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Applied Methods of Valuation of Water-related Ecosystem Services
Published in Robert A. Young, John B. Loomis, Determining the Economic Value of Water, 2014
Robert A. Young, John B. Loomis
Cummings and Taylor (1999) devised a “cheap talk” method of avoiding hypothetical bias. In game theory, cheap talk refers to nonbinding communication between players. In CVM survey research, cheap talk is an element of a questionnaire that explains the problem of hypothetical bias in survey questionnaire responses. Cummings and Taylor and others following this approach often find that cheap talk is effective in removing or reducing hypothetical bias for persons inexperienced in valuing the good being evaluated. Cheap talk appears to be a useful addition to a CVM questionnaire design although follow-up research has produced mixed results with different length cheap talk scripts (Champ et al. 2009).
Feedback control using a strategic sensor
Published in International Journal of Control, 2021
The problem of strategic communication between a receiver and a better informed sender, known as the cheap-talk game, has been studied in the economics literature (Battaglini, 2002; Crawford & Sobel, 1982). This problem has more recently attracted attention in the engineering community, where it has application in privacy-constrained communication and cyber-security (Farokhi, Sandberg, Shames, & Cantoni, 2015; Farokhi, Teixeira, & Langbort, 2017) and estimation (Dobakhshari, Li, & Gupta, 2016; Westenbroek, Dong, Ratliff, & Sastry, 2017). These studies mostly consider static estimation problems. In Farokhi et al. (2017), a dynamic estimation setup is considered; however, the sensor and the receiver act myopically (i.e. they do not consider the effects of their actions in the future). This could be reasonable for monitoring purposes but conservative in control formulations (as the sensor would not consider the effects of its actions in the future). It is worth mentioning that the problem of dynamic cheap-talk games has been recently studied in the economics literature (Golosov, Skreta, Tsyvinski, & Wilson, 2014). In contrast with Golosov et al. (2014), in this paper, we restrict the problem formulation to Gaussian random variables and quadratic cost functions. Thus, our model is much closer to the assumptions typically made in the control and estimation community. Further, this allows us to explicitly compute the equilibrium and study its properties. Finally, note that all the above-mentioned studies only focus on estimation issues and the effects of control are mostly unexplored.