Generational Risk–Is It a Big Deal?: Simulating an 80-Period OLG Model with Aggregate Shocks

By Jasmina Hasanhodzic and Laurence Kotlikoff

The theoretical literature on generational risk assumes that this risk is large and that the government can effectively share it. To assess these assumptions, this paper simulates a realistically calibrated 80-period overlapping generations life-cycle model with aggregate productivity shocks. Previous solution methods could not handle large-scale OLG models such as ours due to the well-known curse of dimensionality. The prior state of the art is Krueger and Kubler (2004, 2006), whose sparse-grid method handles 10 to 30 periods depending on the model’s realism. Other methods used to solve large-scale, multi-period life-cycle models are tenuous because they rely on either local approximations (Rios-Rull, 1994, 1996) or summary statistics of state variables (Krusell and Smith, 1997, 1998). We build on a new algorithm by Judd, Maliar, and Maliar (2009, 2011), which restricts the state space to the model’s ergodic set. This limits the required computation and effectively banishes the dimensionality curse in models like ours. We find that intrinsic generational risk is quite small, that government policies can produce generational risk, and that bond markets can help share generational risk. We also show that a bond market can mitigate risk-inducing government policy. Our simulations produce very small equity premia for three reasons. First, there is relatively little intrinsic generational risk. Second, intrinsic generational risk hits both the young and the old in similar ways. And third, artificially inducing risk between the young and the old via government policy elicits more net supply as well as more net demand for bonds, by the young and the old respectively, leaving the risk premium essentially unchanged. Our results hold even in the presence of rare disasters and very high risk aversion. They echo Lucas’ (1987) and Krusell and Smith’s (1999) point that macroeconomic fluctuations are too small to have major microeconomic consequences.

Interesting application of promising new computational techniques. It is also interesting to see a result that indicates that the government introducing artificial risk is not necessarily welfare reducing. I have a paper with a similar result I need to finish now…

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