Joint Estimation Technique Research Articles

The Economics of Fish Consumption Advisories: Insights from Revealed and Stated Preference Data

Measuring how fish consumption advisories affect angler’s utility has proven difficult. Relying on stated preference (SP) data is problematic because of hypothetical bias. Revealed preference (RP) data benefits from using actual behavior; however, co-linearity often makes it difficult to model the array of advisory severity levels across different species and catch rates. The array of advisories also makes traditional joint estimation impractical. This paper describes an alternative joint estimation technique, based on an index of SP parameter, that we used for estimating the effect of fish consumption advisories on the Fox River/Green Bay.

Paleomagnetism of the southwestern U.S.A. recorded by 0–5 Ma igneous rocks

The issue of permanent nondipole contributions to the time‐averaged field lies at the very heart of paleomagnetism and the study of the ancient geomagnetic field. In this paper we focus on paleomagnetic directional results from igneous rocks of the southwestern U.S.A. in the age range 0–5 Ma and investigate both the time‐averaged field and its variability about the mean value. Several decades of work in the southwestern United States have resulted in the publication of paleomagnetic data from over 800 individual paleomagnetic sites. As part of a new investigation of the San Francisco Volcanics, we collected paleomagnetic samples from 47 lava flows, many of which have been previously dated. The new data combined with published data are highly scattered. Contributions to the scatter were considered, and we find that removal of data sets from tectonically active areas and judicious selection according to Fisher's [1953] precision parameter results in an axially symmetric data distribution with normal and reverse modes that are indistinguishable from antipodal. Monte Carlo simulations suggest that a minimum of 5 samples per site are needed to estimate the precision parameter sufficiently accurately to allow its use as a determinant of data quality. Numerical simulations from statistical paleosecular variation models indicate the need for several hundred paleomagnetic sites to get an accurate determination of the average field direction and are also used to investigate the directional bias that results from averaging unit vectors rather than using the full field vector. Average directions for the southwestern U.S.A. show small deviations from a geocentric axial dipole field, but these cannot be considered statistically significant. Virtual geomagnetic pole (VGP) dispersions are consistent with those from globally distributed observations analyzed by McElhinny and McFadden [1997]. However, a systematic investigation of the effect of imposing a cutoff on VGPs with large deviations from the geographic axis indicates that while it may reduce bias in calculating the average direction, such a procedure can result in severe underestimates of the variance in the geomagnetic field. A more satisfactory solution would be to use an unbiased technique for joint estimation of the mean direction and variance of the field distribution.

Estimating incidence of dementia subtypes: assessing the impact of missed cases

In many community-based studies on the incidence of dementia, a target population is screened and a subsample is clinically evaluated at baseline and follow-up. Incidence rates are affected by missed cases at both exams and this complicates the estimation of these rates. Recent work proposes a regression-based technique for joint estimation of prevalence and incidence and suggests the use of surrogate information obtained on the entire cohort at both times to calculate the expected score equation contribution for individuals missing clinical exams at one or both times. This helps to quantify the impact of missed diagnosis upon the incidence estimates and their confidence intervals. We extend this work to the setting of subtypes of dementia for use in the Honolulu–Asia Aging Study on incidence of dementia. The technique is applied using two separate models for the effect of age on dementia incidence. Subsequently, shrinkage estimation methods are applied to provide more precise estimates of the rates. Published in 2000 by John Wiley & Sons, Ltd.

Monetary anticipation and the demand for money in the U.K.: Testing rationality in the Shock‐Absorber hypothesis

AbstractThe Carr‐Darby shock‐absorber hypothesis that unanticipated changes in the money supply cause changes in real balances but anticipated changes have a unit impact on the price level (and therefore leave real balances unchanged) is tested using two‐step and joint estimation techniques. For the U.K., two‐step methods appear to support the shock‐absorber hypothesis, but the superior joint estimation technique decisively rejects the hypothesis, particularly the implicit rational expectations cross‐equation restrictions.

Asymptotic Efficiencies of Three Methods of Estimation for the Inverse Gaussian-Poisson Distribution

SUMMARY The two parameters of the inverse Gaussian-Poisson distribution may be estimated by (a) sample moments, (b) the proportion of zeros and the mean in the sample, and (c) by maximum likelihood. In the paper the asymptotic variances for all three joint estimation techniques and the corresponding efficiencies for methods (a) and (b) are derived. For 0 > 0 90 and oc 0 90, both methods (a) and (b) are very inefficient and the maximum likelihood estimation technique should be employed.

Asymptotic efficiencies of three methods of estimation for the inverse Gaussian-Poisson distribution

SUMMARY The two parameters of the inverse Gaussian-Poisson distribution may be estimated by (a) sample moments, (b) the proportion of zeros and the mean in the sample, and (c) by maximum likelihood. In the paper the asymptotic variances for all three joint estimation techniques and the corresponding efficiencies for methods (a) and (b) are derived. For 0 > 0 90 and oc 0 90, both methods (a) and (b) are very inefficient and the maximum likelihood estimation technique should be employed.

The determinants of intra-urban household mobility

This study integrates the sociological and economic approaches in explaining mobility. Households are hypothesized to be more likely to move when they have experienced some unforeseen change in their short-run equilibrium. Linear probability modelsof mobility are estimated using the Zellner-Lee joint estimation technique for a pooled time-series of data collected on a cross section of 3187 San Francisco households. Households make their residential and workplace mobility decisions interdependently. The probability of residential mobility increases with a change in workplace, family size, and changes in family size and decreases with age and housing market tightness. The probability of workplace mobility increases with a change in residence and labor market tightness, decreases with age, and varies by occupation. The effects of income and education are unclear.