Lack of Health Care: A Root Cause of Homelessness

Close to 41.2 million people in the United States lacked health insurance for all of 2001. Extensive research exists on the effects of homelessness on health, but the high costs of health care as a cause of homelessness for low-income individuals have not been visibly examined. The loss and lack of health insurance places millions of adults and children in the position of being one accident or illness away from homelessness. A Commonwealth Fund study of loss of health insurance found that 40 percent of uninsured respondents had difficulty paying for basic necessities such as food, rent, and utilities as a result of high medical bills

The Futility of Utility: how market dynamics marginalize Adam Smith

Econometrics is based on the nonempiric notion of utility. Prices, dynamics, and market equilibria are supposed to be derived from utility. Utility is usually treated by economists as a price potential, other times utility rates are treated as Lagrangians. Assumptions of integrability of Lagrangians and dynamics are implicitly and uncritically made. In particular, economists assume that price is the gradient of utility in equilibrium, but I show that price as the gradient of utility is an integrability condition for the Hamiltonian dynamics of an optimization problem in econometric control theory. One consequence is that, in a nonintegrable dynamical system, price cannot be expressed as a function of demand or supply variables. Another consequence is that utility maximization does not describe equiulibrium. I point out that the maximization of Gibbs entropy would describe equilibrium, if equilibrium could be achieved, but equilibrium does not describe real markets. To emphasize the inconsistency of the economists' notion of 'equilibrium', I discuss both deterministic and stochastic dynamics of excess demand and observe that Adam Smith's stabilizing hand is not to be found either in deterministic or stochastic dynamical models of markets, nor in the observed motions of asset prices. Evidence for stability of prices of assets in free markets simply has not been found.Comment: 46 pages. accepte

Detector and Event Visualization with SketchUp at the CMS Experiment

We have created 3D models of the CMS detector and particle collision events in SketchUp, a 3D modelling program. SketchUp provides a Ruby API which we use to interface with the CMS Detector Description to create 3D models of the CMS detector. With the Ruby API, we also have created an interface to the JSON-based event format used for the iSpy event display to create 3D models of CMS events. These models have many applications related to 3D representation of the CMS detector and events. Figures produced based on these models were used in conference presentations, journal publications, technical design reports for the detector upgrades, art projects, outreach programs, and other presentations.Comment: 5 pages, 6 figures, Proceedings for CHEP 2013, 20th International Conference on Computing in High Energy and Nuclear Physic

Response to worrying trends in econophysics

This article is a response to the recent “Worrying Trends in Econophysics” critique written by four respected theoretical economists [1]. Two of the four have written books and papers that provide very useful critical analyses of the shortcomings of the standard textbook economic model, neo-classical economic theory [2,3] and have even endorsed my book [4]. Largely, their new paper reflects criticism that I have long made [4,5,6,7,] and that our group as a whole has more recently made [8]. But I differ with the authors on some of their criticism, and partly with their proposed remedy.General equilibrium; uncertainty; conservation laws; money nonconservation; nonintegrability of dynamical systems; financial markets; stochastic processes

Making dynamic modelling effective in economics

Mathematics has been extremely effective in physics, but not in economics beyond finance. To establish economics as science we should follow the Galilean method and try to deduce mathematical models of markets from empirical data, as has been done for financial markets. Financial markets are nonstationary. This means that 'value' is subjective. Nonstationarity also means that the form of the noise in a market cannot be postulated a priroi, but must be deduced from the empirical data. I discuss the essence of complexity in a market as unexpected events, and end with a biological speculation about market growth.Economics; fniancial markets; stochastic process; Markov process; complex systems