The turmoil that started with increased defaults in the subprime mortgage market has generated instability in the financial system around the world. To better understand the root causes of this financial instability, we quantify the relative importance of various drivers behind subprime borrowers' decision to default. In our econometric model, we allow borrowers to default either because doing so increases their lifetime wealth or because of short-term budget constraints, treating the decision as the outcome of a bivariate probit model with partial observability. We estimate our model using detailed loan-level data from LoanPerformance and the Case-Shiller home price index. According to our results, one main driver of default is the nationwide decrease in home prices. The decline in home prices caused many borrowers' outstanding mortgage liability to exceed their home value, and for these borrowers default can increase their wealth. Another important driver is deteriorating loan quality: The increase of borrowers with poor credit and high payment to income ratios elevates default rates in the subprime market. We discuss policy implications of our results. Our findings point to flaws in the securitization process that led to the current wave of defaults. Also, we use our model to evaluate alternative policies aimed at reducing the rate of default.
Multiproduct firms can set separate prices for all possible bundled combinations of its products "mixed bundling"). However, this is impractical for firms with more than a few products, because the number of prices increases exponentially with the number of products. We find that simple pricing strategies are often nearly optimal. Specifically, we show that bundle-size pricing--setting prices that depend only on the size of bundle purchased--tends to be more profitable than offering the individual products priced separately and tends to closely approximate the profits from mixed bundling. (JEL D24, D42, L11, L13, L25)
How has the entry of satellite television affected the pricing and product quality of incumbent cable firms' programming packages? I estimate a model in which firms compete over both price and product quality (as determined by what channels are offered). Satellite entry typically causes cable firms to raise quality and lower price. However, in some markets, cable optimally responds by raising both price and quality or by lowering both price and quality. A counterfactual scenario that eliminates quality competition results in, on average, softer price competition and lower aggregate consumer surplus, but greater surplus for consumers with weaker preferences for quality. Copyright (c) 2010, RAND..
Differences in the organizational structure of CMBS loan originators may reflect differences in the incentives they face for underwriting risky loans. We treat an originator's type-that is, commercial bank, investment bank, insurance company, finance company, conduit lender, or foreign-owned entity-as a proxy for incentives related to warehousing risk, balance sheet lending, and regulatory constraints. After controlling for observable credit characteristics of over 30,000 loans securitized into CMBS after 1999, we find considerable differences in loan performance across originator types. The results suggest that moral hazard-captured by lack of warehousing risk-negatively affected the quality of loans underwritten by conduit lenders. On the other hand, despite opportunities for adverse selection, balance sheet lenders-commercial banks, insurance companies and finance companies-actually underwrote higher quality loans.
We study identi…cation and estimation of …nite-horizon dynamic discrete choice models with a terminal action. We …rst demonstrate a new set of conditions for the identi…cation of agents' time preferences. Then we prove conditions under which the per-period utilities are identi…ed for all actions in the agent's choice-set, without having to normalize the utility for one of the actions. Finally, we develop a computationally tractable semiparametric estimator. The estimator uses a two-step approach that does not use either backward induction or forward simulation. Our methodology can be implemented using standard statistical packages without the need to write specialized computational routines, as it involves linear (or nonlinear) projections only. Monte Carlo studies demonstrate the superior performance of our estimator compared with existing two-step estimation methods.Monte Carlo studies further demonstrate that the ability to identify the per-period utilities for all actions is crucial for counterfactual predictions. As an empirical illustration, we apply the estimator to the optimal default behavior of subprime mortgage borrowers, and the results show that the ability to identify the discount factor, rather than assuming an arbitrary number as typically done in the literature, is also crucial for obtaining correct counterfactual predictions. These …ndings highlight the empirical relevance of key identi…cation results of the paper.
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