As of Aug. 2, 2021, 1693 injury claims associated with COVID-19 medical countermeasures have been filed in the Countermeasures Injury Compensation Program (CICP), of which 686 claims were related to COVID-19 vaccines and urgently needed compensation decisions. However, from an economic and public policy perspective, we find that the CICP design has unintended consequences: locating CICP in the executive agency DHHS potentially creates a conflict of interest, and not permitting judicial review generates a lack of checks and balances, both of which could jeopardize justice. These fundamental problems would subsequently weaken four key performance indicators of CICP compared with its judicial counterpart in the Court of Federal Claims. CICP lacks accountability, transparency, and cost-effectiveness efficiency, with 94% of its total costs spent on administration rather than compensation. CICP’s ability to compensate is also questionable. If COVID-19 claims were compensated at its historical rate, CICP would face around $21.16 million in compensation outlays and $317.94 million in total outlays, 72.1 times its current balance. To ensure just compensation for injured petitioners during COVID-19 and future public health emergencies, we recommend Congress (1) initiate a major reform by relocating CICP from DHHS to the Claims Court or (2) keep CICP within DHHS and make incremental changes by permitting judicial review of DHHS administrative adjudication of CICP claims. We further recommend Congress audit and adjust budgets for CICP and DHHS promptly propose an injury table for COVID-19 claims. This is the first study that contributes an economic perspective to the limited literature on CICP and also provides unique and rich economic data.

This study proposes a semi-parametric estimation method, Box-Cox power transformation unconditional quantile regression, to estimate the impact of changes in the distribution of the explanatory variables on the unconditional quantile of the outcome variable. The proposed method consists of running a nonlinear regression of the recentered influence function (RIF) of the outcome variable on the explanatory variables. We also show the asymptotic properties of the proposed estimator and apply the estimation method to address an existing puzzle in labor economics-why the 50th/10th percentile wage gap has been falling in the USA since the late 1980s. Our results show that declining unionization can explain approximately 10% of the decline in the 50/10 wage gap in 1990-2000 and 23% in 2000-2010.