Assessing the importance of uninsurable wage risk for individual financial choices faces two challenges. First, the identification of the marginal effect requires a measure of at least one component of risk that cannot be diversified or avoided. Moreover, measures of uninsurable wage risk must vary over time to eliminate unobserved heterogeneity. Second, evaluating the economic significance of risk requires knowledge of the size of all the wage risk actually faced. Existing estimates are problematic because measures of wage risk fail to satisfy the "non-avoidability" requirement. This creates a downward bias which is at the root of the small estimated effect of wage risk on portfolio choices. To tackle this problem we match panel data of workers and firms and use the variability in the profitability of the firm that is passed over to workers to obtain a measure of uninsurable risk. Using this measure to instrument total variability in individual earnings, we find that the marginal effect of uninsurable wage risk is much larger than estimates that ignore endogeneity. We bound the economic impact of risk and find that its overall effect is contained, not because its marginal effect is small but because its size is small. And the size of uninsurable wage risk is small because firms provide substantial wage insurance.

We propose a new approach to identify the strength of the precautionary motive and the extent of self-insurance in response to earnings risk based on Euler equation estimates. To address endogeneity problems, we use Norwegian administrative data and instrument consumption and earnings volatility with the variance of firm-specific shocks. The instrument is valid because firms pass some of their productivity shocks onto wages; moreover, for most workers, firm shocks are hard to avoid. Our estimates suggest a coefficient of relative prudence of 2, in a very plausible range.

Using error‐free data on life‐cycle portfolio allocations of a large sample of Norwegian households, we document a double adjustment as households age: a rebalancing of the portfolio composition away from stocks as they approach retirement and stock market exit after retirement. When structurally estimating an extended life‐cycle model, the parameter combination that best fits the data is one with a relatively large risk aversion, a small per‐period participation cost, and a yearly probability of a large stock market loss in line with the frequency of stock market crashes in Norway.