2,926 research outputs found
Rule of Thumb and Dynamic Programming
This paper studies the relationships between learning about rules of thumb (represented by classifier systems) and dynamic programming. Building on a result about Markovian stochastic approximation algorithms, we characterize all decision functions that can be asymptotically obtained through classifier system learning, provided the asymptotic ordering of the classifiers is strict. We demonstrate in a robust example that the learnable decision function is in general not unique, not characterized by a strict ordering of the classifiers, and may not coincide with the decision function delivered by the solution to the dynamic programming problem even if that function is attainable. As an illustration we consider the puzzle of excess sensitivity of consumption to transitory income: classifier systems can generate such behavior even if one of the available rules of thumb is the decision function solving the dynamic programming problem, since bad decisions in good times can "feel better" than good decisions in bad times.
Can Habit Formation be Reconciled with Business Cycle Facts?
Many asset pricing puzzles can be explained when habit formation is added to standard preferences. We show that utility functions with a habit then gives rise to a puzzle of consumption volatility in place of the asset pricing puzzles when agents can choose consumption and labor optimally in response to more fundamental shocks. We show that the consumption reaction to technology shocks are too small by an order of magnitude when a utility includes a habit. Alternative models with consistent and exogenous but stochastic labor input are considered. A model with persistent technology shocks and stochastic labor is shown to be potentially consistent with substantial consumption variability aswell as procyclical labor input and labor productivity even when a habit is present.
Employment Duration and Resistance to Wage Reductions: Experimental Evidence
One of the long-standing puzzles in economics is why wages do not fall sufficiently in recessions so as to avoid increases in unemployment. Put differently, if the competitive market wage declines, why don't employers simply force their employees to accept lower wages as well? As an alternative to reviewing statistical data we have performed an experiment with a lower competitive wage in the second phase of an employment relationship that is known to both parties. Our hypothesis is that employers will not lower wages correspondingly and that employees will resist such wage cuts. Our experiment casts two subjects in the highly stylized roles of employer and employee. We find at most mild evidence for resistance to wage declines. Instead, the experimental results can be more fruitfully interpreted in terms of an "ultimatum game", in which some surplus between employers and employees is split. In this view, wages and their lack of decline are simply the mechanical tool for accomplishing this split.wage flexibility;ratchet effect (of wages);(wage) bargaining;labour market;ultimatum game;fair wages
Informe previo de los estudios mineralĂłgicos y geoquĂmicos del yacimiento de SN y W de Monte Neme (Carballo, NO de España)
Resumen] En este trabajo se presentan brevemente datos preliminares mineralĂłgicos y geoquĂmicos de la roca encajante (un neis porfidoblĂĄstico) de los filones mineralizados de Sn y W, de la wolframita (H/F=O,53) y de unos placeres de playa al NE del yacimiento.[Abstract] In this paper we present briefly preliminary dates of mineralogical and geochemical analysis of the wall rock (a porphyroblastic gneiss) of the Sn and W mineralized veins, of the wolframite (H/F=O,53) and of sorne beach placers in the NE of the deposite[Zusammenfassung] In der vorliegenden Arbeit werden kurz die vorlaufigen Ergebnisse mineralogischer und geochemischer Analysen des Nebengesteins(ein porphyroblastischer Gneis) der Sn- und W-vererzten Gange, des Wolframits (H/F=O,53) und einiger Strandseifen im NE der Lagerstatte vorgestellt
On Adjusting the H-P Filter for the Frequency of Observations
This paper studies how the HP-Filter should be adjusted, when changing the frequency of observations. The usual choices in the literature are to adjust the smoothing parameter by multiplying it with either the square of the observation frequency ratios or simply with the observation frequency. In contrast, the paper recommends to adjust the filter parameter by multiplying it with the fourth power of the observation frequency ratios. Based on this suggestion, some well-known comparisons of business cycles moments across countries and time periods are recomputed. In particular, we overturn a finding by Backus and Kehoe (1992) on the historical changes in output volatility and return instead to older conventional wisdom (Baily, 1978, Lucas, 1977): based on the new HP-Filter adjustment rule, output volatility turns out to have decreased after the Second World War.
Conception de réseau iBGP
LâInternet est constituĂ© de plus de 25,000 AS (Autonomous System) Ă©changeant des informations de routage grĂące Ă BGP (Border Gateway Protocol). Dans un AS de taille importante,il nâest pas possible dâĂ©tablir une session BGP entre chaque paire de routeur pour des raisons de scalabilitĂ©. On a alors recours Ă la rĂ©flexion de route. Cependant, cette technique induit une opacitĂ© en terme de diffusion des routes, et peut provoquer lâapparition de routages sous-optimaux (en terme de coĂ»t IGP), des dĂ©flexions de routes, voire des boucles de routage. Dans ce travail nous proposons une solution pour construire une topologie de rĂ©flexion de route permettant dâavoir un routage identique Ă celui dâun full mesh iBGP, y compris en cas de panne simple dâĂ©quipement, et en installant un minimum de sessions iBGP. Nous avons appliquĂ© cette mĂ©thode sur le rĂ©seau dâun opĂ©rateur tier-1 et calculĂ© une topologie iBGP robuste Ă tout cas de panne simple. La topologie obtenue reste de taille comparable Ă celle actuellement dĂ©ployĂ©e
Internet scalability: properties and evolution
Copyright © 2008 IEEEMatthew Roughan; Steve Uhlig; Walter Willinge
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