Tariff Wars and Trade Deals with Costly Government

We study a simple model of tariff wars and trade deals in which government revenue collection and disbursement uses resources. The introduction of costly governments leads to lower non–cooperative tariffs, the possibility that a less costly government may win a tariff war, and fully cooperative trade deals where countries lower tariffs but do not eliminate them, even with lump–sum taxes and transfers.

Cohort, Year and Age Effects in Canadian Wage Data

We use Canadian Surveys of Consumer Finances 1971-1993 to study the wages of full-time, full-year male and female workers. Median real wages of 24-year-old males without a university degree fell by 25% between 1978 and 1993. For 24-year-old females the decline was more modest and reversed in 1987, but real wages in 1993 were still significantly lower than they were in 1978. We investigate whether these changes are permanent "cohort" effects or more temporary "year" effects. Graphs of median wages against year and age indicate some periods where year effects are more prominent than cohort effects and other periods where the reverse is true. We then compare the results from two models, one assigning the trends to year effects, the other assigning them to cohort effects, and use these models to produce real wage projections.SCF; wages; cohort

A Coalition-formation Approach to Equilibrium Federations and Trading Block s

We develop a model in which states may choose to form coalitions to capture efficiency gains from policy coordination. Joining a coalition entails setting the policy variable to maximize the coalition's aggregate payoff at a Nash equilib- rium against non-members, and to commit to a transfer scheme to share the gains. With two states, the unique equilibrium structure is complete federation; with more than two states, incomplete federation can be the unique equilibrium. Interpreting this result in temrs of customs unions, the trend to trading bloc formation may be equilibrium behavious even with cooperation and transfers within customs unions.

Stochastic evolution of cosmological parameters in the early universe

We develop a stochastic formulation of cosmology in the early universe, after considering the scatter in the redshift-apparent magnitude diagram in the early epochs as an observational evidence for the non-deterministic evolution of early universe. We consider the stochastic evolution of density parameter in the early universe after the inflationary phase qualitatively, under the assumption of fluctuating $w$ factor in the equation of state, in the Fokker-Planck formalism. Since the scale factor for the universe depends on the energy density, from the coupled Friedmann equations we calculated the two variable probability distribution function assuming a flat space geometry.Comment: 10 page

Early-type galaxies in the SDSS. I. The sample

A sample of nearly 9000 early-type galaxies, in the redshift range 0.01 < z < 0.3, was selected from the Sloan Digital Sky Survey using morphological and spectral criteria. This paper describes how the sample was selected, presents examples of images and seeing corrected fits to the observed surface brightness profiles, describes our method for estimating K-corrections, and shows that the SDSS spectra are of sufficiently high quality to measure velocity dispersions accurately. It also provides catalogs of the measured photometric and spectroscopic parameters. In related papers, these data are used to study how early-type galaxy observables, including luminosity, effective radius, surface brightness, color, and velocity dispersion, are correlated with one another.Comment: 63 pages, 21 figures. Accepted by AJ (scheduled for April 2003). This paper is part I of a revised version of astro-ph/0110344. The full version of Tables 2 and 3, i.e. the tables listing the photometric and spectroscopic parameters of ~ 9000 galaxies, are available at http://astrophysics.phys.cmu.edu/~bernardi/SDSS/Etypes/TABLE

Predicting Phospholipidosis Using Machine Learning

Phospholipidosis is an adverse effect caused by numerous cationic amphiphilic drugs and can affect many cell types. It is characterized by the excess accumulation of phospholipids and is most reliably identified by electron microscopy of cells revealing the presence of lamellar inclusion bodies. The development of phospholipidosis can cause a delay in the drug development process, and the importance of computational approaches to the problem has been well documented. Previous work on predictive methods for phospholipidosis showed that state of the art machine learning methods produced the best results. Here we extend this work by looking at a larger data set mined from the literature. We find that circular fingerprints lead to better models than either E-Dragon descriptors or a combination of the two. We also observe very similar performance in general between Random Forest and Support Vector Machine models.</p