Replication data for: Systematic Bias and Nontransparency in US Social Security Administration Forecasts

Principal Investigator(s): View help for Principal Investigator(s) Konstantin Kashin; Gary King; Samir Soneji

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KKS_JEP2015			10/21/2021 10:26:AM
LICENSE.txt	text/plain	14.6 KB	10/12/2019 02:02:PM

Project Citation:

Kashin, Konstantin, King, Gary, and Soneji, Samir. Replication data for: Systematic Bias and Nontransparency in US Social Security Administration Forecasts. Nashville, TN: American Economic Association [publisher], 2015. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2019-10-12. https://doi.org/10.3886/E113949V1

Project Description

Summary: We offer an evaluation of the Social Security Administration demographic and financial forecasts used to assess the long-term solvency of the Social Security Trust Funds. This same forecasting methodology is also used in evaluating policy proposals put forward by Congress to modify the Social Security program. Ours is the first evaluation to compare the SSA forecasts with observed truth; for example, we compare forecasts made in the 1980s, 1990s, and 2000s with outcomes that are now available. We find that Social Security Administration forecasting errors—as evaluated by how accurate the forecasts turned out to be—were approximately unbiased until 2000 and then became systematically biased afterward, and increasingly so over time. Also, most of the forecasting errors since 2000 are in the same direction, consistently misleading users of the forecasts to conclude that the Social Security Trust Funds are in better financial shape than turns out to be the case. Finally, the Social Security Administration's informal uncertainty intervals appear to have become increasingly inaccurate since 2000. At present, the Office of the Chief Actuary, at the Social Security Administration, does not reveal in full how its forecasts are made. Every future Trustees Report, without exception, should include a routine evaluation of all prior forecasts, and a discussion of what forecasting mistakes were made, what was learned from the mistakes, and what actions might be taken to improve forecasts going forward. And 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.

Scope of Project

Subject Terms: Social Security; Solvency

JEL Classification:
C53 Forecasting Models; Simulation Methods
H55 Social Security and Public Pensions

Geographic Coverage: United States

Time Period(s): 1982 – 2010

Data Type(s): aggregate data

Methodology

Data Source: Social Security Administration Trustees' Reports

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Published Versions

V1 [2019-10-12]

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