FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2897074087> ?p ?o ?g. }

• W2897074087 abstract "Author(s): Chen, Baizhu | Advisor(s): Singh, Nirvikar | Abstract: This dissertation has three chapters, with emphasis on the efficiency of online lending using multiple identification strategies. The first chapter presents a theoretical model (1) to help illustrate the behavior of lenders and borrowers in a P2P market and (2) to derive a reduced form model for empirical analysis. In the model, borrowers decide whether or not to default. The benefit of default is that a borrower gets to increase consumption if he chooses not to repay. On the other hand, I assume that default imposes a direct utility loss on the borrower. This loss is assumed to be random and unobservable by lenders or anyone other than the borrower. Ex-ante, when lenders choose whether or not fund a loan, they compare the expected return of the loan vs. their opportunity costs. The opportunity cost is also assumed to be random and unobservable by others. Also, the expected return of the loan depends on lender’s subjective expectations of default risk. The subjective expectations are formulated based on the observed borrower characteristics and loan information. I present methods of testing whether the lenders’ subjective expectations of default is the same as the objective ones.In the second chapter, using a unique dataset of peer-to-peer (P2P) lending with detailed loan and borrower information, I study which borrower characteristics lenders value when choosing loans to fund, and whether lenders value characteristics that minimize the probability of default. In this online context, the researcher observes everything that the lender does, enabling unbiased estimation of borrower characteristics that lenders favor. However, estimating characteristics that predict loan default is problematic due to selection at the funding stage. I implement three strategies to address this issue: (1) restricting attention to borrower characteristics for which there is no evidence of selection in the first stage; (2) exploiting variation in the probability of funding caused by contemporaneous competition on the platform; and (3) bounding the default estimates in the style of Lee (2009). The results imply that P2P lenders consider employment borrower characteristics as most important when making funding decisions, but disregard several characteristics that are valuable predictors of default risk. Specifically, lenders overestimate the importance of verified employment information, and underestimate the importance of verified education level and marital status.The third chapter estimates the effect of credit insurance in the peer-to-peer (P2P) lending market. Online lending is a fast growing area of finance. However, it is often plagued by asymmetric information problems and high credit risk, especially in developing countries that do not have well-established financial and credit rating systems. To address this issue, some Chinese P2P marketplaces have incorporated loan insurance into their online platforms. We estimate the treatment effects of credit insurance on the P2P market by exploiting a unique quasi-experiment. Specifically, loan guarantees gradually became available on a top Chinese P2P lending platform to borrowers from 31 major cities between 2012 and 2014 through 12 waves of business expansion. Our empirical results suggest that the availability of credit insurance resulted in significant, strong, and persistent treatment effects on the market demand and supply. The adoption of credit insurance was associated with dramatic increases in the number of loan listings, funding probability per loan, and bidding amount per lender. The average funding time per loan decreased by about 170 hours." @default.
• W2897074087 created "2018-10-26" @default.
• W2897074087 creator A5024863046 @default.
• W2897074087 date "2018-01-01" @default.
• W2897074087 modified "2023-09-27" @default.
• W2897074087 title "Essays on the Efficiency of Online Lending" @default.
• W2897074087 hasPublicationYear "2018" @default.
• W2897074087 type Work @default.
• W2897074087 sameAs 2897074087 @default.
• W2897074087 citedByCount "0" @default.
• W2897074087 crossrefType "journal-article" @default.
• W2897074087 hasAuthorship W2897074087A5024863046 @default.
• W2897074087 hasConcept C10138342 @default.
• W2897074087 hasConcept C119857082 @default.
• W2897074087 hasConcept C122251271 @default.
• W2897074087 hasConcept C139719470 @default.
• W2897074087 hasConcept C144133560 @default.
• W2897074087 hasConcept C149782125 @default.
• W2897074087 hasConcept C151730666 @default.
• W2897074087 hasConcept C162118730 @default.
• W2897074087 hasConcept C162324750 @default.
• W2897074087 hasConcept C175444787 @default.
• W2897074087 hasConcept C178350159 @default.
• W2897074087 hasConcept C2776291640 @default.
• W2897074087 hasConcept C2777764128 @default.
• W2897074087 hasConcept C2779343474 @default.
• W2897074087 hasConcept C2779806880 @default.
• W2897074087 hasConcept C2780695315 @default.
• W2897074087 hasConcept C41008148 @default.
• W2897074087 hasConcept C69637215 @default.
• W2897074087 hasConcept C71387314 @default.
• W2897074087 hasConcept C86803240 @default.
• W2897074087 hasConceptScore W2897074087C10138342 @default.
• W2897074087 hasConceptScore W2897074087C119857082 @default.
• W2897074087 hasConceptScore W2897074087C122251271 @default.
• W2897074087 hasConceptScore W2897074087C139719470 @default.
• W2897074087 hasConceptScore W2897074087C144133560 @default.
• W2897074087 hasConceptScore W2897074087C149782125 @default.
• W2897074087 hasConceptScore W2897074087C151730666 @default.
• W2897074087 hasConceptScore W2897074087C162118730 @default.
• W2897074087 hasConceptScore W2897074087C162324750 @default.
• W2897074087 hasConceptScore W2897074087C175444787 @default.
• W2897074087 hasConceptScore W2897074087C178350159 @default.
• W2897074087 hasConceptScore W2897074087C2776291640 @default.
• W2897074087 hasConceptScore W2897074087C2777764128 @default.
• W2897074087 hasConceptScore W2897074087C2779343474 @default.
• W2897074087 hasConceptScore W2897074087C2779806880 @default.
• W2897074087 hasConceptScore W2897074087C2780695315 @default.
• W2897074087 hasConceptScore W2897074087C41008148 @default.
• W2897074087 hasConceptScore W2897074087C69637215 @default.
• W2897074087 hasConceptScore W2897074087C71387314 @default.
• W2897074087 hasConceptScore W2897074087C86803240 @default.
• W2897074087 hasLocation W28970740871 @default.
• W2897074087 hasOpenAccess W2897074087 @default.
• W2897074087 hasPrimaryLocation W28970740871 @default.
• W2897074087 hasRelatedWork W143127431 @default.
• W2897074087 hasRelatedWork W2014575815 @default.
• W2897074087 hasRelatedWork W2043252556 @default.
• W2897074087 hasRelatedWork W2113679958 @default.
• W2897074087 hasRelatedWork W2126059816 @default.
• W2897074087 hasRelatedWork W2145478089 @default.
• W2897074087 hasRelatedWork W2193693952 @default.
• W2897074087 hasRelatedWork W2295583595 @default.
• W2897074087 hasRelatedWork W2413071179 @default.
• W2897074087 hasRelatedWork W2474339611 @default.
• W2897074087 hasRelatedWork W2610668331 @default.
• W2897074087 hasRelatedWork W2893331683 @default.
• W2897074087 hasRelatedWork W2960184114 @default.
• W2897074087 hasRelatedWork W2969458352 @default.
• W2897074087 hasRelatedWork W3121912353 @default.
• W2897074087 hasRelatedWork W3125953204 @default.
• W2897074087 hasRelatedWork W3126134856 @default.
• W2897074087 hasRelatedWork W3189867295 @default.
• W2897074087 hasRelatedWork W652071198 @default.
• W2897074087 hasRelatedWork W1581160321 @default.
• W2897074087 isParatext "false" @default.
• W2897074087 isRetracted "false" @default.
• W2897074087 magId "2897074087" @default.
• W2897074087 workType "article" @default.