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Non-Discretionary Inputs

In: Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis

Author

Listed:
  • John Ruggiero

    (University of Dayton)

Abstract

A motivating factor for Data Envelopment Analysis (DEA) was the measurement of technical efficiency in public sector applications with unknown input prices. Many applications, including public sector production, are also characterized by heterogeneous producers who face different technologies. This chapter discusses existing approaches to measuring performance when non-discretionary inputs affect the transformation of discretionary inputs into outputs. The suitability of the approaches depends on underlying assumptions about the relationship between non-discretionary inputs and outputs. One model treats non-discretionary inputs like discretionary inputs but uses a non-radial approach to project inefficient decision making units (DMUs) to the frontier holding non-discretionary inputs fixed. A potential drawback is the assumption that convexity holds with respect to non-discretionary inputs and outputs. Alternatively, the assumption of convexity can be relaxed by comparing DMUs only to other DMUs with similar environments. Other models use multiple stage models with regression to control for the effect that non-discretionary inputs have on production.

Suggested Citation

  • John Ruggiero, 2007. "Non-Discretionary Inputs," Springer Books, in: Joe Zhu & Wade D. Cook (ed.), Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis, chapter 0, pages 85-101, Springer.
    • Handle: RePEc:spr:sprchp:978-0-387-71607-7_5
    DOI: 10.1007/978-0-387-71607-7_5
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