Nonparametric estimation of the determinants of inefficiency

Parmeter, Christopher F.; Wang, Hung‐Jen; Kumbhakar, Subal C.

doi:10.1007/s11123-016-0479-x

Cited by 44 publications

(39 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Parmeter and Kumbhakar (2014) discuss about a distribution free inefficiency effects model which was first proposed in Simar, Lovell and van den Eeckaut (1994) and later explained in details in Wang and Schmidt (2002) and Alvarez, Amsler, Orea and Schmidt (2006). Parmeter, Wang and Kumbhakar (2016) non-parametrically estimate distribution free inefficiency effects using a partly linear model initially proposed by Robinson (1988). This model is similar to the one proposed by Deprins andSimar (1989a, 1989b) and extended by Deprins (1989).…”

Section: Introductionmentioning

confidence: 90%

An Alternative Specification for Technical Efficiency Effects in a Stochastic Frontier Production Function

Paul

Shankar

2017

SSRN Journal

View full text Add to dashboard Cite

This paper proposes an alternative specification for technical efficiency effects in a stochastic production frontier model. The proposed specification is distribution free and thus eschews onesided error term present in almost all the existing inefficiency effects models. The efficiency effects are represented by the standard normal cumulative distribution function of exogenous variables which ensures the efficiency scores to lie in a unit interval. An empirical exercise based on widely used Philippines rice farming data set illustrates the simplicity and usefulness of the proposed model. AbstractThis paper proposes an alternative specification for technical efficiency effects in a stochastic production frontier model. The proposed specification is distribution free and thus eschews one-sided error term present in almost all the existing inefficiency effects models. The efficiency effects are represented by the standard normal cumulative distribution function of exogenous variables which ensures the efficiency scores to lie in a unit interval. An empirical exercise based on widely used Philippines rice farming data set illustrates the simplicity and usefulness of the proposed model.

show abstract

Section: Introductionmentioning

confidence: 90%

An Alternative Specification for Technical Efficiency Effects in a Stochastic Frontier Production Function

Paul

Shankar

2017

SSRN Journal

View full text Add to dashboard Cite

show abstract

“…With panel data, one can relax the distribution assumption on the inefficiency term (see Schmidt and Sickles 1984, Cornwell, Schmidt, and Sickles 1990and Lee and Schmidt 1993, Horrace and Parmeter 2011and Parmeter, Wang, and Kumbhakar 2017 for different approaches). However, flexibility in modeling the frontier is still limited to a known parametric functional form such as Cobb-Douglas or translog.…”

Section: Adkinsmentioning

confidence: 99%

Does Economic Freedom Affect the Production Frontier? A Semiparametric Approach With Panel Data

2018

View full text Add to dashboard Cite

This paper applies a multistep semiparametric stochastic production frontier estimator to investigate the effects of economic freedom (EF) on the production frontier and technical efficiency. We allow output elasticities and technical efficiency to depend on EF, estimate a smooth coefficient stochastic production frontier, and compare with parametric alternatives. Our results highlight the flexibility of semiparametric approaches as we find parametric approaches are too restrictive in estimating marginal productivity. Output elasticities of labor, human capital, and physical capital vary with the level of EF and our average efficiency estimates are at least 20% higher than those obtained from parametric counterparts. (JEL C14, O43)

show abstract

“…Annual data from 1975-1976 to 1984-1985 12 A potential limitation of our specification as well most other distribution free inefficiency effects models including the recent one by Parmeter et al (2017) is that the firms with the same z have the same efficiency. However, in most practical applications if sufficient number of variables are included into the (in) efficiency effects model then it is less likely that any two firms in the same time period or the same firm across different time periods will have the same z vector.…”

Section: An Empirical Illustrationmentioning

confidence: 99%

“…Parmeter et al (2017) non-parametrically estimate distribution free inefficiency effects using a partly linear model initially proposed by Robinson (1988). This model is similar to the one proposed by Deprins andSimar (1989a, 1989b) and extended in Deprins (1989).…”

Section: Introductionmentioning

confidence: 98%