Estimates Of Risk Aversion Research Articles

Induced worry increases risk aversion in patients with generalized anxiety

Generalized anxiety disorder is characterized by disruptions in decision-making, including an enhanced aversion to uncertain outcomes (i.e., risk aversion), which is not specific to negative outcomes (i.e., no loss aversion). It is unknown if this uncertainty bias is a trait-like causal factor contributing to anxiety symptoms, or a state-like feature triggered by anxiety symptoms such as worry chains. Here, in-patients with Major Depression Disorder (MDD), with (N = 16) or without (N = 24) Generalized anxiety (GA) symptoms, and healthy controls (N = 23), completed an economic decision-making task before and after worry induction. They were asked to choose between a certain monetary payoff, and an uncertain gamble, allowing for estimation of risk and loss aversion through a computational prospect-theoretic model. There were no significant differences in risk and loss aversion between any of the three groups at baseline. After worry induction, patients with GA symptoms, compared to those without, showed increased risk aversion. This increase was modulated by the severity of anxiety symptoms. These findings suggest that decision-making disruptions in anxiety disorder may be driven by anxiety symptoms such as worry, rather than causing them. This could shape etiological models, motivate standardization of emotional state in research on decision-making in anxiety disorders, support treatment strategies primarily aimed at worry management, and could guide novel interventions focusing on uncertainty exposure across aversive and appetitive domains.

A Sieve‐SMM Estimator for Dynamic Models

This paper proposes a Sieve Simulated Method of Moments (Sieve‐SMM) estimator for the parameters and the distribution of the shocks in nonlinear dynamic models where the likelihood and the moments are not tractable. An important concern with SMM, which matches sample with simulated moments, is that a parametric distribution is required. However, economic quantities that depend on this distribution, such as welfare and asset prices, can be sensitive to misspecification. The Sieve‐SMM estimator addresses this issue by flexibly approximating the distribution of the shocks with a Gaussian and tails mixture sieve. The asymptotic framework provides consistency, rate of convergence, and asymptotic normality results, extending existing results to a new framework with more general dynamics and latent variables. An application to asset pricing in a production economy shows a large decline in the estimates of relative risk aversion, highlighting the empirical relevance of misspecification bias.

Empirical Pricing Kernel and Option-Implied Risk Aversion in China 50 ETF

ABSTRACT Based on an analysis of the China 50 ETF options and their underlying assets, we measure the empirical pricing kernel and implied risk aversion. By employing a Markov-switching GARCH model, the estimated results show a monotonically decreasing pricing kernel under a high-volatility regime and a U-shaped pricing kernel under a low-volatility regime. The implied risk aversion is inversely S-shaped under both high- and low-volatility regimes. However, the implied risk aversion under the low-volatility regime has a wide range. Investors’ risk aversion perspective helps explain patterns of pricing kernels and risk aversion estimates. Finally, we find that implied risk aversion is predictive of short-term (excess) market returns based on in-sample and out-of-sample tests.

Peso problems in the estimation of the C‐CAPM

This paper shows that the consumption‐based capital asset pricing model (C‐CAPM) with low‐probability disaster risk rationalizes pricing errors. We find that implausible estimates of risk aversion and time preference are not puzzling if market participants expect a future catastrophic change in fundamentals, which just happens not to occur in the sample (a “peso problem”). A bias in structural parameter estimates emerges as a result of pricing errors in quiet times. While the bias essentially removes the pricing error in the simple models when risk‐free rates are constant, time‐variation may also generate large and persistent estimated pricing errors in simulated data. We also show analytically how the problem of biased estimates can be avoided in empirical research by resolving the misspecification in moment conditions.

Regulatory Induced Risk Aversion in Coal Contracting at US Power Plants: Implications for Environmental Policy

Seminal work argues that electric utilities sign long-term contracts with coal suppliers prior to making relationship-specific investments in order to avoid the possibility of ex post hold-up. This paper provides empirical evidence that risk aversion also plays an important role in the coal contracting behavior of US power plants. Specifically, I show that plants facing more spot coal price uncertainty sign longer duration coal contracts, purchase contract coal from a larger number of origin counties, and pay higher contract coal prices. One plausible mechanism for this risk aversion is that regulators are less likely to incorporate high input cost realizations into the regulated output price they set for electric utilities. Using my estimate of plant-level risk aversion, I calculate that the ratio of the aggregate costs incurred by plants under cap and trade relative to a carbon tax is 1.27. This highlights the importance of implementing climate policy that limits carbon price volatility.

Estimating risk preferences integrating insurance choices with subjective beliefs

This paper combines real-world decisions with experimental elicitations to estimate risk preferences by incorporating individuals’ subjective beliefs in the analysis of insurance data. Unlike most studies estimating risk preferences “in the field”, we refrain from making specific assumptions regarding expectations; rather, we elicit them directly from the respondents. This approach yields risk aversion estimates compatible with a variety of deviations from rational expectations, such as biased subjective risk perceptions. Our results reveal that agents tend to overestimate the probability of recent rare events happening again in the recent future, and that the standard assumption of rational beliefs can lead to biased estimates and policy recommendations. Our empirical application offers new insights into the current debate on crop insurance subsidies. Correcting biased beliefs appears to be an effective strategy to reduce government support and, at the same time, maintain a high level of enrollment.

Eliciting Risk Preferences and Elasticity of Substitution

Risk aversion and elasticity of intertemporal substitution (EIS) are separated via the celebrated recursive utility building on certainty equivalents of indirect utility. Based on an alternative separation method, we formulate a questionnaire for simultaneous and consistent estimation of risk aversion, subjective discount rate, and EIS. From a representative group of 1,153 respondents, we estimate parameters for these preferences and their variability within the population. Risk aversion and the subjective discount rate are found to be in the orders of 2 and 0, respectively, not diverging far away from results from other studies. Our estimate of EIS in the order of 10 is larger than often reported. Background variables like age and income have little predictive power for the three estimates. Only gender has a significant influence on risk aversion in the usually perceived direction that females are more risk-averse than males. Using individual estimates of preference parameters, we find covariance between preferences toward risk and EIS. We present the background reasoning on objectives, the questionnaire, a statistical analysis of the results, and economic interpretations of these, including relations to the literature.

A Simplified Measure of Investor Risk Aversion

This article introduces a simplified measure of investor risk aversion. The singleitem question combines elements from revealed preference and propensity measurement techniques in a way that matches traditional constant relative risk-aversion estimation procedures. Based on survey data from 500 investors living in the United States, scores from the proposed measure were found to correlate with other measures of risk aversion, as well as with indicators of risk-taking. A validity test showed that answers to the proposed measure were statistically associated with equity and cash ownership holdings in respondent portfolios. The simplicity and intuitive nature of the proposed measure and the alignment of question response categories to estimates of constant relative risk aversion make this a potentially valuable addition to the toolkit of researchers, financial educators, investors and those who provide advice to investors.JEL: C83, D10, D11, D14, D19, D81

Inferring informal risk-sharing regimes: Evidence from rural Tanzania

This paper studies informal risk-sharing regimes in a unified framework by examining households’ intertemporal consumption behavior. We exploit a theoretically-consistent link between interest rates and cross-sectional consumption moments to test alternative risk-sharing models without requiring data on interest rates or assuming a restriction to eliminate the need for such data, which are often unavailable in developing economies. We specify tests that allow us to distinguish among models even with temporal dependence in income shocks. Using data from rural Tanzania we find that the consumption pattern is consistent with the self-insurance regime, and that risk aversion varies substantially across districts. Imposing a strict condition on interest rates, as often done in prior literature, misses their intertemporal heterogeneity and biases the estimation of risk aversion.

Risk Preferences and Efficiency of Household Portfolios

We propose a novel approach to infer investors' risk preferences from their portfolio choices, and then use the implied risk preferences to measure the efficiency of investment portfolios. We analyze a dataset spanning a period of six years, consisting of end of month stock trading records, along with investors' demographic information and self-assessed financial knowledge. Unlike estimates of risk aversion based on the share of risky assets, our statistical analysis suggests that the implied risk aversion coefficient of an investor increases with her wealth and financial literacy. Portfolio diversification, Sharpe ratio, and expected portfolio returns correlate positively with the efficiency of the portfolio, whereas a higher standard deviation reduces the efficiency of the portfolio. We find that affluent and financially educated investors as well as those holding retirement related accounts hold more efficient portfolios.

Risk Aversion and Business Cycles in Iran’s Economy

ترجیحات افراد نسبت به ریسک یکی از متغیرهای مهم اقتصادی بوده و تأثیر بسیاری در تصمیمات اقتصادی دارد. تصمیمات سرمایه‌گذاری، مصرف، پس­انداز، خرید بیمه و قراردادهای آتی از جمله تصمیماتی هستند که ترجیحات ریسک در آن نقش کلیدی را بازی می‌کند. با توجه به اهمیت ترجیحات ریسکی در فرآیند تصمیم­گیری، محاسبه شاخصی که بتواند به نحوی وضعیت گرایش ریسک در کل اقتصاد را نشان دهد، ضروری است. هدف از این پژوهش، برآورد سری زمانی پارامتر ریسک گریزی در اقتصاد ایران بر اساس اطلاعات فصلی طی دوره 1396-1381 است. به این منظور از الگوی گارچ در میانگین با پارامترهای متغیر طی زمان استفاده شد. نتایج برآورد ریسک گریزی در اقتصاد ایران نشان داد، این پارامتر در اقتصاد ایران ثابت نبوده و طی دوره‌ی مورد بررسی بین 81/0 تا 6/7 در نوسان بوده است. همچنین نتایج پژوهش نشان داد، ریسک گریزی در دوره‌ی رونق نسبت به رکود به‌مراتب پایین­تر بوده و رفتار ضدچرخه‌‌ای دارد.

A New Method to Determine the Optimal Willingness to Pay in Cost-Effectiveness Analysis

ObjectiveTo provide a new approach to estimate optimal willingness to pay (WTP) for health technology assessment (HTA). Study DesignThis analysis specified utility as a function of income and calibrated it using estimates of relative risk aversion, from which the optimal WTP (K) can be determined using Garber and Phelps’ results (1997). MethodsThis analysis used the highly flexible Weibull utility function, calibrated with estimates of relative risk aversion (r*) derived from multiple data sources. The analysis centered on r* = 1 and conducted sensitivity analysis on r* and key Weibull parameters. For a range of income (M), graphs demonstrated how K/M and K vary with M. Results were compared with estimates of K and K/M from alternative models. Extrapolation from a representative individual to population-wide health plans was discussed. ResultsUsing r* = 1 and central values of other key parameters, K/M (at average income for developed nations) was approximately 2× annual income. Both K and K/M rose with income. Sensitivity analysis showed that results depend moderately on the chosen value of r* and specific Weibull utility function parameters. At average income, the optimal K/M ratio (2×) was modestly lower than many standard recommendations (typically 3× average income) and substantially lower than estimates using value-of-statistical-life approaches. ConclusionsThe new model, although not yet perfected, provides a different way to identify the WTP cutoff for HTA. Extrapolation to more than twice the calibration income ($50 000) is advised against. Analysis of other approaches to estimate the optimal K reveal potential upward biases.

Loan Pricing by Euro Area Risk Averse Banks in an Environment of Extended Central Bank Liquidity Provision

This paper studies bank loan pricing in the euro area over the period October 2008 to October 2014. This period was characterised by market fragmentation and extended liquidity provision by the ECB. For our analysis we develop a theoretical framework which accounts for the main financing risks faced by euro area banks during this challenging period. In our modelling framework risk aversion plays a critical role, and this is challenging for our empirical analysis. We handle this issue by means of a novel econometric approach whereby bank risk aversion is treated as an unobservable random effect. We find that banks that have access to money markets, and are less reliant on ECB financing, can finance at a lower cost, and can thus offer lower bank lending rates. We also find that banks with a lower cost of debt financing offer lower lending rates. Our results also show that after accounting for financing risks, credit risks, market power and bank business model, our empirical estimates of banks' risk aversion are still positively and significantly correlated with country specific effects, thus highlighting the fragmentation of retail banking along national lines within the euro area.

Identification and estimation of risk aversion in first-price auctions with unobserved auction heterogeneity

This paper shows point-identification in first-price auctions with risk aversion and unobserved auction heterogeneity, by exploiting multiple bids per auction and variation in the number of bidders. If the exclusion restriction required for point-identification is violated, the recovered primitives are still valid bounds under weaker restrictions. We propose a Sieve Maximum Likelihood Estimator (SMLE). Monte Carlo experiments illustrate that the estimator performs well and that ignoring unobserved auction heterogeneity can bias risk aversion estimates. In an application to timber auctions we find that the bidders are risk-neutral, but we would reject risk-neutrality without accounting for unobserved auction heterogeneity.

Risk Aversion or Model Uncertainty? An Empirical Cross-Sectional Analysis Across Countries

By analyzing a panel of macro data including both Emerging Markets (EM) and Advanced Economies (AE), we identify that an acceptable level of model uncertainty helps to explain the equity premium existing in all these markets. Model uncertainty aversion is in general higher for EMs than for AEs. In addition, the degree of cross-sectional heterogeneity across countries' estimates of model uncertainty aversion is smaller than the corresponding heterogeneity of the risk aversion estimates in a traditional CRRA preference. We also compute separate costs of model risk and uncertainty for these economies in terms of present consumption, and conclude that the most significant effects come from uncertainty.

Uncovering the Distribution of Option Implied Risk Aversion

This paper explores the dynamics of risk aversion of a representative agent with an iso-elastic utility function. In contrast to most of the existing literature, we estimate the coefficient of relative risk aversion from option prices. To do this, we transform the risk-neutral density function obtained from a cross-section of option prices to an objective distribution function that reflects individuals’ risk aversion through a CRRA utility function. The dynamics of the relative risk-aversion coefficient are obtained by repeating the same estimation procedure over rolling windows. This procedure uncovers strong variation in risk aversion over time. We also propose a simulation procedure to construct confidence intervals for the risk-aversion coefficient in each period. We assess the robustness of these confidence intervals under different assumptions on the data generating process of stock prices. The results imply a strong influence of volatility on the variation of risk aversion. In an empirical application, we compare the forecasting performance of our approach based on our risk-aversion estimates against the method proposed in [1]. Overall, we find that our simulation based approach obtains better forecasting results than bootstrap methods.

Stocks for the Log-Run and CRRA Preferences

Almost Stochastic Dominance has been employed to support the case of stocks for the long-run. It implies that stocks are preferred over bonds in the long-run for all preferences with bounded marginal utility. Unfortunately, this analysis excludes the very central family of Constant Relative Risk Aversion (CRRA) preferences, which have unbounded marginal utility. In this paper, we derive a simple closed-form solution for the portfolio-choice problem of CRRA investors. This solution and the empirical return parameters imply that stocks are preferred over bonds for all CRRA investors with relative risk aversion smaller than 3.9. As most empirical and experimental estimates of relative risk aversion are much smaller than this value, the stocks-for-the-long-run argument turns out to also hold for most CRRA investors. As a by-product, the analysis offers an alternative derivation of the continuous-time CAPM, that does not rely on dynamic programming, and allows for ambiguous investment horizons.

Consumption Discount Rates, Risk Aversion and Wealth in Low-Income Countries: Evidence from a Field Experiment in Rural Ethiopia

It has been argued that people in low-income countries often have high consumption discount rates (CDRs), which contributes to under-investment in capital, such as education and soil conservation. We use a field experiment to estimate CDRs in rural Ethiopia and find that annual rates range from 43% to 106%. We evaluate whether household wealth affects CDRs and test for synergies with field experiment-derived estimates of risk aversion. We find evidence that respondents who are part of wealthier households have lower CDRs and more risk averse respondents have higher rates.

Estimation of Relative Risk Aversion Across Time

This paper examines relative risk aversion in the framework of a three moment asset pricing model that accounts for skewness. Accounting for skewness in calculating risk aversion gives a more accurate series of estimates of risk aversion and helps to reconcile the wide disparity in risk coefficients found in past literature. Risk aversion coefficients are calculated from 1926 to 2014 using stock market returns. This procedure results in a time series of data that can be related to other variables such as real interest rates and changes in demand for various asset classes.

The Taming of the Two - Simulation-Based Asset Pricing with Multi-Period Disasters and Two Consumption Goods

This study proposes a novel approach to facilitate the estimation of the preference parameters of a two consumption good C-CAPM that accounts for multi-period disasters, partial government defaults, and the possible destruction of the stock of the durable good. The maximum likelihood estimation of the disaster process parameters requires a cross-country panel of historical consumption data and international business cycle dates. The estimation of the risk aversion coefficient and the intertemporal elasticity of substitution (IES) is facilitated by the simulated method of moments. The results show that the empirical equity premium can be explained with economically plausible and quite precise risk aversion and IES estimates. This conclusion withstands a battery of robustness checks.