Efficiency and marginal cost pricing in dynamic competitive markets with friction

This paper examines a dynamic general equilibrium model with supply friction. With or without friction, the competitive equilibrium is efficient. Without friction, the market price is completely determined by the marginal production cost. If friction is present, no matter how small, then the market price fluctuates between zero and the "choke-up" price, without any tendency to converge to the marginal production cost, exhibiting considerable volatility. The distribution of the gains from trading in an efficient allocation may be skewed in favor of the supplier, although every player in the market is a price taker.Dynamic general equilibrium model with supply friction, choke-up price, marginal production cost, welfare theorems

MLE-guided parameter search for task loss minimization in neural sequence modeling

Neural autoregressive sequence models are used to generate sequences in a variety of natural language processing (NLP) tasks, where they are evaluated according to sequence-level task losses. These models are typically trained with maximum likelihood estimation, which ignores the task loss, yet empirically performs well as a surrogate objective. Typical approaches to directly optimizing the task loss such as policy gradient and minimum risk training are based around sampling in the sequence space to obtain candidate update directions that are scored based on the loss of a single sequence. In this paper, we develop an alternative method based on random search in the parameter space that leverages access to the maximum likelihood gradient. We propose maximum likelihood guided parameter search (MGS), which samples from a distribution over update directions that is a mixture of random search around the current parameters and around the maximum likelihood gradient, with each direction weighted by its improvement in the task loss. MGS shifts sampling to the parameter space, and scores candidates using losses that are pooled from multiple sequences. Our experiments show that MGS is capable of optimizing sequence-level losses, with substantial reductions in repetition and non-termination in sequence completion, and similar improvements to those of minimum risk training in machine translation

Hadronic ψ\psi production calculated in the NRQCD factorization formalism

The NRQCD factorization formalism of Bodwin, Braaten, and Lepage prescribes how to write quarkonium production rates as a sum of products of short-distance coefficients times non-perturbative long-distance NRQCD matrix elements. We present, in the true spirit of the factorization formalism, a detailed calculation of the inclusive cross section for hadronic $\psi$ production. We find that in addition to the well known {\it color-singlet} production mechanisms, there are equally important mechanisms in which the $c\bar{c}$ pair that forms the $\psi$ is initially produced in a {\it color-octet} state, in either a ${}^3S_1$, ${}^1S_0$, ${}^3P_0$ or ${}^3P_2$ angular-momentum configuration. In our presentation, we emphasize the ``matching'' procedure, which %is the method that allows us to determine the short-distance coefficients appearing in the factorization formula. We also point out how one may systematically include relativistic corrections in these calculations.Comment: 25 pages, 3 postscript figures, use Revtex and epsfig.sty We fixed some typos, added some text regarding a reference, and changed some equations. The file will be available at http://phenom.physics.wisc.edu