How Well Do We Measure Training
01 Jul 1997-Journal of Labor Economics (The University of Chicago Press)-Vol. 15, Iss: 3, pp 507-528
TL;DR: The authors compare various measures of on-the-job training, from a new source that matches establishments and workers, allowing them to compare the responses of employers and employees to identical training questions.
Abstract: This article compares various measures of on‐the‐job training, from a new source that matches establishments and workers, allowing us to compare the responses of employers and employees to identical training questions. Establishments report 25% more hours of training than do workers, although workers and establishments report similar incidence rates of training. Both establishment and worker measures agree that there is much more informal training than formal training. Further, informal training is measured about as accurately as formal training. Finally, we show that measurement error reduces substantially the observed effect of training, in particular the effect of training on productivity growth.
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TL;DR: In this paper, the authors examine the impacts of active labor market policies, such as job training, job search assistance, and job subsidies, and the methods used to evaluate their effectiveness.
Abstract: Policy makers view public sector-sponsored employment and training programs and other active labor market policies as tools for integrating the unemployed and economically disadvantaged into the work force. Few public sector programs have received such intensive scrutiny, and been subjected to so many different evaluation strategies. This chapter examines the impacts of active labor market policies, such as job training, job search assistance, and job subsidies, and the methods used to evaluate their effectiveness. Previous evaluations of policies in OECD countries indicate that these programs usually have at best a modest impact on participants’ labor market prospects. But at the same time, they also indicate that there is considerable heterogeneity in the impact of these programs. For some groups, a compelling case can be made that these policies generate high rates of return, while for other groups these policies have had no impact and may have been harmful. Our discussion of the methods used to evaluate these policies has more general interest. We believe that the same issues arise generally in the social sciences and are no easier to address elsewhere. As a result, a major focus of this chapter is on the methodological lessons learned from evaluating these programs. One of the most important of these lessons is that there is no inherent method of choice for conducting program evaluations. The choice between experimental and non-experimental methods or among alternative econometric estimators should be guided by the underlying economic models, the available data, and the questions being addressed. Too much emphasis has been placed on formulating alternative econometric methods for correcting for selection bias and too little given to the quality of the underlying data. Although it is expensive, obtaining better data is the only way to solve the evaluation problem in a convincing way. However, better data are not synonymous with social experiments. © 1999 Elsevier Science B.V. All rights reserved.
3,352 citations
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TL;DR: In this paper, the authors examined the impact of workplace practices, information technology and human capital investments on productivity and found that what is associated with higher productivity is not so much whether or not an employer adopts a particular work practice but rather how that work practice is actually implemented within the establishment.
Abstract: Using data from a unique nationally representative sample of businesses, the Educational Quality of the Workforce National Employers Survey (EQW-NES), matched with the Bureau of the Census' Longitudinal Research Database (LRD), we examine the impact of workplace practices, information technology and human capital investments on productivity. We estimate an augmented Cobb Douglas production function with both cross section and panel data covering the period of 1987-1993 using both within and GMM estimators. We find that what is associated with higher productivity is not so much whether or not an employer adopts a particular work practice but rather how that work practice is actually implemented within the establishment. We also find that those unionized establishments that have adopted what have been called new or transformed' industrial relations practices that promote joint decision making coupled with incentive based compensation have higher productivity than other similar non-union plants maintain more traditional labor management relations have lower productivity. We also find that the higher the average educational level of production workers or the greater the proportion of non-managerial workers who use computers, the higher is plant productivity.
1,337 citations
TL;DR: In this article, the authors examined the impact of workplace practices, information technology, and human capital investments on productivity and found that it is not whether an employer adopts a particular work practice but rather how that work practice is actually implemented within the establishment that is associated with higher productivity.
Abstract: Using data from a unique nationally representative sample of businesses, we examine the impact of workplace practices, information technology, and human capital investments on productivity. We estimate an augmented Cobb-Douglas production function with both cross section and panel data covering the period of 1987–1993, using both within and GMM estimators. We find that it is not whether an employer adopts a particular work practice but rather how that work practice is actually implemented within the establishment that is associated with higher productivity. Unionized establishments that have adopted human resource practices that promote joint decision making coupled with incentive-based compensation have higher productivity than other similar nonunion plants, whereas unionized businesses that maintain more traditional labor management relations have lower productivity. Finally, plant productivity is higher in businesses with more-educated workers or greater computer usage by nonmanagerial employees.
1,090 citations
Cites background from "How Well Do We Measure Training"
...Our estimates on workplace practices were unchanged with the exception of TQM, which became significantly negative....
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TL;DR: In this article, the authors find that although longitudinal estimates that avoid the first source of bias are substantially smaller than cross-sectional estimates, the former are strongly influenced by errors in measuring HR management practices.
Abstract: Because companies differ in factors such as management ability that may lead to both high performance work systems and enhanced firm performance, conventional estimates of the effects of human resource (HR) management practices on firm performance may be biased upward. Alternatively, if HR management practices are measured with error, estimates of their effects on firm performance may be biased downward. We find that although longitudinal estimates that avoid the first source of bias are substantially smaller than cross-sectional estimates, the former are strongly influenced by errors in measuring HR management practices. Based on independent estimates of the measurement error, we calculate a range of estimates that correct for both biases. We estimate that a one standard deviation increase in our measure of high performance work systems raises the market value of the corporation by approximately $15,000 per employee.
539 citations
TL;DR: In this paper, a meta-analysis from 67 studies suggests that training is positively related to human resource outcomes and organizational performance but is only very weakly related to financial outcomes, and that the relationship between training and firm performance may be mediated by employee attitudes and human capital.
477 citations
References
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TL;DR: In the context of the economist's concern with education as a process of investment in manpower, it is important to be reminded that formal school instruction is neither an exclusive nor a sufficient method of training the labor force as discussed by the authors.
Abstract: IN TIHE context of the economist's concern with education as a process of investment in manpower, it is important to be reminded that formal school instruction is neither an exclusive nor a sufficient method of training the labor force. Graduation from some level of schooling does not signify the completion of a training process. It is usually the end of a more general and preparatory stage, and the beginning of a more specialized and often prolonged process of acquisition of occupational skill, after entry into the labor force. This second stage, training on the job, ranges from formally organized activities such as apprenticeships and other training programs2 to the in-
1,102 citations
TL;DR: The authors show how experiments sometimes serve as instrumental variables to identify program impacts and the most favorable case for experiments ignores variability across persons in response to treatments received.
Abstract: Rs ecent academic debates pit two alternative approaches to policy evaluation against one another. The first is the "experimental" approach, based on the random assignment of accepted program applicants to a recipient, or treatment, group and a non-recipient, or control, group. The second is the "nonexperimental," or "econometric," approach that uses a variety of microdata sources, statistical methods, and behavioral models to compare the outcomes of participants in social programs with those of nonparticipants. The central question addressed in this paper is whether or not randomized social experiments aid in securing answers to basic questions about the evaluation of social programs. There are many distinct and complementary approaches to the study of the impact of public policy, including full general equilibrium analysis of policy impacts (Tinbergen, 1956; Auerbach and Kotlikoff, 1987; Shoven and Whalley, 1992; Kydland and Prescott, 1991) and less ambitious partial equilibrium microeconomic structural research programs, such as those designed to estimate the impact of taxes on labor supply. Both approaches offer answers to many interesting counterfactual policy questions, but their credibility rests critically on the quality of the empirical input used to generate their answers
960 citations
"How Well Do We Measure Training" refers background in this paper
...Administrative records 65% of a population received training, but the recipients’ self-reports indicate only 48% received training (Heckman and Smith 1995, p. 106) ....
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...Finally, the agreement among worker and establishment measures is higher for the aggregate training measure than for any individual training 15 Heckman and Smith (1995) find evidence that workers underreport the incidence of training when comparing administrative and self-reported data for a group…...
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Posted Content•
582 citations
TL;DR: This article used the Panel Study of Income Dynamics (PSID) Validation Study, a two-wave panel survey of workers employed by a large firm that shared its detailed payroll records.
Abstract: This article investigates error properties of survey reports of labor market variables. We use the Panel Study of Income Dynamics (PSID) Validation Study, a two-wave panel survey of workers employed by a large firm that shared its detailed payroll records. Individuals' reports of annual earnings are fairly accurate. Errors are negatively related to true earnings, reducing bias due to measurement error when earnings are used as an independent variable. Biases are moderately larger for changes in earnings. Earnings per hour are less reliably reported than annual earnings. Biases in estimating earnings functions are relatively small, but those in labor supply functions may be important.
441 citations
TL;DR: In this paper, the matching process constitutes a key feature of the on-the-job training model presented in this article and tested with a unique data set containing extensive information concerning on the job training, employer search, wages and wage and productivity growth.
Abstract: Conventional analysis predicts that workers pay part of their on-the-job training costs by accepting a lower starting wage and subsequently realize a return to this investment in the form of greater wage growth. Missing from the conventional treatment of on-the-job training is a discussion of the process by which heterogeneous workers are matched to jobs requiring varying amounts of training. This matching process constitutes a key feature of the on-the-job training model presented in this article and tested with a unique data set containing extensive information concerning on-the-job training, employer search, wages, and wage and productivity growth.
390 citations
"How Well Do We Measure Training" refers background or methods in this paper
...Among others, Barron, Black, and Loewenstein (1987, 1989) , Bishop (1987) , and Holzer (1990a, 1990b ) use this measure of productivity growth....
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...The 1982 EOPP survey has been used extensively (e.g., Bishop and Kang 1984; Barron, Black, and Loewenstein 1989, 1993) and Holzer, Katz, and Krueger 1991) .1 This survey asked employers a series of questions concerning the training that was provided to the most recent worker hired during the first…...
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