TY  - RPRT
        AU  - Schmieder, Johannes F.
        TI  - fevc: Leave-Out Bias-Corrected Variance Decompositions in Stata
        PY  - 2026/Oct/
        PB  - Institute of Labor Economics (IZA)
        CY  - Bonn
        T2  - IZA Discussion Paper
        IS  - 19053
        UR  - https://www.iza.org/publications/dp19053
        AB  - Variance decompositions with worker and firm fixed effects measure heterogeneity and sorting, but estimation noise biases plug-in estimates. This article introduces fevc, a Stata command implementing the leave-out bias correction of Kline, Saggio, and Sølvsten (2020). It reports corrected worker and firm variances, their covariance, and the variance of their sum, with choices over deletion units, controls, and population weights. It also reports standard errors for projections of fixed effects on observed characteristics. A source-only Mata backend provides portability; a parallel Rust backend handles large datasets. Randomized calculations report Monte Carlo standard errors. In public Italian social-security data, the correction halves estimated firm-effect variance and reverses the worker–firm covariance’s sign. In synthetic benchmarks with 6.4 million observations and 28 threads, Rust is 1.3–3.5 times as fast as the KSS Matlab package; under match deletion, measured peak memory is about 30 percent of Matlab’s.
        KW  - fevc
KW  - two-way fixed effects
KW  - variance decomposition
KW  - leave-out estimation
KW  - limited-mobility bias
KW  - Mata
KW  - Rust
KW  - randomized linear algebra
        ER  -