98 resultados para SPATIAL PROPENSITY SCORE MATCHING


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What explains the spatial distribution of wages across US counties? I find that two of the most important factors are spatial technology diffusion and externalities due to the aggregate scale of production. One empirical finding supporting the importance of spatial technology diffusion is that average wages in a county decrease with the average level of schooling in neighboring counties when employment in the county and average wages in neighboring counties are held constant. All empirical results are obtained using anovel instrument for (endogenous) employment at the county-leveland take into account other factors (e.g. productivity-differencesacross states, climate) that may determine wages.

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We formulate a dynamic core-periphery model with frictions in the job matching process to study the interplay between trade costs, migration and regional unemploymentin the short- and long-run. We find that the spatial distribution of unemployment mirrors (inversely) the distribution of economic activities. Further, we highlight a contrast between the short-run and the long-run effects of trade-induced migration on regional unemployment. In particular, an inßow of immigrants from the periphery into the core reduces the unemployment gap in the short-run, but exacerbates unemployment disparities in the long-run.

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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 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.

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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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A class of composite estimators of small area quantities that exploit spatial (distancerelated)similarity is derived. It is based on a distribution-free model for the areas, but theestimators are aimed to have optimal design-based properties. Composition is applied alsoto estimate some of the global parameters on which the small area estimators depend.It is shown that the commonly adopted assumption of random effects is not necessaryfor exploiting the similarity of the districts (borrowing strength across the districts). Themethods are applied in the estimation of the mean household sizes and the proportions ofsingle-member households in the counties (comarcas) of Catalonia. The simplest version ofthe estimators is more efficient than the established alternatives, even though the extentof spatial similarity is quite modest.

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This paper analyses the effect of tobacco prices on the propensity tostart and quit smoking using a pool of the 1993, 1995 and 1997 editionsof the Spanish National Health Surveys. The estimates for severalparametric models of the hazard rate for starting and quitting suggestthat i) The public health measures applied as of 1992 have had asignificative effect on both reducing the hazard of starting andincreasing the hazard of quitting, ii) Prices have a very weak effect onthe hazard of starting in the male population and no significant effectin the female population, iii) The price floor of cigarrettes, proxiedby the average price of a pack of black cigarrettes, has a significanteffect on the quitting hazard which is robust across specifications andapplies to both men and women. The implied price elasticity of the timeup to quitting is situated around -1.4.

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We examine how much of an extra dollar of parental lifetime resources willultimately be passed on to adult children in the form of inter vivostransfers and bequests. We infer bequests from the stock of wealth late inlife. We use mortality rates and age specific estimates of the response oftransfers and wealth to permanent income to compute the expected presentdiscounted values of these responses to permanent income. Our estimatesimply parents pass on between 2 and 3 cents out of an extra dollar ofexpected lifetime resources in bequests and about 2 cents in transfers.The estimates increase with parental income and are smaller for nonwhites.They imply that about 15 percent of the effect of parental income onlifetime resources of adult children is through transfers and bequestsand about 85 percent is through the intergenerational correlation inearnings, although these estimates are sensitive to assumptions about theintergenerational earnings correlation, taxes, and the number of children.We compare our estimates to the implications of alternative computablebenchmark models of savings behavior in order to assess the likelyimportance of intended bequests for the wealth/income relationship.

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Most facility location decision models ignore the fact that for a facility to survive it needs a minimum demand level to cover costs. In this paper we present a decision model for a firm thatwishes to enter a spatial market where there are several competitors already located. This market is such that for each outlet there is a demand threshold level that has to be achievedin order to survive. The firm wishes to know where to locate itsoutlets so as to maximize its market share taking into account the threshold level. It may happen that due to this new entrance, some competitors will not be able to meet the threshold and therefore will disappear. A formulation is presented together with a heuristic solution method and computational experience.

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In this paper we present a model that studies firm mergers in a spatial setting. A new model is formulated that addresses the issue of finding the number of branches that have to be eliminated by a firm after merging with another one, in order to maximize profits. The model is then applied to an example of bank mergers in the city of Barcelona. Finally, a variant of the formulation that introduces competition is presented together with some conclusions.

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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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The main information sources to study a particular piece of music are symbolic scores and audio recordings. These are complementary representations of the piece and it isvery useful to have a proper linking between the two of the musically meaningful events. For the case of makam music of Turkey, linking the available scores with the correspondingaudio recordings requires taking the specificities of this music into account, such as the particular tunings, the extensive usage of non-notated expressive elements, and the way in which the performer repeats fragmentsof the score. Moreover, for most of the pieces of the classical repertoire, there is no score written by the original composer. In this paper, we propose a methodology to pair sections of a score to the corresponding fragments of audio recording performances. The pitch information obtained from both sources is used as the common representationto be paired. From an audio recording, fundamental frequency estimation and tuning analysis is done to compute a pitch contour. From the corresponding score, symbolic note names and durations are converted to a syntheticpitch contour. Then, a linking operation is performed between these pitch contours in order to find the best correspondences.The method is tested on a dataset of 11 compositions spanning 44 audio recordings, which are mostly monophonic. An F3-score of 82% and 89% are obtained with automatic and semi-automatic karar detection respectively,showing that the methodology may give us a needed tool for further computational tasks such as form analysis, audio-score alignment and makam recognition.

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The results of the application of the geophysical electromagnetic prospection methods in the resolution of the problems of the spatial location of the travertine quaternary formations of the Banyoles depression are presented

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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