DETERMINING THE APPROPRIATE DISCOUNT RATES IN PURE CAPITAL RATIONING

This paper proposes an interpretation of the pure capital rationing problem as it is faced by many managers in decentralized firms in which budgets serve as the principal means of control. It is argued that the appropriate objective for situations such as these is the maximization of either undiscounted earnings over the planning horizon or total value of the investments at the horizon. When either objective function is used in conjunction with the frequently encountered linear programming models for the capital rationing problem, shadow prices result which give rise to discount rates that will reproduce the optimal solution using discounted cash flow as a criterion. These results are then used as a means for clarifying several confusing and misleading statements that have appeared in the literature.     

SPECTRAL ANALYSIS IN BUSINESS FORECASTING: THE WIENER-KOLMOGOROV METHOD *

The objective of this paper is to introduce the Wiener-Kolmogorov (WK) method to business researchers and to applied workers who have an interest in spectral techniques. It is seen that the advantage of the WK method is that it provides better forecasts than autoregressive regression analysis when the order of the true autoregressive process is large. The paper outlines the steps involved in the WK method. Also discussed is a labor-saving feature to guide one at the outset as to whether the WK algorithm should be used. A numerical example is given to illustrate the application of the method in time-series forecasting.     

A COMPARATIVE ANALYSIS OF THE PREDICTIVE ABILITY OF ADAPTIVE FORECASTING,RE-ESTIMATION,AND RE-IDENTIFICATION USING BOX-JENKINS TIME-SERIES ANALYSIS ON QUARTERLY EARNINGS DATA

This paper assesses the predictive ability of the Box-Jenkins methodology when utilized in an on-going setting. Three procedures are utilized to update the original forecasts generated from the Box-Jenkins models: adaptive forecasting, re-estimation, and re-identification. The results indicate that constant monitoring of the structure and parameters of the time-series models are necessary through time. It appears that adaptive forecasting techniques are insufficient to update BJ time-series models when used in conjunction with quarterly earnings data. Re-estimation is recommended as each new observation becomes available. Re-identification procedures are recommended on a less frequent basis.     

High precision implementation of Steck's recursion method for use in goodness-of-fit tests

Classical continuous goodness-of-fit (GOF) testing is employed for examining whether the data come from an assumed parametric model. In many cases, GOF tests assume a uniform null distribution and examine extreme values of the order statistics of the samples. Many of these statistics can be expressed by a function of the order statistics and the p-values amount to a joint probability statement based on the uniform order statistics. In this paper, we utilize Steck''s recursion method and propose two high precision computing algorithms to compute the p-values for these GOF statistics. The numerical difficulties in implementing Steck''s method are discussed and compared with solutions provided in high precision libraries.     

Young Adult Gambling Behaviors and their Relationship with the Persistence of ADHD

Young adulthood is a period renowned for engagement in impulsive and risky behaviors, including gambling. There are some indications that young adults exhibit higher gambling rates in comparison to older adults. Problem gambling has also been linked to ADHD. This longitudinal study examines the relationship between gambling and ADHD among an epidemiological sample of young adults (n = 235; males = 179, females = 56) aged 18-24. Results indicate that individuals who report childhood ADHD symptoms which persist into young adulthood experience greater gambling problem severity than participants with no ADHD or those with non-persistent ADHD.     

The Relation Between Popularity and Aggressive,Destructive, and Norm‐Breaking Behaviors: Moderating Effects of Athletic Abilities,Physical Attractiveness,and Prosociality

The aim of this study was to examine the relations between popularity and different types of aggressive, destructive, and norm‐breaking behaviors in a large cross‐sectional sample of adolescents (N=3,312, M age=13.60). We were interested in the extent to which the relations of these behaviors with popularity were moderated by positive features (i.e., athletic abilities, physical attractiveness, and prosociality). From a goal‐framing perspective, it was argued that positive features evoke positive affect, which in turn enhances the positive impact of aggressive, destructive, and norm‐breaking behaviors on popularity. The results supported our notion that these latter behaviors are especially related to popularity in adolescents who also exhibit positive features.     

Mark-specific hazard ratio model with missing multivariate marks

An objective of randomized placebo-controlled preventive HIV vaccine efficacy (VE) trials is to assess the relationship between vaccine effects to prevent HIV acquisition and continuous genetic distances of the exposing HIVs to multiple HIV strains represented in the vaccine. The set of genetic distances, only observed in failures, is collectively termed the ‘mark.’ The objective has motivated a recent study of a multivariate mark-specific hazard ratio model in the competing risks failure time analysis framework. Marks of interest, however, are commonly subject to substantial missingness, largely due to rapid post-acquisition viral evolution. In this article, we investigate the mark-specific hazard ratio model with missing multivariate marks and develop two inferential procedures based on (i) inverse probability weighting (IPW) of the complete cases, and (ii) augmentation of the IPW estimating functions by leveraging auxiliary data predictive of the mark. Asymptotic properties and finite-sample performance of the inferential procedures are presented. This research also provides general inferential methods for semiparametric density ratio/biased sampling models with missing data. We apply the developed procedures to data from the HVTN 502 ‘Step’ HIV VE trial.