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Back to Background Risk

Andreas Fagereng, Luigi Guiso and Luigi Pistaferri
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Luigi Pistaferri: Stanford University and NBER

No 1602, EIEF Working Papers Series from Einaudi Institute for Economics and Finance (EIEF)

Abstract: Estimating the effect of background risk on individual financial choices faces two challenges. First, the identi cation of the marginal effect requires a measure of at least one component of human capital risk that quali fies as "background" (a risk that an individual cannot diversify or avoid). Absent this, estimates suffer from measurement error and omitted variable bias. Moreover, measures of background risk must vary over time to eliminate unobserved heterogeneity. Second, once the marginal effect is identifi ed, an evaluation of the economic signi cance of background risk requires knowledge of the size of all the background risk actually faced. Existing estimates are problematic because measures of background risk fail to satisfy the "non- avoidability" requirement. This creates a downward bias which is at the root of the small estimated effect of background risk. To tackle the identi cation problem we match panel data of workers and fi rms and use the variability in the profi tability of the fi rm that is passed over to workers to obtain a measure of risk that is hardly avoidable. We rely on this measure to instrument total variability in individual earnings and fi nd that the marginal effect of background risk is much larger than estimates that ignore endogeneity. We bound the economic impact of human capital background risk and fi nd that its overall effect is contained, not because its marginal effect is small but because its size is small. And size of background risk is small because fi rms provide substantial wage insurance.

Pages: 54 pages
Date: 2016, Revised 2016-01
New Economics Papers: this item is included in nep-hrm
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Citations: View citations in EconPapers (4)

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Related works:
Working Paper: Back to background risk? (2016) Downloads
Working Paper: Back to background risk? (2016) Downloads
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