6,950 research outputs found
Rational stochastic languages
The goal of the present paper is to provide a systematic and comprehensive
study of rational stochastic languages over a semiring K \in {Q, Q +, R, R+}. A
rational stochastic language is a probability distribution over a free monoid
\Sigma^* which is rational over K, that is which can be generated by a
multiplicity automata with parameters in K. We study the relations between the
classes of rational stochastic languages S rat K (\Sigma). We define the notion
of residual of a stochastic language and we use it to investigate properties of
several subclasses of rational stochastic languages. Lastly, we study the
representation of rational stochastic languages by means of multiplicity
automata.Comment: 35 page
Comparison between unitary and collective models of household labor supply with taxation
Several recent papers have shown the relevance of collective models for the empirical investigation of household labor supply and consumption. Yet the estimation of collective models in the presence of non-linear budget sets and participation decisions remains a daunting task. This paper compares collective and unitary models on the basis of simulated collective data with income taxation. We distinguish the cases of individual and joint taxation. Estimating the unitary model we obtain strikingly different ?preference? parameters depending on the type of taxation. We also obtain substantial differences between predicted adjustments to labor supply following a switch between tax regimes, and hence potentially wide-ranging definitions of revenue-neutral versions of tax reforms. Finally we discuss distortions affecting the welfare analysis of reforms on the basis of unitary estimates when the model generating the data is a collective model. The results suggest that increased efforts should be devoted to the estimation of collective models with taxation. --Pareto optimal allocation,tax reform,simulated data
On the performance of unitary models of household labor supply estimated on “collective” data with taxation
This paper compares collective and unitary models on the basis of simulated collective data with income taxation. We distinguish the cases of individual and joint taxation. Estimating a flexible unitary model, we obtain strikingly different “preference” parameters depending on the type of taxation. We also obtain substantial differences between predicted adjustments to labor supply following a switch between tax regimes. Our results show that even the design of revenue-neutral reforms may be heavily distorted by the use of a unitary model on collective data. Finally, we discuss distortions affecting the welfare analysis of reforms on the basis of unitary estimates when the model generating the data is a collective model. The results suggest that increased efforts should be devoted to the estimation of collective models with taxation.Pareto optimal allocations, policy evaluation, simulated data
Nonlinear dielectric susceptibilities in supercooled liquids: a toy model
The dielectric response of supercooled liquids is phenomenologically modeled
by a set of Asymmetric Double Wells (ADW), where each ADW contains a dynamical
heterogeneity of molecules. We find that the linear macroscopic
susceptibility does not depend on contrary to all higher
order susceptibilities . We show that is
proportional to the moment of , which could pave the way for
new experiments on glass transition. In particular, as predicted by Bouchaud
and Biroli on general grounds [Phys. Rev. B, {\bf 72}, 064204 (2005)], we find
that is proportional to the average value of . We fully
calculate and, with plausible values of few parameters our model
accounts for the salient features of the experimental behavior of of
supercooled glycerol.Comment: 13 pages, 5 figure
Pulse shape optimization for electron-positron production in rotating fields
We optimize the pulse shape and polarization of time-dependent electric
fields to maximize the production of electron-positron pairs via strong field
quantum electrodynamics processes. The pulse is parametrized in Fourier space
by a B-spline polynomial basis, which results in a relatively low-dimensional
parameter space while still allowing for a large number of electric field
modes. The optimization is performed by using a parallel implementation of the
differential evolution, one of the most efficient metaheuristic algorithms. The
computational performance of the numerical method and the results on pair
production are compared with a local multistart optimization algorithm. These
techniques allow us to determine the pulse shape and field polarization that
maximize the number of produced pairs in computationally accessible regimes.Comment: 16 pages, 10 figure
On Probability Distributions for Trees: Representations, Inference and Learning
We study probability distributions over free algebras of trees. Probability
distributions can be seen as particular (formal power) tree series [Berstel et
al 82, Esik et al 03], i.e. mappings from trees to a semiring K . A widely
studied class of tree series is the class of rational (or recognizable) tree
series which can be defined either in an algebraic way or by means of
multiplicity tree automata. We argue that the algebraic representation is very
convenient to model probability distributions over a free algebra of trees.
First, as in the string case, the algebraic representation allows to design
learning algorithms for the whole class of probability distributions defined by
rational tree series. Note that learning algorithms for rational tree series
correspond to learning algorithms for weighted tree automata where both the
structure and the weights are learned. Second, the algebraic representation can
be easily extended to deal with unranked trees (like XML trees where a symbol
may have an unbounded number of children). Both properties are particularly
relevant for applications: nondeterministic automata are required for the
inference problem to be relevant (recall that Hidden Markov Models are
equivalent to nondeterministic string automata); nowadays applications for Web
Information Extraction, Web Services and document processing consider unranked
trees
Measuring Selectivity-Corrected Gender Wage Gaps in the EU
We investigate different techniques to assess the gender pay gap in five EU countries (France, Germany, Italy, Spain and United Kingdom), focusing on self-selection into market work. Results show that selectivity correction has an impact on both wage estimates and wage gap decomposition. If there is a positive correlation between the wage and the propensity to participate, the estimated pay gap understates the true difference in earnings when self-selection is ignored. The estimated pay gap differs considerably at different quantiles of the wage distribution, and is sensitive to the choice of estimator. --
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