the weighted sum of these three interest-groups’ welfare, where the respective weights are
functions of lobbying efforts of individual groups. We then model the choice of IS protection as
a strategic game between a base state and any other state. The regulatory congruence between
these two states’ IS protection provides the basis for our empirical analysis.
Regulatory congruence represented by an overlap or similarity function, derived from our
inter-disciplinary approach, is estimated using data on ecosystem and agronomic characteristics
and on the rent-seeking efforts of the stakeholders or interest-groups. For this purpose, data are
compiled on (i) NXW and NXWS lists of the 48 contiguous states, (ii) states’ ecological
characteristics from Bailey’s Ecoregions of the United States, (iii) states’ agronomic
characteristics from USDA, and (iv) stakeholder lobbying (e.g., dollar value of contributions by
seed producers) from the Institute on Money in State Politics.
The next section presents our approach to the demand and supply of noxious weed
regulation. Data and the econometric procedure for estimating cross-state regulatory congruence
are then described. Discussion of results is followed by a summary and conclusions.
Research Methods
Central to our research is a political and ecological economy model of IS regulation. Political
economy models have become mainstream tools in the analysis of public policies (e.g., Stigler
1971; Peltzman 1976; Becker 1983; Grossman and Helpman 1994; Goldberg and Maggi 1999;
Copeland and Taylor, 2004). In our application of such approaches, we model a prohibited weed
species list as the consequence of the interplay of the supply and demand for IS protection.2
Demand arises from two sources. First, scientifically based concerns exist about the health of
2 Many of these regulations are considered to be nontariff barriers in agriculture. For measurement of non-tariff
barriers and their effects, see Beghin and Bureau (2001), Orden and Roberts (1997), and Hillman (1978).