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Direct-Democracy Rules: The Effect of Direct Democracy on State Immigration Legislation

Published online by Cambridge University Press:  04 April 2018

Andrea Silva
Andrea Silva*
Affiliation:
University of North Texas
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Abstract

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Information

Type
Symposium: Stepping Back or Stepping Out? Latinos, Immigration, and the 2016 Presidential Election
Information
PS: Political Science & Politics , Volume 51 , Issue 2 , April 2018, pp. 298 - 303
Copyright
Copyright © American Political Science Association 2018 

Immigration was a key topic in the 2016 presidential election. During the 2016 presidential cycle, several states proposed and enacted laws in response to constituent interests and concerns regarding immigration. For instance, the National Conference of State Legislatures (2016) stated that 41 state legislatures introduced 159 pieces of immigration-related legislation; 70 of those laws and 159 resolutions passed in 2016. Given the significant number of laws proposed and enacted during this short period, what prompted legislators to propose and put them into effect?

We have limited knowledge of the extent to which state rules in policy making influence state legislators to propose and enact immigration legislation. Current scholarship finds that economics, politics, and demography affect the timing and passage of state immigration policy, yet there is limited knowledge of the effect of state rules on this policy area. This article addresses the weaknesses in extant research and examines the effect that direct-democracy mechanisms (DDMs) have on the proposal and enactment of immigration legislation. I hypothesize that states with DDMs pass more immigration legislation in the legislature than states without them. After a discussion of my theory, variables, method, and results, I offer thoughts about the implications of this work for the 2016 elections and beyond.

THEORY

Most scholarly efforts to explain the passage of immigration law undervalue or ignore the effects of DDMs. I contend that accounting for these institutional differences is critical. The writings on federalism by Pierson (Reference Pierson1995) and Frey (Reference Frey1994) root the theory of the relationship between DDMs and state immigration legislation. Even though immigration is mostly a federal matter in the United States, having a federal system allows state legislators to make immigration laws in policy areas within their jurisdiction. The smaller scope of state politics also allows constituents greater input on state laws. When interest groups live in direct-democracy states, their power to affect legislation increases (Frey Reference Frey1994; Pierson Reference Pierson1995). Even if they are never used, the threat of DDMs increases the influence of constituents in the state-policy sphere (Lupia and Matsusaka Reference Lupia and Matsusaka2004). Legislators may pass laws to accommodate state interest groups and avoid being excluded from the policy process (Boehmke Reference Boehmke2002; Gerber Reference Gerber1996; Reference Gerber, Bowler, Donovan and Tolbert1998). Therefore, in states with DDMs, legislators have incentives to pass legislation to preempt the appropriation of the state immigration-policy agenda (Gerber Reference Gerber1996; Reference Gerber, Bowler, Donovan and Tolbert1998; Matsusaka and McCarty Reference Matsusaka and McCarty2001). Furthermore, the pressures of reelection also bind state legislators to act (Mayhew Reference Mayhew1974). Therefore, legislators are more likely to pass state immigration legislation to enact laws that represent their constituents’ preferences. Informed by this literature, I hypothesize that states with DDMs, particularly direct-statute initiatives,Footnote 1 are more likely to propose and enact state immigration laws than those without DDMs.

DATA

The scope of this dataset comprised all state legislation referencing immigrants from 2004 to 2014, beginning at the height of the media attention on state immigration legislation in the new millennium. I included all 50 states, providing a total of 1,750 observations. My dependent variable was the total number of state immigration laws that reached the enrolled stage by each state legislature in one year.Footnote 2 I included legislation that affects undocumented immigrants as well as legal permanent residents and those with non-immigrant temporary visas. Specifically, I included laws that have an impact on a non-citizen’s ability to access welfare, employment, or healthcare benefits and state licenses. I included the law in the year it passed the legislature; therefore, this dataset contains legislation that was not signed into law. I was interested only in the action of state legislatures, not state executives. I built on Monogan’s (2013) National Council of State Legislature dataset by adding three years (i.e., 2012–2014) to make it current and one previous year to make the dataset comprehensive. The variable of interest in this study was the presence of DDMs and it was dichotomous: 1 represents states that allow direct-statute initiatives and 0 represents states that do not allow them.Footnote 3

CONTROL VARIABLES

In addition to DDMs, my analyses controlled for the effects of variables that measure economic, racial, and political context. I included economic controls such as the unemployment rate and the percentage gross product of agriculture and construction (Borjas Reference Borjas1990; Massey, Durand, and Malone Reference Massey, Durand and Malone2003; Rothman and Espenshade Reference Rothman and Espenshade1992). I included political explanations such as party majority in the state legislature and party identification of the state executive (Amenta and Carruthers Reference Amenta and Carruthers1988; Dolowitz and Marsh Reference Dolowitz and Marsh1996). I also controlled for cultural threat using the percentage of foreign-born and Latino residents in each state (Gulasekaram Reference Gulasekaram2011; Ngai Reference Ngai2004; Sampaio Reference Sampaio2015; Waslin 2011). Finally, I accounted for state legislative institutions and state civil society. I measured legislative professionalization using a categorical variable based on the extent to which legislatures have full-time, well-paid legislators with staff (Boushey and Luedtke Reference Boushey and Luedtke2011; National Conference of State Legislators 2017). I also included a rough measure of the presence of state civil society using a list of 501 (c) organizations with “immigra” in the names categorized by the state of headquarters and the year they were granted tax-exempt status (Internal Revenue Service 2016).Footnote 4 The coding of these variables is available in the online appendix.

More specifically, state legislatures in DDM states pass more immigration laws than states without DDMs (i.e., the state legislatures in DDM states pass 1.3 more state immigration laws per year). Most important, this model shows that DDMs affect legislative behavior on state immigration legislation even when controlling for the effects of other variables.

METHODS

First, the statistical model that best fits this investigation is a cross-sectional time-series model. Panel data included as many cases as possible and allowed for generalizations across states. Second, because state immigration control is a process, the model controlled for the passage of time. Third, because I included information across time and state, the model better controlled the effects of missing or unobserved variables.Footnote 5 Fourth, because this model was a linear regression, it can be interpreted as such. This article presents results of this model; the full model is in table 1 of the online appendix, which also includes a detailed description of variable coding and more detailed analyses. The discussion of the results answers my research question by addressing the relationship between the passage of state immigration laws and state legislative rules. The results obtained from a chi-squared group comparison, a t-test, and general descriptive statistics are encouraging.

RESULTS

To what extent do DDMs increase the likelihood that states will pass immigration legislation? Results from the Prais-Winsten Generalized Least-Squares model shown in table 1 (in the online appendix) address this question and reveal that, as expected, DDMs affect the passage of state immigration law. More specifically, state legislatures in DDM states pass more immigration laws than states without DDMs (i.e., the state legislatures in DDM states pass 1.3 more state immigration laws per year).Footnote 6 Most important, this model shows that DDMs affect legislative behavior on state immigration legislation even when controlling for the effects of other variables. Furthermore, this effect is present even when controlling for the passage of immigration legislation in the previous year. To further investigate the relationship between state immigration laws and DDMs, I include a comparison of the mean total immigration law in states with and without direct-statute initiatives and a chi-square bar plot of the observed and expected proportions of laws passed in DDM states over time. I also include a t-test with equal variance of the number of laws passed by DDM and non-DDM states and a graph of the total number of state laws passed by each group over time and in each state.Footnote 7

The results of a comparison of the mean total immigration law in states with and without direct-statute initiatives in figure 1 show that in states with DDMs, legislators pass more immigration laws, on average, compared to states without DDMs. Although there may be overlap in the confidence intervals, the graph shows that DDM states pass more immigration legislation than non-DDM states. Figure 2 is a chi-square goodness-of-fit bar plot of the observed and expected proportions of laws passed in DDM states over time. The error bars indicate 95% confidence intervals for each observed proportion. Although many of the observed proportions are within the confidence intervals, the laws passed in 2005 and 2007 were significantly different from their expected proportion.

Figure 1

Mean Total Immigration Laws in States with and without Direct-Statute Initiatives

Figure 2

Bar Plot of Proportions between Observed Laws Passed in Direct-Democracy States and the Expected Number of Laws

Note: Error bars indicate 95% confidence intervals for each observed proportion.

Results from a two-sample t-test with equal variances, graphed in figure 3, further support my hypothesis that legislatures in states with DDMs will pass more immigration laws. The corresponding t-statistic is -5.978 with 548 degrees of freedom and p-value < 0.001 (two-tailed test). This t-test shows that the difference of means in total laws passed between DDM and non-DDM states is different from zero. This means that there is a significant difference between the number of laws passed in states with and without DDMs.

Figure 3

Two-Sample T-Test with Equal Variances

We also see this difference reviewing the raw count of state immigration laws passed across time and states in the graphs presented in figures 4 and 5.

Figure 4

Total State Laws Passed in States with and without Direct-Statute Initiatives

Figure 5

Total State Immigration Laws Passed in States with and without Direct-Statute Initiatives

Using panel data consisting of 50 states over 10 years, I found a positive correlation between the presence of DDMs and the passage of state immigration laws. Legislators in those states have had to contend with powerful non-governmental interests when attempting to make or change state immigration legislation.

DISCUSSION AND CONCLUSION

The purpose of this study was to examine how DDMs affect legislative behavior on immigration legislation. I demonstrated a relationship between states that allow their citizens to introduce legislation and an increase in the passage of immigration laws in the legislature. Whereas blunter tools show this relationship with large confidence intervals, using a cross-sectional time-series analysis provided a more precise understanding of the importance of DDMs. This research is a contribution to the study of state immigration legislation—and state legislatures in general—for three reasons. First, much of the literature on state initiatives and referendums is limited to how it affects citizen behavior, when it is used, and how it fits into our representative system (Bowler and Donovan Reference Bowler and Donovan2002). This is one of the few empirical investigations that analyze the effect of DDMs on the behavior of legislators.

Second—and building on the first contribution of this study—examining the relationship among state immigration policy, legislators, and direct democracy has significant ramifications for the type of legislation created and the type of democracy we experience at the state level. If, as Gerber (Reference Gerber1996; Reference Gerber, Bowler, Donovan and Tolbert1998) argued, legislators write and pass laws to assuage the threat of initiative or referendum, then state immigration legislation may be less of a creation of thoughtful policy and more of a legislative reaction to the threat of direct action. Furthermore, legislation may be passed to appease politically extreme groups. This work questions the extent to which we are at the whims of the mischiefs of factions and governed by a tyranny of the minority (Bishin Reference Bishin2009; Madison 1787). The threat by state groups to enter the initiative process may lead legislators to overlook the many and placate the few.

The third contribution of this study is its ability to increase our understanding of how controversial issues (e.g., immigration) are legislated differently in states according to the presence of DDMs. The next step for this project is the creation of a coding rubric to typologize state immigration laws into permissive or restrictive legislation.

In the context of the current Trump administration, DDMs can be a formidable tool to pressure legislators to ignore national discussions of immigration policy and support the policy preferences of state interests. A recent Gallup poll found that 45% of Americans think the economy has improved with immigrants and that 57% believe that immigrants benefit our culture (Gallup 2017). Moreover, 56% of Americans support a path to citizenship for undocumented immigrants (Gallup 2015). Although there is evidence of national opposition to Trump’s restrictive immigration approach, opinions at the state level vary widely. For example, a recent UT–Austin/Texas Tribune survey found that 58% of respondents somewhat or strongly supported requiring local law enforcement to cooperate with federal immigration authorities (Ramsey Reference Ramsey2017). Conversely, a 2012 poll found that 67% of California voters believe undocumented immigrants should remain in the United States and become citizens if they meet certain requirements (DiCamillo and Field 2012). Considering the federal government’s inability to pass immigration reform in the past 20 years, the states will continue to be key actors in the creation of immigration policy (Provine et al. Reference Provine, Varsanyi, Lewis and Decker2016). For better or worse, states are laboratories of immigration legislation, currently creating an uneven patchwork of immigration policy that dictates the lives of one of our most vulnerable populations: non-citizens.

SUPPLEMENTARY MATERIAL

To view supplementary material for this article, please visit https://doi.org/10.1017/S1049096517002396

Footnotes

1. A direct-statute initiative is one that a state adopts via the ballot-initiative process, which is initiated by the citizenry.

2. Enrolled legislation consists of policies passed in the legislative chamber that are awaiting an executive decision.

3. The 14 states with direct-statute initiatives enacted them before 1980 (Initiative and Referendum Institute 2017).

4. This measure of state civil society is an admittedly blunt tool. For this investigation, it conservatively measured the presence of state groups interested in immigration.

5. Specifically, the model assumes a panel-specific AR1 autocorrelation structure and panel-level heteroskedastic errors (Johnson Reference Johnson2004).

6. Holding all variables constant at their means.

7. Please contact the author for more information about the analyses.

References

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Figure 0

Figure 1Mean Total Immigration Laws in States with and without Direct-Statute Initiatives

Figure 1

Figure 2Bar Plot of Proportions between Observed Laws Passed in Direct-Democracy States and the Expected Number of LawsNote: Error bars indicate 95% confidence intervals for each observed proportion.

Figure 2

Figure 3Two-Sample T-Test with Equal Variances

Figure 3

Figure 4Total State Laws Passed in States with and without Direct-Statute Initiatives

Figure 4

Figure 5Total State Immigration Laws Passed in States with and without Direct-Statute Initiatives

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