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Systematic Bias and Nontransparency in US Social Security Administration Forecasts

“At present, the Office of the Chief Actuary, at the Social Security Administration, does not reveal in full how its forecasts are made and, as a result, no other person, party, or organization, in or out of government, has been able to make fully independent quantitative evaluations of policy proposals about Social Security. Even the Congressional Budget Office, which produces Social Security Trust Fund solvency forecasts, relies on the demographic forecasts produced by the Office of the Chief Actuary as inputs for its models. Thus, the Office of the Chief Actuary holds an unusual position within American politics of being the sole supplier of Social Security forecasts, as well as heading the only organization producing fully independent quantitative evaluations of policy proposals to alter Social Security. For each evaluation of a proposed policy, the Office of the Chief Actuary estimates the effect on key financial outcomes that assess the solvency of the Trust Funds. For the vast majority of policy proposals evaluated by the Office of the Chief Actuary, the estimated financial impact is smaller than almost all of SSA’s forecasting errors since 2000. Social Security Administration forecasts of current law and its counterfactual evaluation of policy proposals share the same growing bias because both are based on the same forecasting methodology. Additionally, the uncertainty surrounding the estimated effects of proposed policies, which would likely be larger than the uncertainty in the forecasts under current law, usually dominate the estimated effect of the policy. In the conclusion of the article, we argue that the Social Security Administration and its Office of the Chief Actuary should follow best practices in academia and many other parts of government and make their  forecasting procedures public and replicable, and should calculate and report calibrated uncertainty intervals for all forecasts. In a companion paper, we offer an explanation for the origin of the biases reported here and propose simple structural ways of changing the system to fix the problems going forward [Kashin, King, and Soneji – Journal of Economic Perspectives—Volume 29, Number 2—Spring 2015—Pages 239–258].

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