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This article investigates the roles of psychological biases for deviations between subjective survival beliefs (SSBs) and objective survival probabilities. We model these deviations through age-dependent inverse S-shaped probability weighting functions. Our estimates suggest that implied measures for cognitive weakness increase and relative optimism decrease with age. Direct measures of cognitive weakness and optimism share these trends. Our regression analyses confirm that these factors play strong quantitative roles in the formation of SSBs. Our main finding is that cognitive weakness instead of optimism becomes with age an increasingly important contributor to the well-documented overestimation of survival chances in old age.
This paper investigates the roles psychological biases play in empirically estimated deviations between subjective survival beliefs (SSBs) and objective survival probabilities (OSPs). We model deviations between SSBs and OSPs through age-dependent inverse S-shaped probability weighting functions (PWFs), as documented in experimental prospect theory. Our estimates suggest that the implied measures for cognitive weakness, likelihood insensitivity, and those for motivational biases, relative pessimism, increase with age. We document that direct measures of cognitive weakness and motivational attitudes share these trends. Our regression analyses confirm that these factors play strong quantitative roles in the formation of subjective survival beliefs. In particular, cognitive weakness is an increasingly important contributor to the overestimation of survival chances in old age.
On average young people \undersave" whereas old people \oversave" with respect to the rational expectations model of life-cycle consumption and savings. According to numerous studies on subjective survival beliefs, young people also \underestimate" whereas old people \overestimate" their objective survival chances on average. We take a structural behavioral economics approach to jointly address both empirical phenomena by embedding subjective survival beliefs that are consistent with these biases into a rank-dependent utility (RDU) model over life-cycle consumption. The resulting consumption behavior is dynamically inconsistent. Considering both naive and sophisticated RDU agents we show that within this framework underestimation of young age and overestimation of old age survival probabilities may (but need not) give rise to the joint occurrence of undersaving and oversaving. In contrast to this RDU model, the familiar quasi-hyperbolic discounting (QHD), which is nested as a special case, cannot generate oversaving.
On average, "young" people underestimate whereas "old" people overestimate their chances to survive into the future. We adopt a Bayesian learning model of ambiguous survival beliefs which replicates these patterns. The model is embedded within a non-expected utility model of life-cycle consumption and saving. Our analysis shows that agents with ambiguous survival beliefs (i) save less than originally planned, (ii) exhibit undersaving at younger ages, and (iii) hold larger amounts of assets in old age than their rational expectations counterparts who correctly assess their survival probabilities. Our ambiguity-driven model therefore simultaneously accounts for three important empirical findings on household saving behavior.
Based on a cognitive notion of neo-additive capacities reflecting likelihood insensitivity with respect to survival chances, we construct a Choquet Bayesian learning model over the life-cycle that generates a motivational notion of neo-additive survival beliefs expressing ambiguity attitudes. We embed these neo-additive survival beliefs as decision weights in a Choquet expected utility life-cycle consumption model and calibrate it with data on subjective survival beliefs from the Health and Retirement Study. Our quantitative analysis shows that agents with calibrated neo-additive survival beliefs (i) save less than originally planned, (ii) exhibit undersaving at younger ages, and (iii) hold larger amounts of assets in old age than their rational expectations counterparts who correctly assess their survival chances. Our neo-additive life-cycle model can therefore simultaneously accommodate three important empirical findings on household saving behavior.
Die aktuelle Diskussion über eine Reform der gesetzlichen Rentenversicherung vermischt Fragen nach dem durchschnittlichen Rentenniveau mit Fragen der Umverteilung von Einkommen im Ruhestand zur Bekämpfung einer etwaigen Altersarmut. Dieser Beitrag kritisiert diesen Ansatz und befasst sich mit fünf Kernaussagen: (1) Die aktuell gültige Rentenformel darf unter keinen Umständen abgeschafft werden. (2) Das Renteneintrittsalter sollte an die durchschnittliche Restlebenserwartung nach dem Erreichen des 65. Lebensjahres gekoppelt werden. (3) Eine Integration der Flüchtlinge in den Arbeitsmarkt wird das Rentenniveau in den Jahren 2030 bis 2040 stützen. (4) Sollte trotz allem die Altersarmut steigen, so kann dem durch die Einführung einer Mindestrente begegnet werden. (5) Die private Altersvorsorge muss weiter gestützt werden.
Ongoing demographic change will lead to a relative scarcity of raw labor to the effect that output growth will be decreasing in the next decades, a secular stagnation. As physical capital will be relatively abundant, this decrease of output will be accompanied by reductions of asset returns. We quantify these effects for the US economy by developing an overlapping generations model with risky and risk-free assets. Without adjustments of human capital, risky returns decrease until 2035 by about 0.7 percentage point, and the risk-free rate by about one percentage point, leading to substantial welfare losses for asset rich households. Per capita output is reduced by 6%. Endogenous human capital adjustments strongly mitigate these effects. We conclude that human capital policies will be crucial in the context of labor shortages.
We develop a novel empirical approach to identify the effectiveness of policies against a pandemic. The essence of our approach is the insight that epidemic dynamics are best tracked over stages, rather than over time. We use a normalization procedure that makes the pre-policy paths of the epidemic identical across regions. The procedure uncovers regional variation in the stage of the epidemic at the time of policy implementation. This variation delivers clean identification of the policy effect based on the epidemic path of a leading region that serves as a counterfactual for other regions. We apply our method to evaluate the effectiveness of the nationwide stay-home policy enacted in Spain against the Covid-19 pandemic. We find that the policy saved 15.9% of lives relative to the number of deaths that would have occurred had it not been for the policy intervention. Its effectiveness evolves with the epidemic and is larger when implemented at earlier stages.
We extend the canonical income process with persistent and transitory risk to shock distributions with left-skewness and excess kurtosis, to which we refer as higher- order risk. We estimate our extended income process by GMM for household data from the United States. We find countercyclical variance and procyclical skewness of persistent shocks. All shock distributions are highly leptokurtic. The existing tax and transfer system reduces dispersion and left-skewness of shocks. We then show that in a standard incomplete-markets life-cycle model, first, higher-order risk has sizable welfare implications, which depend crucially on risk attitudes of households; second, higher-order risk matters quantitatively for the welfare costs of cyclical idiosyncratic risk; third, higher-order risk has non-trivial implications for the degree of self-insurance against both transitory and persistent shocks.
We develop a two-sector incomplete markets integrated assessment model to analyze the effectiveness of green quantitative easing (QE) in complementing fiscal policies for climate change mitigation. We model green QE through an outstanding stock of private assets held by a monetary authority and its portfolio allocation between a clean and a dirty sector of production. Green QE leads to a partial crowding out of private capital in the green sector and to a modest reduction of the global temperature by 0.04 degrees of Celsius until 2100. A moderate global carbon tax of 50 USD per tonne of carbon is 4 times more effective.