This paper provides a critical survey of the methods employed to model the effects of risk in econometric models. Most of the popular methods are shown to suffer from errors-in-variables bias, and an instrumental variable method is suggested to overcome this problem. The technique exploits the orthogonality conditions existing between the squared unanticipated variables and functions of variables making up the information set defining the anticipations. An alternative procedure used in the paper is to directly estimate the conditional variance (risk) by non-parametric estimators. Applications are made to foreign exchange markets, interest rates and unemployment/inflation risk relations.
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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number
127.