A Re-examination of the Relation between Democracy and International Trade The Case of Africa

Scholars and policy makers believe that democracy will bring prosperity through integration into the global economy via increased international trade. This study tests two theories as to why democracies might trade more. First, political freedom may be correlated with economic freedom, thus prompting higher levels of economic activity, thereby driving states to trade more. Second, democracy implies higher quality governance either through institutions or policy-making procedures. I utilize a bilateral gravity trade model covering approximately 150 countries from 1950 to 1999, with fixed effects for time, importers and exporters. I find the theory that democracy, and many of its components, promotes international trade unconvincing. Economic freedom does not have the expected impact on international trade levels, but quality of governance variables have broad economic and statistical significance.trade, democracy, governance, Africa, gravity model

A re-examination of the relation between democracy and international trade: The case of Africa

Scholars and policy makers believe that democracy will bring prosperity through integration into the global economy via increased international trade. This study tests two theories as to why democracies might trade more. First, political freedom may be correlated with economic freedom, thus prompting higher levels of economic activity, thereby driving states to trade more. Second, democracy implies higher quality governance either through institutions or policy-making procedures. I utilize a bilateral gravity trade model covering approximately 150 countries from 1950 to 1999, with fixed effects for time, importers and exporters. I find the theory that democracy, and many of its components, promotes international trade unconvincing. Economic freedom does not have the expected impact on international trade levels, but quality of governance variables have broad economic and statistical significance

Sovereign Risk, Elections, and Contagion

This paper aims to quantify the political risk effect and its different economic implications in normal and crisis situations through the proxy analysis of election and the sovereign bond spreads. Our study leads to three main findings. First, in normal economic situations, elections and government turnovers expand bond spreads, demonstrating investors' concern over the possibility of government policies or instability brought by the election. During a crisis, however, investors prefer change, indicating hope in new policies ameliorate public finances. Second, due to the prolonged eurozone sovereign debt crisis, elections in European countries have stronger contagion effects in their own region during a global slowdown period than a normal period. However, their effect does not carry over globally after the 2008 financial crisis. Third, results show that the election induced peak shrinks from 3 months before and after the election date to 1–2 months when the economic situation turns from normal to a downgraded period

A re-examination of the relation between democracy and international trade

Scholars and policy makers believe that democracy will bring prosperity through integration into the global economy via increased international trade. Existing research is plagued by methodological problems that obscure the empirics and avoid the theoretical problem of why democracies may or may not trade more. In this paper, I seek to correct these shortcomings. I test two theories as to why democracies might trade more. First, political freedom may be correlated with economic freedom, thus prompting higher levels of economic activity, thereby driving states to trade more. Second, democracy implies higher quality governance either through institutions or policy making procedures. To test the impact of democracy on trade and the potential transmission mechanisms, I utilize a bilateral gravity trade model covering approximately 150 countries from 1950 to 1999, with fixed effects for time, importers, and exporters. I find the theory that democracy, and many of its components, promotes international trade unconvincing. The coefficients are the theoretically correct sign; however, many are statistically or economically insignificant and fragile to changes in modeling or data. Economic freedom does not have the expected impact on international trade levels, but quality of governance variables have broad economic and statistical significance

Verifying likelihoods for low template DNA profiles using multiple replicates

AbstractTo date there is no generally accepted method to test the validity of algorithms used to compute likelihood ratios (LR) evaluating forensic DNA profiles from low-template and/or degraded samples. An upper bound on the LR is provided by the inverse of the match probability, which is the usual measure of weight of evidence for standard DNA profiles not subject to the stochastic effects that are the hallmark of low-template profiles. However, even for low-template profiles the LR in favour of a true prosecution hypothesis should approach this bound as the number of profiling replicates increases, provided that the queried contributor is the major contributor. Moreover, for sufficiently many replicates the standard LR for mixtures is often surpassed by the low-template LR. It follows that multiple LTDNA replicates can provide stronger evidence for a contributor to a mixture than a standard analysis of a good-quality profile. Here, we examine the performance of the likeLTD software for up to eight replicate profiling runs. We consider simulated and laboratory-generated replicates as well as resampling replicates from a real crime case. We show that LRs generated by likeLTD usually do exceed the mixture LR given sufficient replicates, are bounded above by the inverse match probability and do approach this bound closely when this is expected. We also show good performance of likeLTD even when a large majority of alleles are designated as uncertain, and suggest that there can be advantages to using different profiling sensitivities for different replicates. Overall, our results support both the validity of the underlying mathematical model and its correct implementation in the likeLTD software

Theoretical Formulation of Principal Components Analysis to Detect and Correct for Population Stratification

The Eigenstrat method, based on principal components analysis (PCA), is commonly used both to quantify population relationships in population genetics and to correct for population stratification in genome-wide association studies. However, it can be difficult to make appropriate inference about population relationships from the principal component (PC) scatter plot. Here, to better understand the working mechanism of the Eigenstrat method, we consider its theoretical or “population” formulation. The eigen-equation for samples from an arbitrary number () of populations is reduced to that of a matrix of dimension , the elements of which are determined by the variance-covariance matrix for the random vector of the allele frequencies. Solving the reduced eigen-equation is numerically trivial and yields eigenvectors that are the axes of variation required for differentiating the populations. Using the reduced eigen-equation, we investigate the within-population fluctuations around the axes of variation on the PC scatter plot for simulated datasets. Specifically, we show that there exists an asymptotically stable pattern of the PC plot for large sample size. Our results provide theoretical guidance for interpreting the pattern of PC plot in terms of population relationships. For applications in genetic association tests, we demonstrate that, as a method of correcting for population stratification, regressing out the theoretical PCs corresponding to the axes of variation is equivalent to simply removing the population mean of allele counts and works as well as or better than the Eigenstrat method

The Potential for Enhancing the Power of Genetic Association Studies in African Americans through the Reuse of Existing Genotype Data

We consider the feasibility of reusing existing control data obtained in genetic association studies in order to reduce costs for new studies. We discuss controlling for the population differences between cases and controls that are implicit in studies utilizing external control data. We give theoretical calculations of the statistical power of a test due to Bourgain et al (Am J Human Genet 2003), applied to the problem of dealing with case-control differences in genetic ancestry related to population isolation or population admixture. Theoretical results show that there may exist bounds for the non-centrality parameter for a test of association that places limits on study power even if sample sizes can grow arbitrarily large. We apply this method to data from a multi-center, geographically-diverse, genome-wide association study of breast cancer in African-American women. Our analysis of these data shows that admixture proportions differ by center with the average fraction of European admixture ranging from approximately 20% for participants from study sites in the Eastern United States to 25% for participants from West Coast sites. However, these differences in average admixture fraction between sites are largely counterbalanced by considerable diversity in individual admixture proportion within each study site. Our results suggest that statistical correction for admixture differences is feasible for future studies of African-Americans, utilizing the existing controls from the African-American Breast Cancer study, even if case ascertainment for the future studies is not balanced over the same centers or regions that supplied the controls for the current study

On the Analysis of Genome-Wide Association Studies in Family-Based Designs: A Universal, Robust Analysis Approach and an Application to Four Genome-Wide Association Studies

For genome-wide association studies in family-based designs, we propose a new, universally applicable approach. The new test statistic exploits all available information about the association, while, by virtue of its design, it maintains the same robustness against population admixture as traditional family-based approaches that are based exclusively on the within-family information. The approach is suitable for the analysis of almost any trait type, e.g. binary, continuous, time-to-onset, multivariate, etc., and combinations of those. We use simulation studies to verify all theoretically derived properties of the approach, estimate its power, and compare it with other standard approaches. We illustrate the practical implications of the new analysis method by an application to a lung-function phenotype, forced expiratory volume in one second (FEV1) in 4 genome-wide association studies

Sequestration and Scavenging of Iron in Infection

The proliferative capability of many invasive pathogens is limited by the bioavailability of iron. Pathogens have thus developed strategies to obtain iron from their host organisms. In turn, host defense strategies have evolved to sequester iron from invasive pathogens. This review explores the mechanisms employed by bacterial pathogens to gain access to host iron sources, the role of iron in bacterial virulence, and iron-related genes required for the establishment or maintenance of infection. Host defenses to limit iron availability for bacterial growth during the acute-phase response and the consequences of iron overload conditions on susceptibility to bacterial infection are also examined. The evidence summarized herein demonstrates the importance of iron bioavailability in influencing the risk of infection and the ability of the host to clear the pathogen

Disentangling Signatures of Selection Before and After European Colonization in Latin Americans

Throughout human evolutionary history, large-scale migrations have led to intermixing (i.e., admixture) between previously separated human groups. Although classical and recent work have shown that studying admixture can yield novel historical insights, the extent to which this process contributed to adaptation remains underexplored. Here, we introduce a novel statistical model, specific to admixed populations, that identifies loci under selection while determining whether the selection likely occurred post-admixture or prior to admixture in one of the ancestral source populations. Through extensive simulations, we show that this method is able to detect selection, even in recently formed admixed populations, and to accurately differentiate between selection occurring in the ancestral or admixed population. We apply this method to genome-wide SNP data of ∼4,000 individuals in five admixed Latin American cohorts from Brazil, Chile, Colombia, Mexico, and Peru. Our approach replicates previous reports of selection in the human leukocyte antigen region that are consistent with selection post-admixture. We also report novel signals of selection in genomic regions spanning 47 genes, reinforcing many of these signals with an alternative, commonly used local-ancestry-inference approach. These signals include several genes involved in immunity, which may reflect responses to endemic pathogens of the Americas and to the challenge of infectious disease brought by European contact. In addition, some of the strongest signals inferred to be under selection in the Native American ancestral groups of modern Latin Americans overlap with genes implicated in energy metabolism phenotypes, plausibly reflecting adaptations to novel dietary sources available in the Americas