The QLIM Procedure |

Stochastic Frontier Production and Cost Models |

Stochastic frontier production models were first developed by Aigner, Lovell, and Schmidt (1977) and Meeusen and van den Broeck (1977). Specification of these models allow for random shocks of the production or cost but also include a term for technological or cost inefficiency. Assuming that the production function takes a log-linear Cobb-Douglas form, the stochastic frontier production model can be written as

where . The term represents the stochastic error component and is the nonnegative, technology inefficiency error component. The error component is assumed to be distributed iid normal and independently from . If , the error term, , is negatively skewed and represents technology inefficiency. If , the error term is positively skewed and represents cost inefficiency. PROC QLIM models the error component as a half normal, exponential, or truncated normal distribution.

In case of the normal-half normal model, is iid , is iid with and independent of each other. Given the independence of error terms, the joint density of and can be written as

Substituting into the preceding equation gives

Integrating out to obtain the marginal density function of results in the following form:

where and .

In the case of a stochastic frontier cost model, and

The log-likelihood function for the production model with producers is written as

Under the normal-exponential model, is iid and is iid exponential. Given the independence of error term components and , the joint density of and can be written as

The marginal density function of for the production function is

and the marginal density function for the cost function is equal to

The log-likelihood function for the normal-exponential production model with producers is

The normal-truncated normal model is a generalization of the normal-half normal model by allowing the mean of to differ from zero. Under the normal-truncated normal model, the error term component is iid and is iid . The joint density of and can be written as

The marginal density function of for the production function is

and the marginal density function for the cost function is

The log-likelihood function for the normal-truncated normal production model with producers is

For more detail on normal-half normal, normal-exponential, and normal-truncated models, see Kumbhakar and Knox Lovell (2000) and Coelli, Prasada Rao, and Battese (1998).

Copyright © 2008 by SAS Institute Inc., Cary, NC, USA. All rights reserved.