A Causal Inference of Employee Empowerment on Organizational Performance in the US federal agency, using a Propensity Score Matching method

Employee empowerment is a key principle of NPR and NPM reforms and it has been popularly utilized in organizations of the public as well as private sectors to innovate organizational structure and environment and to improve... [ view full abstract ]

Employee empowerment is a key principle of NPR and NPM reforms and it has been popularly utilized in organizations of the public as well as private sectors to innovate organizational structure and environment and to improve its outcomes such as performance, job satisfaction, and commitment. Despite its widespread popularity, however, the understanding and effectiveness of employee empowerment have been hindered by lack of empirical researches in the public sector. Even though there have been many empirical outputs on its use and consequences published by public management scholars, the critique might be still reasonably applicable to current studies since almost all of them have been focused on correlations and limited in causality. The goal of this paper is to make a causal inference with more confidence on employee empowerment’s organizational performance, using a non-experimental method of propensity score matching (PSM) on 2012 Federal Employee Viewpoint Survey (FEVS) data. By assuming each employee’s perceived different levels of employee empowerment as difference in treatment intensity of employee empowerment provided by managers of each agency, this paper uses agency’s demographic and organizational characteristics as observable selection variables to match employees in four different levels of empowerment intensity, which are paired into three groups, each of which is composed of one of three levels (the least, the better, or the best treatment ) referenced to the fair level of empowerment treatment. After checking common support areas and balances on propensity score and observable selection variables for three paired groups, various estimation techniques are applied with nearest neighbors match (nnmatch), propensity score match (psmatch2) with frequency weighting or inverse of propensity score weighting, and doubly robust propensity score (pscore)-weighting regression. Furthermore, generalized propensity score (gpscore) and dose response function for continuous empowerment treatment are applied. Results from various matching estimations for 4 level discrete empowerment treatment and continuous treatment showed that there are significant causal effects on organizational performance depending on treatment intensity of employee empowerment. For example, from the doubly robust pscore-weighting regression estimation, the first level that felt the lowest empowerment treatment showed half of performance (-0.506) perceived, comparied to the second level that felt fair empowerment treatment as a reference level. The third or fourth levels that felt better or best revealed 0. 196 or 0.392 times higher perceived performance than the reference level, respectively. In addition, the continuous treatment effect estimation showed that 1 unit increase in empowerment treatment perceived by individuals induced 0.467 unit increase in organizational performance perceived. This first attempt in the public sector to estimate a causal effect of employee empowerment on organizational performance using PSM method requires further studies to estimate more rigorous and correct estimation on empowerment effects on organizational performance, by improving in choosing selection variables that are assumed as the underlying factors by which each agency decide whether to participate in the program, here decide treatment intensity in exercising employee empowerment strategy, or by using objective or alternative measures on organizational performance to avoid common source bias in near future.