dentify the independent, dependent, and any intervening variables. Indicate whether the relationships among them are direct or inverse

profileyasmine
Hannah_et_al-2018-Policy_Studies_Journal4.pdf

Defiant Innovation: The Adoption of Medical

Marijuana Laws in the American States

A. Lee Hannah and Daniel J. Mallinson

Diffusion research often characterizes the role of the federal government in innovation adoption as a

supportive one, either increasing the likelihood of adoption or its speed. We examine the adoption of

medical marijuana laws (MMLs) from 1996 to 2014 to shed light on what motivates states to adopt

innovations that are in explicit defiance of federal law. Furthermore, we examine whether federal

signals have any influence on the likelihood of adoption. In doing so, we utilize implementation

theory to expand our understanding of how the federal government’s position impacts state policy

innovation adoption. We find mixed evidence for the influence of federal signals on the adoption of

MMLs. The results suggest that medical marijuana policies are much more likely to be adopted in

states when proponents have the political or institutional capital, rather than a medical or fiscal need.

Moreover, this political capital is sufficient independent of the federal government’s real or perceived

position.

KEY WORDS: medical marijuana, policy diffusion, federalism

扩散研究常认为联邦政府在创新采纳中扮演着支持的角色, 它不是提高了政策采纳的可能性,

就是加快了采纳的步伐。我们分析了1996年到2014年间的医用大麻法案, 以此来阐明是什么促

使各州采纳那些明显违背联邦法律的创新。我们还分析了联邦的信号是否影响了政策采纳的可

能性。借此, 我们利用政策执行理论来扩展我们对于联防政府的立场对于州政策创新影响的理

解。我们发现联邦信号对于医用大麻法案采纳的影响复杂且模糊。结果表明, 医用大麻政策更

可能被那些支持者们有政治或制度资源的州, 而非那些有医疗或财政需求的州所采纳。而且, 这

些政治资源足够独立于联邦政府真实的或被感知的立场。

Introduction

The American federal system creates opportunities for sharing and learning

among localities, states, and the federal government. Often touted as laboratories of

democracy,1 the states experiment with new policy ideas, which may spread hori-

zontally to other states, as well as exhibit vertical influence on the federal govern-

ment’s issue agenda. Yet, federalism also generates conflict. For example, states

compete with each other for tax resources and residents (Dye, 1990; Tiebout, 1956).

402

doi: 10.1111/psj.12211

VC 2017 Policy Studies Organization

The Policy Studies Journal, Vol. 46, No. 2, 2018

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They also wrestle with the federal government over the proper boundaries of state

sovereignty and the implementation of federal initiatives (Rabe, 2007; Thompson &

Gusmano, 2014). Moreover, from the early doctrine of nullification to the passage of

medical and recreational marijuana policies in the modern era, states sometimes

actively defy federal law. We explore the concept of defiant innovation—a process

whereby states, through initiatives or the legislature, pass laws that not only circum-

vent, but also reimagine federal law. The study of policy diffusion brings insight into

the complex intergovernmental relationships fostered by federalism, yet it does not

address vertical conflict as much as vertical influence. We do so by examining the

adoption of medical marijuana laws. Moreover, we build bridges between theories

of policy implementation and diffusion in order to provide a framework for identify-

ing diffusion patterns that typify defiance.

We use the diffusion of medical marijuana to address the question of what moti-

vates states to adopt innovations that are in explicit defiance of federal law. This is

important for establishing whether the expected determinants of diffusion have the

same effect when states are defiantly adopting. This study also speaks to whether

defiant innovation is motivated differently than the well-studied cases of states

undermining federal mandates (Balla & Deering, 2015; Gormley, 2006; Regan &

Deering, 2009; Shelly, 2008). The two are linked, yet distinct, because in the first case

states are actively innovating in a policy area expressly prohibited by the federal

government and in the second states are refusing incentives and/or mandates to

implement federal initiatives. We seek to determine whether these two acts are moti-

vated differently.

The extent to which medical marijuana can be labeled “defiant” has fluctuated

over time since California first passed medical marijuana in 1996. At times, the fed-

eral government has signaled deference to the states on these issues, providing

implicit support for experimentation. At other times, the federal government has

been proactive and even aggressive in enforcing marijuana laws (O’Keefe, 2013).

Such variation in credible commitments to marijuana prohibition enforcement by the

federal government provides a useful test of how those commitments impact the

willingness of states to innovate in an area of federal–state conflict. Not only does

this address an important gap in policy diffusion research, it is timely given that

eight states have already legalized recreational marijuana and several additional

states are likely to consider legalization in the next 2 years (Steinmetz, 2016). Further-

more, national polling data shows increasing support for marijuana legalization

(Jones, 2015). It is likely that the factors driving state adoption of MMLs are consis-

tent with broader trends in marijuana policy. An understanding of the mechanisms

that drive the adoption of these policies might help to anticipate future development

of recreational marijuana as the federal landscape continues to evolve.

We find mixed evidence for the role of federal commitments to enforcement in

the adoption of MMLs. States were less likely to adopt medical marijuana policies

when the conservative Bush administration was in office. However, while President

Obama’s administration signaled a less interventionist approach from the federal

government, states were no more likely to adopt an MML. While different adminis-

trations signal implicit support or opposition to medical marijuana, we find that

Hannah/Mallinson: Defiant Innovation 403

explicit signals in the form of Drug Enforcement Administration (DEA) marijuana

seizures also do not affect states’ probability of adopting. Thus, the federal govern-

ment had less of an impact on the timing of MML adoptions than would be

expected. Instead, we find that state-level factors such as the availability of the initia-

tive and citizen liberalism increase the likelihood of medical marijuana adoption and

cultural differences, like the number of evangelical adherents, decrease the likelihood

of adoption. Further, states are more likely to adopt if they are ideologically similar

to previous adopters. Taking the results as a whole, the evidence suggests that states

moved forward in defiance with little consideration of the federal government’s

position.

The Logic of State Defiance

States do not always act in accordance with the will of the federal government.

This was most clear during attempts at nullification and interposition prior to the

American Civil War and school integration during the 1950s and 1960s and finally

resolved by the Supreme Court in 1971 (Swann v. Charlotte-Mecklenburg Board of Edu-

cation 402 U.S. 1). The doctrines of nullification, meaning states have the right to nul-

lify, or not implement, federal laws they view as unconstitutional, and interposition,

claiming that states stand as a barrier between citizens and unconstitutional federal

acts, arose from states determining that they were protecting their citizens from the

federal government.2 While the courts have dismissed both doctrines (e.g., Cooper v.

Aaron 358 U.S. 1 [1958]), states still attempt to nullify federal mandates with which

they do not agree. The question remains as to whether acts of defiance spread among

the states in a fundamentally different manner than policies that are supported by

the federal government or those whereby the federal government takes a neutral

stance.

Policy implementation research provides a foundation for developing a cogent

theory of how states respond to federal signals and why they, at times, innovate in

defiance of federal law. Goggin, Bowman, Lester, and O’Toole (1990) sought to pro-

vide testable hypotheses for why states vary in their willingness to implement fed-

eral priorities and subsequent success. Fiscal Federalism, whereby the federal

government induces state implementation through financial incentives, in particular,

created the potential for principal–agent problems (Chubb, 1985). Extant policy diffu-

sion research regarding state responsiveness to federal signals often focuses on

instances when the federal government incentivizes diffusion, meaning when states

respond positively to national coercion (Nicholson-Crotty, 2009; Welch & Thompson,

1980). These are cases where the agent states are working for the principal. Of course,

states can also fail to implement federal priorities (i.e., shirk) or even redesign federal

policy (i.e., sabotage).3 Furthermore, the federal government does not only provide

inducements (i.e., positive signals) for state action, but also utilizes constraints (i.e.,

negative signals). For either federal inducements or constraints to be implemented

by the states, the signals sent to them must be credible, clear, consistent, repeated,

and received (Allen, Pettus, & Haider-Markel, 2004; Goggin et al., 1990).

404 Policy Studies Journal, 46:2

States vary in their receptivity to these signals, not only cross-sectionally, but

also temporally. Goggin et al. (1990) hypothesized that states with supportive legisla-

tures and advocacy coalitions will implement federal policy more quickly than those

with weaker, or less supportive, institutions. Ecological capacity (i.e., a combination

of economic, political, and situational capacities) is also important to both implemen-

tation and diffusion theory. States with greater financial and institutional capacity

are in a stronger position to implement federal policy quickly and effectively. In dif-

fusion parlance, slack resources allow states to overcome obstacles to adoption

(Walker, 1969). Conversely, ecological capacity provides the resources to resist fed-

eral signals. Moreover, implementation is temporally dynamic; as a state’s capacity

changes or the legitimacy of the signal sender erodes or improves over time, states

can change their implementation behavior. This temporal dynamic is vital for under-

standing the spread of defiant innovations like medical marijuana policies.

Table 1 establishes a framework for differentiating the observable expectations

of adoption patterns when the federal government and states are either in concor-

dance or discordance over a specific policy. Each can take three positions on a given

policy: pro, anti, or neutral. It is important to note that this table presents the overall

adoption pattern that is observable when a plurality of states falls into each category.

A typology of the macrolevel patterns will allow future research to address how

additional policies fit within each category. After describing these macrolevel pat-

terns, we will shift the unit of analysis to the individual states, so as to establish test-

able hypotheses for our subsequent event history analysis of medical marijuana

adoption.

Perhaps the two most obvious and well-supported categories in Table 1 are

those in which the federal government sends positive signals through financial

incentives (Welch & Thompson, 1980), issue attention (McCann, Shipan, & Volden,

2015), legislative activity (Karch, 2006), or mandates (Woods & Bowman, 2011), and

those in which the federal government is assumed to have a neutral position (e.g.,

Berry & Berry, 1990). For policies like the Civil Defense Compact, the federal govern-

ment increased state financial capacity for implementation, and thus states

Table 1. Expected Diffusion Patterns When the Federal Government Takes a Pro-, Anti-, or Neutral Stance and States Take Pro-, Anti-, or Neutral Stances to an Innovation

Federal Government

State Government

Pro Neutral Anti Pro Rapid adoption

(Civil Defense Compact)

Characteristic- dependent adoption

(Lotteries)

Expanding adoption, declining enforcement

(Medical Marijuana)

Neutral Compliance with partisan reservations

(Common Core)

Highly regionalized issue

(Colorado River Compact)

Limited defiance, varying enforcement

(Medical Marijuana)

Anti Formal opposition (REAL ID)

Limited adoption (Stem Cell Research)

Limited defiance, widespread enforcement

(Medical Marijuana)

Hannah/Mallinson: Defiant Innovation 405

responded quickly in adopting the innovation (Goggin et al., 1990; Nicholson-Crotty,

2009; Savage, 1985; Welch & Thompson, 1980). When the federal government is neu-

tral toward an innovation, like a state lottery, states are prompted to adopt based on

the expected internal determinants and external influences theorized by Berry and

Berry (1990, 2013). Thus, the policy’s overall adoption pattern should resemble a nor-

mal s-curve (Boushey, 2010; Gray, 1973; Mallinson, 2016) with relatively wide adop-

tion over time.

It is also theoretically possible to have a plurality of states take neutral positions

on policies for which the federal government sends positive, negative, or neutral sig-

nals. Policies of highly regional significance seem most likely to fit into the neutral-

neutral category. The protection and management of rivers (e.g., the Colorado River

Compact) for example, may garner little interest from a plurality of the states and

the federal government.

In the case of a positive federal position and a neutral plurality, we would expect

neutral states to experience vocal partisan reservations to the given policy that would

initially limit adoption (e.g., Common Core). Nonetheless, federal incentives can

push states from a neutral to a generally positive stance. The rate of adoption would

increase as this shift occurs, emphasizing the point that a policy can start in one cate-

gory, with a particular expected pattern of spread, and move into another category

via changes in federal signals and/or circumstances in the states. Gay marriage pro-

vides a useful example of this principle. Congruence between state and federal pol-

icy fluctuated across time as states moved in a direction different than the federal

government, until the courts stepped in to settle the law.

There is further evidence of what happens when the federal government sends

positive signals regarding a policy that states simply do not want. For example, Con-

gress passed the REAL ID Act (2005) in response to recommendations by the 9/11

Commission (2004) that the government establish standards for personal identifica-

tion, including those issued by states (e.g., drivers licenses). Maine was the first state

to adopt a law opposing the federal REAL ID requirements and, within 18 months,

20 other states followed suit (Regan & Deering, 2009). In this case, the federal gov-

ernment is trying to induce states to produce a desired policy outcome, but states

refuse. Medicaid expansion under the Affordable Care Act highlights how financial

inducements can erode state resistance over time (Jacobs & Callaghan, 2013). State

resistance is certainly not new. Maryland did not choose to enforce federal alcohol

prohibition in the 1920s and states like New York chose to abandon enforcing alcohol

prohibition prior to the ratification of the Twenty-First Amendment, which repealed

Prohibition. Even further back in American history, states like Pennsylvania refused

to enforce Fugitive Slave Laws (O’Keefe, 2013).

In the case of a policy where the federal government expresses neutrality toward

state action and a plurality of states are opposed, it is likely that very few states will

take up such a cause. Take stem cell research funding, for example. In his early work

on this policy, Karch (2010) identified state stem cell funding as an example of lim-

ited diffusion. Between 1999 and 2008, seven states provided financial support for

stem cell research, three legalized the conduct of this research (without funding),

and six restricted it. In fact, state funding of stem cell research has not substantially

406 Policy Studies Journal, 46:2

expanded further since then (Gugliotta, 2015). Karch (2012) later demonstrated that

while the innovation was not widely adopted, the Bush administration’s banning of

federal research funding prompted many states to consider their own support.

While, on one hand, the federal government communicated its disagreement with

the policy by banning its own source of funding, it did nothing to prevent states

from instituting their own programs. Thus, the federal government is expressing

neutrality toward state innovation. The result was a limited pattern of adoption with

a few concurring anti-innovation states adopting their own bans on research.

The final three categories, which we find exemplified in the spread of MMLs,

are those where the federal government prohibits an activity that states desire (i.e.,

the growth, distribution, and consumption of marijuana). This is distinct from cases

like REAL ID, where the states are refusing to implement a federal program.

Granted, both are principal–agent problems, whereby the states as agents are not

implementing the principal’s desires. The distinction is that mandate resistance is a

case of agent shirking, whereas a defiant innovation, like an MML, is sabotage. In

defiant innovation, states are not only simply allowing a banned activity, but they

are actively promoting the development of a new program even when the federal gov-

ernment bans it. Marijuana is presently classified as a Schedule I drug under the

Controlled Substances Act of 1970 (CSA). Thus, the distinction from mandate refusal;

states are innovating in defiance of federal law by authorizing the distribution of

marijuana for medical purposes.4

States, of course, diverge in their willingness to engage in defiant innovation. A

shrinking, but still substantial, minority is supportive of federal law or is legitimately

dissuaded from acting against federal interests, and thus sees no reason to enact

allowances for marijuana use. Other states are sympathetic, but lack the ecological

capacity to enact defiant innovations and risk retribution (e.g., lawsuits) by the fed-

eral government or peer states (Kamin, 2015). As the plurality of states shifts from

opposed to the innovation, to neutral, to positive, the patterns of both adoption and

enforcement change. We now transition to addressing states as the unit of analysis

and drawing further on implementation and principal–agent theory to derive

hypotheses specific to the predictors of defiant innovation.

Expectations for the State-Level Predictors of Defiant Innovation

Explicit Federal Government Signals

A state’s decision to adopt a policy innovation is typically a function of their

internal motivations, the obstacles to adoption and availability of resources for over-

coming those obstacles, the effects of other policies and availability of alternative sol-

utions, and the influence of external actors (Berry & Berry, 1990, 2013). The federal

government is one external actor that increases the resources available to states for

innovation (Eyestone, 1977; Welch & Thompson, 1980), as well as the obstacles for

adoption (Karch, 2007). The executive branch, in particular, is dependent on states to

implement a host of domestic policy initiatives. From Medicaid to the Elementary

and Secondary Education Act to the War on Drugs, the states play a major role in

Hannah/Mallinson: Defiant Innovation 407

the success or failure of these programs. Increasingly, federalism scholars have noted

the shift in legislatively driven cooperative federalism to executive-driven coopera-

tive federalism (Gais & Fossett, 2005). Meaning, the executive branch has been taking

an increased role in shaping and reshaping intergovernmental implementation in the

face of gridlock in Congress and diminished legislative control (Bulman-Pozen &

Metzger, 2016; Gais & Fossett, 2005). The use of waivers for No Child Left Behind

and the Affordable Care Act clearly demonstrates the practical effects and limitations

of executive federalism (Dinan, 2014; Saultz, McEachin, & Fusarelli, 2016; Thompson

& Gusmano, 2014).

The dependence of the federal government on the states for policy imple-

mentation provides ample opportunity for states to shirk or sabotage their role.

The federal government, of course, uses the tools at its disposal (grants, waivers,

cross-over sanctions, among others) to encourage states to faithfully implement

the law. These tools send explicit signals to the states regarding the executive’s

expectations regarding proper policy implementation. Federal signals must be

credible and legitimate in the eyes of state officials for “implementation to pro-

ceed promptly and without modifications” (Goggin et al., 1990, p. 175). While

prior diffusion research corroborates the importance of credible and legitimate

signals (Allen et al., 2004), much of the extant research focuses on instances

where the federal government is promoting an innovation. In contrast, defiant

innovation modifies dissonant federal policies.

We argue that the federal government sends two kinds of signals—explicit

and implicit—to which the states respond. Explicit commitments come in the

form of executive branch enforcement activities. In the case of No Child Left

Behind, the Obama administration sent explicit signals regarding its desire to

reform the implementation of that law through the use of waivers (Saultz et al.,

2016). In the present case of MMLs, the Department of Justice (DOJ) and Drug

Enforcement Agency (DEA) have authority over the enforcement of federal drug

laws. This enforcement power includes the ability to seize marijuana. We

hypothesize that increased seizure of marijuana sends explicit signals regarding

the executive branch’s support of federal marijuana prohibition. There are, of

course, stronger signals at the president’s disposal, namely the millions of dol-

lars in funds and equipment sent to local police departments for the purpose of

executing the drug war. To our knowledge, the president has yet to use this

major stick against states acting in defiance of federal law. Thus, we use the mea-

sure of seizures as the clearest signal of the executive branch’s commitment to

marijuana prohibition. Given that states vary in their ecological capacity to defy

federal law, stronger signals from the executive branch should raise the obstacles

to adoption to the point that the diffusion of a defiant innovation like medical

marijuana would slow, but not stop (Rabe, 2007). Conversely, the weakening of

explicit signals should prompt increased innovation activity.

Explicit Federal Commitments Hypothesis: Increased federal enforcement

decreases the likelihood that states will adopt a defiant innovation and

decreased enforcement has the opposite effect.

408 Policy Studies Journal, 46:2

When campaigning for office, presidents also send implicit signals regarding

their favorability toward a host of policies under their jurisdiction. Even after the

president is able to use their powers to send explicit signals regarding state imple-

mentation, some presidents maintain an image of promarijuana or antimarijuana

that may not directly match with their enforcement of the law. For example, Presi-

dent Obama has received criticism for increasing marijuana enforcement activities

during his presidency (Tau, 2012). This sends conflicting signals, as states strategi-

cally anticipate how the federal government will receive their defiant actions.

Changes in presidential administration provide one implicit signal of agreement or

disagreement with state defiance. It is possible that an administration can have a pos-

itive or negative impact on state innovation, even if the perception of their views on

a policy deviates from more explicit signals sent to the states.

Implicit Federal Commitments Hypothesis: Changes in presidential

administrations alter the likelihood of adopting a defiant innovation.

Demand

Demand for the innovation should have a particularly strong effect, providing

an impetus for defying federal law. This demand could be for the products of the

policy itself, medical marijuana for example, or state fiscal demand if the innovation

has a substantial influence on the state’s fiscal health. States regularly propose alter-

native means for raising revenue in order to avoid less politically palatable increases

to income and consumption taxes (Berry & Berry, 1990; Nelson & Mason, 2007). For

example, in the case of medical marijuana, states not only levy taxes on individuals,

they also tax dispensaries and distributors (Hickey, 2014). In many states, this has

led to substantial windfalls (Oosting, 2014; Stern, 2015).

Usage Demand Hypothesis: The likelihood of a state innovating defiantly

increases as internal demand for that innovation concomitantly increases.

Fiscal Demand Hypothesis: States facing fiscal stress are more likely to

adopt a defiant innovation that can raise additional revenue.

Ecological Capacity

Ecological capacity “encompasses state wealth, state institutional capabilities,

and state situational contexts” (Goggin et al., 1990, p. 135). Such capacity is necessary

for rapid and effective implementation (Goggin et al., 1990) and innovation adoption

(Walker, 1969). A state’s ecological capacity should thus condition its ability to

respond to federal signals in defiance. The popular initiative is an important institu-

tional capability for defiance, as it provides a means for citizens that are dissatisfied

Hannah/Mallinson: Defiant Innovation 409

with federal policy to circumvent state legislators reticent to defy the federal govern-

ment. Thus, if public opinion is growing increasingly incongruent with federal policy

and usage demand is increasing, state defiance actually increases opinion-policy con-

gruence and improves citizen perceptions of state responsiveness (Ferraiolo, 2008).

Moreover, the initiative serves as a legitimizer of innovative policies and sets the

agenda for other states, including legislatures in states that do not have the initiative

(Magleby, 1988). Finally, while initiatives are sponsored by outside groups, their

inclusion on the ballot still indicates a degree of state defiance, since they must be

certified by a state’s executive branch. In the case of MMLs, the first five laws

(Alaska, California, Maine, Oregon, and Washington) were adopted through direct

initiative between 1996 and 1999. Hawaii became the first state, in 2000, to pass an

MML through the state legislature.5

Initiative Availability Hypothesis: States with an available initiative pro-

cess are more likely to adopt an MML.

Other institutional, political, and social factors that should impact the likelihood

of MML innovation include legislative professionalism (McCann et al., 2015), voter

liberalism (Berry, Ringquist, Fording, & Hanson, 1998), and prohibitionist religious

culture (Frendreis & Tatalovich, 2010; Jensen, 2003). Many of these relate to a state’s

political culture, which shapes the policy choices made by states (Elazar, 1966) and

intergovernmental implementation (Goggin et al., 1990). These components of a

state’s ecological capacity influence its willingness to defy or support federal law.

Thus, while we expect federal signals to be weak, internal characteristics should be

prevalent predictors of adoption.

Ecological Capacity Hypothesis: Internal characteristics of the state, like

ideology, religious and political cultures, and institutional capacity (e.g.,

legislative professionalism) condition the likelihood that states will react

positively or negatively to federal signals in deciding to adopt a defiant

innovation.

Diffusion

Diffusion scholars have long found that innovations may spread outward from

an innovator state to geographically contiguous states (Berry & Berry, 1990; Walker,

1969). In short, states that share borders are more likely to follow the political hap-

penings of their neighbors than those across the country. States that share borders

are also likely to be more similar in terms of their internal characteristics than states

that are farther away. Finally, neighbors are in direct competition (Berry & Baybeck,

2005; Dye, 1990), which is relevant given the large sums of tax revenue marijuana

can yield. Thus, it is important to test whether neighbor states are in fact influencing

each other.

410 Policy Studies Journal, 46:2

Neighbor Hypothesis: A state is more likely to adopt a defiant innovation

as the proportion of its contiguous neighbors that previously adopted also

increases.

While spatial relationships are important for policy diffusion, geography does

not provide the only means of similarity through which policies can diffuse. Ideolog-

ical similarity is a potential pathway of policy learning (Grossback, Nicholson-

Crotty, & Peterson, 2004) and likely relevant for acts of defiance. If states are choos-

ing to defy federal policy, they may be doing so based on ideological differences,

meaning the set of states willing to defy are connected more through ideology than

geography. Thus, it will be ideological peers, not contiguous neighbors, which influ-

ence defiant innovation.

Relative Ideology Hypothesis: A state is more likely to adopt a defiant

innovation if the ideology of past adopters falls closer to its own.

We now turn to describing our operationalization of these concepts and analyti-

cal technique for testing the above hypotheses.

Data and Analytical Technique

Dependent Variable

Data were collected on the 50 states from 1996 through 2014. Of these states, 23

passed MMLs, either by voter initiative or statute (see Figure 1 for a map of these

states). We employ event history analysis (EHA) to test the hypotheses presented

above (Berry & Berry, 1990). The time period covered in the model starts in the year

of the first passage of medical marijuana legislation (1996) and advances to 2014. In

1996, California voters approved Ballot Proposition 215, making California the first

state to adopt and drop out of the dataset. By 2014, 27 states remain in the risk set.6

Independent Variables

Credible commitments for federal marijuana prohibition enforcement by the

executive branch have varied over time, resulting in uncertainty for states, dispensa-

ries, and other businesses that support the marijuana industry. As medical marijuana

legislation emerged in the states, the Clinton administration made the War on Drugs

a priority in order to avoid being seen as soft on crime (National Research Council,

2014). It was not until the waning days of his administration that President Clinton

argued for marijuana decriminalization (Wenner, 2000). During the George W. Bush

administration, funding was increased for global drug interdiction and the federal

government remained committed to marijuana prohibition enforcement (Gaumond,

Davis, & Hill, 2009). The commitment to enforcement wavered during the Obama

administration. In 2009, DOJ issued the Ogden (2009) memo, which suggested that

Hannah/Mallinson: Defiant Innovation 411

DOJ would not expend resources prosecuting individuals that were acting in compli-

ance with state MMLs. DOJ, however, stepped back from this assurance in 2011 by

asserting their commitment to enforcing the CSA (Cole, 2011). Finally, in 2013, DOJ

announced that it would leave primary enforcement of marijuana law to states with

“strong and effective regulatory and enforcement systems to control the cultivation,

distribution, sale, and possession of marijuana” (Cole, 2013). It also threatened to

pursue enforcement action if state enforcement mechanisms are not robust enough.

While this paves the way for states to operate medical and recreational marijuana

programs with less threat of federal government involvement, there are no guaran-

tees that the government’s “wait and see” approach will remain as administrations

change.

There is an arresting gap, however, between the rhetoric and practices of all

three presidents. Figure 2 displays one marker of this by plotting the total amount of

marijuana seized domestically (1,000 kilograms) by the DEA from 1986 through

2014. It also demarcates the first year in office of Clinton (1993), Bush (2001), and

Obama (2009). Strikingly, marijuana seizures declined rapidly prior to Clinton taking

office, stayed relatively steady during the Clinton administration, declined again

during the Bush administration, and increased rapidly under the Obama administra-

tion to levels not seen since Ronald Reagan’s expansion of the War on Drugs. This,

of course, is not the only way in which the executive branch enforces federal mari-

juana prohibitions, but seizures are highly meaningful to states, like California, that

Figure 1. Map of States with Medical Marijuana Laws as of 2014 (Shading Based on Years Since Law Was First Passed).

412 Policy Studies Journal, 46:2

encourage the development of a network of private suppliers for their medical mari-

juana programs. Thus, the states have received different implicit and explicit signals

regarding their policy experiments with marijuana. In fact, President Obama has

been criticized for these conflicting messages (Scherer, 2012).

Thus, we examine both the implicit and explicit signals of administrative com-

mitment to federal marijuana prohibition. We use two dichotomous indicators

denoting the Bush Administration and the Obama Administration as implicit mea-

sures of the federal government’s preferences. We expect that different administra-

tions signal changes in federal drug policy to the states. We anticipate that the more

conservative Bush administration discouraged states from adopting medical mari-

juana policies. Meanwhile, we expect that states were encouraged to adopt with less

fear of federal intervention during the Obama administration. The Clinton adminis-

tration serves as the reference category for each of these comparisons. We also model

explicit changes in the federal government’s stance by controlling for the Federal

Seizures of marijuana in a given year by the DEA.

We consider usage and demand in the state by including Marijuana Treatment

Admission Data (TEDS),7 Cancer Incidence Rate, and Glaucoma Prevalence. We

expect that higher rates of marijuana use will remove the stigma associated with

marijuana use and increase support for adopting an MML. We also anticipate that

demand for the program will increase in states with a higher number of potential

patients that could benefit from the drug. In 22 of the 23 laws we examined, cancer

and glaucoma are listed as debilitating medical conditions in the text of the laws;

and in most cases they are listed first. We that expect states with a higher preponder-

ance of cancer or glaucoma may experience greater pressure from citizens to increase

access to this medical treatment. To examine fiscal opportunity, we included a

lagged measure of Fiscal Health measured as the ratio of total-state-revenue-minus-

total-state-spending to total-spending (Berry & Berry, 1990). We expect that states

with lower year-end balances or deficits are more likely to adopt an MML.

Along with these measures based on our hypotheses, we include a number of

internal characteristics as controls that we expect to affect the probability of a state

Figure 2. Marijuana Seized by the U.S. Drug Enforcement Administration (in 1,000 kilograms), 1986– 2014.

Hannah/Mallinson: Defiant Innovation 413

adopting an MML. We control for the role of states’ institutional capacity by includ-

ing an indicator for Initiative Availability and Legislative Professionalism. The

ability to use the direct initiative should increase the likelihood of a state passing a

law. We also expect that more professional legislatures will be able to devote the

time and resources to taking up this controversial and complex policy (Huber & Shi-

pan, 2002; Huber, Shipan, & Pfahler, 2001). Next, we consider characteristics of the

state electorates. We use a citizen ideology measure (Citizen Liberalism) developed

by Berry and colleagues to test the relationship between a state’s ideology and its

adoption of medical marijuana policy (Berry, Fording, Ringquist, Hanson, & Klarner,

2010; Berry et al., 1998). We expect that more liberal states are more likely to pass

MMLs. While there is an ideological dimension to support for medical marijuana

(Pew Research Center, 2015), there is also a moral dimension that we capture with

the statewide Evangelical Rate, which captures the size of prohibitionist religious

cultures in a state (Frendreis & Tatalovich, 2010).

Finally, we consider the role of state-to-state diffusion. We created a Proportion

of Neighbors with MML to account for the fraction of neighboring states that have

previously adopted an MML. We expect that states are increasingly likely to adopt a

law if their neighbors are also passing them. We also construct the Relative Ideology

of States Adopting MMLs and expect that states are more likely to adopt MMLs if

states that are ideologically similar have already passed the law (Grossback et al.,

2004). Finally, we include the Time After the First Adoption to account for remain-

ing duration dependence (Beck, Katz, & Tucker, 1998). Table A1 in the appendix fur-

ther describes each of the independent variables and provides summary statistics

along with the data source.

Results

To illustrate the consistent spread of this innovation, regardless of changes in the

federal government’s position on the issue, Figure 3 displays the cumulative total

number of states that adopted medical marijuana programs between 1996 and 2014.

It also displays separate cumulative adoption curves for states adopting via a legisla-

ture and those adopting via a popular initiative. Immediately evident is that many of

the innovators and early adopters took up MMLs through the initiative, as it pro-

vided early cover for legislators that did not want to be identified with marijuana

policy. Figure 3 also shows that the expansion of medical marijuana programs

remained consistent after the initial period of rapid adoption and that many of these

later adoptions were passed by legislatures. In fact, initial ballot success and growing

public support further pushed legislatures to consider and adopt MMLs (Ferraiolo,

2008).

Table 2 provides results from a logistic EHA model predicting MML adoption.

The model includes traditional policy diffusion variables accounting for ecological

capacity and regional diffusion as well as signals from the federal government and

ideological diffusion. Finally, the second column reports odds ratios for the variables

that are statistically significant. Federal signals appear to have had little impact on

defiant adoption of an MML. The explicit signal of DEA seizures has no effect.

414 Policy Studies Journal, 46:2

Figure 3. State Adoptions of Medical Marijuana Laws, 1996–2014.

Table 2. Results of Logistic Regression Model Predicting Medical Marijuana Policy Adoption in the U.S. States (1996–2014)

Coefficients Odds Ratios

Federal Signals Marijuana Seizures in kilograms (10k) 20.02 (0.02) Bush Administration –3.85* (1.73) 0.021

[0.001, 0.408] Obama Administration –4.811 (2.77) 0.008

[0.000, 1.211] Ecological Capacity Initiative Availability 1.11* (0.52) 3.029

[1.084, 8.464] Legislative Professionalism 0.07 (2.77) Citizen Liberalism 0.09* (0.03) 1.097

[1.031, 1.167] Evangelical Rate –0.011 (0.00) 0.989

[0.974, 1.003] Fiscal Healtht-1 20.64 (3.27) Demand Marijuana TEDS 0.00 (0.00) Glaucoma Percent 25.09 (3.11) Cancer Incidence Rate

(per 100,000) 0.00 (0.00)

Diffusion Proportion of State Neighbors with MML 0.16 (1.50) Relative Ideology of States Adopting MML –0.13* (0.05) 0.881

[0.799, 0.965] Time After First Adoption 0.51** (0.19) Constant 1.78 (4.93) N 768 Log Likelihood 274.48

Wald v2 33.3** 1 indicates statistical significance at p < 0.10 (two-tailed); *p < 0.05, **p < 0.01. Robust standard errors reported in parentheses. 95% confidence intervals reported in brackets.

Hannah/Mallinson: Defiant Innovation 415

Additionally, while the likelihood of adoption is lower during the conservative Bush

administration, it remains so during the more implicitly, though less explicitly, sup-

portive Obama administration. In terms of the odds of adoption, they declined by

nearly 100 percent in the Bush and Obama administrations (each relative to the Clin-

ton administration).8

Regarding state ecological capacity, not only the initiative, but also citizen liber-

alism and Protestant fundamentalism are important. A one standard deviation

(14.99) increase in citizen liberalism results in a 145 percent increase in the odds of

adopting an MML. Additionally, the odds decrease by 130 percent with a one stan-

dard deviation (117.8) increase in evangelical adherents. Having an initiative process

available increases the odds of adopting an MML by 203 percent. The results for

medical usage demand are not significant (cancer and glaucoma incidence). Mean-

while, there is no evidence that increased marijuana use motivates a state to act on

passing an MML. Finally, fiscal health does not have a statistically significant effect

on the probability of adoption.

Perhaps most intriguing, from the standpoint of traditional expectations of

diffusion patterns, is that MMLs did not experience regional diffusion through

contiguous neighbor adoptions. Instead, MMLs have an important ideological

component, whereby states that are less ideologically similar to those that

already adopted are less likely to adopt an MML.9 Substantively speaking, a one

standard deviation (8.17) increase in the ideological distance between a state and

those that adopted previously results in a 97 percent reduction in the odds of

adopting an MML.

Furthermore, the combination of the ideological spread of this policy with

the declining likelihood of adoption after the initial innovation and early adop-

tion phases suggests that MML adoption may be reaching a saturation point,

whereby most of the states that have demand for an MML already have it and

those that support federal marijuana prohibition are less likely to consider adopt-

ing without fundamental changes in their internal political or social context.

Thus, while many states still have no medical marijuana statute, the policy may

have already saturated the states that are willing to act in defiance of federal

law. States in the South and Midwest (see Figure 2), for example, are likely reti-

cent to adopt such a policy, and are more likely to be supportive of the federal

prohibition in the first place. Consequently, these laggard states may be less

likely to adopt moving forward, short of the emergence of substantial internal

pressures due to fiscal stress and gains in cultural acceptability. The results sug-

gest that medical marijuana policies are much more likely to be adopted when

proponents have the political or institutional capital, rather than a medical or fis-

cal need. Moreover, this political capital is sufficient independent of the federal

government’s real or perceived position.

Discussion and Conclusion

What motivates states to innovate in defiance of federal law? Past research dem-

onstrates that internal demand, institutional capacity, and financial constraints are

416 Policy Studies Journal, 46:2

associated with state decisions to shirk the implementation of federal policy (Balla &

Deering, 2015; Palazzolo, Moscardelli, Patrick, & Rubin, 2008; Regan & Deering,

2009); however, we take this a step further to test whether these dynamics hold in

the case of states sabotaging federal law by defiantly innovating new policy. We

find that, in the case of medical marijuana policy, policy adoption was most

clearly associated with components of a state’s ecological capacity (the initiative,

evangelical rate, and citizen liberalism). Furthermore, this policy exhibits an

ideological, not a geographical, pattern of spread. The states most willing to act

in defiance did so early on and adoption became increasingly less likely over

time. This was the case not only during the conservative Bush administration,

but also after the Obama administration implicitly signaled greater openness to

these programs. Early adoptions via the initiative gave way to a mixture of legis-

lative and initiative adoptions, thus corroborating the legitimizing effect of the

popular initiative (Magleby, 1988).

The decline in the likelihood of adoption during both the Bush and Obama

administrations appears to be less likely due to the clarity of federal signals regard-

ing marijuana prohibition enforcement, and more to the saturation of adoption in

states that were willing, and had the necessary capacity, to defy federal law. One

way to view this is that the policy is becoming less defiant over time. This appears to

be true, as the tide of public opinion is shifting in support of loosening marijuana

restrictions. Adoption by a now majority of the states further legitimizes this defiant

position, while eroding the legitimacy of the federal government’s position. That

being said, President Obama’s increased enforcement efforts and the election of Don-

ald Trump, and particular the confirmation of Senator Jeff Sessions as Attorney Gen-

eral, demonstrates that even as the federal government’s view loses legitimacy, state

action today is not less defiant. It remains to be seen whether the Trump administra-

tion will enhance domestic interdiction efforts, but the appointment of Jeff Sessions

will put in place an Attorney General that is a staunch opponent of drug legalization.

Pennsylvania, Florida, North Dakota, and Arkansas demonstrated in 2016, however,

that as demand grows, cultural norms change, and states face increasingly difficult

fiscal challenges (Kiewiet & McCubbins, 2014), laggard states will still follow, but

they may do so sparingly.

The combination of both the significant and null results in this study paint a

picture of how defiant innovation progressed in the case of medical marijuana

laws, but in a way that likely captures other acts of state statutory defiance in an

era of gridlock and polarization. The popular initiative and ideology were impor-

tant driving forces of MML adoption in the states, regardless of mixed and vary-

ing implicit and explicit federal signals regarding prohibition enforcement. While

the expression of changing popular opinion initially occurred through popular

initiatives, ideologically similar states appear to have been emboldened by these

actions and thus the policy spread among those states that were most likely to

agree with the early defiant actors, and thus disagree with the federal govern-

ment. Over time, as these like-minded states followed suit, the pool of potential

adopters dwindled. Nonadopters, who are themselves more ideologically similar

to each other than to adopters, will likely not adopt without a shift in internal

Hannah/Mallinson: Defiant Innovation 417

support for the policy or substantially increased external influence. This is impor-

tant for the broader study of policy diffusion, as there is limited attention to how

and why policies do not fully diffuse (Karch, 2010) and how the motivations for

adopting change as diffusion unfolds (Rogers, 2003). While ecological capacity is

important for both mandate refusal and this case of defiant innovation, the ideo-

logical bifurcation of adopters and non-adopters and the importance of citizen

initiatives for spurring and legitimizing diffusion are key distinctions. These find-

ings provide an important starting point for differentiating types of state defiance

and developing a fuller picture of how vertical diffusion operates in the United

States.

American federalism is not neat and tidy, in that the federal government encour-

ages innovation through issue attention and financial incentives while also taking up

and nationalizing successful innovations from the states. There is an important ele-

ment of struggle within federalism. There are costs for states and municipalities that

defy the federal government. Cities and universities across the United States are

presently facing the possibility of federal sanctions for refusal to report undocu-

mented immigrants to U.S. Immigration and Customs Enforcement (Arrieta-Kenna,

2016).10 The federal government could conceivably do the same thing to states with

recreational and medical marijuana provisions by withholding billions of dollars in

federal money committed to the War on Drugs. Additionally, the Trump administra-

tion could take the states to court and test the Supreme Court’s support for federal

preemption (Kamin, 2015). This is why the merging of diffusion and implementation

studies is so important. States, particularly when choosing to defy federal law, must

respond to changes not only in their ecological capacity to innovate, but also in the

overall federal ecosystem. If federal signals clarify and intensify in the next adminis-

tration, states may make different choices in either (a) defying in the first place or (b)

how they choose to defy.

Future work building on the theoretical foundation established here can help

explicate not only the when of defiance, but also the how. State approaches to mari-

juana are not identical and that variation can be used to understand the extent to

which choices are dependent on internal capacities or external forces from peer states

and/or the credibility and legitimacy of federal commitments. The study of policy

diffusion can speak to the practical effects of this struggle in a powerful way by iden-

tifying how patterns of policy adoption vary as the relationship between the federal

government and the states varies across policies. State and local defiance in policy

areas that are either expressly prohibited by the federal government or where the

government has made unclear legal commitments is unlikely to subside, particularly

in an era of fragmented federalism.

A. Lee Hannah is an assistant professor of political science in the School of Public

and International Affairs at Wright State University. His research focuses on feder-

alism and marijuana policy, the diffusion of public policy, and education policy.

Daniel J. Mallinson is an assistant professor of public policy and administration in

the School of Public Affairs at Penn State Harrisburg. His research focuses on pol-

icy diffusion, elite behavior, pedagogy, and several policy topics.

418 Policy Studies Journal, 46:2

Notes

The authors would like to thank Liam Anderson, Michael Berkman, Charles Crabtree, Christopher Ojeda,

Julianna Pacheco, and Eric Plutzer for thoughtful and helpful feedback on earlier manuscripts. And we

would like to thank the editor and the three anonymous reviewers of this journal for their valuable com-

ments. Replication files available at: https://dataverse.harvard.edu/dataverse/LeeHannah

1. Supreme Court Justice Louis Brandeis, dissent, New State Ice Co. v. Lieberman, 285 U.S. 262 (1932).

2. The concepts of nullification and interposition originated with Thomas Jefferson and James Madi-

son’s Kentucky and Virginia Resolutions of 1798 and 1799, which were in response to the federal pas-

sage of the Alien and Sedition Acts.

3. These terms are adapted from the study of street-level bureaucracy (Brehm & Gates, 1997).

4. The Tenth Amendment and Supreme Court precedent (see New York v. United States 505 U.S. 144 [1992]

and Printz v.United States 521 U.S. 898 [1997]) prohibit the federal government from commandeering

state resources to enforce federal law. Thus, states can decide to not use their own resources in support

of federal law and leave implementation solely to the federal government. Put another way, permitting

behavior that the federal government prohibits does not constitute preemption, as the federal govern-

ment can invest the resources required to enforce its own policy (Garvey, 2012). This is the principle

upon which states are choosing to remove their own resources from the pursuit of the federal War on

Drugs, at least for marijuana (Kamin, 2015). Legal uncertainty arises from the additional steps taken to

promote the marijuana industry through medicinal, and especially recreational, programs.

5. From 1996 to 2014, 11 of the 23 states that adopted medical marijuana policies did so through a direct

initiative. Twenty-three states have access to the popular initiative. Of these 23 initiative states, 12

states passed MMLs and 11 of these states did so by initiative. Of the states that passed an MML in the

legislature, only one state had the initiative as an option (Illinois), a state where the law nominally

grants the option of the initiative but initiatives rarely qualify for the ballot (Bowler & Donovan,

2004).

6. There is a limitation in our analysis that warrants mentioning. The subset of states that have an initia-

tive process available to citizens (n 5 23) faces competing risks of either initiative adoption or legisla- tive adoption. Given the fact that there is likely dependence in these risks, and the relatively small

nature of our dataset, we did not model the competing risks in this article. Future work that pools

within-state marijuana policy (i.e., examines different marijuana policy choices) and among a variety

of defiant innovations will be better positioned to address this problem. The competing risks most

likely affect the estimates for initiative availability and legislative professionalism. It is also likely that

by not addressing the potential for competing risks, that we are using a more conservative test for

those two effects. The effect of initiative availability is ultimately strong enough to achieve statistical

significance in our pooled sample, but legislative professionalism is not. It is important to keep this in

mind when interpreting our results.

7. TEDS provides data on individuals that are admitted to treatment for excessive consumption of mari-

juana/hashish. These data provide the most objective measure of marijuana use for the time period

under study (Pacula, Powell, Heaton, & Sevigny, 2015). The Substance Abuse and Mental Health

Services Administration (SAMHSA) collects marijuana use data in the National Survey on Drug Use

and Health (NSDUH) survey. However, NSDUH has determined that state-level estimates for 2002

and years later are not comparable with data prior to 2002 due to methodological changes (O’Keefe &

Earleywine, 2011). While measures of TEDS include some who are sent to treatment as part of a plea

bargain (and may not be dependent), the data provide “relatively consistent coverage of states in all

years, reducing the problem of sampling over time” (Pacula et al., 2015, p. 14).

8. Both Bush and Obama Administrations are significantly distinguishable from the Clinton administra-

tion. The Bush and Obama administrations are not statistically distinguishable from one another.

9. While the results regarding vertical and horizontal influences on state adoption behavior run counter

to the typical expectations, it does not disprove that regional diffusion occurred. The standard limita-

tions of this type of macrolevel observational analysis apply, in that we cannot isolate the specific

causal pathway of diffusion. That being said, evidence for the observable implications of neighbor-

based learning and the influence of federal signals is lacking.

10. See, for example, H.R. 83, the Mobilizing Against Sanctuary Cities Act, in the 115th Congress.

Hannah/Mallinson: Defiant Innovation 419

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Appendix

Table A1. Variable Descriptions, Summary Statistics, and Sources

Variable Description Mean St. Dev.

Marijuana Seizures in kilogramsa

DEA domestic drug seizures in 10k kilograms. 34.65 16.64

Initiative Availabilityb Dummy 5 1 if the direct initiative is available in the state. 0.40 0.49 Legislative

Professionalismb Squire’s (1992) updated professionalism index—Average

of 1996–2005 values 0.18 0.11

State Citizen Ideologyc Ideology score for state government and citizens based on Berry et al. (1998) revised 1960–2013 citizen ideology series.

48.17 14.99

Evangelical Rated Rates of adherents in evangelical churches per 1,000 population.

167.00 117.78

Fiscal Healthe Fiscal health is calculated as a ratio of ((Total Revenuestate2Total Expendituresstate)/Total Expendituresstate)

0.05 0.12

Marijuana TEDSf Marijuana Treatment Episode Data Set (TEDS) collected annually by state substance abuse agencies. Admissions per 100,000 aged 12 and over.

125.23 69.99

Glaucoma Prevalenceg

Estimated state-by-state prevalence rates of glaucoma aged 40 and over (%).

1.87 0.16

Cancer Incidence Rateh

Age-Adjusted Invasive Cancer Incidence Rates by State. Rates are per 100,000 persons and are age-adjusted to the 2,000 U.S. standard population (SL Interpolation of 1999–2012 estimates)

485.60 43.43

Proportion of Neighbors with MMLsb

Proportion of geographic neighbors with MMLs at start of year.

0.09 0.18

Relative Ideologybc Distance between a state’s ideology (Berry et al., 1998) and the average ideology of previously adopting states (Grossback et al., 2004)

15.52 8.17

Time from first adoptionb Number of years since first law passed in 1996. 8.26 5.43

aConstructed by authors based on data from Drug Enforcement Agency (DEA) – http://www.dea.gov/ resource-center/statistics.shtml. bConstructed by authors. cConstructed by authors based on data from https://rcfording.wordpress.com/state-ideology-data/. dConstructed by authors based on data from the Association of Religion Data Archives. http://www. thearda.com eConstructed by authors from U.S. Census Annual Survey of State and Local Finances - https://www. census.gov/govs/local/. fConstructed by authors from Substance Abuse & Mental Health Data Archive from https://datafiles. samhsa.gov/study/treatment-episode-data-set-admissions-teds-1992-2012-nid13582. gConstructed by authors based on Prevent Blindness America from http://visionproblemsus.org/glau- coma/glaucoma-map.html. hConstructed by authors based on data from Centers for Disease Control and Prevention. https://nccd. cdc.gov/uscs/cancersrankedbystate.aspx.

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