25 resultados para Returns from Exile


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The literature on multinationality and firm performance has generally disregarded the role of geography. However, the location of FDI assumes particular importance in terms of the link between multinationality at the firm level. The purpose of this paper is to consider the multinationality-performance relationship within the context of greater emphasis on the importance of location, but also emphasising the importance of the location decision. This paper draws on firm-level data covering over 16,000 multinationals from 46 countries over the period of 1997-2007 and allows for different effects upon the performance of the multinational firm depending on the level of development of the host economy. In our results, we find a clear positive relation between multinationality and firm performance. However, investment in developing countries is associated with larger effects on performance than in the case of investment in developed countries. We also find that the return to investing in developing countries is U-shaped. This indicates that multinationals are likely to face losses in the early stage of their investment in developing countries before the positive returns are realized. Overall, our results suggest that the net gains for multinationals from greater geographical diversification have not yet been fully explored. Geographical diversification into developing countries may be an important source of competitive advantages that deserves more serious consideration from business leaders and academics alike. © 2013 Springer-Verlag Berlin Heidelberg.

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In a Data Envelopment Analysis model, some of the weights used to compute the efficiency of a unit can have zero or negligible value despite of the importance of the corresponding input or output. This paper offers an approach to preventing inputs and outputs from being ignored in the DEA assessment under the multiple input and output VRS environment, building on an approach introduced in Allen and Thanassoulis (2004) for single input multiple output CRS cases. The proposed method is based on the idea of introducing unobserved DMUs created by adjusting input and output levels of certain observed relatively efficient DMUs, in a manner which reflects a combination of technical information and the decision maker's value judgements. In contrast to many alternative techniques used to constrain weights and/or improve envelopment in DEA, this approach allows one to impose local information on production trade-offs, which are in line with the general VRS technology. The suggested procedure is illustrated using real data. © 2011 Elsevier B.V. All rights reserved.

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Models for the conditional joint distribution of the U.S. Dollar/Japanese Yen and Euro/Japanese Yen exchange rates, from November 2001 until June 2007, are evaluated and compared. The conditional dependency is allowed to vary across time, as a function of either historical returns or a combination of past return data and option-implied dependence estimates. Using prices of currency options that are available in the public domain, risk-neutral dependency expectations are extracted through a copula repre- sentation of the bivariate risk-neutral density. For this purpose, we employ either the one-parameter \Normal" or a two-parameter \Gumbel Mixture" specification. The latter provides forward-looking information regarding the overall degree of covariation, as well as, the level and direction of asymmetric dependence. Specifications that include option-based measures in their information set are found to outperform, in-sample and out-of-sample, models that rely solely on historical returns.

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1. Exchange of carbon dioxide (CO2) from soils can contribute significantly to the global warming potential (GWP) of agro-ecosystems. Due to variations in soil type, climatic onditions and land management practices, exchange of CO2 can differ markedly in different geographical locations. The food industry is developing carbon footprints for their products necessitating integration of CO2 exchange from soils with other CO2 emissions along the food chain. It may be advantageous to grow certain crops in different geographical locations to minimize CO2 emissions from the soil, and this may provide potential to offset other emissions in the food chain, such as transport. 2. Values are derived for the C balance of soils growing horticultural crops in the UK, Spain and Uganda. Net ecosystem production (NEP) is firstly calculated from the difference in net primary production (NPP) and heterotrophic soil respiration (Rh). Both NPP and Rh were estimated from intensive direct field measurements. Secondly, net biome production (NBP) is calculated by subtracting the crop biomass from NEP to give an indication of C balance. The importance of soil exchange is discussed in the light of recent discussions on carbon footprints and within the context of food life-cycle assessment (LCA). 3. The amount of crop relative to the biomass and the Rh prevailing in the different countries were the dominant factors influencing the magnitude of NEP and NBP. The majority of the biomass for lettuce Lactuca sativa and vining peas Pisum sativum, was removed from the field as crop; therefore, NEP and NBP were mainly negative. This was amplified for lettuces grown in Uganda (-16·5 and -17 t C ha-1 year-1 compared to UK and Spain -4·8 to 7·4 and -5·1 to 6·3 t C ha-1 year-1 for NEP and NBP, respectively) where the climate elevated Rh. 4. Synthesis and applications. This study demonstrates the importance of soil emissions in the overall life cycle of vegetables. Variability in such emissions suggests that assigning a single value to food carbon footprints may not be adequate, even within a country. Locations with high heterotrophic soil respiration, such as Spain and Uganda (21·9 and 21·6 t C ha-1 year-1, respectively), could mitigate the negative effects of climate on the C costs of crop production by growth of crops with greater returns of residue to the soil. This would minimize net CO2 emissions from these agricultural ecosystems.

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We examine the returns to UK government bonds before, during and between the phases of quantitative easing to identify the side effects for the market itself. We show that the onset of QE led to a sustained reduction in the costs of trading and removed some return regularities. However, controlling for a wide range of market activity, including issuance and QE announcements, we find evidence that investors could have earned excess returns after costs by trading in response to the purchase auction calendar. Drawing on economic theory, we explore the implications of these findings for both the efficiency of the market and the costs of government debt management in both the short and long run.

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We test for departures from normal and independent and identically distributed (NIID) log returns, for log returns under the alternative hypothesis that are self-affine and either long-range dependent, or drawn randomly from an L-stable distribution with infinite higher-order moments. The finite sample performance of estimators of the two forms of self-affinity is explored in a simulation study. In contrast to rescaled range analysis and other conventional estimation methods, the variant of fluctuation analysis that considers finite sample moments only is able to identify both forms of self-affinity. When log returns are self-affine and long-range dependent under the alternative hypothesis, however, rescaled range analysis has higher power than fluctuation analysis. The techniques are illustrated by means of an analysis of the daily log returns for the indices of 11 stock markets of developed countries. Several of the smaller stock markets by capitalization exhibit evidence of long-range dependence in log returns. © 2012 Elsevier Inc. All rights reserved.

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We report an empirical analysis of long-range dependence in the returns of eight stock market indices, using the Rescaled Range Analysis (RRA) to estimate the Hurst exponent. Monte Carlo and bootstrap simulations are used to construct critical values for the null hypothesis of no long-range dependence. The issue of disentangling short-range and long-range dependence is examined. Pre-filtering by fitting a (short-range) autoregressive model eliminates part of the long-range dependence when the latter is present, while failure to pre-filter leaves open the possibility of conflating short-range and long-range dependence. There is a strong evidence of long-range dependence for the small central European Czech stock market index PX-glob, and a weaker evidence for two smaller western European stock market indices, MSE (Spain) and SWX (Switzerland). There is little or no evidence of long-range dependence for the other five indices, including those with the largest capitalizations among those considered, DJIA (US) and FTSE350 (UK). These results are generally consistent with prior expectations concerning the relative efficiency of the stock markets examined. © 2011 Elsevier Inc.

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Purpose – The use of key accounts has become a mature trend and most industrial firms use this concept in some form. Selling firms establish key account teams to attend to important customers and consolidate their selling activities. Yet, despite such increased efforts on behalf of key accounts, sufficient research has not quantified the returns on key account strategy nor has it firmly established performance differences between key and non-key accounts within a firm. In response to this shortcoming, this study aims to examine returns on key accounts. Design Methodology/approach – Data were collected from a global consulting firm. The data collection started two years after the implementation of the key account program. Data were collected on recently acquired customers (within the previous year) at two time periods: year 1 and year 3 (based on company access of data). Findings – Initially, key accounts perform as well or better than other types of accounts. However, in the long term, key accounts are less satisfied, less profitable and less beneficial for a firm’s growth than other types of accounts. Because the returns to key account expenditures, thus, appear mixed, firms should be cautious in expanding their key account strategies. Research limitations implications – The study contributes to research in three areas. First, most research on the effectiveness of key accounts refers to the between-firm level, whereas this study examines the effect within a single firm. Second, this study examines the temporal aspects of key accounts, namely, what happens to key accounts over time, in comparison with other accounts in a fairly large sample. Third, it considers the survival rates of key accounts versus other types of accounts. Practical implications – The authors suggest that firms also need to track their key accounts better because the results show that key accounts are less satisfied, less profitable and less beneficial for a firm’s growth than other types of accounts. Originality/value – Extant research has not examined these issues.

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Research Question/Issue - Which forms of state control over corporations have emerged in countries that made a transition from centrally-planned to marked-based economies and what are their implications for corporate governance? We assess the literature on variation and evolution of state control in transition economies, focusing on corporate governance of state-controlled firms. We highlight emerging trends and identify future research avenues. Research Findings/Insights - Based on our analysis of more than 100 articles in leading management, finance, and economics journals since 1989, we demonstrate how research on state control evolved from a polarized approach of public–private equity ownership comparison to studying a variety of constellations of state capitalism. Theoretical/Academic Implications - We identify theoretical perspectives that help us better understand benefits and costs associated with various forms of state control over firms. We encourage future studies to examine how context-specific factors determine the effect of state control on corporate governance. Practitioner/Policy Implications - Investors and policymakers should consider under which conditions investing in state-affiliated firms generates superior returns.

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It is important to help researchers find valuable papers from a large literature collection. To this end, many graph-based ranking algorithms have been proposed. However, most of these algorithms suffer from the problem of ranking bias. Ranking bias hurts the usefulness of a ranking algorithm because it returns a ranking list with an undesirable time distribution. This paper is a focused study on how to alleviate ranking bias by leveraging the heterogeneous network structure of the literature collection. We propose a new graph-based ranking algorithm, MutualRank, that integrates mutual reinforcement relationships among networks of papers, researchers, and venues to achieve a more synthetic, accurate, and less-biased ranking than previous methods. MutualRank provides a unified model that involves both intra- and inter-network information for ranking papers, researchers, and venues simultaneously. We use the ACL Anthology Network as the benchmark data set and construct the gold standard from computer linguistics course websites of well-known universities and two well-known textbooks. The experimental results show that MutualRank greatly outperforms the state-of-the-art competitors, including PageRank, HITS, CoRank, Future Rank, and P-Rank, in ranking papers in both improving ranking effectiveness and alleviating ranking bias. Rankings of researchers and venues by MutualRank are also quite reasonable.