Researchers are often in a position of attempting to measure attributes
of a density function without being able to observe the variable in
question directly (like willingness to pay for a program designed
to achieve environmental improvement), but only some other variable
associated with it. Typically, the observed variable comes in a limited
form however (thumbs up or down on a referendum for example). This has
given rise to a wide variety of procedures not only to estimate moments
associated with the density function in question, but also to estimate how
the target variable is influenced by exogenously determined variables
(like income). Results obtained from logistic, ordered probit and
ordinary least squares (OLS) regressions are presented and discussed.
Avenues of future approaches statisticians should consider in addressing
this topic are explored.
Meet the speaker in Room 212 Cockins Hall at 4:30 p.m. Refreshments will be served.