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@@ -282,7 +282,7 @@ This also serves to constrain the model's ability to fit the data by declining t
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Beyond those basic assumptions, we calibrate the model to include uncertainty after retirement.
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Specifically, we assume that there are expenditure shocks in retirement that can reduce *disposable* income net of exogenous expenditures by maintaining transitory income shocks at their age-64 variance (while zeroing out permanent income shocks); see also @flExpShocks for a recent estimation of expense shocks.
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This assumption acts as a kind of shorthand for other modeling assumptions that focus on modeling the dynamics of medical and nursing home expenses in old age, e.g. @ameriks2011joy and @DeNardi2010.
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Even if old age medical expenses were incorporated into the model more realistically, this feature *cannot* be the primary explanation for the drawdown failure, as the phenomenon has been documented even in countries with much more robust public health insurance than the United States (e.g., see @Hattrem2022 for wealth accumulation among retired Norwegians, or @AustralianWealth2021 for Australians).
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Even if old age medical expenses were incorporated into the model more realistically, this feature *cannot* be the primary explanation for the drawdown failure, as the phenomenon has been documented even in countries with much more robust public health insurance than the United States, including Sweden (@Ljunge2013), Norway (@Hattrem2022), Australia (@AustralianWealth2021), Canada (@Hamilton2001), Japan (@Niimi2018), and the United Kingdom (@Crawford2018).
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In principle, the presence of such shocks provides a precautionary motive to draw down wealth more slowly.
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However, our estimation results show that even when we include this calibration of expense shocks, the model still predicts much more drawdown of wealth than the data show.
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