In a March 2019 clip that only garnered widespread attention months after the fact, finance guru Suze Orman insisted that the financial hardships of the millennial generation could be traced to their purportedly irresponsible coffee-consumption habits. While the well-deserved mockery she received tended to point out glaring truths about generational inequality, very little coverage of her comments identified a more amusing irony of Orman's backstory: She derives her legitimacy as a self-help guru from her struggles during her upbringing, but was privileged enough to have received a loan of $50,000 from friends, interest-free. The problem for millennials is not their individual choices but the structural policies holding them back. Therefore, the solution is policy, not pedantic life advice. The recent Loan Shark Prevention Act introduced by AOC and Bernie Sanders is a crucial and popular first step towards a solution.
The average millennial, financially precarious and victimized by usury, couldn't conceive of such a proposition. A 2018 survey by CNBC found that 51% of millennials have at least considered taking payday loans to make ends meet, despite the enormous APR associated with so-called "cash advances." While abstaining from coffee might put a couple bucks back in the pockets of young people, it is laughable that the record one trillion dollars of credit-card debt that the millennial generation accumulated would be meaningfully reduced by altered caffeine habits.
As we talked about previously: with such a large field (and with it being this early) in the 2020 Democratic primary campaign, it is difficult to measure candidate support in a useful way. This problem is even more acute when looking at differences across groups, since the data becomes even harder to parse as the number of observations decreases. None of this has stopped pundits from discussing age gaps, ideology gaps, and race gaps between supporters of various candidates. This analysis relies on comparing topline support between different demographic groups, which means that it is generally only comparing voters’ first choices and is therefore ignoring the broader contours of support.
In the previous blog, I used survey data and a random utility model to identify support for candidates beyond the number-one choice. I extend this method here, using new data from YouGov Blue and a MaxDiff model to estimate variation in support across different subsets of voters. The YouGov Blue survey ran from May 30 to June 3, and includes 625 voters whoindicate they will probably vote in the Democratic primary. To measure support, they gave voters sets of five candidates to compare and asked them to select their top and bottom choice from those five candidates. I then modeled that selection as a function of latent candidate support, which itself was a function of voter demographics: ideology, race, sex, age, income, and education. And the end results show candidate support for different demographic groups while holding all else constant. Formally, this is a Hierarchical Bayes MaxDiff model.
In a recent GQ magazine article, Way to Win co-founder Tory Gavito and DfP co-founder Sean McElwee presented compelling new evidence on the question of whether Democrats should persuade swing voters or galvanize their base to have the best chances of retaking the White House. One graphic in particular gained significant attention:
The 2020 Democratic Primary features a large number of candidates sending signals regarding their ideological commitments, with many of them attempting to claim the label of being the most “progressive.” But what do they mean when they say “progressive,” and which of them is, in fact, the most progressive? While being progressive is inherently vague and context-dependent, we can provide more than mere guesswork and armchair assumptions. The Washington Post recently started providing data on what stances each of the Democratic candidates are taking on a variety of issues. We can use this resource to compare candidates across issues and provide an overall metric of where each candidate stands comparatively.
For those of you interested in the details, I explain in full how I use a latent variable method to estimate candidate progressivism further below. In general, I combine the positions collected by the Post along with a data collected from DfP volunteers on how progressive positions are relative to each other to place the candidates in a single dimension of ideology. This is done by assuming that each candidate selects the position that is closest to their own ideology.
“Economic populism” and “identity politics” aremutuallyexclusive, thepunditstellus. Progressives can either embrace an agenda of economic justice, downplaying (or even moving to the right on) issues of race, identity, and immigration; or they can embrace racial justice, downplaying economic and kitchen table issues, but not both. While some countries’ ideological landscapes may suggest some invidious trade-offs be made between emphasizing these two priorities, at least in the United States we don’t have to; they go hand in hand.
The World Values Survey and European Values Study have been conducted every few years since 1980. Looking at data from countries in the Organization for Cooperation and Development (OECD), a group of industrialized peer countries of the United States, we built statistical models to explore the association between economic ideology and racial resentment cross-nationally.
We created an index for economic ideology from data on attitudes towards economic redistribution, the appropriate role of the state in the economy, and economic competition. We used data on attitudes towards people of other races and immigrants to construct an index for racial resentment. Adjusting our models to control for education and religiosity, we find a strong association between left-leaning economic views and lower levels of racial resentment (and between right-leaning economic views and higher levels of racial resentment) in the United States. Interestingly, this relationship is stronger in the United States than it is in other countries.
Decades ago, in a more conservative Virginia, Dick Saslaw became the leader of Senate Democrats. And since then, he’s just...stuck around, with his outdated attitudes and deep corporate ties just as bad as they’ve always been. Saslaw has a long history of thinly-veiled Islamophobia, was the lone Democrat to defend Ralph Northam during the governor’s blackface scandal, and is a wholly-owned subsidiary of Dominion Energy. But just saying “Dick Saslaw is an Islamophobic blackface-enabler bought and paid for by Dominion” doesn’t do it justice.
Today’s farm equipment has more in common with computers than plowshares. Modern tractors have can steer themselves and cost more than a few hundred thousand dollars. But the technology inside can be used to prevent farmers from repairing or altering the machines they own. Many farm equipment manufacturers, such as John Deere, build software into their equipment that prevents anyone other than “certified dealers” from making repairs. This puts farmers in tough situations.
Imagine a farmer’s tractor breaks down on a Monday. Previously, if this farmer was capable of fixing the issue, they could simply make the repairs themselves and continue on with their day. But with many modern machines and their coded restrictions, farmers have to bring in a technician approved by the manufacturer. This might be a few days and costs money just to request. This situation is causing consternation among America’s farmers.
The Green New Deal aims to leverage the full resources of the United States economy—public and private—to take on twin crises of climate and inequality. While taxation, regulation and investment (and the occasional cow fart and mythical train to Hawaii) have featured prominently in most debates about the Green New Deal, commentators and wonks have largely overlooked one of the less sexy but more impactful policy levers: government purchasing power. We at Data for Progress believe that a key part of any Green New Deal—and one that we could begin implementing in many states right now—is the “Buy Clean” standard.
Buy Clean is a procurement policy that would require the government to take climate pollution and labor protection into account when determining which corporations win government contracts. The federal government is the world’s single largest customer—and the dollars it spends are yours as a taxpayer. We can leverage the billions of dollars spent every year on federal contracts to incentivize clean and green investments while empowering the unions and workers that brought us the weekend and the welfare state. And while the legislative path to a Green New Deal runs through a tough senate map and 60-vote filibuster, we can start pushing for Buy Clean through a federal infrastructure package and state level legislation right now.
Donald Trump’s recent decision to escalate the ongoing trade war with China resulted in an additional $60 billion in retaliatory tariffs being levied against the United States. While these new tariffs will affect a wide variety of goods that American consumers purchase, the decision further aggravates the plight of American farmers, who have traditionally sold China an enormous amount of soybeans. The trade war has already cost some $9 billion in net farm income since 2018, and crop futures are looking even bleaker after this new round of retaliatory tariffs were announced.
For an industry that has seen record-numbers of bankruptcies that rival the peak of the Great Recession, this development is not good. From Vox, to Newsweek, to CBS,to CNN, to local public radio, to even Fox News, almost anyone in the business of popular commentary is arguing that these tariffs are going to have nasty impacts. In fact, the situation is so severe that even the Heritage Foundation is raising alarm.
Many Democrats already focused on the 2020 presidential race but there are important 2019 elections that deserve attention. Republicans hold a one vote majority in both chambers of Virginia’s legislature, but elections this November have the potential to change that. The entire legislature is up for reelection, and Republicans majorities are precarious. A few districts that could flip if Democrats give it all we’ve got.
Virginia could be the first state of the former Confederacy where mainstream, progressive Democrats take full control of state government, but that only happens if the Democratic base is engaged. Here at Data for Progress, we’ve identified ten races where your money is most needed. In all ten of these districts, only one Democrat filed to run, so there is no primary. Every penny you give will be used to beat a Republican and take back Virginia for the people.
In this post, we investigate an open-ended text response to the seemingly simple question of what electability means. On our latest survey, we asked respondents,
Lately, there has been a lot of talk about whether candidates for office are "electable" or not. When you hear this being talked about, what do you think people mean by "electability"?
In short, we find that electability is what you want it to be. Voters define “electability” in a highly tautological fashion -- basically, as “the ability to get votes.” The only consistent concept expressed across subgroups includes the ability for a candidate to appeal to “a broad set of voters,” but little beyond that. The term simply does not appear to have much meaning.
Housing is the largest single expense for the average American, costing one third to one half of pay for millions of Americans. Twenty-one million American families – over a sixth of the United States – are considered cost-burdened and at elevated risk of homelessness. Millions are taking on extra jobs or cutting back on healthcare or food to stay housed. At least 553,000 homeless Americans are living on the street.
According to the National Low Income Housing Coalition, “85% of Americans believe ensuring everyone has a safe, decent, affordable place to live should be a ‘top national priority.’”
Americans need more affordable homes, and progressive politicians need a plan to give it to them.
