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  2. ASSA Annual Meeting
  3. 2022
  4. Preliminary Program
  5. Estimating Saving and Health
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Estimating Saving and Health

Paper Session

Saturday, Jan. 8, 2022 12:15 PM - 2:15 PM (EST)

Hosted By: Econometric Society
  • Chair: Mariacristina De Nardi, University of Minnesota

Why Do Couples and Singles Save during Retirement?

Mariacristina De Nardi
,
University of Minnesota
Eric French
,
University College London
John Jones
,
Federal Reserve Bank of Richmond
Rory McGee
,
University of Western Ontario

Abstract

The savings of retired couples tends to rise with age, whereas the savings of
singles tends to fall. To understand the saving of couples and singles, we build
a model of retirees facing uncertain longevity and medical expenses and potentially
having bequest motives towards spouses and other heirs. We estimate
the model with the Simulated Method of Moments and data from the AHEAD.
We nd that both couples and singles save to self-insure against future medical
expenses, but that for couples, bequest motives are more important. That is,
couples at all permanent income levels hold net worth at very advanced ages to
leave bequests to surviving spouses, and couples in the top permanent income
tercile also seek to leave bequests to non-spousal heirs.

An Adversarial Approach to Structural Estimation

Tetsuya Kaji
,
University of Chicago
Elena Manresa
,
New York University
Guillaume Pouliot
,
University of Chicago

Abstract

We propose a new simulation-based estimation method, adversarial estimation, for structural models. The estimator is formulated as the solution
to a minimax problem between a generator (which generates synthetic observations using the structural model) and a discriminator (which classifies if an
observation is synthetic). The discriminator maximizes the accuracy of its classification while the generator minimizes it. We show that, with a sufficiently
rich discriminator, the adversarial estimator attains parametric efficiency under
correct specification and the parametric rate under misspecification. We advocate the use of a neural network as a discriminator that can exploit adaptivity
properties and attain fast rates of convergence. We apply our method to the
elderly’s saving decision model and show that including gender and health profiles in the discriminator uncovers the bequest motive as an important source
of saving across the wealth distribution, not only for the rich.

Old Age Savings and House Price Shocks

Rory McGee
,
University of Western Ontario

Abstract

Elderly households hold most of their wealth in housing, maintain high levels
of wealth throughout retirement, and often leave bequests. The value of their
houses are subject to large shocks. To what extent do these shocks affect their
savings, consumption, and bequests? Answering this question requires separating precautionary savings, bequest motives, and the desire to remain in one’s
home. I develop and estimate a structural model of retirement savings decisions
with realistic risks, housing, and heterogeneity in bequest preferences. I exploit
policy changes to the taxation of housing and bequests to separately identify
the different motives for holding wealth. Estimates show approximately half of
retirees have no bequest motive. House price changes are quantitatively important, with 1/4 of increases passed on to future generations. I use the estimated
model to evaluate means-tested programs insuring retirees’ Long Term Care expenses. I
find exemptions providing marginal liquidity have larger insurance value than
fully eliminating Long Term Care expense risk per pound it costs the government.

Long-Term Health Insurance: Theory Meets Evidence

Juan Pablo Atal
,
University of Pennsylvania
Hanming Fang
,
University of Pennsylvania
Martin Karlsson
,
University of Duisburg-Essen
Nicolas R. Ziebarth
,
Cornell University

Abstract

To insure policyholders against contemporaneous health expenditure shocks and future reclassification risk, long-term health insurance constitutes an alternative to community-rated short-term contracts with an individual mandate. In this paper, we study the German long-term health insurance (GLTHI) from a life-cycle perspective. The GLTHI is one of the few real-world long-term health insurance markets. We first present and discuss insurer regulation, premium setting, and the main market principles of the GLTHI. Then, using unique claims panel data from 620 thousand policyholders over 7 years, we propose a new method to classify and model health transitions. Feeding the empirical inputs into our theoretical model, we assess the welfare effects of the GLTHI over policyholders’ lifecycle. We find that GLTHI achieves a high level of welfare against several benchmarks. Finally, we conduct counterfactual policy simulations to illustrate the welfare consequences of integrating GLTHI into a hybrid insurance system similar to the current system in the United States.
JEL Classifications
  • D1 - Household Behavior and Family Economics
  • E2 - Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy