Journal
JOURNAL OF ECONOMICS AND BUSINESS
Volume 61, Issue 1, Pages 51-69Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.jeconbus.2008.01.001
Keywords
Transactions data; Censored data; Tobit model; Log-normal distribution; Consumer credit; Payment schedule
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The rent-to-own (RTO) industry, by offering immediate access to household goods for a small periodic fee with no credit check or down payment, has strong appeal to lowincome and financially distressed consumers. An important policy question is whether an RTO agreement is used as a rental/ lease with build-in purchase option or as something more akin to an installment loan. Given the embedded options to return the item or to purchase it early, the actual rent paid by RTO customers is substantially lower than the oft-reported total rent which assumes that agreements go to term. We employ a log-normal censored regression model to analyze the influence of customer demographics as well as the transactional details of the contract on the rent paid by consumers using rent-to-own. Our main conclusions are (1) it is the working poor that are likely to pay more rent, (2) there appears to be a clientele effect with customers paying more rent under bi-weekly and monthly, as opposed to weekly, payment schedules, and (3) customers who exhibit delinquency in making contractual payments generally end up paying more rent. Further, our data allows some observations on annual percentage rates by illustrating the business risk present for RTO stores as well as the cross-subsidization of consumers. (C) 2008 Elsevier Inc. All rights reserved.
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