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).