Why Development Levels Differ: The Sources of Differential Economic Growth in a Panel of High and Low Income Countries

Average income per capita in the countries of the OECD was more than 20 times larger in 2000 than that of the poorest countries of sub-Sahara Africa and elsewhere, and many of the latter are not only falling behind the world leaders, but have even regressed in recent years. At the same time, other low-income countries have shown the capacity to make dramatic improvements in income per capita. Two general explanations have been offered to account for the observed patterns of growth. One view stresses differences in the efficiency of production are the main source of the observed gap in output per worker. A competing explanation reverses this conclusion and gives primary importance to capital formation. We examine the relative importance of these two factors as an explanation of the gap using 112 countries over the period 1970-2000. We find that differences in the efficiency of production, as measured by relative levels of total factor productivity, are the dominant factor accounting for the difference in development levels. We also find that the gap between rich and most poor nations is likely to persist under prevailing rates of saving and productivity change. To check the robustness of these conclusions, we employ different models of the growth process and different assumptions about the underlying data. Although different models of growth produce different relative contributions of capital formation and TFP, we conclude that the latter is the dominant source of gap. This conclusion must, however, be qualified by the poor quality of data for many developing countries.

The GAINS Model for Greenhouse Gases: Emissions, Control Potentials and Control Costs for Methane

This report estimates current and future emissions of methane in 42 regions in Europe, assesses the potential for reducing emissions and quantifies the costs of the available emission control measures. The report identifies 28 control measures, ranging from animal feed changes over waste management options to various approaches for gas recovery and utilization. For each of these options, the report examines country-specific applicability and removal efficiency and determines the costs. As a result, methane emissions in Europe are estimated for the year 1990 at 64,200 kt CH4. Assuming the penetration of emission controls as laid down in the current legislation, emissions would decline up to 2020 by 11,700 kt CH4 per year. Full application of the presently available emission control measures could achieve an additional decline in European methane emissions by 24,000 kt per year. 75 percent of this potential could be attained at a cost of less than two billion Euros/year or 50 Euros/t CO2-equivalent, while the further 5,000 kt CH4/year would require costs of 12 billion Euros/year

The GAINS Model for Greenhouse Gases - Version 1.0: Methane (CH4)

Many of the traditional air pollutants and greenhouse gases have common sources, offering a cost-effective potential for simultaneous improvements of traditional air pollution problems and climate change. A methodology has been developed to extend the RAINS integrated assessment model to explore synergies and trade-offs between the control of greenhouse gases and air pollution. With this extension, the GAINS (GHG-Air pollution INteraction and Synergies) model will allow the assessment of emission control costs for the six greenhouse gases covered under the Kyoto Protocol (CO2, CH4, N2O and the three F-gases) together with the emissions of air pollutants SO2, NOx, VOC, NH3 and PM. This report describes the first implementation (Version 1.0) of the model extension model to incorporate CH4 emissions. GAINS Version 1.0 assesses the options for reducing N2O emissions from the various source categories. It quantifies for 43 countries/regions in Europe country-specific application potentials of the various options in the different sectors of the economy, and estimates the societal resource costs of these measures. Mitigation potentials are estimated in relation to an exogenous baseline projection that is considered to reflect current planning. The report identifies 28 control measures, ranging from animal feed changes over waste management options to various approaches for gas recovery and utilization. For each of these options, the report examines country-specific applicability and removal efficiency and determines the costs. As a result, CH4 emissions in Europe are estimated for the year 1990 at 63,600 kt CH4. Assuming the penetration of emission controls as laid down in the current legislation, emissions would decline up to 2020 by 12,600 kt CH4 per year. Full application of the presently available emission control measures could achieve an additional decline in European CH4 emissions by 24,000 kt per year. Seventy percent of this potential could be attained at a cost of less than two billion Euro/year or Euro/ton CO2- equivalent, while the further 7,000 kt CH4/year would require costs of 12 billion Euro/year

Biomechanical properties of bone in a mouse model of Rett syndrome

Rett syndrome (RTT) is an X-linked genetic disorder and a major cause of intellectual disability in girls. Mutations in the methyl-CpG binding protein 2 (<i>MECP2</i>) gene are the primary cause of the disorder. Despite the dominant neurological phenotypes, <i>MECP2</i> is expressed ubiquitously throughout the body and a number of peripheral phenotypes such as scoliosis, reduced bone mineral density and skeletal fractures are also common and important clinical features of the disorder. In order to explore whether MeCP2 protein deficiency results in altered structural and functional properties of bone and to test the potential reversibility of any defects, we have conducted a series of histological, imaging and biomechanical tests of bone in a functional knockout mouse model of RTT. Both hemizygous <i>Mecp2</i><sup>stop/y</sup> male mice in which <i>Mecp2</i> is silenced in all cells and female <i>Mecp2</i><sup>stop/+</sup> mice in which <i>Mecp2</i> is silenced in ~ 50% of cells as a consequence of random X-chromosome inactivation, revealed significant reductions in cortical bone stiffness, microhardness and tensile modulus. Microstructural analysis also revealed alterations in both cortical and cancellous femoral bone between wild-type and MeCP2-deficient mice. Furthermore, unsilencing of <i>Mecp2</i> in adult mice cre-mediated stop cassette deletion resulted in a restoration of biomechanical properties (stiffness, microhardness) towards wild-type levels. These results show that MeCP2-deficiency results in overt, but potentially reversible, alterations in the biomechanical integrity of bone and highlights the importance of targeting skeletal phenotypes in considering the development of pharmacological and gene-based therapies

Bayesian detection of periodic mRNA time profiles without use of training examples

BACKGROUND: Detection of periodically expressed genes from microarray data without use of known periodic and non-periodic training examples is an important problem, e.g. for identifying genes regulated by the cell-cycle in poorly characterised organisms. Commonly the investigator is only interested in genes expressed at a particular frequency that characterizes the process under study but this frequency is seldom exactly known. Previously proposed detector designs require access to labelled training examples and do not allow systematic incorporation of diffuse prior knowledge available about the period time. RESULTS: A learning-free Bayesian detector that does not rely on labelled training examples and allows incorporation of prior knowledge about the period time is introduced. It is shown to outperform two recently proposed alternative learning-free detectors on simulated data generated with models that are different from the one used for detector design. Results from applying the detector to mRNA expression time profiles from S. cerevisiae showsthat the genes detected as periodically expressed only contain a small fraction of the cell-cycle genes inferred from mutant phenotype. For example, when the probability of false alarm was equal to 7%, only 12% of the cell-cycle genes were detected. The genes detected as periodically expressed were found to have a statistically significant overrepresentation of known cell-cycle regulated sequence motifs. One known sequence motif and 18 putative motifs, previously not associated with periodic expression, were also over represented. CONCLUSION: In comparison with recently proposed alternative learning-free detectors for periodic gene expression, Bayesian inference allows systematic incorporation of diffuse a priori knowledge about, e.g. the period time. This results in relative performance improvements due to increased robustness against errors in the underlying assumptions. Results from applying the detector to mRNA expression time profiles from S. cerevisiae include several new findings that deserve further experimental studies