Friday, November 3, 2017

Stanford University findings on the ACA and the labor market

Stanford Economics Professor Mark Duggan was quoted as concluding that

"While the Affordable Care Act had a significant effect on health insurance coverage, it did not have a substantial effect on the U.S. labor market as many had expected" and

"the Affordable Care Act has not had the negative effect on jobs the law’s critics claimed it would."

He was referring to a working paper distributed by the National Bureau Economic of Research, which states that

labor market outcomes in the aggregate were not significantly affected.”

Theirs is a working paper and I'm sure that the authors are eager to add data and analysis, so I understand the above conclusions to have been modestly offered. With that said, it is worth recognizing that the above conclusions are not what the working paper shows.

  1. Table 4 (the paper's first table on labor market outcomes) shows that the ACA reduced nationwide labor force participation by 349,190 in 2016, plus however much the ACA reduced labor force participation in a geographic area that was fully insured before the ACA, which I call the HFIA (Hypothetically Fully Insured Area).  This effect is economically significant and, when combined with items (2) and (3) below, is easily in line with "the negative effect on jobs that the law's critics claimed it would be."

    [Admittedly, the 349,190 is probably not statistically significant by the usual criteria, but the quotes above are not claiming that either side could be correct. Rather they claim to decisively reject "critics" who made claims right in line with the Duggan-Goda-Jackson point estimate. See below for the derivation of the 349,190]

  2. The paper assumes, without much explanation, that the HFIA part of the ACA's impact is zero.  But other work has shown that near-elderly insured people were given a tremendous incentive to retire early.  In other words, basic economics tells us that the HFIA part is likely positive (i.e., in the same direction as the 349,190) and we should not assume it to be close to zero until we have further measurement.

  3. The empirical methods in the paper, which emphasize differences among geographic areas such as Medicaid expansion states versus other states, are not designed to detect effects of the employer penalty.  The employer penalty is the same amount throughout the nation.  The penalty creates large labor-market distortions; those distortions that have been measured in other studies have proven to be similar across geographic areas.  Moreover, the employer penalty did not apply until the 2016 coverage year, whereas 8/9 of the working paper's data is before that date. This is an especially serious problem for the low-income population, where the employer penalty in effect has them working 50-60 days per year for the government, on top of the implicit and explicit employment/income taxes they would pay even without the ACA (this fact is nowhere mentioned in the paper). For this reason, the authors' claim than that "lower income individuals were actually incentivized to work more" is especially incredible.

To derive the 349,190, look at the first "Out of the labor force" column of that table.  The first row says that the M variable reduces out of the force by 0.0847 on average for each working-age person in the U.S.  The second row says that the E variable increases out of the labor force by 0.0962.  The mean of the M and E variables are, respectively, 0.073 and 0.086 (p. 11 of the paper). So, relative to the HFIA, their regression says that the U.S. has increased out of the labor force by 0.0021 per working-age person:

0.0021 = 0.073*(-0.0847) + 0.086*(.0962)

To get a number of people, multiply by the number of working age people (difference between these two), and you get 349,190.

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