922 resultados para Multidimensional matching
Resumo:
This paper points out an empirical puzzle that arises when an RBC economy with a job matching function is used to model unemployment. The standard model can generate sufficiently large cyclical fluctuations in unemployment, or a sufficiently small response of unemployment to labor market policies, but it cannot do both. Variable search and separation, finite UI benefit duration, efficiency wages, and capital all fail to resolve this puzzle. However, both sticky wages and match-specific productivity shocks help the model reproduce the stylized facts: both make the firm's flow of surplus more procyclical, thus making hiring more procyclical too.
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We investigate the coevolution between philopatry and altruism in island-model populations when kin recognition occurs through phenotype matching. In saturated environments, a good discrimination ability is a necessary prerequisite for the emergence of sociality. Discrimination decreases not only with the average phenotypic similarity between immigrants and residents (i.e., with environmental homogeneity and past gene flow) but also with the sampling variance of similarity distributions (a negative function of the number of traits sampled). Whether discrimination should rely on genetically or environmentally determined traits depends on the apportionment of phenotypic variance and, in particular, on the relative values of e (the among-group component of environmental variance) and r (the among-group component of genetic variance, which also measures relatedness among group members). If r exceeds e, highly heritable cues do better. Discrimination and altruism, however, remain low unless philopatry is enforced by ecological constraints. If e exceeds r, by contrast, nonheritable traits do better. High e values improve discrimination drastically and thus have the potential to drive sociality, even in the absence of ecological constraints. The emergence of sociality thus can be facilitated by enhancing e, which we argue is the main purpose of cue standardization within groups, as observed in many social insects, birds, and mammals, including humans.
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According to Ljungqvist and Sargent (1998), high European unemployment since the 1980s can be explained by a rise in economic turbulence, leading to greater numbers of unemployed workers with obsolete skills. These workers refuse new jobs due to high unemployment benefits. In this paper we reassess the turbulence-unemployment relationship using a matching model with endogenous job destruction. In our model, higher turbulence reduces the incentives of employed workers to leave their jobs. If turbulence has only a tiny effect on the skills of workers experiencing endogenous separation, then the results of Lungqvist and Sargent (1998, 2004) are reversed, and higher turbulence leads to a reduction in unemployment. Thus, changes in turbulence cannot provide an explanation for European unemployment that reconciles the incentives of both unemployed and employed workers.
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This paper generalizes the original random matching model of money byKiyotaki and Wright (1989) (KW) in two aspects: first, the economy ischaracterized by an arbitrary distribution of agents who specialize in producing aparticular consumption good; and second, these agents have preferences suchthat they want to consume any good with some probability. The resultsdepend crucially on the size of the fraction of producers of each goodand the probability with which different agents want to consume eachgood. KW and other related models are shown to be parameterizations ofthis more general one.
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This paper analyzes the problem of matching heterogeneous agents in aBayesian learning model. One agent gives a noisy signal to another agent,who is responsible for learning. If production has a strong informationalcomponent, a phase of cross-matching occurs, so that agents of low knowledgecatch up with those of higher one. It is shown that:(i) a greater informational component in production makes cross-matchingmore likely;(ii) as the new technology is mastered, production becomes relatively morephysical and less informational;(iii) a greater dispersion of the ability to learn and transfer informationmakes self-matching more likely; and(iv) self-matching leads to more self-matching, whereas cross-matching canmake less productive agents overtake more productive ones.
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This paper establishes a general framework for metric scaling of any distance measure between individuals based on a rectangular individuals-by-variables data matrix. The method allows visualization of both individuals and variables as well as preserving all the good properties of principal axis methods such as principal components and correspondence analysis, based on the singular-value decomposition, including the decomposition of variance into components along principal axes which provide the numerical diagnostics known as contributions. The idea is inspired from the chi-square distance in correspondence analysis which weights each coordinate by an amount calculated from the margins of the data table. In weighted metric multidimensional scaling (WMDS) we allow these weights to be unknown parameters which are estimated from the data to maximize the fit to the original distances. Once this extra weight-estimation step is accomplished, the procedure follows the classical path in decomposing a matrix and displaying its rows and columns in biplots.
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This paper explains the divergent behavior of European an US unemploymentrates using a job market matching model of the labor market with aninteraction between shocks an institutions. It shows that a reduction inTF growth rates, an increase in real interest rates, and an increase intax rates leads to a permanent increase in unemployment rates when thereplacement rates or initial tax rates are high, while no increase inunemployment occurs when institutions are "employment friendly". The paperalso shows that an increase in turbulence, modelle as an increase probabilityof skill loss, is not a robust explanation for the European unemploymentpuzzle in the context of a matching model with both endogenous job creationand job estruction.
Resumo:
This paper theoretically and empirically documents a puzzle that arises when an RBC economy with a job matching function is used to model unemployment. The standard model can generate sufficiently large cyclical fluctuations in unemployment, or a sufficiently small response of unemployment to labor market policies, but it cannot do both. Variable search and separation, finite UI benefit duration, efficiency wages, and capital all fail to resolve this puzzle. However, either sticky wages or match-specific productivity shocks can improve the model's performance by making the firm's flow of surplus more procyclical, which makes hiring more procyclical too.
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This paper examines properties of optimal poverty assistance programs under different informational environments using an income maintenanceframework. To that end, we make both the income generating ability andthe disutility of labor of individuals unobservable, and compare theresulting benefit schedules with those of programs found in the UnitedStates since Welfare Reform (1996). We find that optimal programs closelyresemble a Negative Income Tax with a Benefit Reduction rate that dependson the distribution of population characteristics. A policy of workfare(unpaid public sector work) is inefficient when disutility of labor isunobservable, but minimum work requirements (for paid work) may be usedin that same environment. The distortions to work incentives and thepresence of minimum work requirements depend on the observability andrelative importance of the population's characteristics.
Endogeneous matching in university-industry collaboration: Theory and empirical evidence from the UK
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We develop a two-sided matching model to analyze collaboration between heterogeneousacademics and firms. We predict a positive assortative matching in terms of both scientificability and affinity for type of research, but negative assortative in terms of ability on one sideand affinity in the other. In addition, the most able and most applied academics and the mostable and most basic firms shall collaborate rather than stay independent. Our predictionsreceive strong support from the analysis of the teams of academics and firms that proposeresearch projects to the UK's Engineering and Physical Sciences Research Council.
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This paper compares two well known scan matching algorithms: the MbICP and the pIC. As a result of the study, it is proposed the MSISpIC, a probabilistic scan matching algorithm for the localization of an Autonomous Underwater Vehicle (AUV). The technique uses range scans gathered with a Mechanical Scanning Imaging Sonar (MSIS), and the robot displacement estimated through dead-reckoning with the help of a Doppler Velocity Log (DVL) and a Motion Reference Unit (MRU). The proposed method is an extension of the pIC algorithm. Its major contribution consists in: 1) using an EKF to estimate the local path traveled by the robot while grabbing the scan as well as its uncertainty and 2) proposing a method to group into a unique scan, with a convenient uncertainty model, all the data grabbed along the path described by the robot. The algorithm has been tested on an AUV guided along a 600m path within a marina environment with satisfactory results
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The matching function -a key building block in models of labor market frictions- impliesthat the job finding rate depends only on labor market tightness. We estimate such amatching function and find that the relation, although remarkably stable over 1967-2007,broke down spectacularly after 2007. We argue that labor market heterogeneities are notfully captured by the standard matching function, but that a generalized matching functionthat explicitly takes into account worker heterogeneity and market segmentation is fullyconsistent with the behavior of the job finding rate. The standard matching function canbreak down when, as in the Great Recession, the average characteristics of the unemployedchange too much, or when dispersion in labor market conditions -the extent to which somelabor markets fare worse than others- increases too much.