ωikj,k=c,s,m, be the vector of differences in lobbying efforts between i-th and j-th states,
distinguished by consumer (c), seed-producer (s), and commodity-producer (m)
interest groups.
Objective functions of the i-th and j-th state problems then become:6
G ( Lj ) = max {B( Lj ; cβ, I j, Aj ,ωc,, ω ,ωm ) - C ( Lj ; cβ, I i, A j ω, ωs ,ωm )}
(6) Lij .
G ( Lf) = {B ( L„; L*., Iji, A f,ω, ωs,ω; ) - C ( L,; L*, Ijr, Af,ω, ω^ ,ω )}
The reaction functions for states i and j would then be:
(7) Lij =Ri(Lji);Lji =Rj(Lij),
resulting in a Nash-type solution as follows:
(8) L*ij =L*ij(Iij,Aij,ωicj,ωisj,ωimj ),∀i,j.
Equation (8) suggests that the similarity between any two states’ weed import regulations should
be a function of dissimilarities between (a) their ecosystem and agricultural characteristics, each
of which demand biological protection, and (b) their relative lobbying or welfare-weight ratios,
ωikj , which influence producers’ ability to use weed regulations as rent-seeking, import
protection. We expect the influence of Iij and Aij on overlap Lij to be negative because when
ecosystems and cropping patterns differ, weeds regarded as biologically and economically
damaging should differ also. That is, larger ecological and agronomic dissimilarities between
states should lead to lower regulatory congruence.
Note that the degree of overlap, Lij, is negatively related to the stringency of the i-th
state’s regulation (Li). Because the sign of equation (1) depends on the relative sizes of the
6 We suppress income and factor price differences by assuming integrated factor markets among US states.