Dean Corbae

Band Spectral Regression with Trending Data

Band spectral regression with both deterministic and stochastic trends is considered. It is shown that trend removal by regression in the time domain prior to band spectral regression can lead to biased and inconsistent estimates in models with frequency dependent coefficients. Both semiparametric and nonparametric regression formulations are considered, the latter including general systems of two-sided distributed lags such as those arising in lead and lag regressions. The bias problem arises through omitted variables and is avoided by careful specification of the regression equation. Trend removal in the frequency domain is shown to be a convenient option in practice. An asymptotic theory is developed and the two cases of stationary data and cointegrated nonstationary data are compared. In the latter case, a levels and differences regression formulation is shown to be useful in estimating the frequency response function at nonzero as well as zero frequencies.

Laryngeal Cancer Cost Analysis: Association of Case‐Mix and Treatment Characteristics With Medical Charges

Objectives: To examine the relationship of various pretreatment case‐mix characteristics and treatment modalities with medical charges incurred during diagnosis, treatment, and 2‐year follow‐up for patients with laryngeal cancer.

Cost-identification analysis in oral cavity cancer management

The objectives of this study were to investigate potential relationships between pretreatment patient-mix characteristics, treatment modalities, and costs generated during the pretreatment work-up, treatment, and 1-year follow-up periods for patients with oral cavity cancer (OCC). Another objective was to identify potential areas for cost reduction and improved resource allocation in the management of OCC patients. Using a retrospective cohort of 73 patients with OCC, pretreatment patient-mix characteristics and treatment modalities were evaluated in relation to university-based charges incurred during the pretreatment evaluation, treatment, and 1 -year follow-up periods. Simple regression and stepwise multiple regression analyses were used to develop predictive models for cost based on independent variables, including age, AJCC TNM clinical stage, smoking history, American Society of Anesthesiologists (ASA) class, comorbidity as defined by the Kaplan-Feinstein grade and treatment modality. The dependent measurements included all physician, office, and hospital charges incurred at the University of Iowa Hospitals and Clinics during the pretreatment evaluation, treatment, and follow-up periods, as well as the total pretreatment through 1-year follow-up management costs. Independent variables that were identified as being significantly associated with treatment costs included T classification, N classification, TNM stage, unimodality versus multimodality treatment, and the Kaplan-Feinstein comorbidity grade. Age, smoking status, and ASA class were not significantly associated with costs. The majority of the OCC management costs were incurred during the treatment period. The most substantial decreases in management costs for OCC will be realized through measures that allow identification and treatment of disease at an early stage, in which single-modality treatment may effectively be used. Resource allocation for OCC should support the investigation of measures through which the diagnosis and treatment of OCC at the earliest possible stage is facilitated. The presence of comorbid illness is a significant component in the determination of management costs for OCC and should be included in analyses of resource allocation for OCC. The singular diagnosis of OCC encompasses a wide range of patient illness severity, and diagnosis-related reimbursement schemes for OCC treatment should optimally differentiate between early and advanced stage disease.

A reexamination of the consumption function using frequency domain regressions

This paper reexamines the permanent income hypothesis (PIH) in the frequency domain. In contrast to some time domain tests, our frequency domain approach provides an explicit and natural test ofboth the permanentand transitory implications of the PIH for jointly nonstationary consumption and income data. Using a simple theoretical model, we demonstrate that the PIH implies the marginal propensity to consume (MPC) out of zero frequency income is unity. The PIHalso implies that the theoretical MPC out of transitory (or high frequency) income is smaller than the long-run MPC. These theoretical restrictions are natural implications of Friedmans hypothesis that agents consume out of permanent or low frequency income and (dis)save out of transitory or high frequency income.We test this full set of restrictions directly using spectral regression techniques. Under our set of assumptions, the derived disposable income process is shown to have a unit root and to be cointegrated with consumption. We therefore employ a systems spectral regression procedure that accommodates stochastic trends in the consumption and income series as well as the joint dependence in these series. In view of the relatively recent development of these systems spectral estimators, we also conduct Monte Carlo simulations across both low and high frequencies to assess properties of the estimator relative to established single equation techniques. New empirical estimates of the consumption function and tests of the PIH based on systems spectral regression methods are reported for U.S. aggregate consumption and income data over the period 1948–1993. The empirical results provide some evidence for the theoretical implications of the PIH.