196 resultados para [JEL:C32] Mathematical and Quantitative Methods - Econometric Methods: Multiple
Resumo:
We formulate performance assessment as a problem of causal analysis and outline an approach based on the missing data principle for its solution. It is particularly relevant in the context of so-called league tables for educational, health-care and other public-service institutions. The proposed solution avoids comparisons of institutions that have substantially different clientele (intake).
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In this article two aims are pursued: on the one hand, to present arapidly converging algorithm for the approximation of square roots; on theother hand and based on the previous algorithm, to find the Pierce expansionsof a certain class of quadratic irrationals as an alternative way to themethod presented in 1984 by J.O. Shallit; we extend the method to findalso the Pierce expansions of quadratic irrationals of the form $2 (p-1)(p - \sqrt{p^2 - 1})$ which are not covered in Shallit's work.
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This paper ia an attempt to clarify the relationship between fractionalization,polarization and conflict. The literature on the measurement of ethnic diversityhas taken as given that the proper measure for heterogeneity can be calculatedby using the fractionalization index. This index is widely used in industrialeconomics and, for empirical purposes, the ethnolinguistic fragmentation isready available for regression exercises. Nevertheless the adequacy of asynthetic index of hetergeneity depends on the intrinsic characteristicsof the heterogeneous dimension to be measured. In the case of ethnicdiversity there is a very strong conflictive dimension. For this reasonwe argue that the measure of heterogeneity should be one of the class ofpolarization measures. In fact the intuition of the relationship betweenconflict and fractionalization do not hold for more than two groups. Incontrast with the usual problem of polarization indices, which are ofdifficult empirical implementation without making some arbitrary choiceof parameters, we show that the RQ index, proposed by Reynal-Querol (2002),is the only discrete polarization measure that satisfies the basic propertiesof polarization. Additionally we present a derivation of the RQ index froma simple rent seeking model. In the empirical section we show that whileethnic polarization has a positive effect on civil wars and, indirectly ongrowth, this effect is not present when we use ethnic fractionalization.
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This paper investigates the link between brand performance and cultural primes in high-risk,innovation-based sectors. In theory section, we propose that the level of cultural uncertaintyavoidance embedded in a firm determine its marketing creativity by increasing the complexityand the broadness of a brand. It determines also the rate of firm product innovations.Marketing creativity and product innovation influence finally the firm marketingperformance. Empirically, we study trademarked promotion in the Software Security Industry(SSI). Our sample consists of 87 firms that are active in SSI from 11 countries in the period1993-2000. We use the data coming from SSI-related trademarks registered by these firms,ending up with 2,911 SSI-related trademarks and a panel of 18,213 observations. We estimatea two stage model in which first we predict the complexity and the broadness of a trademarkas a measure of marketing creativity and the rate of product innovations. Among severalcontrol variables, our variable of theoretical interest is the Hofstede s uncertainty avoidancecultural index. Then, we estimate the trademark duration with a hazard model using thepredicted complexity and broadness as well as the rate of product innovations, along with thesame control variables. Our evidence confirms that the cultural avoidance affects the durationof the trademarks through the firm marketing creativity and product innovation.
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By means of Malliavin Calculus we see that the classical Hull and White formulafor option pricing can be extended to the case where the noise driving thevolatility process is correlated with the noise driving the stock prices. Thisextension will allow us to construct option pricing approximation formulas.Numerical examples are presented.
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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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We compare a set of empirical Bayes and composite estimators of the population means of the districts (small areas) of a country, and show that the natural modelling strategy of searching for a well fitting empirical Bayes model and using it for estimation of the area-level means can be inefficient.
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Minkowski's ?(x) function can be seen as the confrontation of two number systems: regular continued fractions and the alternated dyadic system. This way of looking at it permits us to prove that its derivative, as it also happens for many other non-decreasing singular functions from [0,1] to [0,1], when it exists can only attain two values: zero and infinity. It is also proved that if the average of the partial quotients in the continued fraction expansion of x is greater than k* =5.31972, and ?'(x) exists then ?'(x)=0. In the same way, if the same average is less than k**=2 log2(F), where F is the golden ratio, then ?'(x)=infinity. Finally some results are presented concerning metric properties of continued fraction and alternated dyadic expansions.
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The generalization of simple correspondence analysis, for two categorical variables, to multiple correspondence analysis where they may be three or more variables, is not straighforward, both from a mathematical and computational point of view. In this paper we detail the exact computational steps involved in performing a multiple correspondence analysis, including the special aspects of adjusting the principal inertias to correct the percentages of inertia, supplementary points and subset analysis. Furthermore, we give the algorithm for joint correspondence analysis where the cross-tabulations of all unique pairs of variables are analysed jointly. The code in the R language for every step of the computations is given, as well as the results of each computation.
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In this article we propose using small area estimators to improve the estimatesof both the small and large area parameters. When the objective is to estimateparameters at both levels accurately, optimality is achieved by a mixed sampledesign of fixed and proportional allocations. In the mixed sample design, oncea sample size has been determined, one fraction of it is distributedproportionally among the different small areas while the rest is evenlydistributed among them. We use Monte Carlo simulations to assess theperformance of the direct estimator and two composite covariant-freesmall area estimators, for different sample sizes and different sampledistributions. Performance is measured in terms of Mean Squared Errors(MSE) of both small and large area parameters. It is found that the adoptionof small area composite estimators open the possibility of 1) reducingsample size when precision is given, or 2) improving precision for a givensample size.
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In this paper we attempt to describe the general reasons behind the world populationexplosion in the 20th century. The size of the population at the end of the century inquestion, deemed excessive by some, was a consequence of a dramatic improvementin life expectancies, attributable, in turn, to scientific innovation, the circulation ofinformation and economic growth. Nevertheless, fertility is a variable that plays acrucial role in differences in demographic growth. We identify infant mortality, femaleeducation levels and racial identity as important exogenous variables affecting fertility.It is estimated that in poor countries one additional year of primary schooling forwomen leads to 0.614 child less per couple on average (worldwide). While it may bepossible to identify a global tendency towards convergence in demographic trends,particular attention should be paid to the case of Africa, not only due to its differentdemographic patterns, but also because much of the continent's population has yet toexperience improvement in quality of life generally enjoyed across the rest of theplanet.
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We consider two fundamental properties in the analysis of two-way tables of positive data: the principle of distributional equivalence, one of the cornerstones of correspondence analysis of contingency tables, and the principle of subcompositional coherence, which forms the basis of compositional data analysis. For an analysis to be subcompositionally coherent, it suffices to analyse the ratios of the data values. The usual approach to dimension reduction in compositional data analysis is to perform principal component analysis on the logarithms of ratios, but this method does not obey the principle of distributional equivalence. We show that by introducing weights for the rows and columns, the method achieves this desirable property. This weighted log-ratio analysis is theoretically equivalent to spectral mapping , a multivariate method developed almost 30 years ago for displaying ratio-scale data from biological activity spectra. The close relationship between spectral mapping and correspondence analysis is also explained, as well as their connection with association modelling. The weighted log-ratio methodology is applied here to frequency data in linguistics and to chemical compositional data in archaeology.
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A Method is offered that makes it possible to apply generalized canonicalcorrelations analysis (CANCOR) to two or more matrices of different row and column order. The new method optimizes the generalized canonical correlationanalysis objective by considering only the observed values. This is achieved byemploying selection matrices. We present and discuss fit measures to assessthe quality of the solutions. In a simulation study we assess the performance of our new method and compare it to an existing procedure called GENCOM,proposed by Green and Carroll. We find that our new method outperforms the GENCOM algorithm both with respect to model fit and recovery of the truestructure. Moreover, as our new method does not require any type of iteration itis easier to implement and requires less computation. We illustrate the methodby means of an example concerning the relative positions of the political parties inthe Netherlands based on provincial data.
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Principal curves have been defined Hastie and Stuetzle (JASA, 1989) assmooth curves passing through the middle of a multidimensional dataset. They are nonlinear generalizations of the first principalcomponent, a characterization of which is the basis for the principalcurves definition.In this paper we propose an alternative approach based on a differentproperty of principal components. Consider a point in the space wherea multivariate normal is defined and, for each hyperplane containingthat point, compute the total variance of the normal distributionconditioned to belong to that hyperplane. Choose now the hyperplaneminimizing this conditional total variance and look for thecorresponding conditional mean. The first principal component of theoriginal distribution passes by this conditional mean and it isorthogonal to that hyperplane. This property is easily generalized todata sets with nonlinear structure. Repeating the search from differentstarting points, many points analogous to conditional means are found.We call them principal oriented points. When a one-dimensional curveruns the set of these special points it is called principal curve oforiented points. Successive principal curves are recursively definedfrom a generalization of the total variance.
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By means of classical Itô's calculus we decompose option prices asthe sum of the classical Black-Scholes formula with volatility parameterequal to the root-mean-square future average volatility plus a term dueby correlation and a term due to the volatility of the volatility. Thisdecomposition allows us to develop first and second-order approximationformulas for option prices and implied volatilities in the Heston volatilityframework, as well as to study their accuracy. Numerical examples aregiven.