			Home About us Contact

Simple Version (simple + version)

Distribution by Scientific Domains

Business, Economics, Finance and Accounting	50%

Selected Abstracts

A re-examination of the excess smoothness puzzle when consumers estimate the income process

JOURNAL OF FORECASTING, Issue 5 2001
Anurag N. Banerjee
Abstract The excess smoothness puzzle is explored using a simple version of the permanent income hypothesis. The new feature is that consumers do not know the observed data-generating process for income. Instead they estimate the income process every period using the past income data and update their income forecasts as new data arrive. Two scenarios are examined: first, where the income has a linear deterministic trend and second, where the income has a constant trend. There is a misspecification bias in the estimate of the marginal propensity to consume (MPC). This bias is of second-order importance in the first scenario while it is of first-order importance in the second. We conclude that the second scenario, which may be relevant for less developed countries, may offer a potential solution to the excess smoothness puzzle. Copyright © 2001 John Wiley & Sons, Ltd. [source]

Direct parametric inference for the cumulative incidence function

JOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES C (APPLIED STATISTICS), Issue 2 2006
Jong-Hyeon Jeong
Summary., In survival data that are collected from phase III clinical trials on breast cancer, a patient may experience more than one event, including recurrence of the original cancer, new primary cancer and death. Radiation oncologists are often interested in comparing patterns of local or regional recurrences alone as first events to identify a subgroup of patients who need to be treated by radiation therapy after surgery. The cumulative incidence function provides estimates of the cumulative probability of locoregional recurrences in the presence of other competing events. A simple version of the Gompertz distribution is proposed to parameterize the cumulative incidence function directly. The model interpretation for the cumulative incidence function is more natural than it is with the usual cause-specific hazard parameterization. Maximum likelihood analysis is used to estimate simultaneously parametric models for cumulative incidence functions of all causes. The parametric cumulative incidence approach is applied to a data set from the National Surgical Adjuvant Breast and Bowel Project and compared with analyses that are based on parametric cause-specific hazard models and nonparametric cumulative incidence estimation. [source]

Import Quotas and Entry Deterrence

AUSTRALIAN ECONOMIC PAPERS, Issue 2 2000
Neil Campbell
Using a simple version of the Milgrom and Roberts entry deterrence model, it is shown that adjusting a quota so that a greater volume of imports is allowed, can facilitate entry into the domestic industry. That is, the easing of a quota, can cause the domestic incumbent to shift from deterring entry to accommodating entry. [source]

Jacobian mapping between vertical coordinate systems in data assimilation

THE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 627 2007
Y. J. Rochon
Abstract Radiances measured by remote-sensing instruments are now the largest component of the atmospheric observation network. The assimilation of radiances from nadir sounders involves fast radiative transfer (RT) models which project profiles provided by forecast models onto the observation space for direct comparison with the measurements. One of the features typically characterizing fast RT models is the use of a fixed vertical coordinate. If the vertical coordinate of the RT model is not identical to that used by the forecast model, an interpolation of forecast profiles to the RT model coordinate is necessary. In variational data assimilation, the mapping of the Jacobians (derivatives of the RT model output with respect to its inputs) from the RT model coordinate to the forecast model coordinate is also required. This mapping of Jacobians is accomplished through the adjoint of the forecast profile interpolator. As shown, the nearest-neighbour log-linear interpolator commonly used operationally can lead to incorrect mapping of Jacobians and, consequently, to incorrect assimilation. This incorrect mapping occurs as a result of leaving out intermediate levels in the interpolation. This problem has been previously masked in part through the smoothing effect of forecast-error vertical correlations on the analysis increments. To solve this problem, two simple versions of an interpolator relying on piecewise log-linear weighted averaging over the layers are investigated. Both markedly improve Jacobian mappings in the assimilation of observations, with one being slightly favoured over the other. This interpolator is being incorporated into the RTTOV model used by several operational weather forecasting centres. Copyright © 2007 Crown in the right of Canada. Published by John Wiley & Sons, Ltd. [source]