Individual-level loss aversion in riskless and risky choices

Loss aversion can occur in riskless and risky choices. Yet, there is no evidence whether people who are loss averse in riskless choices are also loss averse in risky choices. We measure individual-level loss aversion in riskless choices in an endowment effect experiment by eliciting both WTA and WTP from each of our 360 subjects (randomly selected customers of a car manufacturer). All subjects also participate in a simple lottery choice task which arguably measures loss aversion in risky choices. We find substantial heterogeneity in both measures of loss aversion. Loss aversion in the riskless choice task and loss aversion in the risky choice task are highly significantly and strongly positively correlated. We find that in both choice tasks loss aversion increases in age, income, and wealth, and decreases in education.Loss aversion, endowment effect, field experiments

An experimental test of loss aversion and scale compatibility

This paper studies two important reasons why people violate procedure invariance, loss aversion and scale compatibility. The paper extends previous research on loss aversion and scale compatibility by studying loss aversion and scale compatibility simultaneously, by looking at a new decision domain, medical decision analysis, and by examining the effect of loss aversion and scale compatibility on "well-contemplated preferences." We find significant evidence both of loss aversion and scale compatibility. However, the sizes of the biases due to loss aversion and scale compatibility vary over trade-offs and most participants do not behave consistently according to loss aversion or scale compatibility. In particular, the effect of loss aversion in medical trade-offs decreases with duration. These findings are encouraging for utility measurement and prescriptive decision analysis. There appear to exist decision contexts in which the effects of loss aversion and scale compatibility can be minimized and utilities can be measured that do not suffer from these distorting factors.Decision analysis, utility theory, loss aversion, scale compatibility, health

The Nature of Risk Preferences: Evidence from Insurance Choices

We use data on households' deductible choices in auto and home insurance to estimate a structural model of risky choice that incorporates "standard" risk aversion (concave utility over final wealth), loss aversion, and nonlinear probability weighting. Our estimates indicate that nonlinear probability weighting plays the most important role in explaining the data. More specifically, we find that standard risk aversion is small, loss aversion is nonexistent, and nonlinear probability weighting is large. When we estimate restricted models, we find that nonlinear probability weighting alone can better explain the data than standard risk aversion alone, loss aversion alone, and standard risk aversion and loss aversion combined. Our main findings are robust to a variety of modeling assumptions.

Myopic loss aversion, disappointment aversion, and the equity premium puzzle

This paper takes a close look at the 'behavioural finance' explanations of the equity premium puzzle, namely myopic loss aversion (Benartzi and Thaler, 1995) and disappointment aversion (Ang, Bekaert and Liu, 2000). The paper proposes a simple specification of loss and disappointment aversion and brings these theories to the data. The main conclusion of the paper is that a highly short-sighted investment horizon is required for the historical equity premium to be explained by loss aversion, while reasonable values for disappointment aversion are found also for long investment horizons. So, stocks may lose only in the short term, but may disappoint also in the long term. JEL Classification: G11, G12disappointment aversion, equity premium puzzle, investment horizon, Myopic loss aversion, reference dependence

Probability Distortion and Loss Aversion in Futures Hedging

We analyze how the introduction of probability distortion and loss aversion in the standard hedging problem changes the optimal hedge ratio. Based on simulated cash and futures prices for soybeans, our results indicate that the optimal hedge changes considerably when probability distortion is considered. However, the impact of loss aversion on hedging decisions appears to be small, and it diminishes as loss aversion increases. Our findings suggest that probability distortion is a major driving force in hedging decisions, while loss aversion plays just a marginal role.Marketing,

A consistency test of the time trade-off

This paper tests the internal consistency of time trade-off utilities. We find significant violations of consistency in the direction predicted by loss aversion. The violations disappear for higher gauge durations. We show that loss aversion can also explain that for short gauge durations time trade-off utilities exceed standard gamble utilities. Our results suggest that time trade-off measurements that use relatively short gauge durations, like the widely used EuroQol algorithm (Dolan 1997), are affected by loss aversion and lead to utilities that are too high.Cost-Utility Analysis, Time Trade-Off, Loss Aversion

Principal agent problems under loss aversion: an application to executive stock options

Executive stock options reward success but do not penalise failure. In contrast, the standard principalagent model implies that pay is normally monotonically increasing in performance. This paper shows that, under loss aversion, the use of carrots but not sticks is a feature of an optimal compensation contract. Low risk aversion and high loss aversion is particularly propitious to the use of options. Moreover, loss aversion on the part of executives explains the award of at the money options rather than discounted stock or bonus related pay. Other features of stock option grants are also explained, such as resetting or reloading with an exercise price equal to the current stock price

Quantifying Loss Aversion: Evidence from a UK Population Survey

We estimate loss aversion using on an online survey of a representative sample of over 4,000 UK residents. The average aversion to a loss of £500 relative to a gain of the same amount is 2.41, but loss aversion varies significantly with characteristics such as gender, age, education, financial knowledge, social class, employment status, management responsibility, income, savings and home ownership. Other influencing factors include marital status, number of children, ease of savings, rainy day fund, personality type, emotional state, newspaper and political party. However, once we condition on all the profiling characteristics of the respondents, some factors, in particular gender, cease to be significant, suggesting that gender differences in risk and loss attitudes might be due to other factors, such as income differences

LOSS AVERSION AND LABOR SUPPLY

In many occupations, workers’ labor supply choices are constrained by institutional rules regulating labor time and effort provision. This renders explicit tests of the neoclassical theory of labor supply difŽ cult. Here we present evidence from studies examining labor supply responses in “neoclassical environments” in which workers are free to choose when and how much to work. Despite the favorable environment, the results cast doubt on the neoclassical model. They are, however, consistent with a model of reference-dependent preferences exhibiting loss aversion and diminishing sensitivity.labor supply, loss aversion, neoclassical environments

Asymmetry, Loss Aversion and Forecasting

Conditional volatility models, such as GARCH, have been used extensively in financial applications to capture predictable variation in the second moment of asset returns. However, with recent theoretical literature emphasising the loss averse nature of agents, this paper considers models which capture time variation in the second lower partial moment. Utility based evaluation is carried out on several approaches to modelling the conditional second order lower partial moment (or semi-variance), including distribution and regime based models. The findings show that when agents are loss averse, there are utility gains to be made from using models which explicitly capture this feature (rather than trying to approximate using symmetric volatility models). In general direct approaches to modelling the semi-variance are preferred to distribution based models. These results are relevant to risk management and help to link the theoretical discussion on loss aversion to emprical modellingAsymmetry, loss aversion, semi-variance, volatility models.