A Dynamic Look at Subprime Loan Performance

Does delinquency have any predictive power for the future performance of a mortgage? Analysis of a sample of subprime mortgages from the Loanperformance database on securitized private-label pool collateral using a two-step estimation procedure to control for the endogeneity of delinquency reveals strong support for the distressed prepayment theory that very delinquent loans are more likely to prepay than to default and that prepayment rates increase substantially as delinquency intensity increases. While delinquency leads predominantly to termination of a loan through prepayment, negative equity leads to termination through default. Does delinquency have any predictive power for the future performance of a mortgage? Analysis of a sample of subprime mortgages from the Loanperformance database on securitized private-label pool collateral using a two-step estimation procedure to control for the endogeneity of delinquency reveals strong support for the distressed prepayment theory that very delinquent loans are more likely to prepay than to default and that prepayment rates increase substantially as delinquency intensity increases. While delinquency leads predominantly to termination of a loan through prepayment, negative equity leads to termination through default

The live method for generalized additive volatility models.

We investigate a new separable nonparametric model for time series, which includes many autoregressive conditional heteroskedastic (ARCH) models and autoregressive (AR) models already discussed in the literature. We also propose a new estimation procedure called LIVE, or local instrumental variable estimation, that is based on a localization of the classical instrumental variable method. Our method has considerable computational advantages over the competing marginal integration or projection method. We also consider a more efficient two-step likelihood-based procedure and show that this yields both asymptotic and finite-sample performance gains.

Efficient Estimation of a Dynamic Error-Shock Model

This paper is concerned with the estimation of the parameters in a dynamic simultaneous equation model with stationary disturbances under the assumption that the variables are subject to random measurement errors. The conditions under which the parameters are identified are stated. An asymptotically efficient frequency-domain class of instrumental variables estimators is suggested. The procedure consists of two basic steps. The first step transforms the model in such a way that the observed exogenous variables are asymptotically orthogonal to the residual terms. The second step involves an iterative procedure like that of Robinson [13].

TECHNICAL EFFICIENCY OF RURAL WATER UTILITIES

Technical efficiency of rural water utilities is determined using frontier production functions. An indirect production function is developed to model the two-step production process of a local government-controlled firm. Data from 26 rural Nevada water utilities are used to estimate inefficiency in terms of firm-specific variables. A multistep estimation procedure is used instead of single-step maximum likelihood estimation. Model selection tests are used to choose the best model. Privately owned utilities are most efficient; self-governing water districts are the least efficient. Municipal governments operate the most and least efficient utilities.Resource /Energy Economics and Policy,

ESTIMATION OF A DEMAND SYSTEM WITH LIMITED DEPENDENT VARIABLES

The study employs the full-information maximum-likelihood method to estimate a censored translog demand system. U.S. household consumption of steak, roast, and ground beef are used to demonstrate the application of the estimation procedure. The proposed methodology produces more efficient estimates than the popular two-step procedures found in demand literature.Demand and Price Analysis,