The elicitation of the elasticity of intertemporal substitution (EIS), discount factor, and risk attitude parameters in dynamic models is of central importance to economics, finance and public policy. This paper suggests an alternative method to jointly elicit and estimate these three parameters...

This paper studies dynamic programming for quantile preference models, in which the agent maximizes the stream of the future τ-quantile utilities, for τ ∈ (0,1). We suggest numerical methods, based on value function iterations, for solving the quantile recursive dynamic programming, and...

Payoff quantiles have been used for decision making in banking and investment (in the form of Value-at-Risk) and in the mining, oil and gas industries (in the form of "probabilities of exceeding" a certain level of production). However, it is unknown how common quantile-based decision making...

This note shows that the Generalized Expected Discounted Utility (GEDU) model is not dynamically consistent and does not allow for a complete separation of the parameters characterizing risk aversion and the elasticity of intertemporal substitution (EIS). Therefore, the model is not convenient...

This paper conducts a laboratory experiment to assess the optimal portfolio allocation under quantile preferences (QP) and compare the model's predictions with those of the expected utility theory using a mean-variance (MV) utility function. We estimate the risk aversion coefficients associated...

The elicitation of the elasticity of intertemporal substitution (EIS), discount factor, and risk attitude parameters is of central importance to economics, finances and public policy. This paper jointly elicits and estimates these parameters using experimental data. We employ a new model based...

This paper derives tests for skewness and kurtosis for the panel data one-way error component model. The test statistics are based on the between and within transformations of the pooled OLS residuals, and are derived in a moment conditions framework. We establish the limiting distribution of...

This article investigates estimation of censored quantile regression (QR) models with fixed effects. Standard available methods are not appropriate for estimation of a censored QR model with a large number of parameters or with covariates correlated with unobserved individual heterogeneity....