103 resultados para Network security


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This paper studies the impact of an unfunded social security system on the distribution of bequests in a framework where savings are due both by life cycle and by random altruistic motivations. We show that the impact of social security on the distribution of bequests depends crucially on the importance of the bequest motive in explaining savings behavior. If the bequest motive is strong, then an increase in the social security tax raises the bequests left by altruistic parents. On the other hand, when the importance of bequests in motivating savings is sufficiently low, theincrease in the social security tax could result in a reduction of the bequests left by altruistic parents under some conditions on the attitude of individuals toward risk and on the relative returns associated with private saving and social security. Some implications concerning the transitional effects of introducing an unfunded social security scheme are also discussed.

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This paper provides a quantitative evaluation of the intra--cohortredistributive elements of the United States social security system in thecontext of a computable general equilibrium model. I determine how thewell--being of individuals that differ across {\sl gender, race} and {\sl education}is affected by government social security policy. I find that females, whitesand non--college graduates stand less to gain (lose) from reductions(increases) in the size of social security than males, non--whites andcollege graduates, respectively. Differences in mortality risk and laborproductivity translate into differences in the magnitudes of capitalaccumulation and labor supply distortions, that are responsible for theobserved welfare difference between types. Results imply that the currentprogram is lifetime progressive across gender and education, yet lifetimeregressive across race.

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The Network Revenue Management problem can be formulated as a stochastic dynamic programming problem (DP or the\optimal" solution V *) whose exact solution is computationally intractable. Consequently, a number of heuristics have been proposed in the literature, the most popular of which are the deterministic linear programming (DLP) model, and a simulation based method, the randomized linear programming (RLP) model. Both methods give upper bounds on the optimal solution value (DLP and PHLP respectively). These bounds are used to provide control values that can be used in practice to make accept/deny decisions for booking requests. Recently Adelman [1] and Topaloglu [18] have proposed alternate upper bounds, the affine relaxation (AR) bound and the Lagrangian relaxation (LR) bound respectively, and showed that their bounds are tighter than the DLP bound. Tight bounds are of great interest as it appears from empirical studies and practical experience that models that give tighter bounds also lead to better controls (better in the sense that they lead to more revenue). In this paper we give tightened versions of three bounds, calling themsAR (strong Affine Relaxation), sLR (strong Lagrangian Relaxation) and sPHLP (strong Perfect Hindsight LP), and show relations between them. Speciffically, we show that the sPHLP bound is tighter than sLR bound and sAR bound is tighter than the LR bound. The techniques for deriving the sLR and sPHLP bounds can potentially be applied to other instances of weakly-coupled dynamic programming.

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We use network and correspondence analysis to describe the compositionof the research networks in the European BRITE--EURAM program. Our mainfinding is that 27\% of the participants in this program fall into one oftwo sets of highly ``interconnected'' institutions --one centered aroundlarge firms (with smaller firms and research centers providing specializedservices), and the other around universities--. Moreover, these ``hubs''are composed largely of institutions coming from the technologically mostadvanced regions of Europe. This is suggestive of the difficulties of attainingEuropean ``cohesion'', as technically advanced institutions naturally linkwith partners of similar technological capabilities.

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The network choice revenue management problem models customers as choosing from an offer-set, andthe firm decides the best subset to offer at any given moment to maximize expected revenue. The resultingdynamic program for the firm is intractable and approximated by a deterministic linear programcalled the CDLP which has an exponential number of columns. However, under the choice-set paradigmwhen the segment consideration sets overlap, the CDLP is difficult to solve. Column generation has beenproposed but finding an entering column has been shown to be NP-hard. In this paper, starting with aconcave program formulation based on segment-level consideration sets called SDCP, we add a class ofconstraints called product constraints, that project onto subsets of intersections. In addition we proposea natural direct tightening of the SDCP called ?SDCP, and compare the performance of both methodson the benchmark data sets in the literature. Both the product constraints and the ?SDCP method arevery simple and easy to implement and are applicable to the case of overlapping segment considerationsets. In our computational testing on the benchmark data sets in the literature, SDCP with productconstraints achieves the CDLP value at a fraction of the CPU time taken by column generation and webelieve is a very promising approach for quickly approximating CDLP when segment consideration setsoverlap and the consideration sets themselves are relatively small.

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This paper uses Social Security records to study internal migrationin Spain. This is the first paper that uses this data source, whichhas some advantages with respect to existing data sources: it includesonly job-seeking migrants and it allows to identify temporary migration. Within the framework of an extended gravity model, we estimate a Generalized Negative Binomial regression on gross migration flows between provinces. We quantify the effect of local labor market imbalances on workers' mobility and discuss the equilibrating role of internal migration in Spain. Our main results show that the effect of employment opportunities have changed after 1984; migrants seem to be more responsive to economic conditions but, consistently with previous studies for the Spanish labor market, the migration response to wage differentials is wrongly signed. Our analysis also confirms the larger internal mobility of highly qualified workers.

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166 countries have some kind of public old age pension. What economic forcescreate and sustain old age Social Security as a public program? We document some of the internationally and historically common features of Social Security programs including explicit and implicit taxes on labor supply, pay-as-you-go features, intergenerational redistribution, benefits which areincreasing functions of lifetime earnings and not means-tested. We partition theories of Social Security into three groups: "political", "efficiency" and "narrative" theories. We explore three political theories in this paper: the majority rational voting model (with its two versions: "the elderly as the leaders of a winning coalition with the poor" and the "once and for all election" model), the "time-intensive model of political competition" and the "taxpayer protection model". Each of the explanations is compared with the international and historical facts. A companion paper explores the "efficiency" and "narrative" theories, and derives implicationsof all the theories for replacing the typical pay-as-you-go system with a forced savings plan.

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Why are the old politically successful? We build a simple interest group model in which political pressure is time-intensive, showing that in the political competitive equilibrium each group lobbies for government policies that lower their own value of time but the old do so to a greater extent and as a result are net gainers from the political process. What distinguishes the elderly from other political groups (and what makes them more succesful) is that they have lower labor productivity and/or that we are all likely to become elderly at some point, while we are relatively unlikely to change gender, race, sexual orientation, or even ocupation, The model has a variety of implications for the design of social security programs, which we test using data from the Social Security Administration. For example, the model predicts that social security programs with retirement incentives are larger and that the old are more "single-minded" in their politics, implications which we verify using cross-country government finance data and cross-country political participation surveys. Finally, we show that the forced savings programs intended to "reform" the social security system may increase the amount of intergenerational redistribution. As a model for evaluating policy reforms, ours has the attractive feature that reforms must be time time consistent from a political point of view rather than a public interest point of view.

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The objective of this paper is to compare the performance of twopredictive radiological models, logistic regression (LR) and neural network (NN), with five different resampling methods. One hundred and sixty-seven patients with proven calvarial lesions as the only known disease were enrolled. Clinical and CT data were used for LR and NN models. Both models were developed with cross validation, leave-one-out and three different bootstrap algorithms. The final results of each model were compared with error rate and the area under receiver operating characteristic curves (Az). The neural network obtained statistically higher Az than LR with cross validation. The remaining resampling validation methods did not reveal statistically significant differences between LR and NN rules. The neural network classifier performs better than the one based on logistic regression. This advantage is well detected by three-fold cross-validation, but remains unnoticed when leave-one-out or bootstrap algorithms are used.

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In this paper we explore the mechanisms that allow securities analysts to value companies in contexts of Knightian uncertainty, that is, in the face of information that is unclear, subject to unforeseeable contingencies or to multiple interpretations. We address this question with a grounded-theory analysis of the reports written on Amazon.com by securities analyst Henry Blodget and rival analysts during the years 1998-2000. Our core finding is that analysts' reports are structured by internally consistent associations that includecategorizations, key metrics and analogies. We refer to these representations as calculative frames, and propose that analysts function as frame-makers - that is, asspecialized intermediaries that help investors value uncertain stocks. We conclude by considering the implications of frame-making for the rise of new industry categories, analysts' accuracy, and the regulatory debate on analysts'independence.

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This work proposes novel network analysis techniques for multivariate time series.We define the network of a multivariate time series as a graph where verticesdenote the components of the process and edges denote non zero long run partialcorrelations. We then introduce a two step LASSO procedure, called NETS, toestimate high dimensional sparse Long Run Partial Correlation networks. This approachis based on a VAR approximation of the process and allows to decomposethe long run linkages into the contribution of the dynamic and contemporaneousdependence relations of the system. The large sample properties of the estimatorare analysed and we establish conditions for consistent selection and estimation ofthe non zero long run partial correlations. The methodology is illustrated with anapplication to a panel of U.S. bluechips.