Kazuki Tomioka, Thomas T. Yang, Xibin Zhang
arXiv 12 Dec 2024 · Econometrics · publishedJournal of Business and Economic Statistics (2026)
arXiv:2412.08831 · PDF · DOI · OpenAlex · Extracted main text
Stochastic frontier models have attracted significant interest over the years due to their unique feature of including a distinct inefficiency term alongside the usual error term. To effectively separate these two components, strong distributional assumptions are often necessary. To overcome this limitation, numerous studies have sought to relax or generalize these models for more robust estimation. In line with these efforts, we introduce a latent group structure that accommodates heterogeneity across firms, addressing not only the stochastic frontiers but also the distribution of the inefficiency term. This framework accounts for the distinctive features of stochastic frontier models, and we propose a practical estimation procedure to implement it. Simulation studies demonstrate the strong performance of our proposed method, which is further illustrated through an application to study the cost efficiency of the U.S. commercial banking sector.
appendix boundary found by appendix_command · 32% of the source is main text. Read the extracted text to check this.
The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Greene (2005) Fixed and Random Effects in Stochastic Frontier Models | 0.941 | 6 | 3 | 83% |
| 2 | Greene (2005) Reconsidering Heterogeneity in Panel Data Estimators of the Stochastic Frontier Model | 0.928 | 10 | 5 | 80% |
| 3 | Yao et al (2019) Semiparametric Smooth Coefficient Stochastic Frontier Model With Panel Data | 0.909 | 8 | 5 | 75% |
| 4 | Chen (2019) Estimating Latent Group Structure in Time-Varying Coefficient Panel Data Models | 0.843 | 3 | 3 | 100% |
| 5 | Tsionas and Kumbhakar (2014) Firm Heterogeneity, Persistent and Transient Technical Inefficiency: A Generalized True Random-Effects Model | 0.737 | 3 | 2 | 100% |
| 6 | Lai and Kumbhakar (2023) Panel Stochastic Frontier Model With Endogenous Inputs and Correlated Random Components | 0.644 | 2 | 2 | 100% |
| 7 | Atak et al (2025) Specification Tests for Time-Varying Coefficient Panel Data Models | 0.585 | 3 | 3 | 33% |
| 8 | Feng et al (2017) A Varying-Coefficient Panel Data Model with Fixed Effects: Theory and an Application to US commercial Banks | 0.585 | 3 | 1 | 100% |
| 9 | Zhou et al (2020) Nonparametric Estimation of the Determinants of Inefficiency in the Presence of Firm Heterogeneity | 0.511 | 5 | 2 | 20% |
| 10 | Chen et al (2014) Consistent Estimation of the Fixed Effects Stochastic Frontier Model | 0.511 | 4 | 2 | 25% |
Showing the top 10 of 45 scored citations.