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This paper is the first in a larger project to estimate Congress-Administrator-President (CAP) scores, or ideal point estimates for federal cabinet secretaries, presidents, and members of congress on a common scale. In this paper, we present ideal point estimates for labor secretaries, presidents, and members of the Senate from 1991-2002. Two sets of estimates have been generated: (a) single-congress W-NOMINATE estimates with bootstrapped standard errors (Lewis and Poole 2004), and (b) Markov Chain Monte Carlo (MCMC) methods in a Bayesian framework (Clinton, Jackman, and Rivers 2004; Martin and Quinn 2003). Administrative positions have been constructed through a content analysis of congressional testimony in which an administrator expresses a position on a bill submitted to a roll-call vote in the current Senate session. Results indicate that most labor secretaries have ideal points distinct from their appointing presidents, questioning the assumptions of much of the theoretical literature on the executive branch. Also, using the CAP scores for labor secretaries and senators, we examine the effect of secretary preferences on the allocation of distributive policy projects. We find that the distances between the labor secretary and senators of the same party (Republican) in the 107 th Congress are directly related to the amount of labor department funding allocated to the senator?s state: the further the secretary?s ideal point is from senators of her own party, the less those senators receive in labor outlays. The implications are that the preferences of unelected officials have a direct impact on policy outcomes in Congress. [ABSTRACT FROM AUTHOR]

This paper systematically assesses the common claim that the United States is becoming increasingly isolated from the rest of the world in multilateral institutions. It employs a new data set that includes post-Cold War roll-call votes in multilateral institution that are identified as important by the U.S. State Department. A multilevel item-response model is developed that allows for differentiation between trends in the preferences of states and trends in the agenda. The model is estimated using Markov Chain Monte Carlo methods. The results reveal that states have indeed gradually shifted their preferences away from the U.S. from 1991 to 2001. But, these changes are independent from shifts in the agenda. During the first half of the 1990s the agenda became more positive for the U.S. thanks to its multilateral initiatives, whereas unilateralist tendencies led to an opposite shift since 1998. Changes in preferences, however, develop at a constant rate. This suggests that the unilateralist turn in U.S. foreign policy is not solely responsible for the increased gap between the U.S. and the rest of the world. The paper discusses the policy and theoretical implications of these findings as well as interesting deviations from the common trend by individual countries. Check author’s web site for an updated version of the paper. [ABSTRACT FROM AUTHOR]

The spatial theory of political control posits that bureaucratic drift results from asymmetric information gathered by agencies, veto opportunities for political branches, agency policy preferences, and transactions costs (e.g., Weingast and Moran 1983; Calvert, McCubbins, and Weingast 1990; McCubbins, Noll, Weingast 1987, 1989; Banks and Weingast 1992). The canonical model formally represents interbranch bargaining among the president and houses of Congress. To this model, we add a quasi-autonomous administrative agent—which shares policy setting authority with an interest group. The agent and group must bargain for a policy choice in the final round of the political control game, rather than simply setting policy as in the canonical model. This model uncovers the incentive for the president to strategically choose an agent to enhance his welfare from policy outcomes that occurs quite apart from any informational or transactions cost sources. We compare preexisting models and our spatial bargaining model to generate competing empirical implications. Testing these spatial theories requires ideal point estimates for the House, Senate, and president, which have been available (Poole and Rosenthal 1997; Clinton, Jackman, and Rivers 2003), and administrative agencies, which have not. To empirically test these implications, we estimate ideal points and the distances between the relevant actors (the president, administrative agency heads and regulatory commission members, and members of Congress) in the competing models. Using Markov Chain Monte Carlo (MCMC) ideal point estimation (Clinton, Jackman, and Rivers 2003), we are able to compare the distances between the ideal points of these actors on a comparable scale. The ideal point estimates presented in this paper are improvements over past work in the area for three reasons: (1) ideal points for administrative agents are estimated; (2) the MCMC method allows us to estimate ideal points over time for presidents, which are only available as NOMINATE scores for a president’s entire tenure in office; and (3) directly comparable ideal point estimates are available for members of Congress, presidents, and administrative agents. Thus, not only are these estimates ideal for testing political control models, but are likely to be useful for scholars testing other theories. [ABSTRACT FROM AUTHOR]