随机元边界的贝叶斯估计

IF 1.8 4区经济学 Q2 ECONOMICS

Economics Letters Pub Date : 2025-05-04 DOI:10.1016/j.econlet.2025.112368

Ioannis Skevas

引用次数: 0

摘要

本文提出了一种贝叶斯方法来估计用于元前沿分析的分层面板数据随机前沿模型。它使用基于贝叶斯仿真的推理和用户友好的软件，需要最少的编码。仿真和实际数据验证了模型的可靠性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Bayesian estimation of stochastic metafrontiers

This paper presents a Bayesian method for estimating a hierarchical panel data stochastic frontier model for metafrontier analysis. It uses Bayesian simulation-based inference and user-friendly software, requiring minimal coding. Applications to simulated and real data confirm the model’s reliability.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Economics Letters ECONOMICS-

CiteScore

3.20

自引率

5.00%

发文量

348

审稿时长

30 days

期刊介绍： Many economists today are concerned by the proliferation of journals and the concomitant labyrinth of research to be conquered in order to reach the specific information they require. To combat this tendency, Economics Letters has been conceived and designed outside the realm of the traditional economics journal. As a Letters Journal, it consists of concise communications (letters) that provide a means of rapid and efficient dissemination of new results, models and methods in all fields of economic research.