Matlab code for computing robust empirical Bayes confidence intervals (EBCIs)

Reference: Armstrong, Timothy B., Michal Kolesár, and Mikkel Plagborg-Møller (2022), "Robust Empirical Bayes Confidence Intervals", Econometrica 90(6), 2567-2602 (also available as arXiv:2004.03448)

See also the ebci R package by Michal Kolesár (who deserves all intellectual credit for the code structure) and the ebciStata Stata package

Tested in Matlab R2021a on Windows 10 PC, 64-bit

ebci: EBCI routines

• cva.m: robust EBCI critical value
• ebci.m: main function for computing parametric or robust EBCIs
• parametric_ebci_maxnoncov.m: worst-case non-coverage probability of parametric EBCI
• Additional auxiliary functions

vignette: example code with empirical illustration

• cz.csv: Chetty & Hendren (2018) data set (obtained from https://opportunityinsights.org/data/)
• run_ebci.m: annotated script with examples

Matlab's Optimization Toolbox must be installed.

This software package is based upon work supported by the National Science Foundation under grant numbers SES-2049765 (Armstrong), SES-22049356 (Kolesár), and SES-1851665 (Plagborg-Møller), and by work supported by the Alfred P. Sloan Research Fellowship (Kolesár).