983 resultados para Intégration du marché


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Les auteurs présentent un survol des logiciels de portails de bibliothèque. La notion de portail de bibliothèque est d’abord définie, puis les principales fonctionnalités de ce type de produit (métarecherche, personnalisation, authentification) sont présentées et expliquées. Un aperçu du marché des logiciels de portail est ensuite donné. Des questions reliées à la fiabilité des résultats et à la formation des utilisateurs sont également soulevées. // The authors present a brief review of software for library portals. The concept of library portals is defined and their main functionalities subsequently presented and explained (meta search engines, personalization, authentication). A general survey of the market for portal software is given before addressing certain questions about the reliability of their results and user training.

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Latent variable models in finance originate both from asset pricing theory and time series analysis. These two strands of literature appeal to two different concepts of latent structures, which are both useful to reduce the dimension of a statistical model specified for a multivariate time series of asset prices. In the CAPM or APT beta pricing models, the dimension reduction is cross-sectional in nature, while in time-series state-space models, dimension is reduced longitudinally by assuming conditional independence between consecutive returns, given a small number of state variables. In this paper, we use the concept of Stochastic Discount Factor (SDF) or pricing kernel as a unifying principle to integrate these two concepts of latent variables. Beta pricing relations amount to characterize the factors as a basis of a vectorial space for the SDF. The coefficients of the SDF with respect to the factors are specified as deterministic functions of some state variables which summarize their dynamics. In beta pricing models, it is often said that only the factorial risk is compensated since the remaining idiosyncratic risk is diversifiable. Implicitly, this argument can be interpreted as a conditional cross-sectional factor structure, that is, a conditional independence between contemporaneous returns of a large number of assets, given a small number of factors, like in standard Factor Analysis. We provide this unifying analysis in the context of conditional equilibrium beta pricing as well as asset pricing with stochastic volatility, stochastic interest rates and other state variables. We address the general issue of econometric specifications of dynamic asset pricing models, which cover the modern literature on conditionally heteroskedastic factor models as well as equilibrium-based asset pricing models with an intertemporal specification of preferences and market fundamentals. We interpret various instantaneous causality relationships between state variables and market fundamentals as leverage effects and discuss their central role relative to the validity of standard CAPM-like stock pricing and preference-free option pricing.

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This paper studies vertical R&D spillovers between upstream and downstream firms. The model incorporates two vertically related industries, with horizontal spillovers within each industry and vertical spillovers between the two industries. Four types of R&D cooperation are studied : no cooperation, horizontal cooperation, vertical cooperation, and simultaneous horizontal and vertical cooperation. Vertical spillovers always increase R&D and welfare, while horizontal spillovers may increase or decrease them. The comparison of cooperative settings in terms of R&D shows that no setting uniformly dominates the others. Which type of cooperation yields more R&D depends on horizontal and vertical spillovers, and market structure. The ranking of cooperative structures hinges on the signs and magnitudes of three competitive externalities (vertical, horizontal, and diagonal) which capture the effect of the R&D of a firm on the profits of other firms. One of the basic results of the strategic investment literature is that cooperation between competitors increases (decreases) R&D when horizontal spillovers are high (low); the model shows that this result does not necessarily hold when vertical spillovers and vertical cooperation are taken into account. The paper proposes a theory of innovation and market structure, showing that the relation between innovation and competition depends on horizontal spillovers, vertical spillovers, and cooperative settings. The private incentives for R&D cooperation are addressed. It is found that buyers and sellers have divergent interests regarding the choice of cooperative settings and that spillovers increase the likelihood of the emergence of cooperation in a decentralized equilibrium.

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It is often thought that a tariff reduction, by opening up the domestic market to foreign firms, should lessen the need for a policy aimed at discouraging domestic mergers. This implicitly assumes that the tariff in question is sufficiently high to prevent foreign firms from selling in the domestic market. However, not all tariffs are prohibitive, so that foreign firms may be present in the domestic market before it is abolished. Furthermore, even if the tariff is prohibitive, a merger of domestic firms may render it nonprohibitive, thus inviting foreign firms to penetrate the domestic market. In this paper, we show, using a simple example, that in the latter two cases, abolishing the tariff may in fact make the domestic merger more profitable. Hence, trade liberalization will not necessarily reduce the profitability of domestic mergers.

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Analyses of trade quotas typically assume that the quota restricts the flow of some nondurable good. Many real-world quotas, however, restrict the stock of durable imports. We consider the cases where (1) anyone is free to export against such quotas and where (2) only those allocated portions of the total quota are free to export against such quotas. Recent econometric investigations of such quotas have focused on the price of the durable as an indicator of tightness induced by the quota. We show why this is an inappropriate indicator and suggest alternatives.

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The aim of this paper is to demonstrate that, even if Marx's solution to the transformation problem can be modified, his basic conclusions remain valid. the proposed alternative solution which is presented hare is based on the constraint of a common general profit rate in both spaces and a money wage level which will be determined simultaneously with prices.

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The aim of this paper is to demonstrate that, even if Marx's solution to the transformation problem can be modified, his basic concusions remain valid.

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In this paper, we look at how labor market conditions at different points during the tenure of individuals with firms are correlated with current earnings. Using data on individuals from the German Socioeconomic Panel for the 1985-1994 period, we find that both the contemporaneous unemployment rate and prior values of the unemployment rate are significantly correlated with current earnings, contrary to results for the American labor market. Estimated elasticities vary between 9 and 15 percent for the elasticity of earnings with respect to current unemployment rates, and between 6 and 10 percent with respect to unemployment rates at the start of current firm tenure. Moreover, whereas local unemployment rates determine levels of earnings, national rates influence contemporaneous variations in earnings. We interpret this result as evidence that German unions do, in fact, bargain over wages and employment, but that models of individualistic contracts, such as the implicit contract model, may explain some of the observed wage drift and longer-term wage movements reasonably well. Furthermore, we explore the heterogeneity of contracts over a variety of worker and job characteristics. In particular, we find evidence that contracts differ across firm size and worker type. Workers of large firms are remarkably more insulated from the job market than workers for any other type of firm, indicating the importance of internal job markets.

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In this paper we propose exact likelihood-based mean-variance efficiency tests of the market portfolio in the context of Capital Asset Pricing Model (CAPM), allowing for a wide class of error distributions which include normality as a special case. These tests are developed in the frame-work of multivariate linear regressions (MLR). It is well known however that despite their simple statistical structure, standard asymptotically justified MLR-based tests are unreliable. In financial econometrics, exact tests have been proposed for a few specific hypotheses [Jobson and Korkie (Journal of Financial Economics, 1982), MacKinlay (Journal of Financial Economics, 1987), Gib-bons, Ross and Shanken (Econometrica, 1989), Zhou (Journal of Finance 1993)], most of which depend on normality. For the gaussian model, our tests correspond to Gibbons, Ross and Shanken’s mean-variance efficiency tests. In non-gaussian contexts, we reconsider mean-variance efficiency tests allowing for multivariate Student-t and gaussian mixture errors. Our framework allows to cast more evidence on whether the normality assumption is too restrictive when testing the CAPM. We also propose exact multivariate diagnostic checks (including tests for multivariate GARCH and mul-tivariate generalization of the well known variance ratio tests) and goodness of fit tests as well as a set estimate for the intervening nuisance parameters. Our results [over five-year subperiods] show the following: (i) multivariate normality is rejected in most subperiods, (ii) residual checks reveal no significant departures from the multivariate i.i.d. assumption, and (iii) mean-variance efficiency tests of the market portfolio is not rejected as frequently once it is allowed for the possibility of non-normal errors.

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In this paper, we propose several finite-sample specification tests for multivariate linear regressions (MLR) with applications to asset pricing models. We focus on departures from the assumption of i.i.d. errors assumption, at univariate and multivariate levels, with Gaussian and non-Gaussian (including Student t) errors. The univariate tests studied extend existing exact procedures by allowing for unspecified parameters in the error distributions (e.g., the degrees of freedom in the case of the Student t distribution). The multivariate tests are based on properly standardized multivariate residuals to ensure invariance to MLR coefficients and error covariances. We consider tests for serial correlation, tests for multivariate GARCH and sign-type tests against general dependencies and asymmetries. The procedures proposed provide exact versions of those applied in Shanken (1990) which consist in combining univariate specification tests. Specifically, we combine tests across equations using the MC test procedure to avoid Bonferroni-type bounds. Since non-Gaussian based tests are not pivotal, we apply the “maximized MC” (MMC) test method [Dufour (2002)], where the MC p-value for the tested hypothesis (which depends on nuisance parameters) is maximized (with respect to these nuisance parameters) to control the test’s significance level. The tests proposed are applied to an asset pricing model with observable risk-free rates, using monthly returns on New York Stock Exchange (NYSE) portfolios over five-year subperiods from 1926-1995. Our empirical results reveal the following. Whereas univariate exact tests indicate significant serial correlation, asymmetries and GARCH in some equations, such effects are much less prevalent once error cross-equation covariances are accounted for. In addition, significant departures from the i.i.d. hypothesis are less evident once we allow for non-Gaussian errors.

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We study the problem of testing the error distribution in a multivariate linear regression (MLR) model. The tests are functions of appropriately standardized multivariate least squares residuals whose distribution is invariant to the unknown cross-equation error covariance matrix. Empirical multivariate skewness and kurtosis criteria are then compared to simulation-based estimate of their expected value under the hypothesized distribution. Special cases considered include testing multivariate normal, Student t; normal mixtures and stable error models. In the Gaussian case, finite-sample versions of the standard multivariate skewness and kurtosis tests are derived. To do this, we exploit simple, double and multi-stage Monte Carlo test methods. For non-Gaussian distribution families involving nuisance parameters, confidence sets are derived for the the nuisance parameters and the error distribution. The procedures considered are evaluated in a small simulation experi-ment. Finally, the tests are applied to an asset pricing model with observable risk-free rates, using monthly returns on New York Stock Exchange (NYSE) portfolios over five-year subperiods from 1926-1995.

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We analyze the behavior of a nonrenewable resource cartel that anticipates being forced, at some date in the future, to break-up into an oligopolistic market in which its members will then have to compete as rivals. Under reasonable assumptions about the value function of the individual firms in the oligopolistic equilibrium that follows the break-up, we show that the cartel will then produce more over the same interval of time than it would if there were no threat of dissolution, and that its rate of extraction is a decreasing function of the cartel's life; that there are circumstances under which the cartel will attach a negative marginal value to the resource stocks, in which case the rate of depletion will be increasing over time during the cartel phase; that, for a given date of dissolution, the equilibrium stocks allocated to the post-cartel phase will increase as a function of the total initial stocks, whereas those allocated to the cartel phase will increase at first, but begin decreasing beyond some level of the total initial stocks.

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In this paper, we propose exact inference procedures for asset pricing models that can be formulated in the framework of a multivariate linear regression (CAPM), allowing for stable error distributions. The normality assumption on the distribution of stock returns is usually rejected in empirical studies, due to excess kurtosis and asymmetry. To model such data, we propose a comprehensive statistical approach which allows for alternative - possibly asymmetric - heavy tailed distributions without the use of large-sample approximations. The methods suggested are based on Monte Carlo test techniques. Goodness-of-fit tests are formally incorporated to ensure that the error distributions considered are empirically sustainable, from which exact confidence sets for the unknown tail area and asymmetry parameters of the stable error distribution are derived. Tests for the efficiency of the market portfolio (zero intercepts) which explicitly allow for the presence of (unknown) nuisance parameter in the stable error distribution are derived. The methods proposed are applied to monthly returns on 12 portfolios of the New York Stock Exchange over the period 1926-1995 (5 year subperiods). We find that stable possibly skewed distributions provide statistically significant improvement in goodness-of-fit and lead to fewer rejections of the efficiency hypothesis.

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This paper examines the use of bundling by a firm that sells in two national markets and faces entry by parallel traders. The firm can bundle its main product, - a tradable good- with a non-traded service. It chooses between the strategies of pure bundling, mixed bundling and no bundling. The paper shows that in the low-price country the threat of grey trade elicits a move from mixed bundling, or no bundling, towards pure bundling. It encourages a move from pure bundling towards mixes bundling or no bundling in the high-price country. The set of parameter values for which the profit maximizing strategy is not to supply the low price country is smaller than in the absence of bundling. The welfare effects of deterrence of grey trade are not those found in conventional models of price arbitrage. Some consumers in the low-price country may gain from the threat of entry by parallel traders although they pay a higher price. This is due to the fact that the firm responds to the threat of arbitrageurs by increasing the amount of services it puts in the bundle targeted at consumers in that country. Similarly, the threat of parallel trade may affect some consumers in the hight-price country adversely.

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