Measurements of Gd 152 (p,γ) Tb 153 and Gd 152 (p,n) Tb 152 reaction cross sections for the astrophysical γ process

The total cross sections for the Gd152(p,γ)Tb153 and Gd152(p,n)152Tb reactions have been measured by the activation method at effective center-of-mass energies 3.47≤Ec.m.eff≤7.94 MeV and 4.96≤Ec.m.eff≤7.94 MeV, respectively. The targets were prepared by evaporation of 30.6% isotopically enriched Gd152 oxide on aluminum backing foils, and bombarded with proton beams provided by a cyclotron accelerator. The cross sections were deduced from the observed γ-ray activity, which was detected off-line by an HPGe detector in a low background environment. The results are presented and compared with predictions of statistical model calculations. This comparison supports a modified optical proton+Gd152 potential suggested earlier.Peer reviewedFinal Accepted Versio

The Existence and Persistence of a Winner’s Curse: New Evidence from the (Baseball) Field

This study takes advantage of recent developments in the measurement and valuation of individual output in the baseball labor market to (i) reassess prior evidence that this market is afflicted by the winner’s curse phenomenon and (ii) test whether bidders learn to avoid this curse over time. Though we find no evidence of negative average returns on player contracts for the earliest cohort of baseball free agents, we conclude that teams in that era failed to efficiently discount their bids in accord with available information, especially about risk. What is more, evidence from a larger sample of players signed in the late 1990s shows that teams have continued to overvalue inconsistent free agents and failed to limit their bids to conform to players’ lower values in small markets. This is consistent with experimental evidence that finds bounded-rational behavior when bidders are faced with complex valuation problems involving multiple elements.market efficiency, bounded rationality, overbidding

The impact of education expenditures on growth in the EU28 – a spatial econometric perspective

This paper analyses spatial impact of government expenditures on education on economic growth in the EU28 countries during the period 2004–2013. Employing a novel econometric technique that allows for the estimation of spatial spillovers, our results indicate that government expenditures on education significantly and positively infl uence GDP growth. Moreover, the indirect i.e. the spillover effects are quite large suggesting that the growth models should account for spatial interdependencies. Precisely, we find that education expenditures in one country affect GDP growth in the neighbouring countries, meaning that these spillovers are geographical in nature. Moreover, we find that the degree of interdependence among countries varies according to the average GDP per capita even if their geographical distances are identical. Additionally, immigration is found to be an important channel of spatial transmission

Variation in DNA Substitution Rates among Lineages Erroneously Inferred from Simulated Clock-Like Data

BACKGROUND: The observation of variation in substitution rates among lineages has led to (1) a general rejection of the molecular clock model, and (2) the suggestion that a number of biological characteristics of organisms can cause rate variation. Accurate estimates of rate variation, and thus accurate inferences regarding the causes of rate variation, depend on accurate estimates of substitution rates. However, theory suggests that even when the substitution process is clock-like, variable numbers of substitutions can occur among lineages because the substitution process is stochastic. Furthermore, substitution rates along lineages can be misestimated, particularly when multiple substitutions occur at some sites. Although these potential causes of error in rate estimation are well understood in theory, such error has not been examined in detail; consequently, empirical studies that estimate rate variation among lineages have been unable to determine whether their results could be impacted by estimation error. METHODOLOGY/PRINCIPAL FINDINGS: To evaluate the extent to which error in rate estimation could erroneously suggest rate variation among lineages, we examined rate variation estimated for datasets simulated under a molecular clock on trees with equal and variable branch lengths. Thus, any apparent rate variation in these datasets reflects error in rate estimation rather than true differences in the underlying substitution process. We observed substantial rate variation among lineages in our simulations; however, we did not observe rate variation when average substitution rates were compared between different clades. CONCLUSIONS/SIGNIFICANCE: Our results confirm previous theoretical work suggesting that observations of among lineage rate variation in empirical data may be due to the stochastic substitution process and error in the estimation of substitution rates, rather than true differences in the underlying substitution process among lineages. However, conclusions regarding rate variation drawn from rates averaged across multiple branches are likely due to real, systematic variation in rates between groups

Impact of the Infection Period Distribution on the Epidemic Spread in a Metapopulation Model

Epidemic models usually rely on the assumption of exponentially distributed sojourn times in infectious states. This is sometimes an acceptable approximation, but it is generally not realistic and it may influence the epidemic dynamics as it has already been shown in one population. Here, we explore the consequences of choosing constant or gamma-distributed infectious periods in a metapopulation context. For two coupled populations, we show that the probability of generating no secondary infections is the largest for most parameter values if the infectious period follows an exponential distribution, and we identify special cases where, inversely, the infection is more prone to extinction in early phases for constant infection durations. The impact of the infection duration distribution on the epidemic dynamics of many connected populations is studied by simulation and sensitivity analysis, taking into account the potential interactions with other factors. The analysis based on the average nonextinct epidemic trajectories shows that their sensitivity to the assumption on the infectious period distribution mostly depends on , the mean infection duration and the network structure. This study shows that the effect of assuming exponential distribution for infection periods instead of more realistic distributions varies with respect to the output of interest and to other factors. Ultimately it highlights the risk of misleading recommendations based on modelling results when models including exponential infection durations are used for practical purposes

The effect of the magnitude and direction of institutional distance on the choice of international entry modes

This paper analyzes the relation between institutional regulative distance and the choice of international entry mode. The study contributes to existing literature by considering the relative positions of the origin and destination countries on this relation, examining the possibility that institutional distance may exert an asymmetric effect. The results, using a database of European firms and multilevel analysis techniques, indicate that entry in countries with lower levels of regulatory development than that of the origin is related to modes that require a lower resource commitment. Conversely, entry in countries with higher levels of regulatory development is related to higher resource commitment modes. These findings suggest that the direction of institutional distance is important for the choice of international entry mode.An earlier version of this paper was awarded with the SMG Copenhagen Prize 2011 for the best paper submitted to the EIBA-conference by a young scholar. This study has been partially supported by financial aid from the Spanish Ministries of Economy and Competitiveness, with the Project ECO2012-36160, and Education, with the FPU program scholarship AP2010-1092.Publicad

Increasing returns to scale and regions: a multilevel model for Brazil

This is the final version of the article. It was first available from Associação Keynesiana Brasileira via http://www.akb.org.br/revista/index.php/BKR/article/view/36The paper proposes and tests an alternative way to incorporate a spatial dimension to the Verdoorn Law using multilevel models, tailored to deal with nested data. This methodology allows extending the Verdoorn equation, incorporating elements from Urban Economics to Post-Keynesian growth analysis. The estimations used firm-level data from the Brazilian manufacturing industry from 1996 to 2002. The results showed that, after controlling for firms’ characteristics, the spatial dimension is crucial to explain rates of labour productivity and output growth. Moreover, the estimations showed that substantial knowledge spillovers and urbanisation externalities are beneficial to firms’ growth, whereas localisation externalities tend to be harmful.Research for this paper was partially funded by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) and Fundação de Amparo à Pesquisa do Estado de Minas Gerais (Fapemig). The authors are grateful for technical support provided by Instituto de Pesquisa Econômica Aplicada (IPEA) and by Instituto Brasileiro de Geografia e Estatística (IBGE). The authors would also like to thank Pedro Vasconcelos Maia do Amaral for invaluable comments and suggestions

Modeling single family housing recovery after Hurricane Andrew in Miami-Dade County, FL

This research seeks to improve the current state of knowledge about housing recovery following a major natural disaster through examining single family housing recovery following Hurricane Andrew, a category 5 hurricane, which impacted southern sections of Miami-Dade County in 1992. This inquiry focused on two questions: (1) what is the recovery process for single family housing in a disaster impact area, and (2) how does the housing recovery process vary across households and neighborhoods? To answer these questions, the 1992-96 tax appraisal values for Miami-Dade County were used to measure housing damage and recovery after the storm. Hierarchical Linear Modeling (HLM) was used to quantitatively model this recovery process and identify the major factors in play. With regard to the first question, our findings suggested that Hurricane Andrew caused extensive housing damage in the impact area, rendering an average loss to households of 50.4% of pre-disaster home value. Two years after the storm (1994), the average home value returned to its pre-disaster level. In the subsequent two years (1995-96), the average home value continued growing, representing a 7.6% and 14.9% gain, respectively, over the pre-disaster average. Regarding the second question, our analysis found that the housing recovery process varied significantly across households and neighborhoods. Owner-occupied homes recovered more rapidly than rental units. Household income had a positive effect on housing recovery. Our analysis also suggested that post-disaster home sales had a significant negative effect on housing recovery. Neighborhood race/ethnicity composition affected the housing recovery process. Homes in minority populated neighborhoods (both Hispanic and non-Hispanic Black) recovered more slowly than homes in majority populated areas (non-Hispanic White). When considering Cuban- Hispanics and non-Cuban Hispanics as two separate groups, neighborhoods with a higher concentration of Cuban-Hispanics, while having no clear advantage at the beginning of the recovery period, recovered more rapidly than other minority populated areas. Previous studies suggested that the long-term impact of natural disasters at the aggregated level is minimal, and yet our results showed that the housing impact of Hurricane Andrew lasted at least more than four years. In fact, housing inequality in the impact area increased markedly during the recovery process due to the unequal nature of housing recovery