The Obama strategy in 2008 had a plan A and a plan B. Plan A was to knock out Hillary with big victories in Iowa and New Hampshire. Didn’t work. Plan B was to pad the delegate lead by exploiting small state caucuses and minimizing the damage in Hillary friendly places like New York. That worked, especially since the Hillary campaign was simply incompetent.
Sanders has a similar plan. His Plan A, the early knock out, almost worked. I suspect that Bernie might have even won the popular vote in Iowa, given that the Iowa Democratic Party is refusing to release vote tallies as they did in previous years. So Bernie is on to Plan B. That means he has to accomplish two things:
- Max out caucus states.
- Minimize losses in large primary states.
This is the list of remaining states in February and Super Tuesday and delegate totals for Democrats according to US election central:
- Alabama 60
- American Samoa caucus 10
- Arkansas 37
- Colorado caucus 79
- Georgia 116
- Massachusetts 116
- Minnesota caucus 93
- Nevada 43
- Oklahoma 42
- South Carolina 59
- Tennessee 76
- Texas 252
- Vermont 26
- Virginia 110
You will notice that Bernie has at least three easy states: Vermont, Massachusetts, and probably Minnesota. Then, it gets really hard, really fast. This is not because Hillary will magically become a great campaigner, but the fundamentals favor Hillary.
There are two reasons. First, you win Southern states in the Democratic primary by doing well among Black voters. South Carolina (Feb 27) will be the first test of how well Bernie can move these voters. If he comes up short in South Carolina, it’s bad news because you have more Southern states coming up real fast such as Alabama and Georgia on Super Tuesday and other Southern states soon after that. Second, in March, you will see the types of big states that Hillary dominated in 2008 because of superior name recognition, such as Texas (51% for HRC in 2008), New York (57%), California (51%), Ohio (53%), and Pennsylvania (54%).
Is it impossible for Bernie to win the nomination? Of course not, but he needs to really dominate outside of the establishment friendly mega-states like Ohio and California. That means an immediate and massive turn around in the Black vote, a wipe out in the caucus states, and some strategy for containing the losses from the big states, which even challenged Obama. That sounds really hard to me.
Ever since the publication of Piketty’s Capital in the 21st Century, there’s been a lot of debate about the theory and empirical work. One strand of the discussion focuses on how Piketty handles the data. A number of critics have argued that the main results are sensitive to choices made in the data analysis (e.g., see this working paper). The trends in inequality reported by Piketty are amplified by how he handles the data.
Perhaps the strongest criticism in this vein is made by UC Riverside’s Richard Sutch, who has a working paper claiming that some of Piketty’s major empirical points are simply unreliable. The abstract:
Here I examine only Piketty’s U.S. data for the period 1810 to 2010 for the top ten percent and the top one percent of the wealth distribution. I conclude that Piketty’s data for the wealth share of the top ten percent for the period 1870-1970 are unreliable. The values he reported are manufactured from the observations for the top one percent inflated by a constant 36 percentage points. Piketty’s data for the top one percent of the distribution for the nineteenth century (1810-1910) are also unreliable. They are based on a single mid-century observation that provides no guidance about the antebellum trend and only very tenuous information about trends in inequality during the Gilded Age. The values Piketty reported for the twentieth-century (1910-2010) are based on more solid ground, but have the disadvantage of muting the marked rise of inequality during the Roaring Twenties and the decline associated with the Great Depression. The reversal of the decline in inequality during the 1960s and 1970s and subsequent sharp rise in the 1980s is hidden by a fifteen-year straight-line interpolation. This neglect of the shorter-run changes is unfortunate because it makes it difficult to discern the impact of policy changes (income and estate tax rates) and shifts in the structure and performance of the economy (depression, inflation, executive compensation) on changes in wealth inequality.
From inside the working paper, an attempt to replicate Piketty’s estimate of intergenerational wealth transfer among the wealthy:
The first available data point based on an SCF survey is for 1962. As reported by Wolff the top one percent of the wealth distribution held 33.4 percent of total wealth that year [Wolff 1994: Table 4, 153; and Wolff 2014: Table 2, 50]. Without explanation Piketty adjusted this downward to 31.4 by subtracting 2 percentage points. Piketty’s adjusted number is represented by the cross plotted for 1962 in Figure 1. Chris Giles, a reporter for the Financial Times, described this procedure as “seemingly arbitrary” [Giles 2014].9 In a follow-up response to Giles, Piketty failed to explain this adjustment [Piketty 2014c “Addendum”].
There is a bit of a mystery as to where the 1.2 and 1.25 multipliers used to adjust the Kopczuk-Saez estimates upward came from. The spreadsheet that generated the data (TS10.1DetailsUS) suggests that Piketty was influenced in this choice by the inflation factor that would be required to bring the solid line up to reach his adjusted SCF estimate for 1962. Piketty did not explain why the adjustment multiplier jumps from 1.2 to 1.25 in 1930.
This comes up quite a bit, according to Sutch. There is reasonable data and then Piketty makes adjustments that are odd or simply unexplained. It is also important to note that Sutch is not trying to make inequality in the data go away. He notes that Piketty is likely under-reporting early 20th century inequality while over-reporting the more recent increase in inequality.
A lot of Piketty’s argument comes from international comparisons and longitudinal studies with historical data. I have a lot of sympathy for Piketty. Data is imperfect, collected irregularly, and prone to error. So I am slow to criticize. Still, given that Piketty’s theory is now one of the major contenders in the study of global inequality, we want the answer to be robust.
Over at Statistical Modelling, Andrew Gelman makes a very sensible point about peer review: it is as only as good as your peers. Why do psychologists worship p-values? Because they approve it in peer review. A few choice quotes:
In short, if an entire group of peers has a misconception, peer review can simply perpetuate error. We’ve seen this a lot in recent years, for example that paper on ovulation and voting was reviewed by peers who didn’t realize the implausibility of 20-percentage-point vote swings during the campaign, peers who also didn’t know about the garden of forking paths. That paper on beauty and sex ratio was reviewed by peers who didn’t know much about the determinants of sex ratio and didn’t know much about the difficulties of estimating tiny effects from small sample sizes.
To put it another way, peer review is conditional. Papers in the Journal of Freudian Studies will give you a good sense of what Freudians believe, papers in the Journal of Marxian Studies will give you a good sense of what Marxians believe, and so forth. This can serve a useful role. If you’re already working in one of these frameworks, or if you’re interested in how these fields operate, it can make sense to get the inside view. I’ve published (and reviewed papers for) the journal Bayesian Analysis. If you’re anti-Bayesian (not so many of theseanymore), you’ll probably think all these papers are a crock of poop and you can ignore them, and that’s fine.
Read the whole thing.
A number of writers noticed that we overlooked an important bit of news last week during the Iowa caucus – two Latinos and a Black man took 60% of the Iowa GOP caucus. At the very least, this is newsworthy and merits explanation.
Here’s how we should understand the rise of Rubio and Cruz. The basic elements of minority party politics are as follows:
- African Americans started in the GOP but moved to the Democratic party.
- Groups that were forcibly assimilated into the US tend to go Democrat – Native Americans, Mexicans, Filipinos.
- Groups that benefited from Cold War politics tend to lean GOP more than others – Vietnamese, Cubans.
- Other voluntary migrants vary but if they are harassed or repressed they lean Democrat.
Using these rules of thumb, it is easy to see how Cruz and Rubio make a path to the top of the GOP. They are Cubans, who have influence in the GOP, especially in Florida. They are also from states with strong GOP parties – Florida and Texas. As many folks have noted, they downplay their ethnic background as well and kowtow to the anti-immigration crowd. Briefly, Rubio endorsed some sort of compromise on immigration but walked that back.
The rise of these two candidates does not represent a big swing of Latino voters to the GOP – that would only happen if large numbers of Mexicans defect from the GOP. It does however reflect an opening made possible by the complex history of US foreign relations. In the messy world of Cold War politics, the US chose to favor Cubans and, decades later, their children are steps away from the White House. And oddly, Castro might be alive to see it!
Just in time for Fabio’s proclamation of April as race month, sociologist Jacqueline Olvera has just published an article in Sociology Compass that might interest those looking for a state-of-the-field review of the interrelations among the state, undocumented migration, and the workplace:
“The State, Unauthorized Mexican Migration, and Vulnerability in the Workplace“
For the last 20 years, migration scholars have generated a number of important empirical insights about the ways in which the state, through the enactment of immigration policies, creates workplace vulnerabilities such as discrimination, harassment, wage theft, workplace raids, and the threat of deportation. Recent studies of illegality also examine the role of the state but do so in a way that explores what legal status means and how it is experienced in everyday lives of migrants marked as “illegal” by the state. This article reviews recent research that shows that the state operates in a gray zone of enforcement that puts migrants in ambiguous social spaces and heightens their vulnerability at work. However, research also finds that migrants find ways to exert their agency in challenging work environments.