Extant research in accounting raises issues with the specification and power of discretionary accrual measures. We propose entropy balancing, a recently developed matching technique, as a means to improve the measurement of a normal accrual. Entropy balancing identifies weights for each control sample observation such that the distributions of underlying fundamental determinants of accruals are designed to be identical across treatment and control samples. We show that entropy-balanced accruals are well-specified within samples of extreme financial performance, are significantly associated with ex post indicators of earnings management, and, based on simulations, exhibit sufficient power for detecting earnings management. Finally, in contrast to existing discretionary accruals measures, we find that entropy-balanced discretionary accruals are insignificant (significantly positive) in the year of an initial public offering (seasoned equity offering).