XTKUMBLIENHARD: Stata module to Estimate Generalized Four-Component Panel Data Stochastic Frontier Models

xtkumblienhard is a powerful and user-friendly Stata command designed to estimate Generalized Four-Component Panel Data Stochastic Frontier Models, all in a single line of code. This package streamlines the estimation of a sophisticated stochastic frontier framework where the composite error term is decomposed into four distinct components: unobserved individual heterogeneity, persistent inefficiency, transitory inefficiency and random noise. By clearly separating these sources of variation, xtkumblienhard enables researchers to gain deeper insights into performance dynamics across panel data settings. This model builds on the influential and excellent works of Kumbhakar, Lien and Hardaker (Journal of Productivity Analysis, 2014), Kumbhakar, Wang and Horncastle (Cambridge University Press, 2015), and Nguyen, Sickles and Zelenyuk (Springer, 2022), who originally implemented it through multi-step procedures. The innovation of xtkumblienhard lies in its simplicity: it brings the full power of this four-component framework to Stata users with native ADO language syntax, eliminating the need for complex coding or external scripts. Rather than replacing these foundational and outstanding contributions, xtkumblienhard democratizes access to advanced stochastic frontier analysis, making it faster, easier, and more intuitive for applied researchers, analysts, and students alike. Whether you are studying firm-level productivity, benchmarking efficiency, or exploring heterogeneity in performance, xtkumblienhard is your go-to tool for robust and elegant estimation.