860 resultados para UNCITRAL Model Law on Cross-border Insolvency


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This paper examines the effects of internationalization (international diversification) and diversification across industries (product diversification) through mergers and acquisitions (M&As) on the firm’s risk-return profile. Drawing on the theoretical work of Vachani (1991) and Rugman and Verbeke’s (2004) metrics, we classify firms according to their degree of product diversification and global reach. These two dimensions at the firm-level are moderators for the performance–expansion relationship. To account for the endogeneity of market entry decisions, we develop a panel vector autoregression. We show that global and host-triad multinational enterprises (MNEs) benefit from cross-border M&As, which reinforces their geographic footprint. In contrast to all other types of firms, home-triad firms exhibit higher firm value without a change in risk when conducting cross-industry M&As. This effect, however, depends on the degree of product diversification. For home-triad firms with a small product range engaging in cross- industry transactions is a value-enhancing growth strategy.

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Purpose – Despite recent threats of economic contraction, China still offers attractive opportunities for foreign companies seeking to expand their business activities through joint venturing (JV) partnering entry strategies. Recent research has indicated a growing recognition of the importance of relational factors in JV partnering. The purpose of this paper is to build on recent research findings that identify critical relation success factors in JVs and explores these in the context of a Hong Kong-based civil aviation services company seeking to expand business activities in Greater China. Design/methodology/approach – While the extant management literature focuses primarily on factors relevant to the inter-partner relationship between partners in the formation stage of a joint venture, this research takes a dynamic stakeholder perspective in respect of the relevant relational factors over the evolution of a partnership. The research described in this paper is based on a case-based study that identifies and examines the relevance and importance of uniquely Chinese factors such as guanxi, renqing and mianzi in the specific context of a strategic partnering relationship. Findings – This phenomenological study provides empirical evidence of critical linkages of these to intrinsically Chinese notions of guanxi, mianzi and renqing – it links these to key strategic partnering success factors identified to be trust, conflict resolution, commitment and cooperation. This study thereby reinforces the importance of the uniquely Chinese relational context in cross-border JVs. Moreover, the research findings suggest that these factors underpin the dynamic bi-directional stakeholder relationship in a Sino-foreign strategic partnership. Originality/value – This study conceptually links the uniquely Chinese relational factors (guanxi, mianzi and renqing) to key success factors supporting the establishment of a strategic partnership in a Sino-foreign context; moreover, it contributes empirical evidence substantiating the proposed conceptual linkage.

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This paper investigates whether bank integration measured by cross-border bank flows can capture the co-movements across housing markets in developed countries by using a spatial dynamic panel model. The transmission can occur through a global banking channel in which global banks intermediate wholesale funding to local banks. Changes in financial conditions are passed across borders through the banks’ balance-sheet exposure to credit, currency, maturity, and funding risks resulting in house price spillovers. While controlling for country-level and global factors, we find significant co-movement across housing markets of countries with proportionally high bank integration. Bank integration can better capture house price co-movements than other measures of economic integration. Once we account for bank exposure, other spatial linkages traditionally used to account for return co-movements across region – such as trade, foreign direct investment, portfolio investment, geographic proximity, etc. – become insignificant. Moreover, we find that the co-movement across housing markets decreases for countries with less developed mortgage markets characterized by fixed mortgage rate contracts, low limits of loan-to-value ratios and no mortgage equity withdrawal.

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What is the impact of the economy on cross national variation in far right-wing party support? This paper tests several hypotheses from existing literature on the results of the last three EP elections in all EU member states. We conceptualise the economy affects support because unemployment heightens the risks and costs that the population faces, but this is crucially mediated by labour market institutions. Findings from multiple regression analyses indicate that unemployment, real GDP growth, debt and deficits have no statistically significant effect on far right-wing party support at the national level. By contrast, labour markets influence costs and risks: where unemployment benefits and dismissal regulations are high, unemployment has no effect, but where either one of them is low, unemployment leads to higher far right-wing party support. This explains why unemployment has not led to far right-wing party support in some European countries that experienced the 2008 Eurozone crisis.

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A basic data requirement of a river flood inundation model is a Digital Terrain Model (DTM) of the reach being studied. The scale at which modeling is required determines the accuracy required of the DTM. For modeling floods in urban areas, a high resolution DTM such as that produced by airborne LiDAR (Light Detection And Ranging) is most useful, and large parts of many developed countries have now been mapped using LiDAR. In remoter areas, it is possible to model flooding on a larger scale using a lower resolution DTM, and in the near future the DTM of choice is likely to be that derived from the TanDEM-X Digital Elevation Model (DEM). A variable-resolution global DTM obtained by combining existing high and low resolution data sets would be useful for modeling flood water dynamics globally, at high resolution wherever possible and at lower resolution over larger rivers in remote areas. A further important data resource used in flood modeling is the flood extent, commonly derived from Synthetic Aperture Radar (SAR) images. Flood extents become more useful if they are intersected with the DTM, when water level observations (WLOs) at the flood boundary can be estimated at various points along the river reach. To illustrate the utility of such a global DTM, two examples of recent research involving WLOs at opposite ends of the spatial scale are discussed. The first requires high resolution spatial data, and involves the assimilation of WLOs from a real sequence of high resolution SAR images into a flood model to update the model state with observations over time, and to estimate river discharge and model parameters, including river bathymetry and friction. The results indicate the feasibility of such an Earth Observation-based flood forecasting system. The second example is at a larger scale, and uses SAR-derived WLOs to improve the lower-resolution TanDEM-X DEM in the area covered by the flood extents. The resulting reduction in random height error is significant.

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Balkanisation is a way to describe the breakdown of cross-border banking, as nervous lenders retreat in particular from the more troubled parts of the Eurozone or at least try to isolate operations within national boundaries. It is increasing at the Bank level, however the senior policy makers consider this a negative trend – Mario Draghi, president of the European Central Bank, has talked of the need to “repair this financial fragmentation” and Mark Carney, head of global regulatory body the Financial Stability Board, [and now Governor of the Bank of England] has warned that deglobalising finance will hurt growth and jobs by “reducing financial capacity and systemic resilience”. In this article I would like to examine the impact of banking balkanisation on international trade and provide some initial thoughts about remedies for excessive risk in a banking non-balkanising world.

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Species distribution models (SDM) are increasingly used to understand the factors that regulate variation in biodiversity patterns and to help plan conservation strategies. However, these models are rarely validated with independently collected data and it is unclear whether SDM performance is maintained across distinct habitats and for species with different functional traits. Highly mobile species, such as bees, can be particularly challenging to model. Here, we use independent sets of occurrence data collected systematically in several agricultural habitats to test how the predictive performance of SDMs for wild bee species depends on species traits, habitat type, and sampling technique. We used a species distribution modeling approach parametrized for the Netherlands, with presence records from 1990 to 2010 for 193 Dutch wild bees. For each species, we built a Maxent model based on 13 climate and landscape variables. We tested the predictive performance of the SDMs with independent datasets collected from orchards and arable fields across the Netherlands from 2010 to 2013, using transect surveys or pan traps. Model predictive performance depended on species traits and habitat type. Occurrence of bee species specialized in habitat and diet was better predicted than generalist bees. Predictions of habitat suitability were also more precise for habitats that are temporally more stable (orchards) than for habitats that suffer regular alterations (arable), particularly for small, solitary bees. As a conservation tool, SDMs are best suited to modeling rarer, specialist species than more generalist and will work best in long-term stable habitats. The variability of complex, short-term habitats is difficult to capture in such models and historical land use generally has low thematic resolution. To improve SDMs’ usefulness, models require explanatory variables and collection data that include detailed landscape characteristics, for example, variability of crops and flower availability. Additionally, testing SDMs with field surveys should involve multiple collection techniques.

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The impact of the Tibetan Plateau uplift on the Asian monsoons and inland arid climates is an important but also controversial question in studies of paleoenvironmental change during the Cenozoic. In order to achieve a good understanding of the background for the formation of the Asian monsoons and arid environments, it is necessary to know the characteristics of the distribution of monsoon regions and arid zones in Asia before the plateau uplift. In this study, we discuss in detail the patterns of distribution of the Asian monsoon and arid regions before the plateau uplift on the basis of modeling results without topography from a global coupled atmosphere–ocean general circulation model, compare our results with previous simulation studies and available biogeological data, and review the uncertainties in the current knowledge. Based on what we know at the moment, tropical monsoon climates existed south of 20°N in South and Southeast Asia before the plateau uplift, while the East Asian monsoon was entirely absent in the extratropics. These tropical monsoons mainly resulted from the seasonal shifts of the Inter-Tropical Convergence Zone. There may have been a quasi-monsoon region in central-southern Siberia. Most of the arid regions in the Asian continent were limited to the latitudes of 20–40°N, corresponding to the range of the subtropical high pressure year-around. In the meantime, the present-day arid regions located in the relatively high latitudes in Central Asia were most likely absent before the plateau uplift. The main results from the above modeling analyses are qualitatively consistent with the available biogeological data. These results highlight the importance of the uplift of the Tibetan Plateau in the Cenozoic evolution of the Asian climate pattern of dry–wet conditions. Future studies should be focused on effects of the changes in land–sea distribution and atmospheric CO2 concentrations before and after the plateau uplift, and also on cross-comparisons between numerical simulations and geological evidence, so that a comprehensive understanding of the evolution of the Cenozoic paleoenvironments in Asia can be achieved.

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The PhD dissertation investigates the rise of emerging country multinationals (EMNEs), a phenomenon that has opened up a series of research themes and debates. The main debate in this field is the extent to which the theories/frameworks on foreign direct investment (FDI), which have been developed from investigations on multinationals from developed countries, is relevant in explaining outward FDI from EMNEs. This debate is sparked by research suggesting that EMNEs supposedly do not hold the characteristics that are seen as a prerequisite to engaging in FDI. The underlying theme in this PhD is that the field should move away from a one size fit all categorisation of EMNEs, and explore the heterogeneity within EMNEs. Collecting data through various databases, archival articles and annual reports, there was an examination of the internationalisation process of 136 Latin American Multinationals (LAMNEs). The research explores the differences in internationalisation trajectories and global strategies and classifies firms into one of four categories. The four categories that LAMNEs fall into are: Natural-Resource Vertical Integrator, which are firms that are in resource seeking sectors; Accelerated Global, which depict firms that have become global over a very short period of time; Traditional Global, which are EMNEs that have internationalised at the same pace as developed country MNEs and Local Optimisers that only acquire or internationalise to developing countries. The analysis also looks at which decade LAMNEs engaged in FDI, to see if LAMNEs that internationalised during the 1970s and 1980s, during a time when Latin America had a closed economy, was different to LAMNEs that internationalised during the Washington consensus era of the 1990s or to firms that have only just internationalised within the last decade. The findings show that LAMNEs that internationalised before 1990 were more likely to adopt Local Optimiser strategies. However, more LAMNEs that started to internationalise during the 1990s started to adopt Traditional Global strategies, although Local Optimisers were the most prominent strategy. From 2002, there was more prominence of Accelerated Global strategies and a lot more heterogeneity among LAMNEs. Natural-Resource Vertical Integrator LAMNEs, tended to start to internationalisation process during the 1970s/1980s. Despite the rise of EMNEs, and by extension LAMNEs opting to use cross border merger and acquisitions (M&A), there is little research on whether this entry mode has been successful. Contrary to the argument that EMNEs are “internationalising successfully” through this strategy, the findings show that these firms are highly geared and are running less efficiently against their Western competitors. In comparison, LAMNEs internationalising through a more gradual approach, are outperforming their Western competitors on efficiency and are not highly geared- i.e. do not hold a lot of debt. The conclusion of the thesis is the emphasis of moving away from evaluating firms from their country or region of origin, but rather through the global strategy they are using. This will give a more a robust firm level of analysis, and help develop the understanding of EMNEs and international business theory.

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A new sparse kernel density estimator is introduced based on the minimum integrated square error criterion combining local component analysis for the finite mixture model. We start with a Parzen window estimator which has the Gaussian kernels with a common covariance matrix, the local component analysis is initially applied to find the covariance matrix using expectation maximization algorithm. Since the constraint on the mixing coefficients of a finite mixture model is on the multinomial manifold, we then use the well-known Riemannian trust-region algorithm to find the set of sparse mixing coefficients. The first and second order Riemannian geometry of the multinomial manifold are utilized in the Riemannian trust-region algorithm. Numerical examples are employed to demonstrate that the proposed approach is effective in constructing sparse kernel density estimators with competitive accuracy to existing kernel density estimators.

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Atmosphere only and ocean only variational data assimilation (DA) schemes are able to use window lengths that are optimal for the error growth rate, non-linearity and observation density of the respective systems. Typical window lengths are 6-12 hours for the atmosphere and 2-10 days for the ocean. However, in the implementation of coupled DA schemes it has been necessary to match the window length of the ocean to that of the atmosphere, which may potentially sacrifice the accuracy of the ocean analysis in order to provide a more balanced coupled state. This paper investigates how extending the window length in the presence of model error affects both the analysis of the coupled state and the initialized forecast when using coupled DA with differing degrees of coupling. Results are illustrated using an idealized single column model of the coupled atmosphere-ocean system. It is found that the analysis error from an uncoupled DA scheme can be smaller than that from a coupled analysis at the initial time, due to faster error growth in the coupled system. However, this does not necessarily lead to a more accurate forecast due to imbalances in the coupled state. Instead coupled DA is more able to update the initial state to reduce the impact of the model error on the accuracy of the forecast. The effect of model error is potentially most detrimental in the weakly coupled formulation due to the inconsistency between the coupled model used in the outer loop and uncoupled models used in the inner loop.

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In this paper we deal with a Bayesian analysis for right-censored survival data suitable for populations with a cure rate. We consider a cure rate model based on the negative binomial distribution, encompassing as a special case the promotion time cure model. Bayesian analysis is based on Markov chain Monte Carlo (MCMC) methods. We also present some discussion on model selection and an illustration with a real dataset.

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In interval-censored survival data, the event of interest is not observed exactly but is only known to occur within some time interval. Such data appear very frequently. In this paper, we are concerned only with parametric forms, and so a location-scale regression model based on the exponentiated Weibull distribution is proposed for modeling interval-censored data. We show that the proposed log-exponentiated Weibull regression model for interval-censored data represents a parametric family of models that include other regression models that are broadly used in lifetime data analysis. Assuming the use of interval-censored data, we employ a frequentist analysis, a jackknife estimator, a parametric bootstrap and a Bayesian analysis for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Furthermore, for different parameter settings, sample sizes and censoring percentages, various simulations are performed; in addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended to a modified deviance residual in log-exponentiated Weibull regression models for interval-censored data. (C) 2009 Elsevier B.V. All rights reserved.

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We investigate the critical behavior of a stochastic lattice model describing a predator-prey system. By means of Monte Carlo procedure we simulate the model defined on a regular square lattice and determine the threshold of species coexistence, that is, the critical phase boundaries related to the transition between an active state, where both species coexist and an absorbing state where one of the species is extinct. A finite size scaling analysis is employed to determine the order parameter, order parameter fluctuations, correlation length and the critical exponents. Our numerical results for the critical exponents agree with those of the directed percolation universality class. We also check the validity of the hyperscaling relation and present the data collapse curves.

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Elastic scattering of (8)B and (7)Be on a (58)Ni target has been measured at energies near the Coulomb barrier. The total reaction cross sections were deduced from Optical-model fits to the experimental angular distributions. Comparison with other systems shows evidence for proton-halo effects on (8)B, as well as for neutron-halo on (6)He reactions. While the enhancement in the cross section observed for (8)B is explained in terms of projectile breakup, in the case of (6)He reactions, the particle transfer proces explains the observed enhancement.