Our research had not been in a position to straight link insurance that is individual to payday borrowing; to the knowledge, the information to do so usually do not exist.

Furthermore, although we discovered no proof of this, we’re able to perhaps not rule out of the possibility that state- or county-level alterations in the legislation (or enforcement of laws) of payday advances or other industry modifications could have took place Ca when you look at the duration 2010–14. But, we tested the appropriateness of our approach in lot of methods. First, we stratified our models by age bracket (individuals more youthful or more than age sixty-five): Those who work in younger group will be beneficiaries associated with Medicaid expansion, while those within the older team will never, simply because they could be entitled to Medicare. 2nd, we examined exactly how alterations in payday financing diverse utilizing the share of uninsured individuals when you look at the county before expansion: we might expect you’ll find a higher decrease in payday financing in areas with greater stocks compared to areas with reduced stocks. Final, we carried out an “event study” regression, described above, to assess any time that is preexisting in payday financing. Our additional methodology offered evidence that is reassuring our findings had been due to the Medicaid expansion.

Research Results

The difference-in-differences methodology we relied on contrasted payday financing before and after California’s early Medicaid expansion into the state’s expansion counties versus nonexpansion counties nationwide. To manage for confounding, time-varying facets that affect all counties at specific times (such as for example recessions, holiday breaks, and seasonality), this method utilized nonexpansion counties, in Ca along with other states, being a control team.

Display 1 presents quotes associated with the effect of Medicaid expansion in the overall level of payday financing, our main results; the table that is accompanying in Appendix Exhibit A4. 16 We discovered large relative reductions in borrowing after the Medicaid expansion among individuals more youthful than age sixty-five. How many loans applied for per declined by 790 for expansion counties, compared with nonexpansion counties month. Provided a preexpansion mean of 6,948 loans per that amounts to an 11 percent drop in the number of loans month. This decrease in loan volume equals a $172,000 decrease in borrowing per thirty days per county, from the mean of $1,644,000—a fall of 10 %. And 277 less unique borrowers per county-month took away loans, which represents an 8 % decrease through the preexpansion mean of 3,603.

Aftereffect of very very early expansion of eligibility for Medicaid on month-to-month pay day loans for borrowers younger

Display 2 presents the consequence of Medicaid expansion in the range loans in three age groups: 18–34, 35–49, and 50–64; the accompanying table is in Appendix Exhibit A5. 16 The decrease in the amount of loans each month ended up being completely driven by borrowers more youthful than age fifty (the small enhance among older borrowers had not been significant). For expansion counties in Ca, in accordance with the nonexpansion counties in Ca as well as other states, postexpansion borrowers ages 18–34 took down 486 loans per county-month, in comparison to a preexpansion mean of 2,268—a reduction of 21 per cent. For borrowers ages 35–49, the decrease had been 345 from a preexpansion mean of 2,715, a reduced total of 13 %. This observed relationship across age groups stayed whenever we examined how many unique borrowers and dollars that are total (information maybe perhaps not shown).