market-consumption and ecosystem-preference effects, a rising consumer-welfare weight ωicj
might have either a positive or negative effect on a state’s NXW or NXWS regulatory
congruence with others. For instance, a negative (estimated) coefficient on ωicj in equation (8)
would identify that consumers’ lobby works to lower overlap, i.e., increase regulatory stringence,
and their eco-system gains outweigh market-price effects. Similarly, commodity producer
interests depend upon the relative strength of producer preferences for lower seed prices versus
lower weed-abatement costs. Since seed producers benefit from price increases and agronomic
protection, we anticipate a negative effect on overlap from their lobbying efforts. However, if
seed producers perceive increased regulations as export barriers, then they likely lobby for
greater regulatory congruence. Thus, the impact of welfare weights (ωicj,ωisj,ωimj ) on regulatory
congruence in equation (8) cannot be predicted a priori.
Data Description
To estimate equation (8) we utilize publicly available data. The following describes our
database, which includes measures of relevant regulatory congruence and ecological, agronomic,
and lobbying dissimilarities across states.
Weed Regulatory Congruence (Lij-): Recall that each state has two sets of noxious weed
regulations: NXWS and NXW lists based respectively on FSA and PPA. We first compiled all
50 states’ NXWS lists for the years 1997 and 2002. However, we excluded Alaska and Hawaii
because of significant differences in the list size and ecological make-up (tropical versus tundra).
Each unique species from the 48 NXWS lists is compiled into a global list, which initially
contained about 1300 weed species. There were duplications and other typographical errors in
state NXWS lists, which were eliminated in the compilation of the global list. While some states