Solving the incomplete markets model with aggregate uncertainty using the Krusell–Smith algorithm and non-stochastic simulations

Young, Eric

doi:10.1016/j.jedc.2008.11.010

Cited by 140 publications

(75 citation statements)

References 12 publications

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“…Overall, we are able to match the key features of the data well. However, the simulated offer rate (59.1%) is slightly lower than in the data (64%) 20 .…”

Section: Eshi Offer Statuscontrasting

confidence: 61%

Welfare costs of reclassification risk in the health insurance market

Pashchenko

Porapakkarm

2015

Journal of Macroeconomics

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One of the major problems of the U.S. health insurance market is that it leaves individuals exposed to reclassification risk. Reclassification risk arises because the health conditions of individuals evolve over time, while a typical health insurance contract only lasts for one year. A change in the health status can lead to a significant change in the health insurance premium. We study how costly this reclassification risk is for the welfare of consumers. More specifically, we use a general equilibrium model to quantify the implications of introducing guaranteed renewable contracts into the economy calibrated to replicate the key features of the health insurance system in the U.S. Guaranteed renewable contracts are private insurance contracts that can provide protection against reclassification risk even in the absence of consumer commitment or government intervention. We find that though guaranteed renewable contracts provide a good insurance against reclassification risk, the welfare effects from introducing this type of contracts are small. In other words, the presence of reclassification risk does not impose large welfare losses on consumers. This happens because some institutional features in the current U.S. system substitute for the missing explicit contracts that insure reclassification risk. In particular, a good protection against reclassification risk is provided through employer-sponsored health insurance and government means-tested transfers.

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“…Overall, we are able to match the key features of the data well. However, the simulated offer rate (59.1%) is slightly lower than in the data (64%) 20 .…”

Section: Eshi Offer Statuscontrasting

confidence: 61%

Welfare costs of reclassification risk in the health insurance market

Pashchenko

Porapakkarm

2015

Journal of Macroeconomics

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“…But the results presented here indicate that convenience may be an important element in the choice made as well. In terms of programming, the easiest procedure is the one proposed by Young (2009). In contrast to the grid-based procedure of Ríos-Rull (1997), it does not require calculating the inverse, which can be a costly operation.…”

Section: Discussionmentioning

confidence: 99%

Solving the incomplete markets model with aggregate uncertainty using parameterized cross-sectional distributions

Algan

Allais

Haan

2010

Journal of Economic Dynamics and Control

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a b s t r a c tThis note describes how the incomplete markets model with aggregate uncertainty in Den Haan et al. [Comparison of solutions to the incomplete markets model with aggregate uncertainty. Journal of Economic Dynamics and Control, this issue] is solved using standard quadrature and projection methods. This is made possible by linking the aggregate state variables to a parameterized density that describes the cross-sectional distribution. A simulation procedure is used to find the best shape of the density within the class of approximating densities considered. This note compares several simulation procedures in which there is-as in the model-no cross-sectional sampling variation.

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“…To construct the stationary distribution, we use the method of nonstochastic simulation from Young (2010), modified to accommodate a continuously distributed stochastic state. We create a new, fine grid of points S f on which we approximate the stationary distribution using a his-…”

Section: C2 Stationary Distributionmentioning

confidence: 99%