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There is much debate over whether the life-cycle model of consumption can explain consumption growth patterns patterns observed in household level data sources. We argue that once one departs from simple classroom example, or 'stripped down life-cycle model', the empirical model for consumption growth can be made flexible enough to fit the main features of the data. Using simulation techniques to assess the predictions of a life-cycle model estimated on US consumption data, we find that:

• Allowing demographic variables to affect household preferences and relaxing assumptions about the effects of uncertainty can generate hump-shaped consumption profiles over age that are very similar to those observed in household level data sources, without appealing to alternative explanations such as liquidity constraints, myopia or mental accounting.
• Humps in consumption paths are partly attributable to precautionary savings, and partly due to demographics; Bumps (or tracking - whereby consumption jumps with income) are instead due to the permanent nature of income shocks.
• Neglecting the effects of uncertainty produces consumption profiles that are 'too flat', whereas neglecting the effects of demographics generates consumption profiles that peak 'too late'.