IDEAS home Printed from https://ideas.repec.org/p/ies/wpaper/e201609.html
   My bibliography  Save this paper

Is there a prison size dilemma? An empirical analysis of output-specific economies of scale

Author

Listed:
  • Veerle Hennebel

    (KU Leuven)

  • Richard Simper

    (University of Nottingham)

  • Marijn Verschelde

    (IÉSEG School of Management, LEM (UMR-CNRS 9221))

Abstract

We advocate a nonparametric multi-output framework to estimate output-specific economies of scale and we apply this model to male prisons in England and Wales over the sample period 2009-2012. To estimate output-specific returns to scale in prisons, we consider not only the cost-per-place, but also qualitative outputs such as purposeful out-of-cell activity and successful reintegration. Furthermore, we introduce environmental heterogeneity using the characteristics of the prison(ers). England and Wales offers a unique example to study economies of scale in prisons as the UK has started to build new super-size prisons in order to replace the most outdated prisons.

Suggested Citation

  • Veerle Hennebel & Richard Simper & Marijn Verschelde, 2016. "Is there a prison size dilemma? An empirical analysis of output-specific economies of scale," Working Papers 2016-EQM-09, IESEG School of Management.
  • Handle: RePEc:ies:wpaper:e201609
    as

    Download full text from publisher

    File URL: http://www.ieseg.fr/wp-content/uploads/2012/03/2016-EQM-09_Verschelde.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Lawrence Katz & Steven D. Levitt & Ellen Shustorovich, 2003. "Prison Conditions, Capital Punishment, and Deterrence," American Law and Economics Review, American Law and Economics Association, vol. 5(2), pages 318-343, August.
    2. Kerstens, Kristiaan & Vanden Eeckaut, Philippe, 1999. "Estimating returns to scale using non-parametric deterministic technologies: A new method based on goodness-of-fit," European Journal of Operational Research, Elsevier, vol. 113(1), pages 206-214, February.
    3. Dominique Deprins & Léopold Simar & Henry Tulkens, 2006. "Measuring Labor-Efficiency in Post Offices," Springer Books, in: Parkash Chander & Jacques Drèze & C. Knox Lovell & Jack Mintz (ed.), Public goods, environmental externalities and fiscal competition, chapter 0, pages 285-309, Springer.
    4. Victor V. Podinovski & Finn R. Førsund, 2010. "Differential Characteristics of Efficient Frontiers in Data Envelopment Analysis," Operations Research, INFORMS, vol. 58(6), pages 1743-1754, December.
    5. Gary S. Becker, 1974. "Crime and Punishment: An Economic Approach," NBER Chapters, in: Essays in the Economics of Crime and Punishment, pages 1-54, National Bureau of Economic Research, Inc.
    6. Rafael Di Tella & Ernesto Schargrodsky, 2013. "Criminal Recidivism after Prison and Electronic Monitoring," Journal of Political Economy, University of Chicago Press, vol. 121(1), pages 28-73.
    7. Laurens Cherchye & Bram De Rock & Bart Dierynck & Filip Roodhooft & Jeroen Sabbe, 2013. "Opening the “Black Box” of Efficiency Measurement: Input Allocation in Multioutput Settings," Operations Research, INFORMS, vol. 61(5), pages 1148-1165, October.
    8. Benjamin Hansen, 2015. "Punishment and Deterrence: Evidence from Drunk Driving," American Economic Review, American Economic Association, vol. 105(4), pages 1581-1617, April.
    9. Steven D. Levitt, 1996. "The Effect of Prison Population Size on Crime Rates: Evidence from Prison Overcrowding Litigation," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 111(2), pages 319-351.
    10. Wade D. Cook & Joe Zhu, 2011. "Multiple Variable Proportionality in Data Envelopment Analysis," Operations Research, INFORMS, vol. 59(4), pages 1024-1032, August.
    11. Syrjanen, Mikko J., 2004. "Non-discretionary and discretionary factors and scale in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 158(1), pages 20-33, October.
    12. 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.
    13. J Ruggiero, 2000. "Nonparametric estimation of returns to scale in the public sector with an application to the provision of educational services," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(8), pages 906-912, August.
    14. 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.
    15. Henry Tulkens, 2006. "On FDH Efficiency Analysis: Some Methodological Issues and Applications to Retail Banking, Courts and Urban Transit," Springer Books, in: Parkash Chander & Jacques Drèze & C. Knox Lovell & Jack Mintz (ed.), Public goods, environmental externalities and fiscal competition, chapter 0, pages 311-342, Springer.
    16. Niels Christian Petersen, 1990. "Data Envelopment Analysis on a Relaxed Set of Assumptions," Management Science, INFORMS, vol. 36(3), pages 305-314, March.
    17. Hall, Maximilian J.B. & Liu, Wenbin B. & Simper, Richard & Zhou, Zhongbao, 2013. "The economic efficiency of rehabilitative management in young offender institutions in England and Wales," Socio-Economic Planning Sciences, Elsevier, vol. 47(1), pages 38-49.
    18. Banker, Rajiv D., 1984. "Estimating most productive scale size using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 17(1), pages 35-44, July.
    19. 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.
    20. Cinzia Daraio & Léopold Simar, 2007. "Conditional nonparametric frontier models for convex and nonconvex technologies: a unifying approach," Journal of Productivity Analysis, Springer, vol. 28(1), pages 13-32, October.
    21. Cherchye, Laurens & Rock, Bram De & Walheer, Barnabé, 2015. "Multi-output efficiency with good and bad outputs," European Journal of Operational Research, Elsevier, vol. 240(3), pages 872-881.
    22. Verschelde, Marijn & Rogge, Nicky, 2012. "An environment-adjusted evaluation of citizen satisfaction with local police effectiveness: Evidence from a conditional Data Envelopment Analysis approach," European Journal of Operational Research, Elsevier, vol. 223(1), pages 214-225.
    23. Rogge, Nicky & Simper, Richard & Verschelde, Marijn & Hall, Maximilian, 2015. "An analysis of managerialism and performance in English and Welsh male prisons," European Journal of Operational Research, Elsevier, vol. 241(1), pages 224-235.
    24. Ben Vollaard, 2013. "Preventing crime through selective incapacitation," Economic Journal, Royal Economic Society, vol. 123(567), pages 262-284, March.
    25. Peter Bogetoft, 1996. "DEA on Relaxed Convexity Assumptions," Management Science, INFORMS, vol. 42(3), pages 457-465, March.
    26. Duncombe, William & Yinger, John, 1993. "An analysis of returns to scale in public production, with an application to fire protection," Journal of Public Economics, Elsevier, vol. 52(1), pages 49-72, August.
    27. Leigh Drake & Richard Simper, 2002. "X-efficiency and scale economies in policing: a comparative study using the distribution free approach and DEA," Applied Economics, Taylor & Francis Journals, vol. 34(15), pages 1859-1870.
    28. Podinovski, Victor V. & Kuosmanen, Timo, 2011. "Modelling weak disposability in data envelopment analysis under relaxed convexity assumptions," European Journal of Operational Research, Elsevier, vol. 211(3), pages 577-585, June.
    29. Hayfield, Tristen & Racine, Jeffrey S., 2008. "Nonparametric Econometrics: The np Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i05).
    30. 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.
    31. 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.
    32. Victor Podinovski, 2004. "Efficiency and Global Scale Characteristics on the “No Free Lunch” Assumption Only," Journal of Productivity Analysis, Springer, vol. 22(3), pages 227-257, November.
    33. Rajiv D. Banker & Richard C. Morey, 1986. "Efficiency Analysis for Exogenously Fixed Inputs and Outputs," Operations Research, INFORMS, vol. 34(4), pages 513-521, August.
    34. Fethi, Meryem Duygun & Pasiouras, Fotios, 2010. "Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey," European Journal of Operational Research, Elsevier, vol. 204(2), pages 189-198, July.
    35. V V Podinovski, 2004. "Local and global returns to scale in performance measurement," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(2), pages 170-178, February.
    36. Paolo Buonanno & Steven Raphael, 2013. "Incarceration and Incapacitation: Evidence from the 2006 Italian Collective Pardon," American Economic Review, American Economic Association, vol. 103(6), pages 2437-2465, October.
    37. Atici, Kazim Baris & Podinovski, Victor V., 2012. "Mixed partial elasticities in constant returns-to-scale production technologies," European Journal of Operational Research, Elsevier, vol. 220(1), pages 262-269.
    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. Dewitte, Ruben & Dumont, Michel & Merlevede, Bruno & Rayp, Glenn & Verschelde, Marijn, 2020. "Firm-Heterogeneous Biased Technological Change: A nonparametric approach under endogeneity," European Journal of Operational Research, Elsevier, vol. 283(3), pages 1172-1182.
    2. Antonio Peyrache & Maria C. A. Silva, 2023. "Efficiency decomposition for multi-level multi-components production technologies," Journal of Productivity Analysis, Springer, vol. 60(3), pages 273-294, December.

    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. Podinovski, Victor V., 2017. "Returns to scale in convex production technologies," European Journal of Operational Research, Elsevier, vol. 258(3), pages 970-982.
    2. 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.
    3. Valentin Zelenyuk, 2019. "Data Envelopment Analysis and Business Analytics: The Big Data Challenges and Some Solutions," CEPA Working Papers Series WP072019, School of Economics, University of Queensland, Australia.
    4. 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.
    5. 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.
    6. Halkos, George & Tzeremes, Nickolaos, 2011. "A conditional full frontier modelling for analyzing environmental efficiency and economic growth," MPRA Paper 32839, University Library of Munich, Germany.
    7. Halkos, George & Tzeremes, Nickolaos, 2011. "A conditional full frontier approach for investigating the Averch-Johnson effect," MPRA Paper 35491, University Library of Munich, Germany.
    8. Emrouznejad, Ali & De Witte, Kristof, 2010. "COOPER-framework: A unified process for non-parametric projects," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1573-1586, December.
    9. Cordero, José Manuel & Alonso-Morán, Edurne & Nuño-Solinis, Roberto & Orueta, Juan F. & Arce, Regina Sauto, 2015. "Efficiency assessment of primary care providers: A conditional nonparametric approach," European Journal of Operational Research, Elsevier, vol. 240(1), pages 235-244.
    10. Barnabé Walheer, 2020. "Output, input, and undesirable output interconnections in data envelopment analysis: convexity and returns-to-scale," Annals of Operations Research, Springer, vol. 284(1), pages 447-467, January.
    11. Mehdiloo, Mahmood & Podinovski, Victor V., 2019. "Selective strong and weak disposability in efficiency analysis," European Journal of Operational Research, Elsevier, vol. 276(3), pages 1154-1169.
    12. Barnabé Walheer, 2019. "Disaggregation for efficiency analysis," Journal of Productivity Analysis, Springer, vol. 51(2), pages 137-151, June.
    13. Jean-Paul Chavas & Kwansoo Kim, 2015. "Nonparametric analysis of technology and productivity under non-convexity: a neighborhood-based approach," Journal of Productivity Analysis, Springer, vol. 43(1), pages 59-74, February.
    14. 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.
    15. 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.
    16. 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.
    17. Sushanta Mallick & Aarti Rughoo & Nickolaos G. Tzeremes & Wei Xu, 2020. "Technological Change and Catching-Up in the Indian Banking Sector: A Time-Dependent Nonparametric Frontier Approach," Computational Economics, Springer;Society for Computational Economics, vol. 56(1), pages 217-237, June.
    18. Peter Bogetoft & Joseph M. Tama & Jørgen Tind, 2000. "Convex Input and Output Projections of Nonconvex Production Possibility Sets," Management Science, INFORMS, vol. 46(6), pages 858-869, June.
    19. Georgios Georgiadis & Ioannis Politis & Panagiotis Papaioannou, 2020. "How Does Operational Environment Influence Public Transport Effectiveness? Evidence from European Urban Bus Operators," Sustainability, MDPI, vol. 12(12), pages 1-19, June.
    20. Polemis, Michael L. & Tzeremes, Nickolaos G., 2019. "Competitive conditions and sectors’ productive efficiency: A conditional non-parametric frontier analysis," European Journal of Operational Research, Elsevier, vol. 276(3), pages 1104-1118.

    More about this item

    Keywords

    data envelopment analysis; economies of scale; multi-output production; UK penology;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ies:wpaper:e201609. 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: Lies BOUTEN (email available below). General contact details of provider: https://edirc.repec.org/data/iesegfr.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.