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Sizing Up State Policy Innovation Research
Author(s) -
Berry Frances Stokes
Publication year - 1994
Publication title -
policy studies journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.773
H-Index - 69
eISSN - 1541-0072
pISSN - 0190-292X
DOI - 10.1111/j.1541-0072.1994.tb01480.x
Subject(s) - innovation diffusion , government (linguistics) , state (computer science) , politics , yield (engineering) , economics , public policy , econometrics , economic system , public economics , political science , positive economics , business , computer science , economic growth , marketing , linguistics , philosophy , materials science , algorithm , law , metallurgy
In the literature on state policy innovation, there are three major explanations for what causes a government to adopt a new policy. One is the internal determinants model, which posits that the main factors leading a state to innovate are internal political, social and economic characteristics of the stale. The other two are diffusion models—the regional diffusion model, and the national interaction model—which see slate policy adoptions as emulations of earlier adoptions by other states. Each of the three models has been associated with a distinct strategy for empirical testing. The regional diffusion model has been tested with factor analysis, the national interaction model with time‐series regression, and the internal determinants model with cross‐sectional regression. In this paper, I explore the ability of these “single‐explanation” methodologies to detect the true innovation process underlying stale policy adoptions, by applying these methodologies to data generated from simulated innovation processes with known characteristics. I find that the methodologies often yield incorrect conclusions about the character of innovation. I conclude by presenting an agenda for refining a superior alternative methodology: the event history analysis approach to state policy innovation research introduced by Berry and Berry (1990).