The Institutional Dynamics of Policy Administration: Bureaucratic Influence over Securities Regulation

Abstract

Theory: A dynamic systems model of administrative politics that (1) relaxes restrictive causal assumptions among the president, Congress, and an administrative agency, (2) emphasizes aggregate institutional behavior, and (3) analyzes both anticipated and unanticipated policy behavior is set forth as a more general means to investigate agency-political relationships. Hypotheses: The main set of hypotheses focus on the aggregate institutional relationships among the president, Congress, and administrative agency. These four possible hypotheses include bureaucratic influence, bureaucratic autonomy, mutual influence, and political influence. The purpose here is to assess the relative merits of competing explanations for bureaucratic behavior. Securities regulation is a perfect area of inquiry to investigate these competing perspectives since the findings of existing research on this topic are disparate. Methods: Vector autoregressive time series statistical methods are used to empirically test the dynamic systems model of administrative politics by examining three empirical models of SEC enforcement behavior in relation to presidential and congressional budgetary preference signals for the 1949-92 annual period. Results: The SEC sends potent signals of their own (via their changes in regulatory outputs) that will affect the budgetary preferences of its political principles. However, the SEC's administrative outputs are shown to be somewhat less sensitive to political budgetary preference signals than what one would expect. Presidential and congressional budgetary preference signals (with respect to the SEC) are interdependent to a sizeable extent, thus raising doubts about the separate, independent effect democratic institutions have over the bureaucracy. The implications of this study suggest that conventional theories of agency-political relations serve as an oversimplified way to study administrative behavior. Future research on this topic