# sftt

**Repository Path**: ranglab/sftt

## Basic Information

- **Project Name**: sftt
- **Description**: Stata command sftt, for two-tier stochastic frontier models.
- **Primary Language**: 其他
- **License**: BSD-3-Clause
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-01-25
- **Last Updated**: 2022-09-12

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

**Notice: this repo has been move to [GitHub/arlionn/sftt](https://github.com/arlionn/sftt) and will not be updated here anymore.**

---

# SFTT

The repository of Stata command *sftt*.


## Description
**sftt** fits two-tier stochastic frontier (2TSF) models with multiple model settings. 

**sftt** provides estimators for the
parameters of a linear model with a disturbance that is assumed to be a mixture of three components: 
two measures of inefficiency which are strictly nonnegative and nonpositive respectively,
and a two-sided error term from a symmetric distribution.

**sftt** can fit 2TSF models with distributional assumption.
When using distributional assumption mode, 
this command is applicable to estimate models in exponential/exponential/normal specification
following [Kumbhakar and Parmeter (2009)](https://doi.org/10.1007/s11123-008-0117-3) 
and models in half-normal/half-normal/normal specification following
[Papadopoulos (2015)](https://doi.org/10.1007/s11123-014-0389-8).

**sftt** also fits models with scaling assumption following
[Parmeter (2018)](https://doi.org/10.1007/s11123-017-0520-8).

**sftt sigs** identifies the distribution of each component in the composite error term.

**sftt eff** decomposes the residual and generate measures of inefficiency.


## Acknowledgments
We thank Alecos Papadopoulos for his amazing support.


## Program Authors
[Yujun Lian](mailto:arlionn@163.com) (repo owner).
Lingnan College, Sun Yat-sen University.
Guangzhou, China.

[Chang Liu](mailto:liuch288@mail2.sysu.edu.cn).
Lingnan College, Sun Yat-sen University
Guangzhou, China.

[Christopher F. Parmeter](cparmeter@bus.miami.edu).
Department of Economics, University of Miami
Miami, FL, USA.

## Repository information

This repository is mainly managed on [Gitee](https://gitee.com/ranglab/sftt), and mirrored on [GitHub](https://github.com/liuch288/sftt).