IDEAS home Printed from https://ideas.repec.org/p/zbw/vfsc15/113068.html
   My bibliography  Save this paper

Voting for Inefficiency

Author

Listed:
  • Nieswand, Maria
  • Baake, Pio
  • Wagner, Lilo

Abstract

In this paper, we propose a probabilistic voter model that rationalizes the ineff cient use of labor input in municipality-owned enterprises. Our focus is on the relationship between absolute as well as relative ineff ciency measures and the size of the municipality in which public rms operate. We show that larger communities maintain enterprises, which are on average more eff cient in absolute as well as relative terms and that e ffciency shows a lower variance for large enterprises. Using data from a sample of electricity distribution companies in Germany we find our theoretical predictions consistent with the companies' observed behavior.

Suggested Citation

  • Nieswand, Maria & Baake, Pio & Wagner, Lilo, 2015. "Voting for Inefficiency," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113068, Verein für Socialpolitik / German Economic Association.
  • Handle: RePEc:zbw:vfsc15:113068
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/113068/1/VfS_2015_pid_687.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bădin, Luiza & Daraio, Cinzia & Simar, Léopold, 2012. "How to measure the impact of environmental factors in a nonparametric production model," European Journal of Operational Research, Elsevier, vol. 223(3), pages 818-833.
    2. Cinzia Daraio & Léopold Simar, 2005. "Introducing Environmental Variables in Nonparametric Frontier Models: a Probabilistic Approach," Journal of Productivity Analysis, Springer, vol. 24(1), pages 93-121, September.
    3. Badin, Luiza & Daraio, Cinzia & Simar, Léopold, 2010. "Optimal bandwidth selection for conditional efficiency measures: A data-driven approach," European Journal of Operational Research, Elsevier, vol. 201(2), pages 633-640, March.
    4. 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.
    5. Peter Hall & Jeff Racine & Qi Li, 2004. "Cross-Validation and the Estimation of Conditional Probability Densities," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 1015-1026, December.
    6. Astrid Cullmann, 2012. "Benchmarking and firm heterogeneity: a latent class analysis for German electricity distribution companies," Empirical Economics, Springer, vol. 42(1), pages 147-169, February.
    7. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    8. De Witte, Kristof & Mika, Kortelainen, 2009. "Blaming the exogenous environment? Conditional efficiency estimation with continuous and discrete exogenous variables," MPRA Paper 14034, University Library of Munich, Germany.
    9. Andrei Shleifer & Robert W. Vishny, 1994. "Politicians and Firms," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 109(4), pages 995-1025.
    10. Cazals, Catherine & Florens, Jean-Pierre & Simar, Leopold, 2002. "Nonparametric frontier estimation: a robust approach," Journal of Econometrics, Elsevier, vol. 106(1), pages 1-25, January.
    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. Cordero, José Manuel & Pedraja-Chaparro, Francisco & Pisaflores, Elsa C. & Polo, Cristina, 2016. "Efficiency assessment of Portuguese municipalities using a conditional nonparametric approach," MPRA Paper 70674, University Library of Munich, Germany.
    2. Halkos, George E. & Tzeremes, Nickolaos G., 2013. "A conditional directional distance function approach for measuring regional environmental efficiency: Evidence from UK regions," European Journal of Operational Research, Elsevier, vol. 227(1), pages 182-189.
    3. Cordero Ferrera, Jose Manuel & Alonso Morán, Edurne & Nuño Solís, Roberto & Orueta, Juan F. & Souto Arce, Regina, 2013. "Efficiency assessment of primary care providers: A conditional nonparametric approach," MPRA Paper 51926, University Library of Munich, Germany.
    4. Cordero, Jose M. & Polo, Cristina & Santín, Daniel & Simancas, Rosa, 2018. "Efficiency measurement and cross-country differences among schools: A robust conditional nonparametric analysis," Economic Modelling, Elsevier, vol. 74(C), pages 45-60.
    5. Endre Bjoerndal & Mette Bjoerndal & Astrid Cullmann & Maria Nieswand, 2016. "Finding the Right Yardstick: Regulation under Heterogeneous Environments," Discussion Papers of DIW Berlin 1555, DIW Berlin, German Institute for Economic Research.
    6. Nickolaos G. Tzeremes, 2018. "Financial Development and Countries’ Production Efficiency: A Nonparametric Analysis," JRFM, MDPI, vol. 11(3), pages 1-13, August.
    7. Daraio, Cinzia & Simar, Léopold, 2014. "Directional distances and their robust versions: Computational and testing issues," European Journal of Operational Research, Elsevier, vol. 237(1), pages 358-369.
    8. Christopher Bruffaerts & Bram De Rock & Catherine Dehon, 2013. "The Research Efficiency of US Universities: a Nonparametric Frontier Modelling Approach," Working Papers ECARES ECARES 2013-31, ULB -- Universite Libre de Bruxelles.
    9. George Halkos & Aksel Sundström & Nickolaos Tzeremes, 2015. "Regional environmental performance and governance quality: a nonparametric analysis," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 17(4), pages 621-644, October.
    10. Tzeremes, Nickolaos G., 2015. "Efficiency dynamics in Indian banking: A conditional directional distance approach," European Journal of Operational Research, Elsevier, vol. 240(3), pages 807-818.
    11. Jean Pierre Huiban & Camilla Mastromarco & Antonio Musolesi & Michel Simioni, 2018. "The impact of pollution abatement investments on production technology: a nonparametric approach," SEEDS Working Papers 0918, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Sep 2018.
    12. López-Torres, Laura & Johnes, Jill & Elliott, Caroline & Polo, Cristina, 2021. "The effects of competition and collaboration on efficiency in the UK independent school sector," Economic Modelling, Elsevier, vol. 96(C), pages 40-53.
    13. Maria Nieswand & Stefan Seifert, 2016. "Operational Conditions in Regulatory Benchmarking Models: A Monte Carlo Analysis," Discussion Papers of DIW Berlin 1585, DIW Berlin, German Institute for Economic Research.
    14. Jean Pierre Huiban & Camille Mastromarco & Antonio Musolesi & Michel Simioni, 2016. "The impact of pollution abatement investments on production technology: new insights from frontier analysis," Working Papers hal-01512154, HAL.
    15. Michael Zschille, 2014. "Nonparametric measures of returns to scale: an application to German water supply," Empirical Economics, Springer, vol. 47(3), pages 1029-1053, November.
    16. Nolwenn Roudaut & Anne Vanhems, 2012. "Explaining firms efficiency in the Ivorian manufacturing sector: a robust nonparametric approach," Journal of Productivity Analysis, Springer, vol. 37(2), pages 155-169, April.
    17. De Witte, Kristof & Schiltz, Fritz, 2018. "Measuring and explaining organizational effectiveness of school districts: Evidence from a robust and conditional Benefit-of-the-Doubt approach," European Journal of Operational Research, Elsevier, vol. 267(3), pages 1172-1181.
    18. Bădin, Luiza & Daraio, Cinzia & Simar, Léopold, 2019. "A bootstrap approach for bandwidth selection in estimating conditional efficiency measures," European Journal of Operational Research, Elsevier, vol. 277(2), pages 784-797.
    19. Halkos, George E. & Tzeremes, Nickolaos G., 2014. "Public sector transparency and countries’ environmental performance: A nonparametric analysis," Resource and Energy Economics, Elsevier, vol. 38(C), pages 19-37.
    20. Luiza Bădin & Cinzia Daraio & Léopold Simar, 2014. "Explaining inefficiency in nonparametric production models: the state of the art," Annals of Operations Research, Springer, vol. 214(1), pages 5-30, March.

    More about this item

    JEL classification:

    • H83 - Public Economics - - Miscellaneous Issues - - - Public Administration
    • L32 - Industrial Organization - - Nonprofit Organizations and Public Enterprise - - - Public Enterprises; Public-Private Enterprises
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

    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:zbw:vfsc15:113068. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/vfsocea.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.