Research in Applied Stochastic Processes, Stochastic Models, and Bounded Rationality

Daniel Carpenter

Adaptive Signal Processing, Hierarchy, and Budgetary Control in Federal Regulation, American Political Science Review, 90 (2) (June 1996): 283-302.

• Winner of The Herbert Kaufman Award for Best Paper presented in the Public Administration Section, American Political Science Association annual meetings, August 1992, Chicago.
• Winner of the Best Paper Award, Executive Politics Section, American Political Science Association annual meetings, August 1992, Chicago.

Stochastic Prediction and Estimation of Nonlinear Political Durations: An Application to the Lifetime of Bureaus, in Political Complexity: Nonlinear Models of Politics, ed. Diana Richards, (Ann Arbor: University of Michigan Press, 2000).

Why Do Bureaucrats Delay? Lessons from a Stochastic Optimal Stopping Model of Product Approval, George Krause and Kenneth Meier, eds., Politics, Policy, and Organizations: Frontiers in the Scientific Study of Bureaucracy, (Ann Arbor: University of Michigan Press, 2003).

Political Learning from Rare Events: Poisson Inference, Fiscal Constraints, and the Lifetime of Bureaus, with David Lewis. Political Analysis 12 (3) (Summer 2004), 211-244.

Protection without Capture: Product Approval by a Politically Responsive, Bayesian Regulator, American Political Science Review 98 (4) (November 2004), forthcoming.

Robert Wood Johnson Foundation Scholars in Health Policy Working Paper #13.

Technical Notes for “Protection without Capture.” [to be posted soon]

A Simple Theory of Placebo Learning with Self-Remitting Conditions

Dynamic Stochastic Learning in Regulatory Optimization: Deadlines and Error with Continuous and Discrete Evidence (with Justin Grimmer)

"Optimal Stopping with Memory Constraints: A Note."

"The Non-Neutrality of Organizational Memory: Optimal Stopping by Teams with Poisson Forgetting."

"A Stochastic-Evolutionary Model of Attention."