mergers and acquisitions: evidence from Japanese regional banks," Review of Quantitative Finance and Accounting, Springer, vol. 46(1), pages 47-77, January.
    12. Zervopoulos, Panagiotis & Emrouznejad, Ali & Sklavos, Sokratis, 2019. "A Bayesian approach for correcting bias of data envelopment analysis estimators," MPRA Paper 91886, University Library of Munich, Germany.
    13. Schaper, Philipp, 2017. "Under pressure: how the business environment affects productivity and efficiency of European life insurance companiesAuthor-Name: Eling, Martin," European Journal of Operational Research, Elsevier, vol. 258(3), pages 1082-1094.
    14. Léopold Simar & Paul W. Wilson, 2015. "Statistical Approaches for Non-parametric Frontier Models: A Guided Tour," International Statistical Review, International Statistical Institute, vol. 83(1), pages 77-110, April.
    15. Chiang Kao & Shiang-Tai Liu, 2022. "Stochastic efficiencies of network production systems with correlated stochastic data: the case of Taiwanese commercial banks," Annals of Operations Research, Springer, vol. 315(2), pages 1151-1174, August.
    16. Zervopoulos, Panagiotis D. & Brisimi, Theodora S. & Emrouznejad, Ali & Cheng, Gang, 2016. "Performance measurement with multiple interrelated variables and threshold target levels: Evidence from retail firms in the US," European Journal of Operational Research, Elsevier, vol. 250(1), pages 262-272.
    17. Yiorgos Gadanakis & Francisco José Areal, 2020. "Accounting for rainfall and the length of growing season in technical efficiency analysis," Operational Research, Springer, vol. 20(4), pages 2583-2608, December.
    18. George E. Halkos & Roman Matousek & Nickolaos G. Tzeremes, 2016. "Pre-evaluating technical efficiency gains from possible mergers and acquisitions: evidence from Japanese regional banks," Review of Quantitative Finance and Accounting, Springer, vol. 46(1), pages 47-77, January.
    19. Jaehun Park & Joonyoung Kim & Si-Il Sung, 2017. "Performance Evaluation of Research and Business Development: A Case Study of Korean Public Organizations," Sustainability, MDPI, vol. 9(12), pages 1-16, December.
    20. Mahlberg, Bernhard & Url, Thomas, 2010. "Single Market effects on productivity in the German insurance industry," Journal of Banking & Finance, Elsevier, vol. 34(7), pages 1540-1548, July.

    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:spr:eurase:v:7:y:2017:i:3:d:10.1007_s40822-017-0080-2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.