Food environment and weight outcomes: a stochastic frontier approach

Stochastic 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...

A new approach to stochastic frontier estimation: DEA+

The outcome of a production process might not only deviate from a theoretical maximum due to inefficiency, but also because of non-controllable influences. This raises the issue of reliability of Data Envelopment Analysis in noisy environments. I propose to assume an i.i.d. data generating process with bounded noise component, so that the following approach is feasible: Use DEA to estimate a ps...

Determinants of mutual fund underperformance: A Bayesian stochastic frontier approach

The purpose of this paper is to identify ex ante fund statistics that can be related to future performance of European equity funds. In an efficient market setting, actively managed portfolios cannot outperform a passive benchmark strategy. However, purely by chance, some funds outperform their benchmark ex post, making the identification of performance determinants a difficult task. To allevia...

Benchmarking Organizational Performance of University Extension : a Stochastic Frontier Approach

Regional Disparity of Productivity in China: A Stochastic Frontier Approach

We attempt to use a group-specific stochastic frontier method to analyze temporal change in the regional productivity performance of China. This method allows us to separate China into three different regional groups, namely the eastern, central, and western, each of which can have its own temporal movement of inefficiency. Our estimation indicates that Shanghai is the most efficient economy in...