Showing papers by "John E. Hunter published in 1983"

Quantifying the effects of psychological interventions on employee job performance and work-force productivity.

Abstract: Quantification of the economic impact of psychological programs in organizations requires determination of (a) the size and variability of the resulting increase in job performance, and (b) the economic value of the increase in job performance. The new methods ofmeta-analysis allow attainment of the first of these, and in relation to the second, utility analysis methods enable us to translate job performance increases into estimates of the economic value of the program. In the area of personnel selection, many meta-analytic studies have already been conducted, resulting in precise and genemlizable estimates of the validity of cognitive ability tests and other selection procedures. Utility analyses show that the job performance increases resulting from use of valid selection methods have substantial economic value. Valid selection produces major increases in work-force productivity. State-of-the-art meta-analyses have not yet been carried out for nonselection interventions such as training or motivational programs. Utility analysis of the results of existing reviews suggest, however, that the economic value of many such programs will prove to be large. The combined effects of selection and nonselection interventions can be expected to produce increases in workforce productivity that are large indeed. Applied psychologists have conducted research on a variety of organizational interventions aimed at increasing employee job performance and productivity (Katzell & Guzzo, 1983). The usefulness of this research for business and government has often been bounded by two constraints: (a) the extent to which findings can be made definitive, and (b) the extent to which the impact of findings can be stated in administratively and economically meaningful terms. To render findings definitive, one must reconcile the apparently conflicting results of different studies. To assess the practical impact of findings, one must translate such arcane psychological jargon as "p < .01" into economically meaningful statements such as "a 10% increase in output" or "a reduction of $100 million in labor costs." Recent advances have been made in both areas under the rubrics meta-analysis and utility analysis. This article summarizes, in broad outline, the application of these techniques to the areas of personnel selection and organizational interventions. Meta-analysis is a collection of techniques for quantitatively cumulating results across studies (Glass, McGaw, & Smith, 1981; Hunter, Schmidt, & Jackson, 1982). Meta-analysis has shown that in many areas, there is no real conflict between the results of different studies; the apparent differences are due to sampling error and other artifacts. A stateof-the-art meta-analysis allows the reviewer to correct for the effects of several artifacts that distort findings in individual studies: sampling error, error of measurement, and restriction in range. A review of meta-analysis methods for correlation coefficients and for effect sizes can be found in Hunter et al. (1982). Utility analysis is the assessment of the economic or social impact of organizational programs (Katzell and Guzzo, 1983). A key problem in psychological research is that impact is usually measured on psychological rather than economic scales. For example, job performance is usually measured by supervisor ratings. Thus a special analysis is needed to translate findings into economically meaningful terms, such as dollars of labor savings. In personnel selection, formulas for assessing utility have been available for over 30 years (Brogden, 1949; Cronbach & Gleser, 1965) but have not generally been applied because one parameter in these formulas (the standard deviation of job performance in dollar terms) has been difficult to estimate, Base' line formulas for estimating this parameter now exist (Hunter & Schmidt, 1982; Schmidt, Hunter, McKenzie, & Muldrow, 1979; Schmidt & Hunter, Note 1). Furthermore, the methods of utility analysis have now been extended to the assessment of nonselection organizational interventions such as trainApril 1983 • American Psychologist Copyright 1983 by the American Psychological Association, Inc. 473 ing or performance incentive programs (Schmidt, Hunter, & Pearlman, 1982).

Problems in Measuring the Quality of Investment Information: The Perils of the Information Coefficient

Abstract: (1983). Problems in Measuring the Quality of Investment Information: The Perils of the Information Coefficient. Financial Analysts Journal: Vol. 39, No. 3, pp. 25-33.

Measuring stability and growth in annual EPS

Abstract: T he measurement of stability and growth in earnings per share, or EPS, has been an important concern of researchers and practitioners of financial analysis for years The generally accepted measures of EPS stability and growth are derived from the loglinear regression model Logarithms cannot be used, however, if the EPS series has a negative or zero value In this paper, we introduce measures of EPS stability and growth derived from the simple OLS linear regression model for raw-score data The presence of negative or zero EPS values leaves these measures unaffected Our new measures will be compared to the log-linear regression measures using 10 years of annual EPS data, from the period 1970-1980, collected for each of the Dow Jones 30 industrial companies' Our choice of 10 years of data is consistent with the usual time frame employed in this type of stability and growth analysis The EPS data have been adjusted for stock dividends and splits