Operations Research

Download Advanced Robust and Nonparametric Methods in Efficiency by Cinzia Daraio PDF

By Cinzia Daraio

Offering a scientific and finished remedy of modern advancements in potency research, this ebook makes to be had an intuitive but rigorous presentation of complex nonparametric and powerful tools, with purposes for the research of economies of scale and scope, trade-offs in creation and repair actions, and factors of potency differentials.

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Additional resources for Advanced Robust and Nonparametric Methods in Efficiency Analysis: Methodology and Applications (Studies in Productivity and Efficiency)

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N. The main weakness of this approach is the sensitivity to “super-efficient” outliers. Robust estimators are able to overcome this drawback. e. some observations might lie outside Ψ. The main problem of this approach is the identification of noise from inefficiency. , T }. Panel data allow the measurement of productivity change as well as the estimation of technical progress or regress. Generally speaking, productivity change occurs when an index of outputs changes at a different rate than an index of inputs does.

3 As a more micro level is concerned, Simon (1955, 1957) analyzed the performance of producers in the presence of bounded rationality and satisfying behavior. Later Leibenstein (1966, 1975, 1976, 1978, 1987) argued that production is bound to be inefficient as a result of motivation, information, monitoring, and agency problems within the firm. This type of inefficiency, the so called “X-inefficiency” has been criticized by Stigler (1976) and de Alessi (1983) among others since it reflects an incompletely specified model rather than a failure to optimize.

The nonparametric frontier approach, based on envelopment techniques (DEA FDH), has been extensively used for estimating efficiency of firms as it relays only on very few assumptions for Ψ. On the contrary, the stochastic frontier approach (SFA) allows the presence of noise but it demands parametric restrictions on the shape of the frontier and on the Data Generating Process (DGP) in order to permit the identification of noise from inefficiency and the estimation of the frontier. Fried, Lovell and Schmidt (2006) offer an updated presentation of both approaches.

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