This research utilized a unique supply of nationwide data on pay day loans supplied towards the writers by a business trade team, the Community Financial solutions Association of America (CFSA). The info set consisted of the universe of pay day loans originated by five nationwide storefront payday lending chains with areas all over country. It included info on over ninety-three million loans, which was indeed deidentified for research purposes. For every loan, we observed the dates that the mortgage had been made and had been due, the results of this loan (as an example, a standard or belated repayment), together with ZIP rule for the payday lender’s storefront. The information set covered all loans from 2009 through the first months of 2014. Appendix display A1 maps the continuing states contained in the information set. 16
Techniques
We centered on the state of Ca, which joined into an understanding using the management of President Barack Obama for very very very early county-by-county utilization of the ACA’s Medicaid expansion last year and 2012. We learned the first expansions in Ca, because our information would not provide a time that is sufficiently long to analyze the 2014 expansions and offered reasonably small details about loans in other very early expansion states. We compared California counties that expanded Medicaid early to counties nationwide that failed to achieve this, including four California counties that delayed expansion.
We aggregated the CFSA information towards the county-month degree, producing loan that is aggregate, standard prices, along with other measures of loan volumes and results in each county and thirty days combination. The data that are aggregated contained 58,020 county-month observations for the time scale 2009–13, which covered approximately twenty-four months before and twenty-four months following the Ca Medicaid expansions. Ca rolled down Medicaid expansion over 2011 and 2012, and the dates were used by us of expansion by county given by Benjamin Sommers and coauthors. 17 These times are placed in Appendix Exhibit A2, along side county-specific typical payday that is monthly before to expansion. 16 Appendix Exhibit A3 shows the aggregate research test data. 16 We examined results within the 43 expansion counties in Ca, 
making use of as an evaluation team 920 counties in nonexpanding states and 4 California counties that delayed expansion.
Our main outcomes were three measures of loan amount: the sheer number of loans, how much money borrowed, and also the quantity of unique borrowers
We measured borrowers that are unique the info every month utilising the data set’s anonymized debtor identifiers. Medicaid expansions offer medical insurance for uninsured grownups more youthful than age 65, therefore we stratified our results by age and centered on people more youthful than age 65. Provided past research findings that Medicaid expansions disproportionately benefited those younger than age 50, we further examined the circulation associated with wide range of loans among nonelderly grownups by borrower’s age (18–34, 35–49, and 50–64).
Also, we believed that we possibly may see higher reductions in payday lending within counties with greater preexpansion stocks of low-income uninsured grownups. We investigated this possibility by comparing counties with a higher share of uninsured to people that have a share that is low. Counties classified as having a top share had been those in the most truly effective tercile of this share uninsured with incomes of significantly less than 138 % associated with the federal poverty degree, based on the 2010 Census Bureau’s Small region medical insurance quotes; counties classified as having a minimal share were within the base tercile.
Our additional results had been the stocks of loans that ended in standard, were repaid belated, and had been rollovers. Rollovers are loans which can be taken out in the exact same time a past loan is born, that allows the debtor to give the loan’s extent without repaying the principal—in change for spending a finance fee. We identified likely rollovers within the data as loans that started within two times of the past deadline for similar debtor and exact same loan provider. 18