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Cameron Wimpy

Cameron Wimpy

Political Scientist | Research Manager











I am a political scientist with interests in elections, voting, political behavior, political economy, and research methods. I am currently the Research Director in MIT's Elections and Data Science Lab, where I manage research on the scientific study of elections. Previously, I worked as a contractor in Arlington, VA where I worked on projects for government and non-profit clients.


I am also active in political science and have published in journals such as Electoral Studies, Political Science Research and Methods, and Social Science Quarterly along with book chapters in university and software presses. I have conducted qualitative and survey fieldwork in several African and Middle Eastern countries, and I have presented at professional conferences around the world. I have taught courses on African Politics, American Government, Comparative Politics, Foreign Policy, Middle Eastern Politics, Policy Analysis, Research Methods, and several workshops on advanced econometrics, qualitative methods, LaTeX, R, Stata, and other types of software.


I received my Ph.D. (political science) from Texas A&M University and M.A./B.A. (political science) degrees from Arkansas State University.



My Work

What is and What May Never Be

Economic Voting in Developing Democracies

Objective. We propose and test a theory that media freedom determines the extent of economic voting in developing democracies.


Methods. Building on extant work that suggests economic voting takes place in developing democracies much like it does in established democracies (Lewis-Beck and Stegmaier, 2008), we test our theory using a new collection of aggregate data from elections in 22 developing democracies in Africa.


Results. Media freedom rather than political freedom may be a bigger determinant of economic voting in developing democracies. Moreover, the threshold of political development needed for economic voting is lower than previously suggested by the literature.


Conclusion. Economic voting is alive and well in developing democracies—even those with relatively low levels of economic and political development. Read More

Are Media at Work in Your Neighborhood?

The Effects of Media Freedom, Internet Access and Information Spillover on Workers’ Rights

Objectives. Media freedom advocates assume that free and independent news media will serve as a fourth estate, holding government and economic elites accountable, fostering respect for human rights, and thereby making life better for citizens. Does this assumption hold for workers’ rights? Most political economy studies of workers’ rights focus on how profit-seeking behaviors of firms and government shape labor conditions. In this study we focus on how access to information and information flows potentially empower workers to pressure government and firms to improve labor conditions.


Methods. We consider the effects of media freedom on workers’ rights at both the domestic and international levels using spatial models of the effect of media freedom and internet access on workers’ rights across countries and over time.


Results. The findings overall indicate that there is a spatial component associated with the degree of workers’ rights in a given country. Our results suggest that at least in part this is due to the level of media freedom and information flow across international boundaries.


Conclusion. We identify in this study a substantive connection between media freedom and labor rights. Given their implications for political economy, labor rights have been examined from the perspectives of corporate behavior and government action, but there has been little focus on the behavior of workers and their agency. The inclusion of media freedom adds a new dimension to the analysis, which is largely tied to the potential – and arguably expected – social response of workers themselves. The inclusion of media freedom in a neighbor reflects a critical theoretical assumption (i.e. when workers’ rights are impinged upon at home, a viable exit strategy is motivated (or not) by spatially-dependent information about labor conditions elsewhere. Read More

Does Information Lead to Emulation?

Spatial Dependence in Anti-Government Violence

This study examines whether acts of anti-government violence exhibit spatial dependence across state boundaries. In other words, to what extent can acts of anti-government violence in one country be attributed to violence in neighboring countries? Past research, which has largely focused on civil war or large-scale conflict contagion, finds that geo- graphically proximate states are more likely to experience the cross-boundary diffusion of conflict due to action emulation. However, this assumes that actors are fully aware of conflicts occurring in neighboring countries. To address this, the article argues that the proliferation of communication technology increases access to information about events in neighboring states, thereby allowing emulation to occur and subsequently conditioning the potential for violence to spread. It tests this expectation by modeling the effects of a unique spatial connectivity matrix that incorporates both state contiguity and access to communication technology. An analysis of all acts of anti-government violence in 44 African countries from 2000 to 2011 supports the argument. Read More

Administrative Capacity and Health Care in Africa

Path Dependence as a Contextual Variable

Management clearly matters in a wide variety of both national and substantive contexts from public schools in the U.S., the Netherlands, and Denmark to local governments in England and Columbia to national governments in a variety of contexts. The impact of management or different aspects of management, however, varies across these different contexts. O'Toole and Meier (2015; see the comparative public management framework in chapter 1) present a theory of context whereby context is expected to interact with management and condition the results of public management on performance. Ideally, they argue that one would study management across contexts so that context might be a variable that could be used as an interaction effect within a single equation (see p. x, equation 2). We follow that strategy in this chapter by examining the role of administrative capacity on health outcomes in 36 African nations using the path dependence of being a British colony as the contextual variable. Click here to purchase the book.

X Marks the Spot

Unlocking the Treasure of Spatial-X Models

In recent years, political scientists have made extensive use of spatial econometric models to test a wide range of theories. The vast majority of these studies have used spatial lag or spatial autoregressive (“SAR”) models. While these models have generated an impressive set of new findings about important phenomena, they all make a mightily-restrictive common factor assumption. In effect, SAR models impose the assumption that all changes in the dependent variable of spatially-linked cases will have the same spatial effects. Furthermore, the endogenous nature of outcomes in a SAR model impose both global (though units i and k are unconnected, i affects k through shared connections with j) and feedback effects (i affects j, which feeds back to i), which are typically beyond the scope of our theories. In this paper, we make an argument for relaxing these assumptions and testing for the robustness of spatial findings using spatial-X (“SLX”) models. In addition to providing an estimation tech- nique that is closer to one’s theory of spatial processes, we report the results of two sets of simulations that reveal two advantages of the SLX model. First, SLX models do an adequate job of characterizing spatial dependence, even in the case of endogenous SAR processes. Second, the SAR model does a poor job of estimating spatial effects in the presence of spatial heterogeneity, and under other conditions, falsely suggests the presence of global and feedback effects when none are present. Given these results, the flexibility of the SLX specification, and the relative ease with which SLX models can be estimated and interpreted, the SLX is a good starting point for researchers with expectations about spatial effects.

A General Approach to Interpreting Spatial Econometric Models

In recent years, political scientists have made extensive use of spatial econometric models to test a wide range of theories. The vast majority of these studies have used spatial lag or spatial autoregressive (“SAR”) models. While these models have generated an impressive set of new findings about important phenomena, they all make a mightily-restrictive common factor assumption. In effect, SAR models impose the assumption that all changes in the dependent variable of spatially-linked cases will have the same spatial effects. Furthermore, the endogenous nature of outcomes in a SAR model impose both global (though units i and k are unconnected, i affects k through shared connections with j) and feedback effects (i affects j, which feeds back to i), which are typically beyond the scope of our theories. In this paper, we make an argument for relaxing these assumptions and testing for the robustness of spatial findings using spatial-X (“SLX”) models. In addition to providing an estimation tech- nique that is closer to one’s theory of spatial processes, we report the results of two sets of simulations that reveal two advantages of the SLX model. First, SLX models do an adequate job of characterizing spatial dependence, even in the case of endogenous SAR processes. Second, the SAR model does a poor job of estimating spatial effects in the presence of spatial heterogeneity, and under other conditions, falsely suggests the presence of global and feedback effects when none are present. Given these results, the flexibility of the SLX specification, and the relative ease with which SLX models can be estimated and interpreted, the SLX is a good starting point for researchers with expectations about spatial effects.







My Teaching and Tutorials

Introduction to Comparative Politics

This course introduces undergraduates to the basic process of comparing nations in the positivist paradigm. Using a mixture of textbooks and canonical political science articles students will learn the basic strategies of modern comparativists in political science. I place no normative preference on the difference between cross-national and sub-national research although I do present the tradeoffs of each approach. I have also prepared a graduate survey course that is much more comprehensive in scope with some additional emphasis placed on research design.

Middle East Politics

This course introduces students to the political history and modern states in the Middle East and North Africa. Typically I start with post World War I and pepper links to watershed events prior to that time (e.g., events on the Arabian peninsula in the 7th century). The course then moves quite rapidly into the post World War 2 and 1979 eras with deeper examinations of proper nouns as needed. Thematic topics such as Islam and authoritarian politics, democracy, political terror, and state formation are also discussed throughout.

Political Science Research Methods

I teach multiple versions of this course. The first is a basic undergraduate introduction to quantitative social science research. The second is a more advanced version that centers around the linear econometric model and its assumptions. The graduate-level courses range from scalar-based introductions to matrix-based treatments of special problems such as causality, identification, maximum likelihood, and time series. In all cases my focus is on giving students the applied and theoretical tools to carry out positivist research at their own level of sophistication.

Qualitative Research Design

This several-day workshop introduces (typically graduate) students to qualitative research design with a particular focus on complementing quantitative efforts. The workshop is designed for students trained under a positivist paradigm and employs systematic techniques and software to tackle situations in which large-n data are either not available or cost prohibitive. In any case the goal is to get students to understand that depth and can provide useful context that may not be otherwise available to them.

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