A number of states require that under certain circumstances lenders make available an extended, amortizing loan option in addition to their basic payday loan option. There is a huge degree of variation among states in the form that the extended repayment options take. Most states only require that the option be made available; they do not require that the option be used. 4 Variation between states in extended repayment options may be somewhat muted in this dataset because the lender that provided the data, unlike many lenders, makes extended repayment options available even in states where they are not required.
The data in this paper were provided by a large, anonymous payday lender and consist of all loans made by this lender in 26 states between . Figure 1 maps the states included in the data. The data contain no demographic information about borrowers, but loans made to the same borrower can be linked across time and location. The street address of the storefront at which the loan was made is known. The data include all dimensions of the loan contract, as well as its repayment history. The lender makes no direct online loans, though it refers customers to online lending affiliates through its website. The dataset contains only directly made storefront loans.
Rather than count sequences of consecutive loans, my main repeat borrowing measure is a binary variable measuring whether, exactly 90 days after origination of the current loan, the customer again has an active loan
The data consist of 56,143,566 loans made at 2,906 different stores to 3,428,271 distinct customers. Once simultaneous loans are combined and considered as single loans (as explained below) this number drops to 54,119,468, for an average of 15.8 loans per customer. However, the median number of loans per customer is 7, reflecting the skewness of the distribution. Table 1 presents distributions installment loans CT for many variables in the data.
3 . 1 Variable Definitions
Because payday loans vary in size, price, and length of term, any comparisons should be robust to relabeling. For instance, two simultaneous loans of $250 should be considered equivalent to a single loan of $500–it would be problematic to conclude that in the former case “twice as much” payday lending had occurred as in the latter, since all that must be done to convert one scenario to the other is relabel. Similarly, a customer who takes out twelve 1-week loans in a row, paying $20 each time, and a customer who takes out two 6-week loans at a cost of $120 each, should be treated similarly. Though superficially the former had 11 rollovers while the latter had only one, in each case the customer spent exactly 12 consecutive weeks in debt and paid $240.
In order to construct outcome variables that are agnostic to labeling I depart slightly from standard practice. 5 This definition is agnostic about patterns of borrowing in the interim. For instance, it makes no difference if a customer takes many short loans or fewer longer loans, or whether a customer takes consecutive 2-week loans, or 1-week loans on alternating weeks. All that matters is that indebtedness 90 days later is a positive indication of propensity to stay in debt.
Additionally, all simultaneous loans are combined and considered as single loans. This is done in order to facilitate comparisons in both the volume and average size of loans across regulatory regimes that allow and don’t allow simultaneous borrowing.
Consistently coding state regulations themselves presents another challenge. For analytical tractibility, complex regulations must necessarily be simplified and regularized. The challenge is to do this in such a way as to capture the important details and distinctions of the laws, while eliding less relevant details. Tables 2 and 3 present a simplified matrix of state payday regulations. Explanations of how regulations were interpreted to create the variables in this matrix, as well as how the information in the matrix was further coded in order to perform regression analyses, are provided in detail in Appendix A.