Civil Service Reform as National Security: The Homeland Security Act of 2002

The events of 9/11 have influenced policy making in public administration. The Homeland Security Act of 2002, which created the Department of Homeland Security, contained language that empowered the secretary of homeland security and the director of the Office of Personnel Management to establish a personnel management system outside the normal provisions of the federal civil service. Why did civil service reform succeed as part of this legislation when previous attempts at large‐scale reform had failed? A case analysis of the enactment of civil service reform in the Homeland Security Act points to theories of policy emergence and certain models of presidential and congressional policy making. In this case, civil service reform became associated with national security instead of management reform. An assessment of the rhetorical arguments used to frame this policy image offers a powerful explanation for the adoption of the personnel management reforms in the Homeland Security Act. This case has implications for understanding how policy makers might approach future management reform agendas.     

China: Administrative Corruption — Experience in a Comparative Context

As a new world economy emerges what is being learned about the accompanying phenomenon of administrative corruption? To probe this question we combine study of current developments in China with prevailing theories of corruption. The administrative corruption experience, as it has unfolded during the economic development thrust of the Deng reform era, is described and analysed in a comparative context. In specifically interjecting the American experience we suggest that a balanced control response to corruption —rather than an elimination focus—could be a fruitful avenue for policy and research, and that informal, social approaches to corruption control are pregnant with possibilities. China's experience offers a significant opportunity to push the margin of wisdom on these issues as they relate to economic and political development.     

Logistic Regression in Rare Events Data

We study rare events data, binary dependent variables with dozensto thousands of times fewer ones (events, such as wars, vetoes,cases of political activism, or epidemiological infections)than zeros ("nonevents"). In many literatures, these variableshave proven difficult to explain and predict, a problem thatseems to have at least two sources. First, popular statisticalprocedures, such as logistic regression, can sharply underestimatethe probability of rare events. We recommend corrections thatoutperform existing methods and change the estimates of absoluteand relative risks by as much as some estimated effects reportedin the literature. Second, commonly used data collection strategiesare grossly inefficient for rare events data. The fear of collectingdata with too few events has led to data collections with hugenumbers of observations but relatively few, and poorly measured,explanatory variables, such as in international conflict datawith more than a quarter-million dyads, only a few of whichare at war. As it turns out, more efficient sampling designsexist for making valid inferences, such as sampling all availableevents (e.g., wars) and a tiny fraction of nonevents (peace).This enables scholars to save as much as 99% of their (nonfixed)data collection costs or to collect much more meaningful explanatoryvariables. We provide methods that link these two results, enablingboth types of corrections to work simultaneously, and softwarethat implements the methods developed.