How many newly uninsured? Families USA and the feds paint different pictures

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Families USA released a report this week estimating that 5.4 million adults newly unemployed by the pandemic as of May are also becoming uninsured.

The estimate is based on data and analyses concerning  1) the number of people who have lost jobs (BLS), 2) the likely percentage of newly unemployed who have lost access to health insurance, and 3) the percentage of newly unemployed in the ACA era (2014-2018) who have found other insurance, including Medicaid and marketplace (Urban Institute).

The analysis boils down to a fairly simple equation: about a quarter of those who lose jobs do not find their way to job-based insurance through a family member, Medicaid, marketplace coverage or COBRA. Much higher percentages of the newly unemployed are estimated to become uninsured in states that have refused the ACA Medicaid expansion (42.5%) than in expansion states (22.6%).

5.4 million uninsured adults equates to about a 2.6 percentage point increase in the uninsured rates for Americans aged 18-64.  Based on the most recent National Health Interview Survey (Jan-June 2019), that would suggest an uninsured rate of about 16.3% for ages 18-64. As I've noted recently, more immediate survey data seems to indicate less severe increases in the uninsured population. A Commonwealth Fund survey of about 2300 adults conducted May 13 through June 2 seemed to indicate that a bit less than 2% of the population had recently become uninsured.

More strikingly, the experimental new Household Pulse Survey updated weekly by the CDC -- a joint project of the Census Bureau and National Center for Health Statistics -- shows comparatively little movement since its launch in the week of April 23, when it recorded a national uninsured rate of 12.6%  for ages 18-64 -- more than a percentage point lower than the 2019 NHIS estimate. The weekly updates have been quite volatile but on the whole have ticked upward, reaching 13.5% in the week of June 25 (there'll be another update tomorrow).  Estimates for individual states, shown below, average three percentage points higher in Pulse than in the FUSA study, and vary widely.

The Silver bullet for election prediction may need lengthening

Nate Silver argues that job growth during a presidential election year is the best single indicator of whether a president will be reelected.  After a series of calculations, he pegs Obama's"magic number" for job growth in 2012 at 150,000 jobs gained per month.

I have neurotically tracked Obama's trajectory -- approval ratings and national unemployment numbers -- against Reagan's for 2-3 years, and my intuition is in sync with Silver's conclusions (and partly shaped by his prior analyses, no doubt). Far be it from me with my sixth grade math skills to quarrel with the intricacies of his model. But there's one basic assumption that I would quibble with: that the relevant periods are necessarily defined by the calendar year.

Silver argues that the actual year of election matters a lot, and the three years prior, not so much. When conditions are bad early in a president's term, he may even get extra credit for a late-term surge. More specifically, Silver finds

that job growth during the third year of a president’s term has a positive effect on his re-election odds, while the coefficients attached to the first two years are negative.

But none of these results are statistically significant or particularly close to it; only job growth during the fourth year of a president’s term has a clear effect.

True, perhaps, as far as it goes. But why break the term into years? Why assume that voters' relevant perceptions track the movement of the earth around the sun?

As Silver indicated, the ur-case for unemployment figures tracking closely with election results is lucky Ronald Reagan, who in Silver's model benefited from the 2012 equivalent of 487,000 jobs created in 1984.  Yet my own personal break point for comparing Obama's home-stretch performance to Reagan's has been July in the year prior to election -- because July 1983 is the month in which measured employment surged most dramatically for Reagan, from 10.1% to 9.4%. While that particular break point may be arbitrary, the broader point is that the unemployment rate shrank most dramatically for Reagan in the second half of 1983, from 10.1% in June to 8.0% in January 1984. It fell further, to 7.4% in October 1984.  But morning in America shone brightest at dawn, in late 1983.

Nate Silver's death knell for Obama's jobs measures

One nugget in Nate Silver's exhaustive statistical analysis of the degree to which each of  a broad range of economic variables have affected presidential elections since 1948 makes it pretty clear why Republicans are going to block almost every job-producing measure put forward by President Obama. It's this (charts omitted):

Another poorly performing variable is the unemployment rate. It has had essentially no relationship to election results at all.

However, while the unemployment rate had told us very little, the rate of change in the jobs market has been fairly meaningful. Here, for instance, is a comparison of election results to the rate of payroll jobs growth — the variable you often see highlighted when the government releases its jobs report on the first Friday of each month.

I am tired of this game...

That is, the breathless monthly elephant-groping over the unemployment numbers. Here's Politico, via email alert:

The unemployment rate fell to 9 percent in October from 9.1 percent in September, but the country added a disappointing 80,000 jobs, well below expectations that as many as 100,000 jobs would be created last month, according to data released by the Labor Department on Friday.

"Well below"? Twenty percent is well within the range of the typical revision of prior month's numbers. September's number, for example, was revised up today from 103,000 to to 158,000 -- almost triple the "disappointment" triggered by the margin below consensus for this month, while August was revised up from 0 to 57,000. Those upward revisions exceed the alleged job growth this month.

There's plenty of intelligent deep diving, of course.  Those who follow these numbers closely understand their ambiguities and uncertainties, and the cumulative nature of the light they shed.  But the headline snapshots, the insta-hardening of snap perceptions, are not helpful.