Summary of Stone and Rose (2011): Social Work Research and Endogeneity Bias

Endogeneity bias is a concern in making causal inference in the field of social and behavioral sciences research. Stone and Rose (2011) in their paper “Social Work Research and Endogeneity Bias” discussed different sources of endogeneity bias, and different approaches to address this bias from the perspective of social work research. They mentioned that social work as a discipline is lacking control-capable knowledge – knowledge intended to directly inform practitioners’ change related strategies- generated by research using experimental design. They also mentioned about another school of social work philosophy which assumes that persons live in a complex system or environment comprising of biological, psychological, social and other sub-systems, which continuously generates the bi-directional relationships between persons and the relevant systems, and produces a given set of outcomes. This perspective of social work underscores the reliance of experimentation indicating the threat of ecological validity of findings. To my view, this reality of social work domain increases the threat of endogeneity bias in social work research, but it does not discourage experimentation.

To explain endogeneity the authors refer it to a causal relationship between any two variables in a given system of variables (Stone and Rose, 2011). It is really a complicated definition of ednogeneity. We can explain it in a different way. In any experimental design, we expect that our dependent variable will be endogenous or insider, and our independent variable will be exogenous or outsider. In reality, if the independent variable becomes an insider or a part of dependent variable to some extent or co-exists with dependent variable, the independent variable suffers from endogeneity. In this case, the research design suffers from endogeneity bias.

With reference to the studies in the field of social work, the authors discussed three different sources of endogeneity bias: measurement error, omitted variables, and simultaneity. In the reality of measurement, we are rarely capable of observing the independent variable “x” rather we observe the indicators of independent variable “x*”, which is not a perfect measure  of “x” and is vulnerable to measurement error. This measurement error may become a source of endogeneity bias. Omitted variables might source endogeneity when both or any of the dependent and independent variables is related to some other variables, which are not included in the model, and when they have influence on the outcomes. Simultaneity occurs when one or more independent variables are jointly determined with multiple outcome variables where none of the outcomes is capable of being expressed solely as a function. Thus, reverse causation arises, and it might source endogeneity. The authors explained these sources of endogeneity very well with diagrams.

The authors briefly discussed several statistical and econometric tools that address endogeneity bias. They listed a number of approaches: propensity score matching, fixed effects, interrupted time series, regression discontinuity, instrumental variable technique, and natural experiments, which they found in use across key social work journals. In this paper, the authors urge the social work researchers to become familiar with the concept of endogeneity bias, to become aware of the conditions under which such bias occurs, and to develop suitable approaches to address this bias. Most of the approaches discussed in this article are developed in statistics or in econometrics to deal with very field specific issues. Social work researchers should come forward to developing approaches suitable in dealing our field specific edogeneity bias, which will enhance control-capable knowledge base of social work.

– Stone, S. I.,and Rose R. A. 2011. Social Work Research and Endogeneity Bias. Journal of the Society for Social Work and Research. Vol. 2, Issue 2, p. 54-75

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