Meta-Functional Benefit Transfer for Wetland Valuation: Making the Most of Small Samples

This study applies functional Benefit Transfer via Meta-Regression Modeling to derive valuation estimates for wetlands in an actual policy setting of proposed groundwater transfers in Eastern Nevada. We illustrate how Bayesian estimation techniques can be used to overcome small sample problems notoriously present in Meta-functional Benefit Transfer. The highlights of our methodology are: (i) The hierarchical modeling of heteroskedasticity; (ii) The ability to incorporate additional information via refined priors; and (ii) The derivation of measures of model performance with the corresponding option of model-averaged Benefit Transfer predictions. Our results indicate that economic losses associated with the disappearance of these wetlands can be substantial and that primary valuation studies are warranted.      

HOW IMPORTANT ARE ENDOGENOUS PEER EFFECTS IN GROUP LENDING? ESTIMATING A STATIC GAME OF INCOMPLETE INFORMATION

We quantify the importance of endogenous peer effects in group lending programs by estimating a static game of incomplete information. Endogenous peer effects describe how one's behavior is affected by the behavior of her peers. Using a rich dataset from a group lending program in India, our empirical analysis presents a robust finding of large peer effects. The preferred model suggests that the probability of a member making a full repayment would be 12 percentage points higher if all the fellow members were to make full repayment compared with a scenario in which none of the other members repay in full. We find that peer effects would be overestimated without controlling for unobserved group heterogeneity and that inconsistencies exist in the estimated effects of other variables without modeling peer effects and unobserved heterogeneity. Copyright © 2012 John Wiley & Sons, Ltd.     

Getting a feel for price affect: A conceptual framework and empirical investigation of consumers' emotional responses to price information

Behavioral pricing research is cognitively biased. Therefore, the research agenda for this paper is to examine consumers' emotional responses to price information, or price affect. A conceptual framework of price affect based on appraisal theory is proposed. Moreover, a psychometric measure of price affect capturing positive and negative emotions is derived. A field experiment involving N = 1533 consumers reveals that a price increase leads to changes in price affect. Also, negative price affect is related to passive consumer behavior, whereas positive price affect is associated with proactive consumer behavior. Yet, a price increase reduces the importance of price affect in predicting consumer behavior. In addition, both price cognitions and price affect mediate the effect of a price increase on consumer behavior. Consistent with appraisal theory, a price increase exerts its causal influence on price affect through changes in price cognitions. Similarly, price affect mediates the effect of price cognitions on consumer behavior. Finally, price affect improves the prediction of consumer behavior beyond price cognitions. Results suggest that price affect is a stand alone, previously overlooked predictor of consumer behavior. Implications are discussed. © 2008 Wiley Periodicals, Inc.     

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