Redrawing the Map: How Jowei Chen is Measuring Partisan Gerrymandering

post written by Solmaz Spence

“Gerrymandering”— when legislative maps are drawn to the advantage of one party over the other during redistricting—received its name in 1812, when Massachusetts Governor Elbridge Gerry signed off on a misshapen district that was said to resemble a salamander, which a newspaper dubbed a “gerrymander.”

But although the idea of gerrymandering has been around for a while, proving that a state’s legislature has deliberately skewed district lines to benefit one political party remains challenging.

The problem is that the mere presence of partisan bias in a district map tells us very little about the intentions of those drawing the districts. Factors such as racial segregation, housing and labor markets, and transportation infrastructure can lead to areas where one party’s supporters are more geographically clustered than those of the other party. When this happens, the party with a more concentrated support base achieves a smaller seat share because it racks up large numbers of “surplus” votes in the districts it wins, while falling just short of the winning threshold in many of the districts it loses.

Further, there are many benign reasons that legislatures may seek to redistrict voters—for example, to keep communities of interest together and facilitate the representation of minorities—that may have the unintended consequence of adding a partisan spin to the map.

The research of political scientists Jowei Chen and Jonathan Rodden is helping to differentiate cases of deliberate partisan gerrymandering from other redistricting efforts. Chen, Faculty Associate at the University of Michigan’s Center for Political Studies, and Rodden, Professor of Political Science at Stanford University, have devised a computer algorithm that ignores all partisan and racial considerations when drawing districts, and instead creates thousands of alternative district maps based on traditional districting goals, such as equalizing population, maximizing geographic compactness, and preserving county and municipal boundaries. These simulated maps are then compared against the district map that has been called into question to assess whether partisan goals motivated the legislature to deviate from traditional districting criteria.

We first wrote about Chen and Rodden’s work back in December 2016, detailing a 2015 paper in the Election Law Journal, which used the controversial 2012 Florida Congressional map to show how their approach can demonstrate and unconstitutional partisan gerrymander. Now, this work is back in the spotlight: Chen’s latest research has been cited in several cases of alleged gerrymandering that are currently working through the courts in Pennsylvania, North Carolina, Wisconsin and Maryland.

In January, Chen’s testimony as an expert witness was cited when the Pennsylvania Supreme Court threw out the state’s U.S. House of Representatives district map. In its opinion, the court said the Pennsylvania map unconstitutionally put partisan interests above other line-drawing criteria, such as eliminating municipal and county divisions.

The Pennsylvania districts in question were drawn by the Republican-controlled General Assembly in 2011. Immediately, the shape of the districts was an indicator that at least one traditional criterion of districting—compactness—had been overlooked.

Though few states define exactly what compactness means, it is generally taken to mean that all the voters within a district should live near one another, and that the boundaries of the district should be create a regular shape, rather than the sprawling polygon with donut holes or tentacles that characterized the Pennsylvania district map.

In particular, District 7—said to resemble Goofy kicking Donald Duck—had been called into question. “It is difficult to imagine how a district as roschachian and sprawling, which is contiguous in two locations only by virtue of a medical facility and a seafood/steakhouse, respectively, might plausibly be referred to as compact,” the court wrote.

Although there are more registered Democrats than Republicans in Pennsylvania, Democrats hold only five of the state’s 18 congressional districts. In the 2016 election, Democrats won each of their five House seats with an average of 75 percent of the vote while Republicans’ margin of victory was an average of 62 percent across their 13 districts. This is an indicator of “packing,” a gerrymandering practice that concentrates like-minded voters into as few districts as possible to deny them representation across districts.

Chen’s expert report assessed the district map and carried out simulations to generate alternative districting plans that strictly followed non-partisan, traditional districting criteria, and then measured the extent to which the current district map deviates from these simulated plans.

To measure the partisanship of the computer-simulated plans, Chen overlaid actual Pennsylvania election results from the past ten years onto the simulated districts, and calculated the number of districts that would have been won by Democrats and Republicans under each plan (see Figure 1).

The districting simulation process used precisely the same Census geographies and population data that the General Assembly used in creating congressional districts. In this way, the simulations were able to account for any geographical clustering of voters; if the population patterns of Pennsylvania voters naturally favor one party over the other, the simulated plans would capture that inherent bias.

Generally, the simulations created seven to ten Republican districts; not one of the 500 simulated districting plans created 13 Republican districts, as exists under the Republican-drawn district map. Thus, the map represented an extreme statistical outlier, a strong indication that the enacted plan was drawn with an overriding partisan intent to favor that political party. This led Chen to conclude “with overwhelmingly high statistical certainty that the enacted plan created a pro-Republican partisan outcome that would never have been possible under a districting process adhering to non-partisan traditional criteria.”

A map showing redistricting simulation in Pennsylvania

This table compares the simulated plans to the 2011 Pennsylvania district map with respect to these various districting criteria.

Following its ruling, on February 20 the Pennsylvania Supreme Court released a new congressional district map that has been described in a Washington Post analysis as “much more compact”. In response, the state’s Republican leadership announced plans to challenge the new map in court.

 

 

Understanding the Changing American Electorate

developed by Catherine Allen-West

The American National Election Studies (ANES) has surveyed American citizens before and after every presidential election since 1948.  The survey provides the public with a rigorous, non-partisan scientific basis for studying change over time in American politics.

The interactive graphs below illustrate the changing American electorate and some of the factors that may motivate voters’ choices at the ballot box. Mouse over the graphs for more detail.

Source: ANES Time Series Cumulative File and the 2016 ANES Time Series dataset. ANES offers 62 datasets, all free and available to the public, here.

 

Top 10 Most-Viewed CPS Blog Posts in 2017

post developed by Catherine Allen-West

Since its establishment in 2013, a total of 137 posts have appeared on the Center for Political Studies (CPS) Blog. As we approach the new year, we look back at 2017’s most-viewed posts. Listed below are the posts that you, our dear readers, found most interesting on the blog this year. 


What makes a political issue a moral issue? by Katie Brown and Timothy Ryan (2014)

There are political issues and then there are moral political issues. Often cited examples of the latter include abortion and same sex marriage. But what makes a political issue moral?An extensive literature already asserts a moral vs. not moral issue distinction. Yet, there is no consensus in how to distinguish between moral and non-moral political issues. Further, trying to sort issues into these categories proves challenging.

 


 

The Spread of Mass Surveillance, 1995 to Present by Nadiya Kostyuk and Muzammil M. Hussain (2017)

By closely investigating all known cases of state-backed cross-sector surveillance collaborations, our findings demonstrate that the deployment of mass surveillance systems by states has been globally increasing throughout the last twenty years. More importantly, from 2006-2010 to present, states have uniformly doubled their surveillance investments compared with the previous decade. 

 


 

Why do Black Americans overwhelmingly vote Democrat? by Vincent Hutchings, Hakeem Jefferson and Katie Brown (2014)

In 2012, Barack Obama received 93% of the African American vote but just 39% of the White vote. This 55% disparity is bigger than vote gaps by education level (4%), gender (10%), age (16%), income (16%), and religion (28%). And this wasn’t about just the 2012 or 2008 elections, notable for the first appearance of a major ticket African American candidate, Barack Obama. Democratic candidates typically receive 85-95% of the Black vote in the United States. Why the near unanimity among Black voters?

 


 

Measuring Political Polarization by Katie Brown and Shanto Iyengar (2014)

Both parties moving toward ideological poles has resulted in policy gridlock (see: government shutdowndebt ceiling negotiations). But does this polarization extend to the public in general? To answer this question, Iyengar measured individual resentment with both explicit and implicit measures.

 


 

Is policy driven by the rich, or does government respond to all? by Catherine Allen-West (2016)

The enthusiasm for both Trump and Sanders’ messages about the influence of money in politics brings up an important question: Is policy driven by the rich, or does government respond to all? Political scientists have long been interested in identifying to what degree wealth drives policy, but not all agree on it’s impact.

 

 


 

Exploring the Tone of the 2016 Election by U-M undergraduate students Megan Bayagich, Laura Cohen, Lauren Farfel, Andrew Krowitz, Emily Kuchman, Sarah Lindenberg, Natalie Sochacki, and Hannah Suh, and their professor Stuart Soroka (2017)

Political economists often theorize about relationships between politics and macroeconomics in the developing world; specifically, which political or social structures promote economic growth, or wealth, or economic openness, and conversely, how those economic outcomes affect politics. Answering these questions often requires some reference to macroeconomic statistics. However, recent work has questioned these data’s accuracy and objectivity. An under-explored aspect of these data’s limitations is their instability over time.

 


 

Crime in Sweden: What the Data Tell Us by Christopher Fariss and Kristine Eck (2017)

In a recent piece in the Washington Post, we addressed some common misconceptions about what the Swedish crime data can and cannot tell us. However, questions about the data persist. These questions are varied but are related to two core issues: (1) what kind of data policy makers need to inform their decisions and (2) what claims can be supported by the existing data.

 


 

Moral conviction stymies political compromise by Katie Brown and Timothy Ryan (2014)

Ryan’s overarching hypothesis boils non-compromise down to morals: a moral mindset orients citizens to oppose political compromises and punish compromising politicians. There are all kinds of issues for which some citizens seem resistant to compromises: tax reform, same-sex marriage, collective bargaining, etc. But who is resistant? Ryan shows that part of the answer has to do with who sees these issues through a moral lens.

 


 

Does the order of names on a ballot affect vote choice? by Katie Brown and Josh Pasek (2013)

Ballots list all candidates officially running for a given office so that voters can easily choose between them. But could the ordering of candidate names on a ballot change some voters’ choices? 

 

 

 


 

Inside the American Electorate: The 2016 ANES Time Series Study by Catherine Allen-West, Megan Bayagich and Ted Brader (2017)

Since 1948, the ANES- a collaborative project between the University of Michigan and Stanford University- has conducted benchmark election surveys on voting, public opinion, and political participation. This year’s polarizing election warranted especially interesting responses. 

 

Using Twitter to Observe Election Incidents in the United States

Post developed by Catherine Allen-West

Election forensics is the field devoted to using statistical methods to determine whether the results of an election accurately reflect the intentions of the electors. Problems in elections that are not due to fraud may stem from legal or administrative decisions. Some examples of concerns that may distort turnout or vote choice data are long wait times, crowded polling place conditions, bad ballot design and location of polling stations relative to population.

A key component of democratic elections is the actual, and perceived, legitimacy of the process. Individuals’ observations about how elections proceed can provide valuable, on-the-ground insight into any flaws in the administration of the election. In some countries there are robust systems for recording citizen complaints, but not in the United States. So, a team* of University of Michigan researchers led by Walter Mebane used Twitter to extract observations of election incidents by individuals across the United States throughout the 2016 election, including primaries, caucuses and the general election. Through their observations, the team shows how reported phenomena like waiting in long lines or having difficulties actually casting a vote are associated with state-level election procedures and demographic variables.

The information gathered is the beginnings of what Mebane is calling the “Twitter Election Observatory.”  The researchers collected tweets falling within a ten-day window around each primary/caucus election day and collected tweets continually during the October 1- November 9, 2016 lead up to the general election.

Mebane and his team then coded all of the tweets to extract the “incident observations” — tweets that mentioned an issue or complaint that an individual may have experienced when casting their vote. From the Twitter data, the researchers found that incidents occurred in every state during the general election period. Among the tweets that had recorded location information, the highest count of tweet observations occurred in California, Texas, Florida and New York and the smallest amount in Wyoming, North Dakota, South Dakota and Montana.

Additionally, the researchers calculated the rate of incidents relative to the population of the each state. On a per capita basis, the District of Columbia stands out with the highest rate of incident observation followed by Nevada and North Carolina with Wyoming as the lowest.

Every indication is that Twitter can be used to develop data about individuals’ observations of how American elections are conducted, data that cover the entire country with extensive and intensive local detail. Mebane notes that the frequency, and likely the diversity, of observations may vary depending on how many people care and want to participate in, observe and comment on an election. Ultimately, Mebane would like to dig further into the geolocation information of these tweets to try and pinpoint any incidents with exact polling locations.

*University of Michigan team includes: Walter R. Mebane, Jr., Alejandro Pineda, Logan Woods, Joseph Klaver, Patrick Wu and Blake Miller.

Link to full paper presented at 2017 meeting of the American Association for Political Science.

Donald Kinder Elected to the National Academy of Sciences

Post by Theresa Frasca

Earlier this year, the National Academy of Sciences (NAS) announced the election of the Institute for Social Research’s Donald Kinder, the only University of Michigan professor to be named in 2017 and the 28th professor to be named in U-M’s history. Established by Congress in 1863, the private, non-profit NAS promotes science through its consortium of more than 2,000 distinguished scholars, of which nearly 500 have won Nobel Prizes. NAS serves as  an independent advising entity to the government, and provides recommendations and guidance on matters of scientific or technological importance to the nation.

Photo of Donald Kinder

Donald Kinder

“It is a thrilling surprise to be elected to the National Academy of Sciences,” says Kinder. “I was very pleased when I received the call about my election, and I look forward to working with members on a variety of new projects.” As a member, Kinder will attend NAS membership meetings and help review papers for the multidisciplinary journal, Proceedings of the National Academy of Sciences, as well as provide his expertise on subject-related projects or efforts.

Kinder, a Research Professor at ISR’s Center for Political Studies, is notable for his research on prejudice and how it impacts contemporary American politics. “Most of my work over the last 20 years has focused on racial politics in the United States, as I’ve tried to understand the foundations of public opinion and the role that race plays in elections,” says Kinder. “This area of study has been a long-standing interest of mine that actually started in graduate school. I was in a specific time in a specific place at UCLA in the early 1970s and I became interested in how white suburban voters were affected by the racial identity of one of the mayoral candidates.”

More recently, Kinder’s work has revolved around ideology in the study of American politics and his newest book, Neither Liberal Nor Conservative, debuted in May. “This book is about American politics and how American elites seem highly ideological yet most American citizens are not,” says Kinder. “This is a condition that has been present over the past 50-60 years. In some ways, it’s a surprising argument to make because people who study politics and think about politics usually make the presumption that ordinary people think deeply about politics, too. But the reality is that regular citizens have better things to do with their lives and, as a consequence of that, their thinking is more casual and less organized and certainly less ideological.” The book, written with Louisiana State University professor, and U-M grad, Nathan Kalmoe has received several long-form journalism reviews including in VOX and Washington Monthly.

As Kinder reflects on both his current work and his new election to NAS, he says, “I’ve been at U-M for going on 40 years and what I love about the place is the endless parade of super smart graduate students who come through. I think of my election to the National Academy of Sciences as a reflection of this remarkable place, my great colleagues and wonderful students.”

The Politics of Latinidad

Post developed by Mara Ostfeld and Catherine Allen-West

The effectiveness of America’s system of democratic representation, in practice, turns on broad participation. Yet only about 60 percent of voting eligible Americans cast their vote in presidential elections. This number is nearly cut in half in off-year elections (about 36 percent), and participation in local elections is even lower. This lack of electoral engagement does not fall equally across racial and ethnic subgroups. Latinos, for one, are particularly underrepresented at polling booths across the country. In 2016, eligible Latino voters were about 20 percentage points less likely to vote than their White counterparts, and about 13 percentage points less likely to vote than their Black counterparts.

This fall, a group of 24 University of Michigan undergraduate students sought to explore this disparity and pinpoint what, if anything, works to increase Latino political participation. In the class, entitled The Politics of Latinidad, CPS Faculty Associate and U-M Political Science Professor Mara Ostfeld taught her students how to measure public opinion and challenged them to analyze the factors that affect Latino political participation.

Today, more than 50,000 Latinos live in Detroit and a majority of them reside in City Council District 6 in Southwest Detroit which is precisely where this course focused. The students began by studying the history of Latinos in Southeast Michigan and exploring how Latinos played critical roles in the city’s development dating back to before World War I. They analyzed broad trends in Latino public opinion, and considered how and why these patterns might be similar or different in Detroit. Students then designed their own pre-election polls to take into the field.

In order to understand what affects voter turnout, students surveyed over 300 residents of Southwest Detroit to measure the issues that were most important to them.

Photo of U-M students \

Students pictured here: Storm Boehlke, Mohamad Zawahra, Alex Tabet , Hannel So, Sion Lee.

The results illustrate some powerful patterns. Among the issues that the residents found most important, immigration and crime stood out. Forty-nine and 45 percent of Latinos listed immigration and crime, respectively, as issues of particular concern, with only 31 percent of residents saying that they felt safe in their own home.

Latinos in Southwest Detroit feel extremely high levels of discrimination.  Seventy percent of Latinos surveyed said they felt Latinos face “a great deal” of discrimination. This significantly exceeds the roughly half of Latinos nationwide who say they have experienced discrimination.

Student Alex Garcia visits residents in Detroit.

Local issues were also at the forefront of residents’ minds. Latinos had mixed views on the city’s use of blight tickets to combat housing code violations, with one third of respondents supporting them and one third opposing them.

As local organizations, like Michigan United, continue trying to get a paid sick leave initiative on the ballot in 2018, they can expect strong support among Latinos in Southwest Detroit. About two out of every three Latinos in the area indicated they would be more likely to support a candidate who supports the paid sick leave requirement.

The students then followed up with the residents a month later to see if they planned to vote in the upcoming city council election. At this point, the students implemented some interventions that have been used to increase political participation like, evoking emotions that have been shown to have a mobilizing effect, framing voting as an important social norm, and speaking with voters immediately before an election. With the election now over, students are back in the classroom analyzing the effectiveness of these interventions and will use their first-hand experience to better understand public opinion and political participation.

 

 

Empathy Trumps Fear? The Role of Group Empathy Theory in Shaping U.S. Foreign Policy

Post developed by Catherine Allen-West

There is a long, documented history of large opinion gaps along racial/ethnic lines regarding U.S. military intervention and humanitarian assistance. For example, some research suggests that since minorities are most likely to bear the human costs of war, African Americans and Latinos might be more strongly opposed to foreign intervention. Additionally, research conducted during the Iraq war found that the majority of African Americans didn’t support the war effort because they believed that they would be the ones called upon to do the “fighting and dying” and that the war would tie up resources typically used for domestic social welfare programs, programs upon which the group depends.

One obvious explanation for these opinion gaps is simple group interest. Americans are more likely to intervene to protect the lives and human rights of victims of humanitarian crises or genocides when the victims are “like us” and this narrow racial or ethnic group interest may be what drives racial/ethnic differences in support for foreign intervention or immigration policy in the U.S. This is important because public support for military and humanitarian interventions is crucial to not only the quantity of aid but also its quality and effectiveness.

But this simple in-group, material interest explanation doesn’t always hold up empirically. African Americans were more protective of the rights of Arab Americans after 9/11, even though they perceived themselves to be at higher risk from terrorism.

In a new paper, presented at the 2017 APSA annual meeting, Cigdem V. Sirin, Nicholas A. Valentino, and José D. Villalobos examine variations in political attitudes across three main racial/ethnic groups — Anglos, African Americans, and Latinos — regarding humanitarian emergencies abroad. The researchers tested these differences using their recently developed “Group Empathy Theory” which states that “empathy felt by members of one group for another can improve group-based political attitudes and behavior even in the face of material and security concerns.” Essentially, the researchers predict that a domestic minority group can empathize with an international group experiencing hardship, even when the conflict doesn’t involve the domestic group at all and when extending help oversees is costly.

The researchers tested their theory with a national survey experiment that assessed support for pre-existing foreign policy attitudes about the U.S. responsibility to protect, foreign aid, the U.S. response to the Syrian civil war, as well as the Muslim Ban proposed by Donald J. Trump.

First, they measured levels of group empathy and found that African Americans and Latinos both display significantly higher levels of general group empathy and support for foreign groups in need.

Next, to measure opinions about the U.S. ability to protect, they provided participants with a pair of statements about the role the U.S. should plan in international politics. The first statement read: “As the leader of the world, the U.S. has a responsibility to help people from other countries in need, especially in cases of war and natural disasters.” The second statement was the opposite — denouncing such responsibility to protect. Their results show that African Americans and Latinos are likely to attribute the U.S. higher responsibility to protect people of other countries in need as compared to Anglos. Furthermore, when asked about their opinion on the amount of foreign aid allocated to help countries in need, Latinos and African Americans were more strongly in favor of increasing foreign aid and accepting Syrian refugees than were Anglos.

The researchers further examined potential group-based difference in policy attitudes regarding Trump’s controversial “Muslim ban” which called for a total and complete shutdown of Muslims entering the United States. Again, both Latinos and African Americans exhibited significantly higher opposition than Anglos to the exclusionary policy targeting a specific group solely based on that group’s religion.

Further analyses also supported the researchers’ claims that group empathy is a significant mediator of these racial gaps in support for humanitarian aid and military intervention on behalf of oppressed groups oversees.

This research brings into focus some of the dynamics that shape public opinion of foreign policy. Given the role of the public in steering U.S. leadership decisions, especially as the current administration seeks to implement deep cuts to foreign aid, investigating the role that group empathy plays in public responses to humanitarian emergencies has important broader implications, particularly concerning U.S. foreign policy and national security.

Attitudes Toward Gender Roles Shape Support for Family Leave Policies

Post written by Solmaz Spence

In almost half of two-parent households in the United States, both parents work full-time. Yet when a baby is born, it is still new moms who take the most time off work. On average, new mothers take 11 weeks off work while new dads take just one week, according to a 2016 survey carried out by the Pew Research Center.

In part, that is because many new fathers in the U.S. don’t have access to paid paternity leave. Paid maternity leave is rare, too: in fact, the U.S. is the only developed nation that does not provide a national paid family leave program to new parents.


Only three states (California, New Jersey, and Rhode Island) have their own paid parental leave policies, as do some companies. In Silicon Valley, tech giants like Facebook, Google and Twitter offer gender-neutral paid parental leave policies that can be taken by new moms, dads, and adoptive parents. But that’s not the norm. According to the Society for Human Resource Management’s 2016 Employee Benefits research report, only 18 percent of U.S. organizations offer paid maternity leave, 12 percent provide paid paternity leave, and 17 percent have a paid parental leave plan that can be taken by either parent.

More commonly, birth moms with short-term disability insurance receive some pay for six to eight weeks following childbirth. If new moms want to take more time, or if dads, adoptive parents, or moms who didn’t give birth themselves want time off to bond with a new baby, those eligible under the Family and Medical Leave Act can take unpaid leave for up to 12 weeks.


But even if new fathers had access to parental leave programs, they might not take advantage of them. A survey by Deloitte found that 36 percent of men would not take advantage of their paid parental leave benefits because they worried it might jeopardize their position at work. And parental leave programs that offer more benefits to moms than to dads only reinforce the stereotype of the female caregiver and male breadwinner.

How is support for parental leave policies structured by attitudes about traditional gender roles? To assess this relationship, a team of researchers including Stuart Soroka, faculty associate at the University of Michigan’s Center for Political Studies, along with Allison Harell, Shanto Iyengar and Valérie Lapointe, surveyed 3600 people across Canada, the United States, and the United Kingdom. The results of the survey* were recently published as a chapter in the book, Mothers and Others: The Role of Parenthood in Politics.

The authors came to the study with mixed expectations for how gender role ideologies would influence support for parental leave. On the one hand, because parental leave programs give working mothers time at home after the birth of a child, they can help new moms balance work and motherhood—a struggle that is at the heart of traditional gender role ideology.

On the other hand, women must be employed to access maternity leave benefits, and the central goal of these policies is for women to return to their careers—facts that could conflict with conservative gender role attitudes.

Expanding parental leave to new fathers also has the potential to make men more involved in childcare, women more engaged in their careers, and workplaces friendlier for parents of all kinds. Thus, those holding more traditional views might be less supportive of parental leave policies that can be applied to male recipients.

This study assessed gender role ideology by asking participants how strongly they agreed or disagreed with four statements related to women’s roles in the home and as mothers:

  1. A woman’s place is in the home, not in the office or shop.
  2. A mother who carries out her full family responsibilities doesn’t have time for outside employment.
  3. The employment of mothers leads to more juvenile delinquency.
  4. Women are much happier if they stay at home and take care of their children.

In general, respondents rejected the view that a woman’s employment is detrimental to her perceived duty at home—but there were clear variations in responses. Largely in line with expectations, demographic factors such as being female, having a university education, and being employed were associated with more liberal views; those who are married, have children, and are older had more conservative views.

Next, the researchers investigated whether citizens are more or less generous toward parental leave takers based upon their gender role attitudes as well as the gender stereotypicality of the leave takers.

The researchers presented survey participants with fictional stories that described the situation of several potential parental leave takers: a married female, a single female, a married male, a single male. In each case, respondents were told the amount of leave to which the new parent is entitled in their country, and were asked how much he or she thinks the recipient should receive in monetary benefits.

Across all respondents, there was strong support for more stereotypical leave takers, with respondents opting to give the female parents in the fictional situations about $175 more in benefits than the male parents. The marital status of the leave taker was also important, with married leave takers receiving about $70 more than single parents—despite the fact that one might assume that single parents would be more in need of state support. There thus was a general tendency to enforce gender norms in terms of who benefits from family leave policies.

GRAPH: Support for Parental Leave by Traditional Gender Ideology

This figure shows the relationship between gender role attitudes (plotted on the x axis), and cash support for parental leave policy (show on the y-axis). Across all respondents in the U.S., UK and Canada, support is strongest for more stereotypical leave takers (married females), and least generous for single men.

That said, the researchers found that those who hold more conservative gender role attitudes in the UK and U.S. tended to be less generous toward leave takers overall. Among US survey participants in particular, those with the most conservative gender role attitudes reported giving the fictional recipients about $124 less than respondents who held more progressive attitudes. This was after controlling for the characteristics of the fictional leave takers, and also for the ideological orientation of the respondent with respect to government benefits.

Moreover, those with more traditional gender norms tended to be particularly punitive to non-stereotypical leave takers. (This is clear in the figure above.) The most conservative respondents reported giving single male recipients about $330 less than they would give to married women leave takers. In contrast, for respondents with more progressive gender role ideology, the difference in benefits between married women and single men was about $230.

These results highlight a good deal of complexity in the structure of support for parental leave policy. It is not necessarily the case that women are more supportive of parental leave policy than men, for instance. Although women are more likely to reject traditional gender roles, women who are married with children tend to believe more strongly in the gendered division of parenthood, and thus, are less willing to extend parental leave benefits to men.  In the U.S., and also Canada and the UK, support for parental leave policy reflects a set of complex and often counteracting ideas about gender, parenting, and work.

 


*Race, Gender, and the Welfare State survey (RGWS)

 

The Political Economy of Data Production

Post developed by Catherine Allen-West, Charles Crabtree and Andrew Kerner

ICYMI (In Case You Missed It), the following work was presented at the 2017 Annual Meeting of the American Political Science Association (APSA).  The presentation, titled “The IMF and the Political Economy of GDP Data Production” was a part of the session “Economic Growth and Contraction: Causes, Consequences, and Measurement” on Sunday, September 3, 2017.

Political economists often theorize about relationships between politics and macroeconomics in the developing world; specifically, which political or social structures promote economic growth, or wealth, or economic openness, and conversely, how those economic outcomes affect politics. Answering these questions often requires some reference to macroeconomic statistics. However, recent work has questioned these data’s accuracy and objectivity. An under-explored aspect of these data’s limitations is their instability over time. Macroeconomic data is frequently revised ex post, or after the fact, and as such one could ask the same question of (ostensibly) the same data, and get different answers depending on when the question was asked.

We set out to explore the political economy of data production by examining a newly available dataset of ex post revisions to World Development Indicators (WDI) data.[1]  Ex post revisions occur when newly available information changes national statistical offices’ beliefs about the nature of the economy. Those revisions extend into the past, effectively rewriting history and, in the process, providing a reasonable proxy for the inaccuracy of the initial reports. These revisions affect a wide swath of data, but we focus on Gross Domestic Product (GDP) and GDP-derived measures, like GDP per capita and GDP growth. GDP revisions are common—most GDP data available for download at the WDI are different now than they were at the time of its initial release. Normally these changes are subtle; other times they are substantial enough to condemn prior data releases as misleading.

We use these revisions to answer two related questions. First, how sensitive are political-economy relationships to GDP revisions? Should researchers worry about revisions-driven instability in the state of political-economic knowledge? We show that they should. To illustrate, we subject a simple, bivariate statistical relationships between democracy and growth to re-estimation using alternative versions of the “same” data. The democracy-growth relationship has been a topic of sufficient interest in economics and political science that instability in this relationship should give us reason for pause. Seen in this light our estimates are worrisome. As we show in Figure 1 below, our estimates are unstable across different “observation years” and further, they are unstable in ways that suggest that initial estimates were biased. Rather than simply a diminution of standard errors as more heavily revised data are introduced (which is what we would expect to see if revisions simply reduced random “noise in the data”), the estimated coefficients for Democracy change substantially across models estimated with different revisions of the same country-year GDP growth data.

Figure 1: GDP Growth ~ Democracy

Note: Figure 1 displays the relationship between GDP Growth and Democracy using the results from 21 different regression models. Plotted points represent parameter estimates, thick bars represent 90 percent confidence intervals, and thin bars represent 95 percent confidence intervals. Each point is labeled with the revision year used. The left side of the plot contains results from models estimated using the 2000-2004 data series, while the right side of the plot contains results from models estimated using the 1995-1999 data series. See paper for more details.

This finding anticipates our second question: Given the likelihood that GDP revision are non-random, what accounts for ex post revisions? What does the “political economy” of revisions look like? We show using Kolmogorov-Smirnov tests (see Figure 2) and random forest models (see Figure 3) that the International Monetary Fund (IMF) influences the magnitude of revisions for GDP and GDP-related measures. That is not entirely surprising. Our suspicion that the IMF would have such an effect is a straightforward recognition of its well-publicized efforts to provide financial and human resources to the national statistical offices of the countries in which it works. What we have “uncovered” in this exercise is simply one consequence of the IMF doing precisely what it has publically said it is doing. But this finding’s (retrospective) obviousness does not diminish its importance. Consider the empirical challenges that this presents. Political economists often ask if the IMF affects the way economies functions, but the IMF’s independent effect on the way economies are measured substantially complicates our ability to know if it does. And it doesn’t just complicate our ability to know if the IMF’s policies affect the economy, it complicates our ability to know if anything correlated with IMF participation affects the economy. Many important things correlate with IMF participation, including, for example, democracy, a country’s relationship with the UN, and whether or not a country is an ally of the United States.

Figure 2: Distributions of GDP Growth Changes

Note: Figure 2 presents compares the distributions of GDP growth revisions for years with and without IMF programs. The y-axis indicates the height of the density function and the x-axis indicates the magnitude of GDP growth revisions in percentages points. The solid green line denotes country years with an IMF program, while the dashed black line denotes countries years without a program. See paper for more details.

Figure 3: Predictors of GDP Growth Revisions

Note: Figure 3 presents the results from a random forest model that examines the predictors of GDP growth revisions. The vertical axis ranks variables according to their importance for predicting GDP Growth Changes. The horizontal axis displays estimates of permutation accuracy for each variable, calculated as the difference in mean squared error between a model that is fitted using the observed values for a measure and a model that is fitted using random (but realistic) values for the same measure. This measure is then scaled to represent the percentage increase in mean square error caused by permuting the values of the variable. Positive values indicate that the variables increase the predictive performance of the model, while negative values indicate that the variables decrease the predictive performance of the variables. See paper for more details.

Of course, politics likely affects the way the economy is measured in a variety of ways that have nothing to do with the IMF. Our random forest analysis suggests that democracy might also have an effect, for example, as might public sector corruption, and it is not hard to tell a plausible post hoc story for why that might be. But our aim is not to provide a comprehensive picture of the political economy of data production, but simply to show that it exists, and that it exists in a manner that should alert us to its importance. Taking seriously the political provenance of ostensibly apolitical data is an important (and, we believe, interesting) step towards refining the state of political economy knowledge.


[1] The raw data used in this paper are available at http://databank.worldbank.org/data/reports.aspx?source=WDI-Archives. To facilitate researcher use of this data, we will make it available in an R package, revisions. This package will contain long- and wide-format data sets.

Andrew Kerner is an Assistant Professor in the Political Science department at the University of Michigan, and a faculty associate at the Center For Political Studies.

Charles Crabtree is a PhD student in the Department of Political Science at the University of Michigan.

The Spread of Mass Surveillance, 1995 to Present

ICYMI (In Case You Missed It), the following work was presented at the 2017 Annual Meeting of the American Political Science Association (APSA).  The presentation, titled “Big Data Innovation Transfer and Governance in Emerging High Technology States”  was a part of the session “The Role of Business in Information Technology and Politics” on Friday September 1, 2017. 

Post developed by Nadiya Kostyuk and Muzammil M. Hussain

On August 24, 2017, India’s highest court ruled that citizens have a fundamental right to privacy. Such a ruling may serve to slowdown the government’s deployment of the Aadhaar national ID program, a robust relational database connecting each of India’s 1.3+ billion citizens with their unique 12-digit identity aimed at centralize their physiological, demographic, and digital data shadows — minute pieces of data created when an individual sends an email, updates a social media profile, swipes a credit card, uses an ATM, etc. While the government has presented the Aadhaar system as an improved channel to provide social security benefits for its nationals, India’s civil society organizations have protested it as a means of furthering government surveillance. India’s trajectory in ambitiously modernizing its high-tech toolkit for governance represents a rapidly spreading trend in the contemporary world system of 190+ nations.

Take China as an other example.  China has recently mobilized its government bureaucracies to establish the worlds’ first ever, and largest, national Social Credit System covering nearly 1.4+ billion Chinese citizens. By 2020, China’s citizen management system will include each Chinese national’s financial history, online comments about government, and even traffic violations to rank their ‘trustworthiness.’ Like India’s, these unique ‘social credit’ ratings will reward and punish citizens for their behavioral allegiance with the regime’s goals by scientifically allowing the state to operationalize its vision of a “harmonious socialist society.”

Yet, the implementation of state-sponsored and ‘big data’-enabled surveillance systems to address the operational demands of governance is not limited just to the world’s largest democratic and authoritarian states. This summer, at the annual meetings of the International Communication Association (May 2017, San Diego) and the American Political Science Association (August 2017, San Francisco), the project on Big Data Innovation & Governance (BigDIG) presented findings from the first event-catalogued case-history analysis of 306 cases of mass surveillance systems that currently exist across 139 nation-states in the world system (Kostyuk, Chen, Das, Liang and Hussain, 2017). After identifying the ‘known universe’ of these population-wide data infrastructures that now shape the evolving relationships between citizens and state powers, our investigation paid particular attention to how state-sponsored mass surveillance systems have spread through the world-system, since 1995.

By closely investigating all known cases of state-backed cross-sector surveillance collaborations, our findings demonstrate that the deployment of mass surveillance systems by states has been globally increasing throughout the last twenty years (Figure 1). More importantly, from 2006-2010 to present, states have uniformly doubled their surveillance investments compared with the previous decade.

In addition to unpacking the funding and diffusion of mass surveillance systems, we are also addressing the following questions: Which stakeholders have most prominently expressed support for, benefited from, or opposed these systems, and why? What have been the comparative societal responses to the normalization of these systems for the purposes of population management in recent decades?

The observed cases in our study differ in scope and impact.

Why do stable democracies and autocracies operate similarly, while developing and emerging democracies operate differently? Access to and organization of material, financial, and technocratic resources may provide some context.

While nations worldwide have spent at least $27.1 billion USD (or $7 per individual) to surveil 4.138 billion individuals (i.e., 73 percent of the world population), stable autocracies are the highest per-capita spenders on mass surveillance. In total, authoritarian regimes have spent $10.967 billion USD to surveil 81 percent of their populations (0.1 billion individuals), even though this sub-set of states tends to have the lowest levels of high-technology capabilities. Stable autocracies have also invested 11-fold more than any other regime-type, by spending $110 USD per individual surveilled, followed second-highest by advanced democracies who have invested $8.909 billion USD in total ($11 USD per individual) covering 0.812 billion individuals (74 percent of their population). In contrast to high-spending dictatorships and democracies, developing and emerging democracies have invested $4.784 billion USD (or $1-2 per individual) for tracking 2.875 billion people (72 percent of their population).

It is possible that in a hyper-globalizing environment increasingly characterized by non-state economic (e.g., multi-national corporations) and political (e.g., transnational terror organizations) activity, nation-states have both learned from and mimicked each other’s investments in mass surveillance as an increasingly central activity in exercising power over their polities and jurisdictions. It is also likely that the technological revolution in digitally-enabled big data and cloud computing capabilities as well as the ubiquitous digital wiring of global populations (through mobile telephony and digital communication) have technically enabled states to access and organize population-wide data on their citizens in ways not possible in previous eras. Regardless of the impetuses for increases in mass surveillance efforts, our research aims to provide empirical support to advance theory and guide policy on balancing security needs and privacy concerns at a time where many governments are ambitiously upgrading their governance systems with unbridled hi-tech capabilities.