Probabilistic population forecasts are useful because they describe uncertainty in a quantitatively useful way. One approach (that we call LT) uses historical data to estimate stochastic models (e.g., a time series model) of vital rates, and then makes forecasts. Another (we call it RS) began as...

Demographers have shown that there are regularities in mortality change overtime, and have used these to forecast changes due to population aging. Such models leave out potential economic feedbacks that should be captured by dynamic models such as the general-equilibrium, overlapping-generations...

We present stochastic forecasts of the Social Security trust fund by modeling key demographic and economic variables as historical time series, and using the fitted models to generate computer simulations of future fund performance. We evaluate several plans for achieving long-term solvency by...

We present stochastic forecasts of the Social Security trust fund by modeling key demographic and economic variables as historical time series, and using the fitted models to generate computer simulations of future fund performance. We evaluate several plans for achieving long-term solvency by...

In this paper, we compute distributions of rates of return by cohort for the Social Security retirement system, using a combination of historical data and stochastic forecasts of productivity and mortality rates. Since our forecasts of productivity and mortality are stochastic, the...

We present forecasts of the Social Security trust fund, modeling key demographic and economic variables as time series. We evaluate plans for achieving long-term solvency by raising the normal retirement age (NRA), increasing taxes, or investing some portion of the fund in the stock market....