Paper by Christian Stoltenberg and alumnus Swapnil Singh appeared in Quantitive Economics
This paper investigates whether assuming that households possess advance information on their income shocks helps to overcome the difficulty of standard models to understand consumption insurance in the US. As our main result, we find that the quantitative relevance of advance information crucially depends on the structure of insurance markets. For a realistic amount of advance information, a complete markets model with endogenous solvency constraints due to limited commitment explains several key consumption insurance measures better than existing models without advance information. In contrast, when advance information is integrated into a standard incomplete markets model, it affects household consumption‐saving decisions too little to bridge the gap between the model and the data and can induce counterfactual correlations between current consumption growth and future income growth.
Christian Stoltenberg and Swapnil Singh, “Consumption insurance with advance information”, Quantitative Economics. Volume 11, Issue 2, May 2020, pp. 671–711. doi.org/10.3982/QE1169