On Jointly Estimating Parameters and Missing Data by Maximizing the Complete-Data Likelihood

One approach to handling incomplete data occasionally encountered in the literature is to treat the missing data as parameters and to maximize the complete-data likelihood over the missing data and parameters. This article points out that although this approach can be useful in particular problems, it is not a generally reliable approach to the analysis of incomplete data. In particular, it does not share the optimal properties of maximum likelihood estimation, except under the trivial asymptotics in which the proportion of missing data goes to zero as the sample size increases.     

On Regression Analysis with Data Cleaning via Trimming,Winsorization, and Dichotomization

ABSTRACT

In a two-variable regression model setup, we examine in this paper the effects of trimming and winsorization and dichotomization of the independent variable on the regression estimates and the efficiency of the regression estimation. These results have direct implications in the accounting literature when dealing with the effects of analyst forecast errors on stock returns.     

Minicommunications

This section of the periodical is reserved for Conclusions (Results), Comments, Conjectures, and Microcommunications. Contributions will be welcomed and might even be printed!     

Military Triumph, Racial Transcendence, and Colin Powell

A "black kid of no early promise," Colin Powell became the youngestgeneral in the U.S. Army, and then in short order national securityadvisor, chairman of the Joint Chiefs of Staff, and the nation’ssecretary of state. What does this extraordinary story revealabout contemporary American political life? Analyzing surveyssupplied by the National Election Study and the National BlackElection Study, we first establish that Powell’s rapidrise to prominence is matched by his remarkable popularity amongthe American public. Next, we develop and test two possibleexplanations for Powell’s popularity. One supposes thatthe secret to Powell’s high standing with the public liesin his association with success on the battlefield: Powell asthe victorious general. The other explanation invokes racialprogress, the disappearance of racism among whites, and thedecline of identity politics among blacks: Powell as raciallytranscendent. In the final section of the article, informedby our results, we offer some speculations about American politicstoday—about the political implications of military accomplishmentand about the multiplicity of conditions that are required forAmericans to "see through" race.     

AN ANALYSIS OF PORTFOLIO REVISION STRATEGIES UTILIZING VARIABLE REVISION INTERVALS*

This paper investigates portfolio revision with an emphasis on the decision of when to revise. A statistical technique based on the sequential analysis of the time series of portfolio return relatives determines when revision is to occur. The technique detects changes in the time series which are an indication that the underlying generating process of the time series has changed and that the portfolio should be, if necessary, revised. Thus, the length of the revision interval is variable and a function of the data. The statistical technique is utilized in conjunction with three portfolio revision strategies. These three revision strategies are compared to a buy and hold policy over three nonoverlapping, 12-year investment horizons. The basis of comparison is the net terminal values which include adjustments for transaction costs and taxes. The sensitivity of the statistical technique to its parameters is also analyzed.     

A DYNAMIC OPTIMIZATION MODEL FOR PLANNING IN A MULTI-PRODUCT ENVIRONMENT

This paper describes an extension of the product mix problem and explicitly considers situations where demand can fluctuate over time. The additional decision variables and constraints that must be considered are described, and a revised objective function is discussed. The solution to the proposed linear programming formulation is compared to the traditional simulation and illustrates the potential for increased profits.     

Management Policies to Improve the Effectiveness of Multi-Station Service Organizations*

A SLAM based simulation model of a multi-station, tandem queuing structure characteristic of a variety of service systems is employed to test various design options for the system. The model is based on an extensive study of the State of Florida driver licensing offices. The multiple objectives of low time in the system for customers and the efficient use of personnel resources are employed to measure the benefits of policy options. The use of simulation analysis permits the incorporation of complex system characteristics, therefore providing a realistic representation of the effects of possible management actions. Effective methods to control labor in such systems are suggested.     

Leveraging risk assessment for foodborne outbreak investigations: The Quantitative Risk Assessment-Epidemic Curve Prediction Model

Root cause analysis can be used in foodborne illness outbreak investigations to determine the underlying causes of an outbreak and to help identify actions that could be taken to prevent future outbreaks. We developed a new tool, the Quantitative Risk Assessment-Epidemic Curve Prediction Model (QRA-EC), to assist with these goals and applied it to a case study to investigate and illustrate the utility of leveraging quantitative risk assessment to provide unique insights for foodborne illness outbreak root cause analysis. We used a 2019 Salmonella outbreak linked to melons as a case study to demonstrate the utility of this model (Centers for Disease Control and Prevention [CDC], 2019). The model was used to evaluate the impact of various root cause hypotheses (representing different contamination sources and food safety system failures in the melon supply chain) on the predicted number and timeline of illnesses. The predicted number of illnesses varied by contamination source and was strongly impacted by the prevalence and level of Salmonella contamination on the surface/inside of whole melons and inside contamination niches on equipment surfaces. The timeline of illnesses was most strongly impacted by equipment sanitation efficacy for contamination niches. Evaluations of a wide range of scenarios representing various potential root causes enabled us to identify which hypotheses, were likely to result in an outbreak of similar size and illness timeline to the 2019 Salmonella melon outbreak. The QRA-EC framework can be adapted to accommodate any food–pathogen pairs to provide insights for foodborne outbreak investigations.     

The Effects of Knowledge Management on Team Members' Ratings of Project Success and Impact*

Many organizations are trying to improve the generation and utilization of knowledge. The activities associated with these efforts are identified as organizational knowledge management (KM). While much has been written about knowledge management from the organizational level, the success of such efforts over the long run will depend upon on how KM activities impact important outcomes as perceived by those at the employee level who actually implement the activities. This study used the input‐process‐output framework of team effectiveness to investigate the relationship between selected KM‐related activities on integrated product and process development team members' satisfaction with their project's success and the impact they expected it to have on the organization. The results indicate that team‐level leadership and support (i.e., inputs), along with knowledge generation and dissemination (i.e., processes), are key drivers of member performance‐related ratings (i.e., outputs). Finally, and possibly most importantly, a number of interactions were evident suggesting that the KM processes moderate the effects of the KM inputs. These findings and their implications are discussed.     

Cost Efficiency Benchmarking for Operational Units with Multiple Cost Drivers

We consider the activity‐based costing situation, in which for each of several comparable operational units, multiple cost drivers generate a single cost pool. Our study focuses on published data from a set of property tax collection offices, called rates departments, for the London metropolitan area. We define what may be called benchmark or most efficient costs per unit of driver. A principle of maximum performance efficiency is proposed, and an approach to estimating the benchmark unit costs is derived from this principle. A validation approach for this estimation method is developed in terms of what we call normal‐like‐or‐better performance effectiveness. Application to longitudinal data on a single unit is briefly discussed. We also consider some implications for the more routine case when costs are disaggregated to subpools associated with individual cost drivers.