925 resultados para country risk indexes


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The purpose of this paper is to examine, using panel data econometric techniques, the determinants of a firm’s strategy to invest in a conflict location. To the best of our knowledge this has not been done before. We use a large database of firm-level data that includes 2858 multinational firms that have a subsidiary in a developing country (during 1999-2006). Out of these firms 290 are classified as having a subsidiary in a conflict location. The choice of a conflict location is based on data from the Inter Country Risk Guide (ICRG). We start with the population of multinationals who have chosen to invest in low income countries with weak institutions. Our analysis then proceeds to explain the decision of those firms to invest in conflict locations. We have four hypotheses: (1) Firms with concentrated ownership are more likely to invest in a conflict region; (2) Firms from countries with weaker institutions are more likely to invest in conflict regions; (3) Firms and Countries with less concern over corporate social responsibility are more likely to invest in conflict countries; and (4) that there is large sector level differences in the propensity to invest in a conflict region. The results suggest that all of these hypotheses can be confirmed.

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My dissertation investigates the financial linkages and transmission of economic shocks between the US and the smallest emerging markets (frontier markets). The first chapter sets up an empirical model that examines the impact of US market returns and conditional volatility on the returns and conditional volatilities of twenty-one frontier markets. The model is estimated via maximum likelihood; utilizes the GARCH model of errors, and is applied to daily country data from the MSCI Barra. We find limited, but statistically significant exposure of Frontier markets to shocks from the US. Our results suggest that it is not the lagged US market returns that have impact; rather it is the expected US market returns that influence frontier market returns The second chapter sets up an empirical time-varying parameter (TVP) model to explore the time-variation in the impact of mean US returns on mean Frontier market returns. The model utilizes the Kalman filter algorithm as well as the GARCH model of errors and is applied to daily country data from the MSCI Barra. The TVP model detects statistically significant time-variation in the impact of US returns and low, but statistically and quantitatively important impact of US market conditional volatility. The third chapter studies the risk-return relationship in twenty Frontier country stock markets by setting up an international version of the intertemporal capital asset pricing model. The systematic risk in this model comes from covariance of Frontier market stock index returns with world returns. Both the systematic risk and risk premium are time-varying in our model. We also incorporate own country variances as additional determinants of Frontier country returns. Our results suggest statistically significant impact of both world and own country risk in explaining Frontier country returns. Time-variation in the world risk premium is also found to be statistically significant for most Frontier market returns. However, own country risk is found to be quantitatively more important.

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Much potential for growth in hospitality firms exists in foreign countries, but expansion abroad typicality bears additional risks that could be detrimental to the operations. The authors explore those risks, currency exchange risk, and country risk, and offer practical techniques to access, manage, control, and reduce them. Deriving benefits from global opportunities requires effective management of these areas

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Estimating the required rate of return for hotel properties is a daunting task because a lodging property is considered a hybrid between a real estate asset, and a revenue-generating enterprise affiliated with a hotel brand. Computing the expected rate of return for a hotel becomes even more complicated when a third party foreign investor/entrepreneur is the one performing the computation for an investment hotel in an emerging country. This clinical case illustrates the challenges surrounding the estimation of a project’s cost of equity in the multinational hotel industry. The results reveal that estimating cost of equity in emerging markets for hotel investments continues to be a conundrum. Future investors should make multiple adjustments and use several models when making their capital investment decisions.

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La presente valorización busca determinar el precio de la acción de Cementos Pacasmayo que refleje los fundamentos financieros de la empresa, así como su capacidad de generación de ingresos de acuerdo con sus expectativas de crecimiento. El presente trabajo se divide en nueve secciones. Para valorizar Cementos Pacasmayo, se ha iniciado con la descripción del negocio y se hace un análisis de las características de la empresa, considerando las líneas del negocio, las áreas geográficas y el proceso productivo. En la segunda sección se analiza el macroambiente internacional, regional y doméstico que nos permite entender el contexto de operación de la empresa. En una tercera sección, se ha realizado un análisis FODA y un análisis de las cinco fuerzas de Porter para determinar las fortalezas y las debilidades, así como las oportunidades y las amenazas de la empresa. En la cuarta sección se valora el posicionamiento competitivo, así como factores organizativos y sociales de Pacasmayo. Por otro lado, en la quinta sección, se ha realizado el análisis de los estados financieros para la determinación de las expectativas de crecimiento de la empresa. Considerando los resultados del análisis de la empresa, en la sexta sección se ha determinado conveniente utilizar tres métodos de valorización: flujo de caja descontado, valorización por múltiplos de empresas comparables y valorización por transacciones comparables. En la séptima sección se realiza un análisis de sensibilidad de la proyección de la rentabilidad de Pacasmayo, cuando una o varias variables que conforman el modelo, bajo las cuales se elaboraron las proyecciones financieras, se modifican (crecimiento de ventas, crecimiento perpetuo, country risk premium, costo de ventas, cambio en el WACC, costo de la deuda y cambio en el WACC perpetuo). En la octava sección se detalla el resumen de la inversión, que explica los resultados de los métodos de valoración utilizados (DCF, múltiplos de empresas comparables y valorización por transacciones comparables). Finalmente, se muestran las conclusiones y las recomendaciones para la empresa valorizada.

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Some studies suggest that there are urban-rural variations in cancer incidence but whether these simply reflect urban-rural socioeconomic variation is unclear. We investigated whether there were urban-rural variations in the incidence of 18 cancers, after adjusting for socioeconomic status. Cancers diagnosed between 1995 and 2007 were extracted from the population-based National Cancer Registry Ireland and Northern Ireland Cancer Registry and categorised by urban-rural status, based on population density of area of residence at diagnosis (rural 15 people per hectare). Relative risks (RR) were calculated by negative binomial regression, adjusting for age, country and three area-based markers of socioeconomic status. Risks were significantly higher in both sexes in urban than rural residents with head and neck (males RR urban vs. rural = 1.53, 95 % CI 1.42-1.64; females RR = 1.29, 95 % CI 1.15-1.45), esophageal (males 1.21, 1.11-1.31; females 1.21, 1.08-1.35), stomach (males 1.36, 1.27-1.46; females 1.19, 1.08-1.30), colorectal (males 1.14, 1.09-1.18; females 1.04, 1.00-1.09), lung (males 1.54, 1.47-1.61; females 1.74, 1.65-1.84), non-melanoma skin (males 1.13, 1.10-1.17; females 1.23, 1.19-1.27) and bladder (males 1.30, 1.21-1.39; females 1.31, 1.17-1.46) cancers. Risks of breast, cervical, kidney and brain cancer were significantly higher in females in urban areas. Prostate cancer risk was higher in rural areas (0.94, 0.90-0.97). Other cancers showed no significant urban-rural differences. After adjusting for socioeconomic variation, urban-rural differences were evident for 12 of 18 cancers. Variations in healthcare utilization and known risk factors likely explain some of the observed associations. Explanations for others are unclear and, in the interests of equity, warrant further investigation. © 2014 The New York Academy of Medicine.

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Cultural comparisons enjoy increasing popularity in economics. Since cultural comparison must abandon random allocation to treatments, it is unclear whether differences found between countries can be attributed to country characteristics or are merely driven by differences in subject pools. In experiments in two Chinese cities and at two campuses in Ethiopia, we show that within-country differences are negligible. Differences between the two countries, on the other hand, are large.

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The Simplified Acute Physiology Score II (SAPS II) and Logistic Organ Dysfunction System (LODS) are instruments used to classify Intensive Care Unit (ICU) inpatients according to the severity of their condition and risk of death, and evaluate the quality of nursing care. The objective of this study is to evaluate and compare the performance of SAPS II and LODS to predict the mortality of patients admitted to the ICU. The participants were 600 patients from four ICUs located in Sao Paulo, Brazil. Receiver Operator Characteristic (ROC) curves were used to compare the performance of the indexes. Results: The areas under the ROC curves of LODS (0.69) and SAPS II (0.71) indicated moderate discriminatory capacity to identify death or survival. No statistically significant differences were found between these areas (p=0.26). In conclusion, there was equivalence between SAPS II and LODS to estimate the risk of death of ICU patients.

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Switzerland is currently porcine reproductive and respiratory syndrome virus (PRRSV) free, but semen imports from PRRSV-infected European countries are increasing. As the virus can be transmitted via semen, for example, when a free boar stud becomes infected, and the risk of its import in terms of PRRSV introduction is unknown, the annual probability to accidentally import the virus into Switzerland was estimated in a risk assessment. A quantitative stochastic model was set up with data comprised by import figures of 2010, interviews with boar stud owners and expert opinion. It resulted in an annual median number of 0.18 imported ejaculates (= imported semen doses from one collection from one donor) from PRRSV-infected boars. Hence, one infected ejaculate would be imported every 6 years and infect a mean of 10 sows. These results suggest that under current circumstances, there is a substantial risk of PRRSV introduction into Switzerland via imported boar semen and that measures to enhance safety of imports should be taken. The time from infection of a previously negative boar stud to its detection had the highest impact on the number of imported 'positive' ejaculates. Therefore, emphasis should be placed on PRRSV monitoring protocols in boar studs. Results indicated that a substantial increase in safety could only be achieved with much tighter sampling protocols than currently performed. Generally, the model could easily be customized for other applications like other countries or regions or even sow farms that want to estimate their risk when purchasing semen from a particular boar stud.

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The constellation of adverse cardiovascular disease (CVD) and metabolic risk factors, including elevated abdominal obesity, blood pressure (BP), glucose, and triglycerides (TG) and lowered high-density lipoprotein-cholesterol (HDL-C), has been termed the metabolic syndrome (MetSyn) [1]. A number of different definitions have been developed by the World Health Organization (WHO) [2], the National Cholesterol Education Program Adult Treatment Panel III (ATP III) [3], the European Group for the Study of Insulin Resistance (EGIR) [4] and, most recently, the International Diabetes Federation (IDF) [5]. Since there is no universal definition of the Metabolic Syndrome, several authors have derived different risk scores to represent the clustering of its components [6-11].

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The existing method of pipeline health monitoring, which requires an entire pipeline to be inspected periodically, is both time-wasting and expensive. A risk-based model that reduces the amount of time spent on inspection has been presented. This model not only reduces the cost of maintaining petroleum pipelines, but also suggests efficient design and operation philosophy, construction methodology and logical insurance plans. The risk-based model uses Analytic Hierarchy Process (AHP), a multiple attribute decision-making technique, to identify the factors that influence failure on specific segments and analyzes their effects by determining probability of risk factors. The severity of failure is determined through consequence analysis. From this, the effect of a failure caused by each risk factor can be established in terms of cost, and the cumulative effect of failure is determined through probability analysis. The technique does not totally eliminate subjectivity, but it is an improvement over the existing inspection method.

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The existing method of pipeline health monitoring, which requires an entire pipeline to be inspected periodically, is both time-wasting and expensive. A risk-based model that reduces the amount of time spent on inspection has been presented. This model not only reduces the cost of maintaining petroleum pipelines, but also suggests an efficient design and operation philosophy, construction methodology, and logical insurance plans. The risk-based model uses the analytic hierarchy process (AHP), a multiple-attribute decision-making technique, to identify the factors that influence failure on specific segments and to analyze their effects by determining probability of risk factors. The severity of failure is determined through consequence analysis. From this, the effect of a failure caused by each risk factor can be established in terms of cost, and the cumulative effect of failure is determined through probability analysis. The technique does not totally eliminate subjectivity, but it is an improvement over the existing inspection method.