In New York City, the top source of climate pollution is the energy use of big buildings. To combat this, the city recently enacted a transformative law requiring buildings to slash emissions 40 percent by 2030 and over 80 percent by 2050. Meeting these requirements will involve upgrading buildings to high energy efficiency, which, in practice, can require everything from switching to LED lights and better insulation to temperature sensors and controls tied to better HVAC systems.
The new law covers the city’s 50,000 largest buildings—those over 25,000 square feet. Starting in 2024, these buildings will need to get below pollution-per-square-foot limits tailored to specific types of buildings. These pollution limits will ratchet down in 2030, requiring more pollution cuts, and then again in later years. By 2050, the law will achieve 80 percent pollution reductions through energy efficiency (in combination with a greening electric grid).
Last week, Bernie Sanders’ proposal for a Green New Deal heavily featured his plans to take on the fossil fuel industry. He joins a growing number of 2020 presidential contenders who are proposing to phase out coal, oil, and gas production and to put workers and communities first in a transition to a new economy.
Of the 18 major Democrats remaining in the race, sixteen have taken the No Fossil Fuel Money Pledge to reject campaign contributions above $200 from fossil fuel company executives, PACs, and lobbyists; thirteen support ending new fossil fuel leasing on public lands; and twelve support eliminating all fossil fuel production subsidies and tax giveaways.
As part of our ongoing analysis of the 2020 Democratic primary, we asked a large sample of Democrats to allocate 100 points to different characteristics they want to see in the Democratic nominee. Giving respondents a fixed amount of points to allocate reveals priorities not easy to capture with standard polling questions or even ranking. Last fall, we wrote a seriesofposts using this method, which revealed that Democratic voters’ priorities are surprisingly uniform, despite the fact that the party has a demographically and ideologically diverse base.
The characteristics that respondents ranked included personal characteristics like past experience in politics, candidate demographics, policy positions like taxing the wealthy and climate action, and characteristics related to the candidate’s perceived electability.
The lack of action to stem gun violence is one of the most tragic consequences of the dysfunction in our political system, and over the last several weeks there has been another string of mass shootings connected to white supremacist and misogynist ideologies. Much of the lack of action can be explained by the simple fact that Republican leadership has no interest whatsoever in protecting the public’s health or safety. That’s not the whole story however, and like most issues, American’s views on gun control are fairly complex.
We explore this using a survey of 2,000 adults conducted by Pew Research in August 2016, which contained a battery of questions on various gun control proposals. Pew makes a lot of their survey microdata available to the public (which you can get from their website), and we used this to model opinions in each state using a method called multilevel regression and poststratification (MRP). The state-level estimates of support for each issue are shown in the interactive map above.
In the last post in this series of simulation studies, we focused on parameter identification with the ecological regression. Essentially, when we know exactly what model was used to generate the data, can an ecological regression find the values used to generate the data. Unfortunately, the real world is rarely this simple. Usually, we won’t know what the “true model” that was used to generate the data was. This is especially acute in the “ecological exit polls” case, where we have no idea what model people use to come up with their vote choice. There are other problems that may arise in using the ecological model to infer individual vote too: the relationships between demographics and vote choice are much more complex than the simple linear models used in the last post, and the distribution of voters in precincts may make it difficult or impossible to model vote choice.
So we want a more “realistic” test of our ecological exit polls approach. Using the demographic information from the voter file and precinct-level vote counts we have the data to train an ecological model to infer individual vote choice, but without knowing how individuals actually voted, we cannot validate the model! But we don’t have that data; in fact, if we did know how individuals voted, we wouldn’t need the ecological model in the first place.
If you work hard and you don't get a break, it’s bad for your physical well-being. It’s bad for your mental health. It’s not fair for you or your family. It means having to choose between a paycheck and a parent–teacher conference. It means not having the time to help an elderly parent to a nursing home, to attend a wedding, to celebrate a religious holiday or cherished festival, to mourn the death of a loved one, or to take a much-needed vacation.
Yet, working without a break is all too common in this nation. In New York City alone, almost one million people cannot take a single day of paid personal time. That’s why Mayor Bill de Blasio has set New York City on course to be the first municipality in the United States to guarantee paid time off for workers, and I have news for anyone who thinks this will be controversial: we have the people on our side.
With respect to the mass public, Twitter is not “real life.” However, that doesn’t mean it doesn’t matter. The site is used regularly by the vast majority of people professionally involved in politics, while the President uses it daily to discuss and promote policy (and go on racist tirades against congresswomen who criticize him). Other prominent members of Congress, like Alexandria Ocasio-Cortez, have developed large audiences that allow them share their message with millions of people in real time. Recognizing the importance of tracking the shifting media landscape, Axios produced an interesting graphic at the beginning of this year, tracking the number of interactions important U.S. political accounts generated over the preceding month.
This inspired us, at Data for Progress, to begin tracking similar metrics. Below, we have recreated and updated the Axios graphic using the same accounts (@realDonaldTrump, @AOC, @KamalaHarris, @BarakOBama, @CNN, @SpeakerPelosi, @SenSchumer, @thehill, @ABC, @nytimes, @MSNBC, @NBCNews, @seanhannity, @washingtonpost, @Reuters) along with Kevin McCarthy (@GOPLeader ) and Mitch McConell (@senatemajldr). Over the next few months we may expand the number of accounts we track, and how we track them.
We have been developing a new methodology for the so-called ecological inference (EI) problem, which attempts to recover information about individuals from aggregated data. We’ve used this method to create “ecological exit polls” for primaries where conventional polling is not available.
This has helped us gain some insights on who votes for progressive primary challengers and develop predictive models for field campaigns based on those findings. For example, we found that virulent homophobe and anti-choice crusader Dan Lipinski owes his narrow primary victory over Marie Newman to people who frequently vote in Republican primaries, thanks to the open primary system in Illinois.
Since this is a new methodology, we’ve been working hard to validate its efficacy in a number of different ways. Here we’ll go through the results of a simulation study we conducted as a part of that validation process. The results are encouraging so far, and we plan to build on this work with a series of more comprehensive validations in the future.
The election of Donald Trump has driven a new wave of mobilization among Democrats and progressives. This new activism has led to a lot of pearl-clutching over the activist base pushing the party too far to the left. Because of this, we used the recent Data for Progress / YouGov Blue survey to see how much of a difference there was across activists/non-activists and how active Democratic voters really are.
Voters can be strategic in who they vote for, especially in a primary election. Voters consider not only who they like best, whose political ideology adheres closest to theirs, and who has a chance to win the primary—they also consider who might be able to win in the general election. Voters, then, might make tradeoffs: While they would really prefer one candidate, they might vote for another. This post looks at when and why 2020 Democratic presidential primary voters might make such a tradeoff.
Ever since Bernie Sanders and Donald Trump both launched campaigns for their respective party nominations in 2016, their appeals have invited comparisons invoking the populist style in American politics. In more recent years, such comparisons have extended to other insurgent progressive politicians such as Alexandria Ocasio-Cortez. However, many of these comparisons seem unclear about what exactly populism is -- many pundits seem to simply know it when they see it -- making it hard to tell how valuable such blanket comparisons actually are. What constitutes populism in general, and what separates distinct populist appeals from each other?
