Three essays in international finance

Executive Summary The first essay of this dissertation investigates whether greater exchange rate uncertainty (i.e., variation over time in the exchange rate) fosters or depresses the foreign investment of multinational firms. In addition to the direct capital financing it supplies, foreign investment can be a source of valuable technology and know-how, which can have substantial positive effects on a host country's economic growth. Thus, it is critically important for policy makers and central bankers, among others, to understand how multinationals base their investment decisions on the characteristics of foreign exchange markets. In this essay, I first develop a theoretical framework to improve our knowledge regarding how the aggregate level of foreign investment responds to exchange rate uncertainty when an economy consists of many firms, each of which is making decisions. The analysis predicts a U-shaped effect of exchange rate uncertainty on the total level of foreign investment of the economy. That is, the effect is negative for low levels of uncertainty and positive for higher levels of uncertainty. This pattern emerges because the relationship between exchange rate volatility and 'the probability of investment is negative for firms with low productivity at home (i.e., firms that find it profitable to invest abroad) and the relationship is positive for firms with high productivity at home (i.e., firms that prefer exporting their product). This finding stands in sharp contrast to predictions in the existing literature that consider a single firm's decision to invest in a unique project. The main contribution of this research is to show that the aggregation over many firms produces a U-shaped pattern between exchange rate uncertainty and the probability of investment. Using data from industrialized countries for the period of 1982-2002, this essay offers a comprehensive empirical analysis that provides evidence in support of the theoretical prediction. In the second essay, I aim to explain the time variation in sovereign credit risk, which captures the risk that a government may be unable to repay its debt. The importance of correctly evaluating such a risk is illustrated by the central role of sovereign debt in previous international lending crises. In addition, sovereign debt is the largest asset class in emerging markets. In this essay, I provide a pricing formula for the evaluation of sovereign credit risk in which the decision to default on sovereign debt is made by the government. The pricing formula explains the variation across time in daily credit spreads - a widely used measure of credit risk - to a degree not offered by existing theoretical and empirical models. I use information on a country's stock market to compute the prevailing sovereign credit spread in that country. The pricing formula explains a substantial fraction of the time variation in daily credit spread changes for Brazil, Mexico, Peru, and Russia for the 1998-2008 period, particularly during the recent subprime crisis. I also show that when a government incentive to default is allowed to depend on current economic conditions, one can best explain the level of credit spreads, especially during the recent period of financial distress. In the third essay, I show that the risk of sovereign default abroad can produce adverse consequences for the U.S. equity market through a decrease in returns and an increase in volatility. The risk of sovereign default, which is no longer limited to emerging economies, has recently become a major concern for financial markets. While sovereign debt plays an increasing role in today's financial environment, the effects of sovereign credit risk on the U.S. financial markets have been largely ignored in the literature. In this essay, I develop a theoretical framework that explores how the risk of sovereign default abroad helps explain the level and the volatility of U.S. equity returns. The intuition for this effect is that negative economic shocks deteriorate the fiscal situation of foreign governments, thereby increasing the risk of a sovereign default that would trigger a local contraction in economic growth. The increased risk of an economic slowdown abroad amplifies the direct effect of these shocks on the level and the volatility of equity returns in the U.S. through two channels. The first channel involves a decrease in the future earnings of U.S. exporters resulting from unfavorable adjustments to the exchange rate. The second channel involves investors' incentives to rebalance their portfolios toward safer assets, which depresses U.S. equity prices. An empirical estimation of the model with monthly data for the 1994-2008 period provides evidence that the risk of sovereign default abroad generates a strong leverage effect during economic downturns, which helps to substantially explain the level and the volatility of U.S. equity returns.

An empirical hierarchical Bayesian unification of occupational exposure assessment methods.

In occupational exposure assessment of airborne contaminants, exposure levels can either be estimated through repeated measurements of the pollutant concentration in air, expert judgment or through exposure models that use information on the conditions of exposure as input. In this report, we propose an empirical hierarchical Bayesian model to unify these approaches. Prior to any measurement, the hygienist conducts an assessment to generate prior distributions of exposure determinants. Monte-Carlo samples from these distributions feed two level-2 models: a physical, two-compartment model, and a non-parametric, neural network model trained with existing exposure data. The outputs of these two models are weighted according to the expert's assessment of their relevance to yield predictive distributions of the long-term geometric mean and geometric standard deviation of the worker's exposure profile (level-1 model). Bayesian inferences are then drawn iteratively from subsequent measurements of worker exposure. Any traditional decision strategy based on a comparison with occupational exposure limits (e.g. mean exposure, exceedance strategies) can then be applied. Data on 82 workers exposed to 18 contaminants in 14 companies were used to validate the model with cross-validation techniques. A user-friendly program running the model is available upon request.

The attractiveness of nations in global competition : an empirical assessment of the effects of country attractiveness on the success of strategy for hosting international sports events, 1990-2012

This dissertation aims to investigate empirical evidence on the importance and influence of attractiveness of nations in global competition. The notion of country attractiveness, which has been widely developed in the research areas of international business, tourism and migration, is a multi-dimensional construct to measure a country's characteristics with regard to its market or destination that attract international investors, tourists and migrants. This analytical concept provides an account of the mechanism as to how potential stakeholders evaluate more attractive countries based on certain criteria. Thus, in the field of international sport-event bidding, do international sport event owners also have specific country attractiveness for their sport event hosts? The dissertation attempts to address this research question by statistically assessing the effects of country attractiveness on the success of strategy for hosting international sports events. Based on theories of signaling and soft power, country attractiveness is defined and measured as the three dimensions of sustainable development: economic, social, and environmental attractiveness. This thesis proceeds to examine the concept of sport-event-hosting strategy and explore multi-level factors affecting the success in international sport-event bidding. By exploring past history of the Olympic Movement from theoretical perspectives, the thesis proposes and tests the hypotheses that economic, social and environmental attractiveness of a country may be correlated with its bid wins or the success of sport-event-hosting strategy. Quantitative analytical methods with various robustness checks are employed with using collected data on bidding results of major events in Olympic sports during the period from 1990 to 2012. The analysis results reveal that event owners of international Olympic sports are likely to prefer countries that have higher economic, social, and environmental attractiveness. The empirical assessment of this thesis suggests that high country attractiveness can be an essential element of prerequisites for a city/country to secure in order to bid with an increased chance of success.

Which European Public Sphere? Normative Standards and Empirical Insights from Multilingual Switzerland

Since the beginning of the 1990s, the EU has been increasingly criticised for its democratic deficit, which is intrinsically linked to the absence of a public sphere at the European level. Whereas scholars consider the emergence of such a public sphere as a necessary requirement for the democratisation of the EU, they disagree on the conceptualisation and normative requirements for a meaningful public sphere at the European level. This article takes an empirical perspective and draws on the nation-state context of multilingual Switzerland to get insights into what a European public sphere might realistically look like. Based on a content analysis of the leading quality paper from each German- and French-speaking Switzerland by means of political claims analysis, it shows that three of the most often cited criteria for a European public sphere - horizontal openness and interconnectedness, shared meaning structures, and inclusiveness - are hardly met in the Swiss context. On this basis, it concludes that the normative barrier for finding a European public sphere might be unrealistically high and should be reconsidered.

Use of high-resolution geophysical data to characterize heterogeneous aquifers: influence of data integration method on hydrological predictions

The integration of geophysical data into the subsurface characterization problem has been shown in many cases to significantly improve hydrological knowledge by providing information at spatial scales and locations that is unattainable using conventional hydrological measurement techniques. The investigation of exactly how much benefit can be brought by geophysical data in terms of its effect on hydrological predictions, however, has received considerably less attention in the literature. Here, we examine the potential hydrological benefits brought by a recently introduced simulated annealing (SA) conditional stochastic simulation method designed for the assimilation of diverse hydrogeophysical data sets. We consider the specific case of integrating crosshole ground-penetrating radar (GPR) and borehole porosity log data to characterize the porosity distribution in saturated heterogeneous aquifers. In many cases, porosity is linked to hydraulic conductivity and thus to flow and transport behavior. To perform our evaluation, we first generate a number of synthetic porosity fields exhibiting varying degrees of spatial continuity and structural complexity. Next, we simulate the collection of crosshole GPR data between several boreholes in these fields, and the collection of porosity log data at the borehole locations. The inverted GPR data, together with the porosity logs, are then used to reconstruct the porosity field using the SA-based method, along with a number of other more elementary approaches. Assuming that the grid-cell-scale relationship between porosity and hydraulic conductivity is unique and known, the porosity realizations are then used in groundwater flow and contaminant transport simulations to assess the benefits and limitations of the different approaches.

Patterns of Subject Mix in Higher Education Institutions : A First Empirical Analysis Using the AQUAMETH Database

Teaching and research are organised differently between subject domains: attempts to construct typologies of higher education institutions, however, often do not include quantitative indicators concerning subject mix which would allow systematic comparisons of large numbers of higher education institutions among different countries, as the availability of data for such indicators is limited. In this paper, we present an exploratory approach for the construction of such indicators. The database constructed in the AQUAMETH project, which includes also data disaggregated at the disciplinary level, is explored with the aim of understanding patterns of subject mix. For six European countries, an exploratory and descriptive analysis of staff composition divided in four large domains (medical sciences, engineering and technology, natural sciences and social sciences and humanities) is performed, which leads to a classification distinguishing between specialist and generalist institutions. Among the latter, a further distinction is made based on the presence or absence of a medical department. Preliminary exploration of this classification and its comparison with other indicators show the influence of long term dynamics on the subject mix of individual higher education institutions, but also underline disciplinary differences, for example regarding student to staff ratios, as well as national patterns, for example regarding the number of PhD degrees per 100 undergraduate students. Despite its many limitations, this exploratory approach allows defining a classification of higher education institutions that accounts for a large share of differences between the analysed higher education institutions.

European guidelines for empirical antibacterial therapy for febrile neutropenic patients in the era of growing resistance: summary of the 2011 4th European Conference on Infections in Leukemia.

Owing to increasing resistance and the limited arsenal of new antibiotics, especially against Gram-negative pathogens, carefully designed antibiotic regimens are obligatory for febrile neutropenic patients, along with effective infection control. The Expert Group of the 4(th) European Conference on Infections in Leukemia has developed guidelines for initial empirical therapy in febrile neutropenic patients, based on: i) the local resistance epidemiology; and ii) the patient's risk factors for resistant bacteria and for a complicated clinical course. An 'escalation' approach, avoiding empirical carbapenems and combinations, should be employed in patients without particular risk factors. A 'de-escalation' approach, with initial broad-spectrum antibiotics or combinations, should be used only in those patients with: i) known prior colonization or infection with resistant pathogens; or ii) complicated presentation; or iii) in centers where resistant pathogens are prevalent at the onset of febrile neutropenia. In the latter case, infection control and antibiotic stewardship also need urgent review. Modification of the initial regimen at 72-96 h should be based on the patient's clinical course and the microbiological results. Discontinuation of antibiotics after 72 h or later should be considered in neutropenic patients with fever of unknown origin who are hemodynamically stable since presentation and afebrile for at least 48 h, irrespective of neutrophil count and expected duration of neutropenia. This strategy aims to minimize the collateral damage associated with antibiotic overuse, and the further selection of resistance.

Conceptualising 'precarious prosperity' - Empirical and Theoretical Elements for Debate

Empirical studies have recently pointed towards a socio-structural category largely overlooked in social inequality research: the dynamic positions of households adjacent to those of the poor and yet not representing those of the established, more prosperous positions in society. These results suggest that the population in this category fluctuates into and out of poverty more often than moving into and out of secure prosperity. This category - still lacking theoretical conceptualization - is characterized by both precariousness and a certain degree of prosperity; despite a restricted and uncertain living standard it holds a range of opportunities for action. We seek analytical elements to conceptualize 'precarious prosperity' for comparative empirical research by subjecting various concepts of social inequality research to critical scrutiny. We then operationally define 'precarious prosperity' to screen for this population in three countries. Based on qualitative interviews with households in precarious prosperity, we present first analyses of perceptions and household strategies that underline the relevance of the concept in different countries.

European cancer mortality predictions for the year 2013.

Background Estimated cancer mortality statistics were published for the years 2011 and 2012 for the European Union (EU) and its six more populous countries. Patients and methods Using logarithmic Poisson count data joinpoint models and the World Health Organization mortality and population database, we estimated numbers of deaths and age-standardized (world) mortality rates (ASRs) in 2013 from all cancers and selected cancers. Results The 2013 predicted number of cancer deaths in the EU is 1 314 296 (737 747 men and 576 489 women). Between 2009 and 2013, all cancer ASRs are predicted to fall by 6% to 140.1/100 000 in men, and by 4% to 85.3/100 000 in women. The ASRs per 100 000 are 6.6 men and 2.9 women for stomach, 16.7 men and 9.5 women for intestines, 8.0 men and 5.5 women for pancreas, 37.1 men and 13.9 women for lung, 10.5 men for prostate, 14.6 women for breast, and 4.7 for uterine cancer, and 4.2 and 2.6 for leukaemia. Recent trends are favourable except for pancreatic cancer and lung cancer in women. Conclusions Favourable trends will continue in 2013. Pancreatic cancer has become the fourth cause of cancer death in both sexes, while in a few years lung cancer will likely become the first cause of cancer mortality in women as well, overtaking breast cancer.

European cancer mortality predictions for the year 2014.

BACKGROUND: From most recent available data, we projected cancer mortality statistics for 2014, for the European Union (EU) and its six more populous countries. Specific attention was given to pancreatic cancer, the only major neoplasm showing unfavorable trends in both sexes. PATIENTS AND METHODS: Population and death certification data from stomach, colorectum, pancreas, lung, breast, uterus, prostate, leukemias and total cancers were obtained from the World Health Organisation database and Eurostat. Figures were derived for the EU, France, Germany, Italy, Poland, Spain and the UK. Projected 2014 numbers of deaths by age group were obtained by linear regression on estimated numbers of deaths over the most recent time period identified by a joinpoint regression model. RESULTS: In the EU in 2014, 1,323,600 deaths from cancer are predicted (742,500 men and 581,100 women), corresponding to standardized death rates of 138.1/100,000 men and 84.7/100,000 women, falling by 7% and 5%, respectively, since 2009. In men, predicted rates for the three major cancers (lung, colorectum and prostate cancer) are lower than in 2009, falling by 8%, 4% and 10%, respectively. In women, breast and colorectal cancers had favorable trends (-9% and -7%), but female lung cancer rates are predicted to rise 8%. Pancreatic cancer is the only neoplasm with a negative outlook in both sexes. Only in the young (25-49 years), EU trends become more favorable in men, while women keep registering slight predicted rises. CONCLUSIONS: Cancer mortality predictions for 2014 confirm the overall favorable cancer mortality trend in the EU, translating to an overall 26% fall in men since its peak in 1988, and 20% in women, and the avoidance of over 250,000 deaths in 2014 compared with the peak rate. Notable exceptions are female lung cancer and pancreatic cancer in both sexes.

Do pseudo-absence selection strategies influence species distribution models and their predictions? An information-theoretic approach based on simulated data

Background Multiple logistic regression is precluded from many practical applications in ecology that aim to predict the geographic distributions of species because it requires absence data, which are rarely available or are unreliable. In order to use multiple logistic regression, many studies have simulated "pseudo-absences" through a number of strategies, but it is unknown how the choice of strategy influences models and their geographic predictions of species. In this paper we evaluate the effect of several prevailing pseudo-absence strategies on the predictions of the geographic distribution of a virtual species whose "true" distribution and relationship to three environmental predictors was predefined. We evaluated the effect of using a) real absences b) pseudo-absences selected randomly from the background and c) two-step approaches: pseudo-absences selected from low suitability areas predicted by either Ecological Niche Factor Analysis: (ENFA) or BIOCLIM. We compared how the choice of pseudo-absence strategy affected model fit, predictive power, and information-theoretic model selection results. Results Models built with true absences had the best predictive power, best discriminatory power, and the "true" model (the one that contained the correct predictors) was supported by the data according to AIC, as expected. Models based on random pseudo-absences had among the lowest fit, but yielded the second highest AUC value (0.97), and the "true" model was also supported by the data. Models based on two-step approaches had intermediate fit, the lowest predictive power, and the "true" model was not supported by the data. Conclusion If ecologists wish to build parsimonious GLM models that will allow them to make robust predictions, a reasonable approach is to use a large number of randomly selected pseudo-absences, and perform model selection based on an information theoretic approach. However, the resulting models can be expected to have limited fit.

Land use improves spatial predictions of mountain plant abundance but not presence-absence

Question Does a land-use variable improve spatial predictions of plant species presence-absence and abundance models at the regional scale in a mountain landscape? Location Western Swiss Alps. Methods Presence-absence generalized linear models (GLM) and abundance ordinal logistic regression models (LRM) were fitted to data on 78 mountain plant species, with topo-climatic and/or land-use variables available at a 25-m resolution. The additional contribution of land use when added to topo-climatic models was evaluated by: (1) assessing the changes in model fit and (2) predictive power, (3) partitioning the deviance respectively explained by the topo-climatic variables and the land-use variable through variation partitioning, and (5) comparing spatial projections. Results Land use significantly improved the fit of presence-absence models but not their predictive power. In contrast, land use significantly improved both the fit and predictive power of abundance models. Variation partitioning also showed that the individual contribution of land use to the deviance explained by presence-absence models was, on average, weak for both GLM and LRM (3.7% and 4.5%, respectively), but changes in spatial projections could nevertheless be important for some species. Conclusions In this mountain area and at our regional scale, land use is important for predicting abundance, but not presence-absence. The importance of adding land-use information depends on the species considered. Even without a marked effect on model fit and predictive performance, adding land use can affect spatial projections of both presence-absence and abundance models.