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explanation for policy change. With the assistance of Larry Dodd, my doctoral advisor, I found the explanation I was looking for in a relatively new body of political science literature broadly referred to as learning theory (“social learning,” “political learning,” “policy learning,” or “organizational learning,” depending on whom you consult). The next fifteen years became a scholarly quest to apply learning theory to the study of US telecommunications policy through my dissertation, a subsequent monograph, and several research articles. The present study represents a final effort to complete this quest by developing a more precise and systematic version of the theoretical ideas I began working on nearly fifteen years ago.
This study also grew out of a desire to do something that few scholars of regulatory politics have done: conduct a detailed, indepth, explanatory study of policy decision making by a regulatory agency. The notion that such a study is a scholarly rarity might seem controversial at first, but a close examination of the literature reveals otherwise. Nearly three generations of political scientists and economists have developed “theories of regulation” in which agencies are characterized as politicized, ineffective, inefficient, or some combination of the three. In terms of analytical depth, these studies have ranged from scholarly commentaries to highly formalized theories, but few have mustered substantial empirical evidence to back up their claims. Moreover, few of these studies have shown an appreciation for the difficulties regulatory agencies face in fulfilling their statutory missions. The policy formulation and implementation tasks undertaken by the “alphabet soup” of U.S. federal regulatory agencies—FCC, SEC, EPA, OSHA, USDA, and FDA, among others—are perhaps the most technically complex work undertaken by the civilian bureaucracy. Undoubtedly, perceptions of ineffectiveness and inefficiency occur because even the most competent agency will