Intertemporal excess burden, bequest motives, and the budget deficit

The author aims to empirically determine the significant factors that affect the levels of budget deficits of central governments across time and across countries. He empirically tests two prominent theories of budget deficits-the Barro (1979) tax-smoothing approach, and the still-untested theory of negative bequest motives advocated by Cukierman and Meltzer (1989). The author uses econometric techniques including fixed-effects (both country and time) panel regressions spanning 87 countries over the period 1975 to 1992, and the Griliches treatment of missing data. The author finds relatively stronger statistical support for the tax-smoothing approach among developing countries but not in industrial countries. The existence of empirical evidence supporting the theory of negative bequest motives is indeterminate. The author also conducted post-regression analyses to assess the proportion of observed differences in budget deficits the factors were actually able to explain. These reveal that both theories are generally weak in accounting for inter-temporal changes in budget deficit shares for both industrial and developing countries. The theories performed significantly better in accounting for cross-section differences. The author has many contributions to the literature. First, he analyzes the question of what determines the size of central government budget deficits using cross-country time series data leading into the 1990s. Second, he provides empirical tests of the still-untested Cukierman-Meltzer (1989) negative bequest motive theory of budget deficits. By using the panel data, the author attempts to determine the factors that influence not only the inter-temporal differences in budget deficits but also those factors that lead to cross-country differences. Last but not least, he provides some preliminary evidence that poverty reduction is necessary for long-term government budget deficit reduction.Public Sector Economics&Finance,Environmental Economics&Policies,Economic Theory&Research,Banks&Banking Reform,Municipal Financial Management,Public Sector Economics&Finance,Economic Theory&Research,Economic Stabilization,Banks&Banking Reform,National Governance

Candidate SNPs for carcass and meat traits in Nelore animals and in their crosses with Bos taurus

The objective of this work was to evaluate the effects of single-nucleotide polymorphisms (SNPs) in the genes IGF1 (AF_017143.1: g. 198C>T), MSTN (AF_320998.1:g. 433C>A), MYOD1 (NC_007313:g. 1274A>G) and MYF5 (NC_007303:g.1911A>G) on carcass and meat traits in Nelore (Bos indicus) and Nelore x B. taurus. A total of 300 animals were genotyped and phenotyped for rib eye area (REA), backfat thickness (BT), intramuscular fat (IF), shear force (SF) and myofibrillar fragmentation index (MFI). The effects of allele substitution for each SNP were estimated by regression of the evaluated phenotypes on the number of copies of a particular allele using the general linear model. The polymorphism at IGF1 was non-informative in Nelore animals. In crossbred animals, the IGF1 C allele was associated with greater REA. However, this relation was not significant after Bonferroni correction for multiple testing. The A allele of the MSTN polymorphism was absent in Nelore cattle and was only found in two crossbred animals. The polymorphisms of MYOD1 and MYF5 were little informative in Nelore animals with G allele frequency of 0.097 and A allele frequency of 0.031, respectively. These markers show no association with the analyzed traits in the total sample of evaluated animals

The ASOS Surgical Risk Calculator: development and validation of a tool for identifying African surgical patients at risk of severe postoperative complications

Background: The African Surgical Outcomes Study (ASOS) showed that surgical patients in Africa have a mortality twice the global average. Existing risk assessment tools are not valid for use in this population because the pattern of risk for poor outcomes differs from high-income countries. The objective of this study was to derive and validate a simple, preoperative risk stratification tool to identify African surgical patients at risk for in-hospital postoperative mortality and severe complications. Methods: ASOS was a 7-day prospective cohort study of adult patients undergoing surgery in Africa. The ASOS Surgical Risk Calculator was constructed with a multivariable logistic regression model for the outcome of in-hospital mortality and severe postoperative complications. The following preoperative risk factors were entered into the model; age, sex, smoking status, ASA physical status, preoperative chronic comorbid conditions, indication for surgery, urgency, severity, and type of surgery. Results: The model was derived from 8799 patients from 168 African hospitals. The composite outcome of severe postoperative complications and death occurred in 423/8799 (4.8%) patients. The ASOS Surgical Risk Calculator includes the following risk factors: age, ASA physical status, indication for surgery, urgency, severity, and type of surgery. The model showed good discrimination with an area under the receiver operating characteristic curve of 0.805 and good calibration with c-statistic corrected for optimism of 0.784. Conclusions: This simple preoperative risk calculator could be used to identify high-risk surgical patients in African hospitals and facilitate increased postoperative surveillance. © 2018 British Journal of Anaesthesia. Published by Elsevier Ltd. All rights reserved.Medical Research Council of South Africa gran