Rent-Seeking in Noxious Weed Regulations: Evidence from US States

political-economy variables (dollar and number of contributions) for the 3 stakeholders: seed
industry (includes nursery growers), commodity producer groups (agriculture less seed producers
and nursery growers), and consumer- and environment-interest (ideology) groups. Additionally,
we constructed dollar and number of contribution shares with respect to state totals for each
industry. As before, we constructed a 48x48 dissimilarity-index matrix for each lobby variable.
Note that the lobbying dissimilarity index, ωi = (ω_i- ω_j)/ω_i, continues to be an increasing
function of the base state’s lobby contribution.

The descriptive statistics on regulation overlap and all three categories of explanatory
variables are presented in table 1. In general, the NXWS lists show about 30 to 40 percent
overlap between 1997 and 2002, while overlap in NXW lists is only about 30 percent. However,
the variance of overlap has increased for the two sublists of NXWS regulation and the NXW list.
Lobbying indexes show a general increase between 1997 and 2002, while agronomic variables
changed little during the same period. Ecological variables are observed for 1997 only.

Econometric Procedure and Specification Tests

Given the panel nature (state i and j) of our data set, regulatory congruence in equation (8) is
estimated using three econometric procedures: ordinary least squares (OLS), fixed-effects (FE)
and random-effects (RE) estimators. For the OLS estimator, equation (8) is rewritten as:

(9)         L = ^{α + β} Xj ^{+ ε}

where i, j= 1,..., 48, α₀ is the intercept, Xij is a vector of explanatory variables and β is the

associated parameter vector of interest and ε_ij is the random, disturbance term. The FE

estimation replaces α₀ with state-specific intercepts α_i, i = 1,...,48 , as follows:

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