Christopher Parmeter, Artem Prokhorov, Valentin Zelenyuk
arXiv 20 May 2025 · Econometrics · 1 citations (OpenAlex)
arXiv:2505.14282 · PDF · DOI · OpenAlex · Extracted main text
Big data and machine learning methods have become commonplace across economic milieus. One area that has not seen as much attention to these important topics yet is efficiency analysis. We show how the availability of big (wide) data can actually make detection of inefficiency more challenging. We then show how machine learning methods can be leveraged to adequately estimate the primitives of the frontier itself as well as inefficiency using the `post double LASSO' by deriving Neyman orthogonal moment conditions for this problem. Finally, an application is presented to illustrate key differences of the post-double LASSO compared to other approaches.
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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 | Aigner, D., C. Lovell, and P. Schmidt (1977) Formulation and estimation of stochastic frontier production function models | 0.874 | 6 | 4 | 67% |
| 2 | Belloni, A., V. Chernozhukov, and C. Hansen (2014) b): Inference on Treatment Effects after Selection among High-Dimensional Controls | 0.874 | 6 | 2 | 100% |
| 3 | Belloni, A., V. Chernozhukov, and C. Hansen (2014) a): High-Dimensional Methods and Inference on Structural and Treatment Effects | 0.874 | 6 | 2 | 100% |
| 4 | Jin, F. and L.-f. Lee (2018) Lasso Maximum Likelihood Estimation of Parametric Models with Singular Information Matrices | 0.644 | 2 | 2 | 100% |
| 5 | Amsler, C., A. Prokhorov, and P. Schmidt (2016) Endogeneity in stochastic frontier models | 0.585 | 3 | 1 | 100% |
| 6 | Waldman, D. M (1982) A stationary point for the stochastic frontier likelihood | 0.585 | 3 | 1 | 100% |
| 7 | Alvarez, A. and C. Arias (2004) Technical efficiency and farm size: a conditional analysis | 0.511 | 2 | 1 | 100% |
| 8 | Belloni, A., V. Chernozhukov, and Y. Wei (2016) b): Post-Selection Inference for Generalized Linear Models With Many Controls | 0.511 | 2 | 1 | 100% |
| 9 | Olson, J. A., P. Schmidt, and D. M. Waldman (1980) A Monte Carlo study of estimators of stochastic frontier production functions | 0.511 | 2 | 1 | 100% |
| 10 | Tibshirani, R (1996) Regression Shrinkage and Selection via the Lasso | 0.511 | 2 | 1 | 100% |
Showing the top 10 of 31 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Recent Advances in Causal Analysis of the Stochastic Frontier Model | 0.405 | 1 | 1 |