Spatial autoregressive stochastic frontier model with application to Indonesia’s aquaculture
نویسندگان
چکیده
منابع مشابه
Spatial-temporal Stochastic Frontier Models
The stochastic frontier model with heterogeneous technical efficiency explained by exogenous variables is augmented with a sparse spatial autoregressive component for a crosssection data, and a spatial-temporal component for a panel data. An estimation procedure that takes advantage of the additivity of the model is proposed, computational advantages over simultaneous maximum likelihood estimat...
متن کاملMalaysian white shrimp (P. vannamei) aquaculture: an application of stochastic frontier analysis on technical efficiency
Shrimp aquaculture is playing a vital role in Malaysian agriculture, especially its increasing contribution to economic growth. White shrimp aquaculture is not only the key player in brackish water shrimp aquaculture but also the largest contributor to Malaysian shrimp aquaculture. This study estimates technical efficiency and investigates factors affecting technical inefficiency of Malaysian w...
متن کاملA Laplace Stochastic Frontier Model
We propose a Laplace stochastic frontier model as an alternative to the traditional model with normal errors. An interesting feature of the Laplace model is that the distribution of inefficiency conditional on the composed error is constant for positive values of the composed error, but varies for negative values. Therefore, it may be ideally suited for analyzing industries with many forms on o...
متن کاملSpatial-Temporal Autoregressive Dynamic Model
Although a myriad of methods have been advanced to tackle spatial and temporal structures in data separately, it becomes difficult to analyze these data using classical linear regression models when spatial-temporal structures coexist, especially when the data size is relatively large. In this article, we demonstrate a simple to implement method to handle spatial-temporal structures simultaneou...
متن کاملStochastic Non-Parametric Frontier Analysis
In this paper we develop an approach that synthesizes the best features of the two main methods in the estimation of production efficiency. Specically, our approach first allows for statistical noise, similar to Stochastic frontier analysis, and second, it allows modeling multiple-inputs-multiple-outputs technologies without imposing parametric assumptions on production relationship, similar to...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Physics: Conference Series
سال: 2021
ISSN: 1742-6588,1742-6596
DOI: 10.1088/1742-6596/1863/1/012044