Abstract
The mechanism through which outsourcing favourably impacts on workplace performance, particularly productivity, is still unclear. I explore the hypothesis that it does so by impacting workers’ training. I use AWIRS-1995, a matched employer–employee survey that reports ample information on the extent of technology and organizational change in Australian workplaces. I find that there is a positive and significant impact of outsourcing on training when I do not control for the correlation between ununobservable factors in these two binary outcomes. However, once I control for this correlation using a bivariate probit estimator, the training impact of outsourcing becomes negative. I then assess the sensitivity of the outsourcing effect to endogeneity by using the method advocated by Altonji et al. (J Polit Econ 113(1):151–184, 2005) to find that this latter result persists even in the presence of a low correlation between unobservables.
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Notes
Caveats and limitations of this measure of training are discussed in Magnani (2006a).
The relevant question is: “In which of these categories (including technology), does this workplace benchmark?”
Magnani (2006a) finds evidence of a differential effect of technology innovation and technology diffusion of workers’ training.
According to the labour-cost saving hypothesis, an increase in outsourcing could indicate a desire by the firm to save on labour costs, possibly by reducing its training expenses and thus reducing workers’ training opportunities.
The technology standardization hypothesis appeals to explanations such as special expertise possessed by the outside contractor and that are applicable to the hiring firm. For instance, Segal and Sullivan (1997) and Kahn (2000) suggest that, insofar as tasks requiring substantial investment in firm-specific skills are usually ill-suited to the use of temporary workers, technological standardization makes firm-specific knowledge less important and thus shifts upward the demand for outsourced labour services.
We estimate a large number of specifications for (Contr_up). In the selection of the specification we use to compute the ATT of (Contr_up) on workers’ training we are bound to satisfy the common support requirement and the balancing property requirement.
The CIA states that all relevant differences between the group of workplaces that undergo vertical disintegration and the group of workplaces that do not, are captured by a set of observable characteristics \(\Updelta\), such that the event Y0 is independent from the focal control D, conditional on the propensity p(x), where \(p(x)\equiv \hbox{Pr} (D=1|\Updelta=x)\).
The common support assumption states that in the control group the distribution of the estimated propensity to vertically disintegrate is as similar as possible to the distribution of such propensity in the “treated” group.
The results related to the workplace technology variables are consistent with those already reported in Magnani (2006a).
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Acknowledgments
Thanks to James Chowhan for excellent research assistance. The author wishes to gratefully acknowledge the support of the Canadian Social Science and Humanities Research Council (SSHRC), which approved this research project and allowed Magnani to work with the Statistics Canada WES dataset (SSHRC Project Number: 281868). Special thanks to Thomas Crossley for his assistance in accessing the WES data. Financial support from the Centre of Excellence for Population Ageing Research (CEPAR), University of New South Wales, and from the Australian Research Council Discovery Project scheme (DP0559431) is gratefully acknowledged.
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Magnani, E. Vertical disintegration and training: evidence from a matched employer–employee survey. J Prod Anal 38, 199–217 (2012). https://doi.org/10.1007/s11123-011-0256-9
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DOI: https://doi.org/10.1007/s11123-011-0256-9