Publications by Author: Konstantin Kashin

2016
Scoring Social Security Proposals: Response from Kashin, King, and Soneji
Konstantin Kashin, Gary King, and Samir Soneji. 2016. “Scoring Social Security Proposals: Response from Kashin, King, and Soneji.” Journal of Economic Perspectives, 30, 2, Pp. 245-248. Publisher's VersionAbstract

This is a response to Peter Diamond's comment on a two paragraph passage in our article, Konstantin Kashin, Gary King, and Samir Soneji. 2015. “Systematic Bias and Nontransparency in US Social Security Administration Forecasts.” Journal of Economic Perspectives, 2, 29: 239-258. 

Article
2015
Explaining Systematic Bias and Nontransparency in US Social Security Administration Forecasts
Konstantin Kashin, Gary King, and Samir Soneji. 2015. “Explaining Systematic Bias and Nontransparency in US Social Security Administration Forecasts.” Political Analysis, 23, 3, Pp. 336-362. Publisher's VersionAbstract

The accuracy of U.S. Social Security Administration (SSA) demographic and financial forecasts is crucial for the solvency of its Trust Funds, other government programs, industry decision making, and the evidence base of many scholarly articles. Because SSA makes public little replication information and uses qualitative and antiquated statistical forecasting methods, fully independent alternative forecasts (and the ability to score policy proposals to change the system) are nonexistent. Yet, no systematic evaluation of SSA forecasts has ever been published by SSA or anyone else --- until a companion paper to this one (King, Kashin, and Soneji, 2015a). We show that SSA's forecasting errors were approximately unbiased until about 2000, but then began to grow quickly, with increasingly overconfident uncertainty intervals. Moreover, the errors are all in the same potentially dangerous direction, making the Social Security Trust Funds look healthier than they actually are. We extend and then attempt to explain these findings with evidence from a large number of interviews we conducted with participants at every level of the forecasting and policy processes. We show that SSA's forecasting procedures meet all the conditions the modern social-psychology and statistical literatures demonstrate make bias likely. When those conditions mixed with potent new political forces trying to change Social Security, SSA's actuaries hunkered down trying hard to insulate their forecasts from strong political pressures. Unfortunately, this otherwise laudable resistance to undue influence, along with their ad hoc qualitative forecasting models, led the actuaries to miss important changes in the input data. Retirees began living longer lives and drawing benefits longer than predicted by simple extrapolations. We also show that the solution to this problem involves SSA or Congress implementing in government two of the central projects of political science over the last quarter century: [1] promoting transparency in data and methods and [2] replacing with formal statistical models large numbers of qualitative decisions too complex for unaided humans to make optimally.

Article
Konstantin Kashin, Gary King, and Samir Soneji. 2015. “Replication Data for: Explaining Systematic Bias and Nontransparency in U.S. Social Security Administration Forecasts.”. Published on Harvard Dataverse
Konstantin Kashin, Gary King, and Samir Soneji. 2015. “Replication Data for: Systematic Bias and Nontransparency in U.S. Social Security Administration Forecasts.”. Published on Harvard Dataverse
Systematic Bias and Nontransparency in US Social Security Administration Forecasts
Konstantin Kashin, Gary King, and Samir Soneji. 2015. “Systematic Bias and Nontransparency in US Social Security Administration Forecasts.” Journal of Economic Perspectives, 29, 2, Pp. 239-258. Publisher's VersionAbstract

The financial stability of four of the five largest U.S. federal entitlement programs, strategic decision making in several industries, and many academic publications all depend on the accuracy of demographic and financial forecasts made by the Social Security Administration (SSA). Although the SSA has performed these forecasts since 1942, no systematic and comprehensive evaluation of their accuracy has ever been published by SSA or anyone else. The absence of a systematic evaluation of forecasts is a concern because the SSA relies on informal procedures that are potentially subject to inadvertent biases and does not share with the public, the scientific community, or other parts of SSA sufficient data or information necessary to replicate or improve its forecasts. These issues result in SSA holding a monopoly position in policy debates as the sole supplier of fully independent forecasts and evaluations of proposals to change Social Security. To assist with the forecasting evaluation problem, we collect all SSA forecasts for years that have passed and discover error patterns that could have been---and could now be---used to improve future forecasts. Specifically, we find that after 2000, SSA forecasting errors grew considerably larger and most of these errors made the Social Security Trust Funds look more financially secure than they actually were. In addition, SSA's reported uncertainty intervals are overconfident and increasingly so after 2000. We discuss the implications of these systematic forecasting biases for public policy.

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