From Association to Causation via a Potential Outcomes Approach
Information Systems Research, Vol. 20, No. 2, pp. 295-313, 2009
Posted: 15 Feb 2010
Date Written: 2009
Despite the importance of causal analysis to build a valid base of knowledge and to answer managerial questions, the issue of causality rarely receives the attention it deserves in published empirical work in information systems (IS) and management research that uses observational data. In this paper, we discuss a potential outcomes framework for estimating causal effects and illustrate the application of the framework in the context of a phenomenon that is also of substantive interest to IS researchers. We use a matching technique based on propensity scores to estimate the causal effect of an MBA degree on information technology professionals’ salary in the United States. We demonstrate the utility of this counterfactual or potential outcomes-based framework in providing an estimate of the sensitivity of the estimated causal effects due to selection on unobservables. We also discuss issues related to the heterogeneity of treatment effects that typically do not receive as much attention in alternative methods of estimation, and we show how the potential outcomes approach can provide several new insights into who benefits the most from the interventions and treatments that are likely to be of interest to IS researchers. We discuss the usefulness of the matching technique in IS and management research and provide directions to move beyond establishing association to assessing causation.
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