On the measurement of comparative advantage

This article shows that the distribution of the standard measure of revealed comparative advantage (RCA), which runs from 0 to 8, has problematic properties. Due to its multiplicative specification, it has a moving mean without a useful interpretation, while its distribution depends on the number of countries and industries. This article proposes an alternative, additive RCA, running from –1 to +1, with a bell-shaped distribution that centres on a mean equal to zero, independent of the classifications used. Statistical tests show the additive index to be more stable empirically too. Furthermore, the article proposes an aggregate RCA that runs from 0, when pure intra-industry trade prevails, to 1 in the case of pure inter-industry trade. Comparable conclusions hold for the location quotient (LQ), which is used as a measure for the revealed locational attractiveness of certain regions or countries for certain types of industry.

An International Comparison of National Clusters

The presence of innovative clusters may positively influence domestic economic growth. If it is possible to identify these clusters, economic growth may be increased even further by developing policy that stimulates innovative clusters. Identifying clusters, however, is not an easy task. Input- output tables provide a possibility to identify clusters of sectors. These so-called meso clusters answer the question as to which sectors firms that work together stem from. Hence, meso-clusters provide a framework which indicates how a cluster may be composed. An earlier analysis identified Dutch meso clusters. This opens the possibility to compare these Dutch clusters with clusters in other countries, which helps to answer two questions. Firstly, it shows which clusters exist in which countries. These clusters highlight difference in the way sectors work together in different countries, which may explain different patterns of specialisation or even different economic growth rates. Secondly, differences between similar clusters in different countries are analysed. These differences may stem from, for example, different sectors in similar clusters or from different levels of innovation, productivity, profitability or different export positions of similar clusters. The present paper uses the cluster identification method to compare national clusters in ten countries: Australia, Canada, Denmark, France, Germany Italy, Japan, The Netherlands, The United Kingdom, and The United States. The most remarkable differences between clusters found in these countries and the most interesting differences between the sectors included in the same cluster in different countries are discussed. This provides insight in the differences of the inter-industry linkages in these countries.

A decomposition analysis of the emission of CO2

In 1997 many countries, including the Netherlands, signed the Kyoto treaty. According to this protocol, the emission of CO2 in the Netherlands in the years 2008-2012 should be on average 6% below the level of 1990. However, the emission still shows an increasing pattern. Part of the increase may be compensated by supporting projects abroad, hence the goals may still be reached if domestic emission does not increase too far. All in all, it is not sure whether the Netherlands will meet the goals of this protocol. Several factors contribute to changes in the emission of CO2. The figures of CO2 emission only show the net effect. In order to see whether technological changes decreases the emission of CO2 and whether the increase in CO2 is mainly due to economic growth, this paper uses a decomposition analysis to compute the effect of these factors. In order not to complicate the analysis too much, it was decided to focus on the emissions of CO2 and ignore the other greenhouse gasses. The emission of CO2 is the most important issue, because CO2 is the most important greenhouse gas and because the emission of the other greenhouse gasses is decreasing whereas the emission of CO2 is increasing. Policy is therefore likely to be most effective if it focuses on CO2. Further, the decomposition method can only be used to analyse the emission of producers. Emission by consumers is therefore ignored.

Opportunities for and challenges to further reductions in the “specific power” rating of wind turbines installed in the United States

A wind turbine’s “specific power” rating relates its capacity to the swept area of its rotor in terms of Watt per square meter. For a given generator capacity, specific power declines as rotor size increases. In land-rich but capacity-constrained wind power markets, such as the United States, developers have an economic incentive to maximize megawatt-hours per constrained megawatt, and so have favored turbines with ever-lower specific power. To date, this trend toward lower specific power has pushed capacity factors higher while reducing the levelized cost of energy. We employ geospatial levelized cost of energy analysis across the United States to explore whether this trend is likely to continue. We find that under reasonable cost scenarios (i.e. presuming that logistical challenges from very large blades are surmountable), low-specific-power turbines could continue to be in demand going forward. Beyond levelized cost of energy, the boost in market value that low-specific-power turbines provide could become increasingly important as wind penetration grows

Exploiting the full power of temporal gene expression profiling through a new statistical test: Application to the analysis of muscular dystrophy data

Background: The identification of biologically interesting genes in a temporal expression profiling dataset is challenging and complicated by high levels of experimental noise. Most statistical methods used in the literature do not fully exploit the temporal ordering in the dataset and are not suited to the case where temporal profiles are measured for a number of different biological conditions. We present a statistical test that makes explicit use of the temporal order in the data by fitting polynomial functions to the temporal profile of each gene and for each biological condition. A Hotelling T2-statistic is derived to detect the genes for which the parameters of these polynomials are significantly different from each other. Results: We validate the temporal Hotelling T2-test on muscular gene expression data from four mouse strains which were profiled at different ages: dystrophin-, beta-sarcoglycan and gammasarcoglycan deficient mice, and wild-type mice. The first three are animal models for different muscular dystrophies. Extensive biological validation shows that the method is capable of finding genes with temporal profiles significantly different across the four strains, as well as identifying potential biomarkers for each form of the disease. The added value of the temporal test compared to an identical test which does not make use of temporal ordering is demonstrated via a simulation study, and through confirmation of the expression profiles from selected genes by quantitative PCR experiments. The proposed method maximises the detection of the biologically interesting genes, whilst minimising false detections. Conclusion: The temporal Hotelling T2-test is capable of finding relatively small and robust sets of genes that display different temporal profiles between the conditions of interest. The test is simple, it can be used on gene expression data generated from any experimental design and for any number of conditions, and it allows fast interpretation of the temporal behaviour of genes. The R code is available from V.V. The microarray data have been submitted to GEO under series GSE1574 and GSE3523

Vaginal Microbicides: Detecting Toxicities in Vivo that Paradoxically Increase Pathogen Transmission

BACKGROUND: Microbicides must protect against STD pathogens without causing unacceptable toxic effects. Microbicides based on nonoxynol-9 (N9) and other detergents disrupt sperm, HSV and HIV membranes, and these agents are effective contraceptives. But paradoxically N9 fails to protect women against HIV and other STD pathogens, most likely because it causes toxic effects that increase susceptibility. The mouse HSV-2 vaginal transmission model reported here: (a) Directly tests for toxic effects that increase susceptibility to HSV-2, (b) Determines in vivo whether a microbicide can protect against HSV-2 transmission without causing toxicities that increase susceptibility, and (c) Identifies those toxic effects that best correlate with the increased HSV susceptibility. METHODS: Susceptibility was evaluated in progestin-treated mice by delivering a low-dose viral inoculum (0.1 ID50) at various times after delivering the candidate microbicide to detect whether the candidate increased the fraction of mice infected. Ten agents were tested – five detergents: nonionic (N9), cationic (benzalkonium chloride, BZK), anionic (sodium dodecylsulfate, SDS), the pair of detergents in C31G (C14AO and C16B); one surface active agent (chlorhexidine); two non-detergents (BufferGel®, and sulfonated polystyrene, SPS); and HEC placebo gel (hydroxyethylcellulose). Toxic effects were evaluated by histology, uptake of a 'dead cell' dye, colposcopy, enumeration of vaginal macrophages, and measurement of inflammatory cytokines. RESULTS: A single dose of N9 protected against HSV-2 for a few minutes but then rapidly increased susceptibility, which reached maximum at 12 hours. When applied at the minimal concentration needed for brief partial protection, all five detergents caused a subsequent increase in susceptibility at 12 hours of ~20–30-fold. Surprisingly, colposcopy failed to detect visible sign of the N9 toxic effect that increased susceptibility at 12 hours. Toxic effects that occurred contemporaneously with increased susceptibility were rapid exfoliation and re-growth of epithelial cell layers, entry of macrophages into the vaginal lumen, and release of one or more inflammatory cytokines (Il-1β, KC, MIP 1α, RANTES). The non-detergent microbicides and HEC placebo caused no significant increase in susceptibility or toxic effects. CONCLUSION: This mouse HSV-2 model provides a sensitive method to detect microbicide-induced toxicities that increase susceptibility to infection. In this model, there was no concentration at which detergents provided protection without significantly increasing susceptibility.JHU Woodrow Wilson Fellowship; National Institutes of Health (Program Project A1 45967

Income Trends among U.S. Residential Rooftop Solar Adopters

Berkeley Lab tracks and analyzes solar-adopter demographic characteristics. A central element of this work is an annual report describing income trends of residential solar adopters over time and across geographies. The report is based on household-level income estimates for single-family residential solar adopters across the United States, and is intended to serve as a foundational reference document for policy-makers, industry stakeholders, and other researchers interested in demographic trends among residential solar adopters. The report is published with an accompanying interactive data visualization tool that allows users to further explore the underlying data. In addition to the annual report, Berkeley Lab also conducts targeted topical analyses on issues related to solar-adopter demographics and provides direct analytical support to organizations working to expand access to solar energy among low-to-moderate income households. Requests for analytical support may be submitted through this form: "https://docs.google.com/forms/d/e/1FAIpQLSfOauinm2NRF-9J39aDh3447F9FDTOsP3tpMHJLzH_orKoTpw/viewform" target="_blank">online form.&nbsp