Time to include time to death? The future of health care expenditure predictions
研究发现，预测未来医疗支出时若不考虑死亡时间，会高估支出，偏差随寿命延长而增大，对政策制定者评估老龄化成本有重要参考价值。
Government projections of future health care expenditures--a great concern given the aging baby-boom generation--are based on econometric regressions that control explicitly for age but do not control for end-of-life expenditures. Because expenditures increase dramatically on average at the end of life, predictions of future cost distributions based on regressions that omit time to death as an explanatory variable will be biased upward (or, more explicitly, the coefficients on age will be biased upward) if technology or other social factors continue to prolong life. Although health care expenditure predictions for a current sample will not be biased, predictions for future cohorts with greater longevity will be biased upwards, and the magnitude of the bias will increase as the expected longevity increases. We explore the empirical implications of incorporating time to death in longitudinal models of health expenditures for the purpose of predicting future expenditures. Predictions from a simple model that excludes time to death and uses current life tables are 9% higher than from an expanded model controlling for time to death. The bias increases to 15% when using projected life tables for 2020. The predicted differences between the models are sufficient to justify reassessment of the value of inclusion of time to death in models for predicting health care expenditures.