David A. Swanson

On the validity of MAPE as a measure of population forecast accuracy

The mean absolute percent error (MAPE) is the summary measure most often used for evaluating the accuracy of population forecasts. While MAPE has many desirable criteria, we argue from both normative and relative standpoints that the widespread practice of exclusively using it for evaluating population forecasts should be changed. Normatively, we argue that MAPE does not meet the criterion of validity because as a summary measure it overstates the error found in a population forecast. We base this argument on logical grounds and support it empirically, using a sample of population forecasts for counties. From a relative standpoint, we examine two alternatives to MAPE, both sharing with it, the important conceptual feature of using most of the information about error. These alternatives are symmetrical MAPE (SMAPE) and a class of measures known as M-estimators. The empirical evaluation suggests M-estimators do not overstate forecast error as much as either MAPE or SMAPE and are, therefore, more valid measures of accuracy. We consequently recommend incorporating M-estimators into the evaluation toolkit. Because M-estimators do not meet the desired criterion of interpretative ease as well as MAPE, we also suggest another approach that focuses on nonlinear transformations of the error distribution.

Forecasting the Population of Census Tracts by Age and Sex: An Example of the Hamilton–Perry Method in Action

Small area population projections are useful in a range of business applications. This paper uses a case study to show how this type of task can be accomplished by using the Hamilton–Perry method, which is a variant of the cohort-component projection technique. We provide the documentation on the methods, data, and assumptions used to develop two sets of population projections for census tracts in Clark County, Nevada, and discuss specific factors needed to accomplish this task, including the need to bring expert judgment to bear on the task. Our experience suggests that the Hamilton–Perry Method is an important tool and we advise considering it for small forecasting needs in the private sector.

A new short-term county population projection method.

This paper proposes a new method for short-term county population projections. It is based on a modification of the ratio-correlation method of population estimation. The modified ratio-correlation method can produce projections with a high potential for accuracy without requiring substantial data and intensive intellectual labor inputs. Tests of accuracy are examined for the modified ratio-correlation method and two currently available alternatives using data from Washington state. The tests suggest that the new method performs well. (EXCERPT)

On the utility of population forecasts

Many customers demand population forecasts, particularly for small areas. Although the forecast evaluation literature is extensive, it is dominated by a focus on accuracy. We go beyond accuracy by examining the concept of forecast utility in an evaluation of a sample of 2,709 counties and census tracts. Wefind that forecasters provide “value-added” knowledge for areas experiencing rapid change or areas with relatively large populations. For other areas, reduced value is more common than added value. Our results suggest that new forecasting strategies and methods such as composite modeling may substantially improve forecast utility.

Between a Rock and a Hard Place: The Evaluation of Demographic Forecasts

Forecasting, in general, has been described as an unavoidable yet impossible task. This irony, which comprises the ‘rock’ and the ‘hard place’ in the title, creates a high level of cognitive dissonance, which, in turn, generates stress for those both making and using forecasts that have non-trivial impacts. Why? Because the forecasted numbers that are invariably accorded a high degree of precision inexorably reveal their inevitable imprecision when the numbers forming the actuality finally take place and the numbers comprising the forecasts errors are precisely measured. The current state of the art in demography for dealing with the ‘rock’ and the ‘hard place’ is a less-than-successful strategy because it is based on an acceptance of accuracy as the primary evaluation criterion, which is the source of cognitive dissonance. One way to reduce cognitive dissonance is to change the relationship of the very cognitive elements creating it. We argue that forecast evaluations currently focused on accuracy and based on measures like RMSE and MAPE be refocused to include utility and propose for this purpose the ‘Proportionate Reduction in Error’ (PRE) measure. We illustrate our proposal with examples and discuss its advantages. We conclude that including PRE as an evaluation criterion can reduce stress by reducing cognitive dissonance without, at the same time, either trivializing the evaluation process or substantively altering how forecasts are done and presented.

A Note on the Measurement of Accuracy for Subnational Demographic Estimates

Mean absolute percentage error (MAPE), the measure most often used for evaluating subnational demographic estimates, is not always valid. We describe guidelines for determining when MAPE is valid. Applying them to case study data, we find that MAPE understates accuracy because it is unduly influenced by outliers. To overcome this problem, we calculate a transformed MAPE (MAPET) using a modified Box-Cox method. Because MAPE-T is not in the same scale as the untransformed absolute percentage errors, we provide a procedure for calculating MAPE-R, a measure in the same scale as the original observations. We argue that MAPE-R is a more appropriate summary measure of average absolute percentage error when the guidelines indicate that MAPE is not valid.

Psychologists and Hurricane Katrina: Natural Disaster Response Through Training, Public Education, and Research

Training and Education in Professional Psychology 2008, Vol. 2, No. 2, 83– 88 Copyright 2008 by the American Psychological Association 1931-3918/08/

Applied Demography in the 21st Century

12.00 DOI: 10.1037/1931-3918.2.2.83 Psychologists and Hurricane Katrina: Natural Disaster Response Through Training, Public Education, and Research Stefan E. Schulenberg and Kirsten A. Dellinger Angela J. Koestler The University of Mississippi Nordal Clinic, Vicksburg, Mississippi Ann Marie K. Kinnell David A. Swanson, Mark V. Van Boening, and Richard G. Forgette University of Southern Mississippi The University of Mississippi The purpose of this article was to describe a model of clinical/disaster psychology and illustrate how one psychologist applied training in the aftermath of Hurricane Katrina. The primary focus of the article relates to training graduate students of clinical psychology and assisting evacuees, public education and dissemination, and research. Psychologists may find themselves in similar positions when disasters occur in the future, and the linkage of research and theory with anecdotal accounts may provide mental health professionals with ideas regarding avenues of training to pursue and the various roles that may be served in times of disaster. Recommendations are offered to training programs with regard to infusing tenets of clinical/disaster psychol- ogy into their curriculum. This article describes a variety of strategies that a psychol- ogist may pursue to assist in the mental health response to natural disasters. It is primarily based on my perspective (SES) 1 as an Assistant Professor in Clinical Psychology at The Uni- versity of Mississippi who arrived at this position with special- ized doctoral training in clinical/disaster psychology from The University of South Dakota’s Disaster Mental Health Institute (DMHI). I hope that my experiences will inform training pro- grams and mental health professionals about how clinical/ disaster training may be pursued and applied when a natural disaster occurs. Training in Clinical/Disaster Psychology Training programs and their directors should consider both formal and informal training opportunities for those interested in preparing to provide disaster assistance. Doctoral training in a formal program such as the Disaster Mental Health Institute (DMHI) at The Univer- sity of South Dakota (http://usd.edu/dmhi/) is an important way to gain preparatory training. The DMHI offers a variety of training programs, including a doctoral Specialty Track in Clinical/Disaster Psychology, which is earned conjointly with the Clinical Training Program’s Ph.D. degree. Students take disaster-related coursework, sippi. His research interests include applied demography, forecasting and estimation methods, and mortality differentials. M ARK V. V AN B OENING received his doctorate in Economics from the University of Arizona. He is an associate professor in the Department of Economics at The University of Mississippi and currently serves as the department chair. His research interests include applied microeconomics and experimental economics. R ICHARD G. F ORGETTE earned his doctorate in political science from the University of Rochester. He is professor and chair of the Political Science Department at The University of Mississippi. His research interests include the U.S. Congress, legislative elections, public opinion, and public policy issues. We thank Jessica T. Kaster, PhD, psychologist at Lakeland Mental Health, Moorhead, Minnesota; Michael C. Roberts, PhD, ABPP, professor and direc- tor of the Clinical Child Psychology Program at the University of Kansas; and Larry Smyth, PhD, staff psychologist at the Perry Point VAMC, Perry Point, Maryland, for reviewing a previous draft of this article. C ORRESPONDENCE CONCERNING THIS ARTICLE should be addressed to Stefan E. Schulenberg, Department of Psychology, The University of Mississippi, University, Mississippi 38677. E-mail: sschulen@olemiss.edu S TEFAN E. S CHULENBERG received his doctorate in clinical psychology from The University of South Dakota, where he also specialized in clinical/disaster psychology through the University’s Disaster Mental Health Institute. Dr. Schulenberg is an assistant professor in the Department of Psychology at The University of Mississippi. His research interests include clinical/disaster psy- chology, psychological assessment, test validation, and logotherapy. K IRSTEN A. D ELLINGER received her doctorate in sociology from the University of Texas at Austin. She is an associate professor of sociology in the Department of Sociology and Anthropology at The University of Mississippi. Her research interests include gender and sexuality in the workplace and qualitative methods. A NGELA J. K OESTLER received her doctorate in counseling psychology from the University of Southern Mississippi. She currently works in private practice at the Nordal Clinic in Vicksburg, Mississippi. Her clinical and research interests include the treatment of chronic pain and natural disaster response. A NN M ARIE K. K INNELL received her doctorate in sociology from Indiana University at Bloomington. She is an assistant professor of sociology in the Department of Anthropology and Sociology at the University of Southern Mississippi. Her current research examines the experience of a team of researchers implementing a survey in the context of a natural disaster. D AVID A. S WANSON received his doctorate in sociology from the Uni- versity of Hawaii, where he specialized in population studies and worked at the East West Population Institute. He is a professor of sociology in the Department of Sociology and Anthropology at The University of Missis- Although the article is written from a single perspective, it is a multi-authored work with contributions from each of the coauthors.

In search of the ideal measure of accuracy for subnational demographic forecasts

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What is applied demography

We examine nonlinear transformations of the forecasterror distribution in hopes of finding a summary errormeasure that is not prone to an upward bias and usesmost of the information about that error. MAPE, thecurrent standard for measuring error, often overstatesthe error represented by most of the values becausethe distribution underlying the MAPE is right skewedand truncated at zero. Using a modification to theBox-Cox family of nonlinear transformations, wetransform these skewed forecast error distributionsinto symmetrical distributions for a wide range ofsize and growth rate conditions. We verify thissymmetry using graphical devices and statisticaltests; examine the transformed errors to determine ifre-expression to the scale of the untransformed errorsis necessary; and develop and implement a procedurefor the re-expression. The MAPE-R developed by ourprocess is lower than the MAPE based on theuntransformed errors and is more consistent with arobust estimator of location.