Purpose – The purpose of this paper is to provide additional evidence that housing prices significantly impact aggregate refinancing and thus directly influence mortgage termination. Design/methodology/approach – Regression analysis is applied to examine refinancing activity in US cities....

This dissertation focuses on the mortgage default behavior and the valuation of distressed properties. Three essays are included.The first essay uses New Orleans foreclosure data, where each property has three appraisals, to investigate the factors affecting appraisal bias and accuracy, and to...

There is near universal agreement that estimates and inferences from spatial regression models are sensitive to particular specifications used for the spatial weight structure in these models. We find little theoretical basis for this commonly held belief, if estimates and inferences are based...

Most spatial econometrics work focuses on spatial dependence in the regressand or disturbances. However, LeSage and Pace (2009) show that the bias from applying OLS to a regressand generated from a spatial autoregressive process was exacerbated by spatial dependence in the regressor. Also, the...

This paper investigates the influence of expected foreclosure duration on a borrower's future default propensity. We use the lagged actual time-varying state-level foreclosure times as proxies for borrower's expected benefit from default as the form of "free rent.'' While existing literature...

House prices regression residuals often display spatial dependence, but historically mortgage models (which employ house prices) assume independence and use only the own borrower/loan characteristics. This manuscript uses a spatial probit model to investigate spatial dependence among the...

A number of authors have suggested that omitted variables affect spatial regression methods less than ordinary least-squares (OLS). To explore these conjectures, we derive an expression for OLS omitted variable bias in a univariate model with spatial dependence and show that positive dependence...

While salary benchmarking is widely used to help set compensation, there has been little econometric modeling of peer-group identification and the impacts of benchmarking on the compensation decision. We adapt some empirical tools from spatial econometrics to analyze compensation decisions...

This article provides a matrix representation of the adjustment grid estimator. From this representation, one can invoke the Gauss Markov theorem to examine the efficiency of the ordinary least squares (OLS) and the grid estimator that uses OLS estimates of the adjustments (the quot;plug-inquot;...

Parametric estimators, such as OLS, attain high efficiency for well-specified models. Nonparametric estimators greatly reduce specification error but at the cost of efficiency. Semiparametric estimators compromise between these dual goals of efficiency and specification error. Semiparametric...