63 resultados para Acceleration data structure
Resumo:
The genetic characterization of Native Mexicans is important to understand multiethnic based features influencing the medical genetics of present Mexican populations, as well as to the reconstruct the peopling of the Americas. We describe the Y-chromosome genetic diversity of 197 Native Mexicans from 11 populations and 1,044 individuals from 44 Native American populations after combining with publicly available data. We found extensive heterogeneity among Native Mexican populations and ample segregation of Q-M242* (46%) and Q-M3 (54%) haplogroups within Mexico. The northernmost sampled populations falling outside Mesoamerica (Pima and Tarahumara) showed a clear differentiation with respect to the other populations, which is in agreement with previous results from mtDNA lineages. However, our results point toward a complex genetic makeup of Native Mexicans whose maternal and paternal lineages reveal different narratives of their population history, with sex-biased continental contributions and different admixture proportions. At a continental scale, we found that Arctic populations and the northernmost groups from North America cluster together, but we did not find a clear differentiation within Mesoamerica and the rest of the continent, which coupled with the fact that the majority of individuals from Central and South American samples are restricted to the Q-M3 branch, supports the notion that most Native Americans from Mesoamerica southwards are descendants from a single wave of migration. This observation is compatible with the idea that present day Mexico might have constituted an area of transition in the diversification of paternal lineages during the colonization of the Americas.
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Studies of large sets of SNP data have proven to be a powerful tool in the analysis of the genetic structure of human populations. In this work, we analyze genotyping data for 2,841 SNPs in 12 Sub-Saharan African populations, including a previously unsampled region of south-eastern Africa (Mozambique). We show that robust results in a world-wide perspective can be obtained when analyzing only 1,000 SNPs. Our main results both confirm the results of previous studies, and show new and interesting features in Sub-Saharan African genetic complexity. There is a strong differentiation of Nilo-Saharans, much beyond what would be expected by geography. Hunter-gatherer populations (Khoisan and Pygmies) show a clear distinctiveness with very intrinsic Pygmy (and not only Khoisan) genetic features. Populations of the West Africa present an unexpected similarity among them, possibly the result of a population expansion. Finally, we find a strong differentiation of the south-eastern Bantu population from Mozambique, which suggests an assimilation of a pre-Bantu substrate by Bantu speakers in the region.
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Distance and blended collaborative learning settings are usually characterized by different social structures defined in terms of groups' number, dimension, and composition; these structures are variable and can change within the same activity. This variability poses additional complexity to instructional designers, when they are trying to develop successful experiences from existing designs. This complexity is greatly associated with the fact that learning designs do not render explicit how social structures influenced the decisions of the original designer, and thus whether the social structures of the new setting could preclude the effectiveness of the reused design. This article proposes the usage of new representations (social structure representations, SSRs) able to support unskilled designers in reusing existing learning designs, through the explicit characterization of the social structures and constraints embedded either by the original designers or the reusing teachers, according to well-known principles of good collaborative learning practice. The article also describes an evaluation process that involved university professors, as well as the main findings derived from it. This process supported the initial assumptions about the effectiveness of SSRs, with significant evidence from both qualitative and qualitative data.
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In this paper we study the interaction between ownership structure and customer satisfaction, and their impact on a firm's brand equity. We find that customer satisfaction has a positive direct effect on brand equity but an indirect negative one, through reductions in ownership concentration. This latter effect emerges when managers are focused mainly on satisfying customers. It gives out a warning signal that highlights the perverse effect of implementing policies focused excessively on satisfying customers at the expense of shareholders, on a firm's brand equity. We demonstrate our theoretical contention, empirically, making use of an incomplete panel data comprising 69 firms from 11 different nations for the period 2002-2005.
Resumo:
One of the disadvantages of old age is that there is more past than future: this,however, may be turned into an advantage if the wealth of experience and, hopefully,wisdom gained in the past can be reflected upon and throw some light on possiblefuture trends. To an extent, then, this talk is necessarily personal, certainly nostalgic,but also self critical and inquisitive about our understanding of the discipline ofstatistics. A number of almost philosophical themes will run through the talk: searchfor appropriate modelling in relation to the real problem envisaged, emphasis onsensible balances between simplicity and complexity, the relative roles of theory andpractice, the nature of communication of inferential ideas to the statistical layman, theinter-related roles of teaching, consultation and research. A list of keywords might be:identification of sample space and its mathematical structure, choices betweentransform and stay, the role of parametric modelling, the role of a sample spacemetric, the underused hypothesis lattice, the nature of compositional change,particularly in relation to the modelling of processes. While the main theme will berelevance to compositional data analysis we shall point to substantial implications forgeneral multivariate analysis arising from experience of the development ofcompositional data analysis…
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It is common in econometric applications that several hypothesis tests arecarried out at the same time. The problem then becomes how to decide whichhypotheses to reject, accounting for the multitude of tests. In this paper,we suggest a stepwise multiple testing procedure which asymptoticallycontrols the familywise error rate at a desired level. Compared to relatedsingle-step methods, our procedure is more powerful in the sense that itoften will reject more false hypotheses. In addition, we advocate the useof studentization when it is feasible. Unlike some stepwise methods, ourmethod implicitly captures the joint dependence structure of the teststatistics, which results in increased ability to detect alternativehypotheses. We prove our method asymptotically controls the familywise errorrate under minimal assumptions. We present our methodology in the context ofcomparing several strategies to a common benchmark and deciding whichstrategies actually beat the benchmark. However, our ideas can easily beextended and/or modied to other contexts, such as making inference for theindividual regression coecients in a multiple regression framework. Somesimulation studies show the improvements of our methods over previous proposals. We also provide an application to a set of real data.
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This paper tests for the market environment within which US fiscal policyoperates, that is we test for the incompleteness of the US government bondmarket. We document the stochastic properties of US debt and deficits andthen consider the ability of competing optimal tax models to account forthis behaviour. We show that when a government pursues an optimal taxpolicy and issues a full set of contingent claims, the value of debthas the same or less persistence than other variables in the economyand declines in response to higher deficit shocks. By contrast, ifgovernments only issue one-period risk free bonds (incomplete markets),debt shows more persistence than other variables and it increases inresponse to expenditure shocks. Maintaining the hypothesis of Ramseybehavior, US data conflicts.
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Do high levels of human capital foster economic growth by facilitating technology adoption? If so, countries with more human capital should have adopted more rapidly the skilled-labor augmenting technologies becoming available since the 1970 s. High human capital levels should therefore have translated into fast growth in more compared to less human-capital-intensive industries in the 1980 s. Theories of international specialization point to human capital accumulation as another important determinant of growth in human-capital-intensive industries. Using data for a large sample of countries, we find significant positive effects of human capital levels and human capital accumulation on output and employment growth in human-capital-intensive industries.
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This chapter highlights the problems that structural methods and SVAR approaches have when estimating DSGE models and examining their ability to capture important features of the data. We show that structural methods are subject to severe identification problems due, in large part, to the nature of DSGE models. The problems can be patched up in a number of ways but solved only if DSGEs are completely reparametrized or respecified. The potential misspecification of the structural relationships give Bayesian methods an hedge over classical ones in structural estimation. SVAR approaches may face invertibility problems but simple diagnostics can help to detect and remedy these problems. A pragmatic empirical approach ought to use the flexibility of SVARs against potential misspecificationof the structural relationships but must firmly tie SVARs to the class of DSGE models which could have have generated the data.
Resumo:
This paper presents and estimates a dynamic choice model in the attribute space considering rational consumers. In light of the evidence of several state-dependence patterns, the standard attribute-based model is extended by considering a general utility function where pure inertia and pure variety-seeking behaviors can be explained in the model as particular linear cases. The dynamics of the model are fully characterized by standard dynamic programming techniques. The model presents a stationary consumption pattern that can be inertial, where the consumer only buys one product, or a variety-seeking one, where the consumer shifts among varied products.We run some simulations to analyze the consumption paths out of the steady state. Underthe hybrid utility assumption, the consumer behaves inertially among the unfamiliar brandsfor several periods, eventually switching to a variety-seeking behavior when the stationary levels are approached. An empirical analysis is run using scanner databases for three different product categories: fabric softener, saltine cracker, and catsup. Non-linear specifications provide the best fit of the data, as hybrid functional forms are found in all the product categories for most attributes and segments. These results reveal the statistical superiority of the non-linear structure and confirm the gradual trend to seek variety as the level of familiarity with the purchased items increases.
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When long maturity bonds are traded frequently and traders have non-nestedinformation sets, speculative behavior in the sense of Harrison and Kreps (1978) arises.Using a term structure model displaying such speculative behavior, this paper proposesa conceptually and observationally distinct new mechanism generating time varying predictableexcess returns. It is demonstrated that (i) dispersion of expectations about futureshort rates is sufficient for individual traders to systematically predict excess returns and(ii) the new term structure dynamics driven by speculative trade is orthogonal to publicinformation in real time, but (iii) can nevertheless be quantified using only publicly availableyield data. The model is estimated using monthly data on US short to medium termTreasuries from 1964 to 2007 and it provides a good fit of the data. Speculative dynamicsare found to be quantitatively important, potentially accounting for a substantial fractionof the variation of bond yields and appears to be more important at long maturities.
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A family of scaling corrections aimed to improve the chi-square approximation of goodness-of-fit test statistics in small samples, large models, and nonnormal data was proposed in Satorra and Bentler (1994). For structural equations models, Satorra-Bentler's (SB) scaling corrections are available in standard computer software. Often, however, the interest is not on the overall fit of a model, but on a test of the restrictions that a null model say ${\cal M}_0$ implies on a less restricted one ${\cal M}_1$. If $T_0$ and $T_1$ denote the goodness-of-fit test statistics associated to ${\cal M}_0$ and ${\cal M}_1$, respectively, then typically the difference $T_d = T_0 - T_1$ is used as a chi-square test statistic with degrees of freedom equal to the difference on the number of independent parameters estimated under the models ${\cal M}_0$ and ${\cal M}_1$. As in the case of the goodness-of-fit test, it is of interest to scale the statistic $T_d$ in order to improve its chi-square approximation in realistic, i.e., nonasymptotic and nonnormal, applications. In a recent paper, Satorra (1999) shows that the difference between two Satorra-Bentler scaled test statistics for overall model fit does not yield the correct SB scaled difference test statistic. Satorra developed an expression that permits scaling the difference test statistic, but his formula has some practical limitations, since it requires heavy computations that are notavailable in standard computer software. The purpose of the present paper is to provide an easy way to compute the scaled difference chi-square statistic from the scaled goodness-of-fit test statistics of models ${\cal M}_0$ and ${\cal M}_1$. A Monte Carlo study is provided to illustrate the performance of the competing statistics.
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In this article we examine the potential effect of market structureon hospital technical efficiency as a measure of performance controlled byownership and regulation. This study is relevant to provide an evaluationof the potential effects of recommended and initiated deregulation policiesin order to promote market reforms in the context of a European NationalHealth Service. Our goal was reached through three main empirical stages.Firstly, using patient origin data from hospitals in the region of Cataloniain 1990, we estimated geographic hospital markets through the Elzinga--Hogartyapproach, based on patient flows. Then we measured the market level ofconcentration using the Herfindahl--Hirschman index. Secondly, technicaland scale efficiency scores for each hospital was obtained specifying aData Envelopment Analysis. According to the data nearly two--thirds of thehospitals operate under the production frontier with an average efficiencyscore of 0.841. Finally, the determinants of the efficiency scores wereinvestigated using a censored regression model. Special attention waspaid to test the hypothesis that there is an efficiency improvement in morecompetitive markets. The results suggest that the number of competitors inthe market contributes positively to technical efficiency and there is someevidence that the differences in efficiency scores are attributed toseveral environmental factors such as ownership, market structure andregulation effects.
Resumo:
This paper investigates the role of employee referrals in the labor market.Using an original data set, I find that industries that pay wage premia andhave characteristics associated with high-wage sectors rely mainly on employeereferrals to fill jobs. Moreover, unemployment rates are higher in industries which use employee referrals more extensively. This paper develops an equilibrium matching model which can explain these empirical regularities. Inthis model, the matching process sorts heterogeneous firms and workers into two distinct groups: referrals match "good" jobs to "good" workers, while formalmethods (e.g., newspaper ads and employment agencies) match less-attractive jobs to disadvantaged workers. Thus, well-connected workers who learn quickly aboutjob opportunities use referrals to jump job queues, while those who are less well placed in the labor market search for jobs through formal methods. The split of firms and workers between referrals and formal search is, however, not necessarily efficient. Congestion externalities in referral search imply that unemployment would be closer to the optimal rate if firms and workers 'at themargin' searched formally.
Resumo:
This paper studies the interaction between ownership structure, taken as a proxy for shareholders commitment, and customer satisfaction - the main driver of consumer loyalty - and their impact on a firm s brand equity. The results show that customer satisfaction has a positive direct effect on brand equity but an indirect negative one because of reductions in ownership concentration. This latter effect emerges when managers are mainly customer-oriented. Such result gives out a warning signal that highlights the perverse effect of implementing policies, focused excessively on satisfying customers at the expense of shareholders, on a firm s brand equity. The empirical analysis uses an incomplete panel data comprising 69 firms from 11 nations, for the period 2002-2005.