Learning in the Credit Card Market
By Sumit Agarwal, John C. Driscoll, Xavier Gabaix, David Laibson. 2013
184 citations recorded by the source corpus.
Subfields: Finance, Media Technology, Strategy and Management
View Paper: https://www.semanticscholar.org/paper/8a94544d20e291494a7cec8913c252ea0f36a293
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Citations in the corpus
- FINANCIAL LITERACY, FINANCIAL EDUCATION AND ECONOMIC OUTCOMES (2012, unknown): “…is consistent with the acquisition of increased financial decision-making capital over time, either formally or through learning from experience (Agarwal et al. 2011), but the reversal at older ages highlights the natural limits that the aging process places on individuals’ financial…”
- Defaults and Donations: Evidence from a Field Experiment (2019, background): “4For example, studies of credit card demand have found that consumers do not take various credit card fees into account (Agarwal et al., 2008) and tend to overvalue introductory “teaser (interest) rates” (Ausubel 1999 and Shui and Ausubel 2004) when choosing a credit card.”
- Are Retail Traders Compensated for Providing Liquidity (2016, unknown): “A small select group of retail traders however manage to generate absolute performance (Barber et al., 2014), with some persistence (Coval et al., 2005). Linnainmaa (2010) finds losses on limit orders and gains on market orders in Finland, for portfolios long (short) in stocks that individuals on ag”
- Recency, records and recaps: learning and non-equilibrium behavior in a simple decision problem (2014, unknown): “On the other hand, there is evidence of significant economic costs due to incomplete learning and recency bias in contexts such as credit card late fees [Agarwal et al. 2008], stock market participation [Malmendier & Nagel 2011] and IPO investment [Kaustia & Knupfer 2008].”
- The short-run and long-run effects of behavioral interventions: Experimental evidence from energy conservation (2014, unknown): “The action and backsliding in response to home energy reports is reminiscent of evidence that consumers “learn” about late fees and other charges as we incur them, but we act as if we forget that knowledge over time (Agarwal et al. 2013; Haselhuhn et al. 2012). Similarly, Gallagher (2013) shows that”
- Dynamic Salience with Intermittent Billing: Evidence from Smart Electricity Meters (2014, unknown): “Such “recency effects” of intermittently salient information, or effects that decline as time passes, have been found with late payment fees for credit cards in Agarwal et al. (2013) and personalized home energy reports with normative and educational messages in Allcott and Todd (2012).”