AbstractsEconomics

Influenced by the recent, ongoing financial crisis spreading across the world's economies, my dissertation studies aspects of the connections between securitization – originating and selling loans – in the banking sector and economic instability. In the first chapter, “Bank Monitoring and Liquidity in the Secondary Market for Loans”, I study transactional loans and traditional–relationship loans in a dynamic lending model. In the model, since transactional loans are easier to resell, a bank's benefit from transactional lending over relationship lending is increasing in secondary market loan liquidity (investors' willingness to pay). The relative payoff is also increasing in the proportion of banks that choose transactional lending because lower quality borrowers prefer transactional lenders, who monitor them less. When liquidity rises above a given threshold, all banks switch to transactional lending. However, greater liquidity also increases the economy–wide default risk since banks reduce their monitoring effort. If the latter effect is strong enough, securitization can lower welfare. The previous study suggests that the problems in securitization may come from information asymmetry in both the primary and secondary loan markets. My second chapter, “Securitization and Lending Competition” (with David Frankel), studies the effects of securitization on interbank lending competition when banks see private signals of local applicants' repayment chances. We find that if banks cannot securitize, the outcome is efficient: they lend to their most creditworthy local applicants. With securitization, banks lend also to remote applicants with strong observables in order to lessen the lemons problem they face in selling their securities. This reliance on observables is inefficient and raises the conditional and unconditional default risk. Finally, Chapter 3, “Credit Termination and the Technology Bubbles”, studies the financial instability from a different angle. I consider a credit cycles model in which firms face technology shocks to the riskiness of different types of projects. The new project arriving is more attractive to the firms but even riskier. The riskiness of the new project is not observed by banks as occurred during the technology bubbles. After observing a higher default rate, banks deny future loans to entrepreneurs more often in order to affect their choice of projects ex ante. The model is used to explain the boom–and–bust of the dot–com bubble in the late 1990s.