This study examines the usefulness of the Taylor-rule framework as an organizing device for describing the policy debate and evolution of monetary policy in the United States. Monetary policy during the 1920s and since the 1951 Treasury-Federal Reserve Accord can be broadly interpreted in terms of this framework with rather surprising consistency. In broad terms, during these periods policy has...

Bennett McCallum (2009), applying Evans and Honkapohja’s (2001) results, argues that “learnability” can save New-Keynesian models from their indeterminacies. He claims the unique bounded equilibrium is learnable, and the explosive equilibria are not. However, he assumes that agents can directly observe the monetary policy shock. Reversing this assumption, I find the opposite result: the bounded...

Cylindrical algebraic decomposition (CAD) is an important tool for the investigation of semialgebraic sets. Originally introduced by Collins in the 1970s for use in quantifier elimination it has since found numerous applications within algebraic geometry and beyond. Following from his original work in 1988, McCallum presented an improved algorithm, CADW, which offered a huge increase in the pra...

We wish to acknowledge excellent assistance received from Ron McCallum who offered insightful comments regarding a number of matters including the trade and commerce power, anti-discrimination legislation, restrictions on right of entry and termination of employment, and Andrew Dungan who prepared some background material used here, particularly in Appendix B. Thanks also to

PRACTICAL GASTROENTEROLOGY • SEPTEMBER 2014 Richard W. McCallum, M.D., Professor and Founding Chair of Medicine, Department of Internal Medicine Director, Center for Neurogastroenterology and GI Motility. Joseph Sunny, Jr., M.D., Senior Fellow, Division of Gastroenterology, Hepatology and Nutrition, Texas Tech University Health Sciences Center, Paul L. Foster School of Medicine, El Paso, TX GAS...

This paper explores an instance-based state identification technique called nearest sequence memory presented by McCallum (1994). The algorithm uses a basic k-nearest neighbor approach to solving the problem of hidden state in a reinforcement learning problem. We compare this algorithm with a more commonly used fixed memory representation, history windows.