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Investment and dynamic DEA

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  • Pierre Ouellette
  • Li Yan

    ()

Abstract

A dynamic version of Data Envelopment Analysis (DEA) is developed in the present paper. Our model introduces investment in traditional DEA and imposes intertemporal cost minimization. Adding an intertemporal adjustment constraint into the cost minimization problem, we derive the relation between the DEA variables of the cost function and those of the primary production frontiers’ coefficients. The augmented DEA model can be solved using standard linear programming. This dynamic framework enables computing the production frontiers, measuring the productive efficiencies and evaluating the potential economies all in the presence of adjustment costs.

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File URL: http://hdl.handle.net/10.1007/s11123-007-0079-x
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Bibliographic Info

Article provided by Springer in its journal Journal of Productivity Analysis.

Volume (Year): 29 (2008)
Issue (Month): 3 (June)
Pages: 235-247

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Handle: RePEc:kap:jproda:v:29:y:2008:i:3:p:235-247

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Web page: http://www.springerlink.com/link.asp?id=100296

Related research

Keywords: Adjustment cost; Data envelopment analysis; Efficiency; Multiple outputs/inputs; Quasi-fixed inputs; D24; L23;

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References

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  1. Pierre Lasserre & Pierre Ouellette, 1993. "Dynamic Factor Demands and Technology Measurement Under Arbitrary Expectations," Cahiers de recherche du Département des sciences économiques, UQAM 9509, Université du Québec à Montréal, Département des sciences économiques, revised Jul 1995.
  2. Elvira Silva & Spiro Stefanou, 2003. "Nonparametric Dynamic Production Analysis and the Theory of Cost," Journal of Productivity Analysis, Springer, vol. 19(1), pages 5-32, January.
  3. Elvira Silva & Spiro E. Stefanou, 2007. "Dynamic Efficiency Measurement: Theory and Application," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 89(2), pages 398-419.
  4. Nemoto, Jiro & Goto, Mika, 1999. "Dynamic data envelopment analysis: modeling intertemporal behavior of a firm in the presence of productive inefficiencies," Economics Letters, Elsevier, vol. 64(1), pages 51-56, July.
  5. Pierre Ouellette & Stéphane Vigeant, 2000. "A General Procedure to Recover the Marginal Products of a Cost Minimizing Firm," Journal of Productivity Analysis, Springer, vol. 14(2), pages 143-162, September.
  6. Jiro Nemoto & Mika Goto, 2003. "Measurement of Dynamic Efficiency in Production: An Application of Data Envelopment Analysis to Japanese Electric Utilities," Journal of Productivity Analysis, Springer, vol. 19(2), pages 191-210, April.
  7. 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.
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Citations

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Cited by:
  1. Pierre Ouellette & Valérie Vierstraete, 2008. "Malmquist indexes with quasi-fixed inputs: An application to school districts in Québec," Cahiers de recherche 08-25, Departement d'Economique de la Faculte d'administration à l'Universite de Sherbrooke.
  2. Elvira Silva & Alfons Oude Lansink, 2013. "Dynamic Efficiency Measurement: A Directional Distance Function Approach," CEF.UP Working Papers 1307, Universidade do Porto, Faculdade de Economia do Porto.
  3. Kao, Chiang, 2013. "Dynamic data envelopment analysis: A relational analysis," European Journal of Operational Research, Elsevier, vol. 227(2), pages 325-330.

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