摘要：In econometrics there is a long history of using continuous functions to force distributed lag coefficients to behave in an economically accepted way. For example, geometrically declining lags have often been used to model coefficients that we believe should be declining. Polynomial lags have been used to model lag coefficients expected to increase and then decrease. In this paper a more flexible way of imposing such prior information is investigated. Inequality constraints are used to impose knowledge about the relative magnitudes of coefficients without forcing them to lie on a smooth continuous curve. A Metropolis algorithm is used to get posterior density functions for the lag coefficients and functions of those coefficients for the Nerlove orange data and the Almon capital expenditures data.
