Errors in variables can seriously distort inference when they are not
taken into account explicitly. Coefficient values, their significance,
and whether some explanatory variables should instead be used as inst
ruments are largely a matter of interpretation unless further informat
ion is available. Higher moments of the observable variables impose re
strictions that allow testing for identification and specification and
estimating the parameters of the standard errors-in-variables model.
The argument is developed partly through examples illustrating the poi
nts.