975 resultados para data capture
Resumo:
The stylized facts suggest a negative relationship between tax progressivity and the skill premium from the early 1960s until the early 1990s, and a positive one thereafter. They also generally imply rising tax progressivity, except for the 1980s. In this paper, we ask whether optimal tax policy is consistent with these observations, taking into account the demographic and technological factors that have also affected the skill premium. To this end, we construct a dynamic general equilibrium model in which the skill premium and the progressivity of the tax system are endogenously determined, with the latter being optimally chosen by a benevolent government. We find that optimal policy delivers both a progressive tax system and model predictions which are generally consistent, except for the 1980s, with the stylized facts relating to the skill premium and progressivity. To capture the patterns in the data over the 1980s requires that we adopt a government policy which is biased towards the interests of skilled agents. Thus, in addition to demographic and technological factors, changes in the preferences of policy-makers appear to be a potentially important factor in determining the evolution of the observed skill premium.
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New methods of analysis of patent statistics allow assessing country profiles of technological specialization for the period 1990-2006. We witness a modest decrease in levels of specialization, which we show to be negatively influenced by country size and degree of internationalization of inventive activities.
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It is a well-established fact in the literature on simulating Input-Output tables that mechanical methods for estimating intermediate trade lead to biased results where cross-hauling is underestimated and Type-I multipliers are overstated. Repeated findings to this effect have led to a primary emphasis on advocating the accurate estimation of intermediate trade flows. This paper reviews previous research and argues for a qualification of the consensus view: When simulating IO tables, construction approaches need to consider spill-over effects driven by wage and consumption flows. In particular, for the case of metropolitan economies, wage and consumption flows are important if accurate Type-II multipliers are to be obtained. This is demonstrated by constructing an interregional Input-Output table, which captures interdependencies between a city and its commuter belt, nested within the wider regional economy. In addition to identifying interdependencies caused by interregional intermediate purchases, data on subregional household incomes and commuter flows are used to identify interdependencies from wage payments and household consumption. The construction of the table is varied around a range of assumptions on intermediate trade and household consumption to capture the sensitivity of multipliers.
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The aim of the paper is to identify the added value from using general equilibrium techniques to consider the economy-wide impacts of increased efficiency in household energy use. We take as an illustrative case study the effect of a 5% improvement in household energy efficiency on the UK economy. This impact is measured through simulations that use models that have increasing degrees of endogeneity but are calibrated on a common data set. That is to say, we calculate rebound effects for models that progress from the most basic partial equilibrium approach to a fully specified general equilibrium treatment. The size of the rebound effect on total energy use depends upon: the elasticity of substitution of energy in household consumption; the energy intensity of the different elements of household consumption demand; and the impact of changes in income, economic activity and relative prices. A general equilibrium model is required to capture these final three impacts.
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We examine the complications involved in attributing emissions at a sub-regional or local level. Speci cally, we look at how functional specialisation embedded within the metropolitan area can, via trade between sub-regions, create intra-metropolitan emissions interdependencies; and how this complicates environmental policy implementation in an analogous manner to international trade at the national level. For this purpose we use a 3-region emissions extended input-output model of the Glasgow metropolitan area (2 regions: city and surrounding suburban area) and the rest of Scotland. The model utilises data on commuter flows and household consumption to capture income and consumption flows across sub-regions. This enables a carbon attribution analysis at the sub-regional level, allowing us to shed light on the signi cant emissions interdependencies that can exist within metropolitan areas.
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Using survey expectations data and Markov-switching models, this paper evaluates the characteristics and evolution of investors' forecast errors about the yen/dollar exchange rate. Since our model is derived from the uncovered interest rate parity (UIRP) condition and our data cover a period of low interest rates, this study is also related to the forward premium puzzle and the currency carry trade strategy. We obtain the following results. First, with the same forecast horizon, exchange rate forecasts are homogeneous among different industry types, but within the same industry, exchange rate forecasts differ if the forecast time horizon is different. In particular, investors tend to undervalue the future exchange rate for long term forecast horizons; however, in the short run they tend to overvalue the future exchange rate. Second, while forecast errors are found to be partly driven by interest rate spreads, evidence against the UIRP is provided regardless of the forecasting time horizon; the forward premium puzzle becomes more significant in shorter term forecasting errors. Consistent with this finding, our coefficients on interest rate spreads provide indirect evidence of the yen carry trade over only a short term forecast horizon. Furthermore, the carry trade seems to be active when there is a clear indication that the interest rate will be low in the future.
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This paper proposes full-Bayes priors for time-varying parameter vector autoregressions (TVP-VARs) which are more robust and objective than existing choices proposed in the literature. We formulate the priors in a way that they allow for straightforward posterior computation, they require minimal input by the user, and they result in shrinkage posterior representations, thus, making them appropriate for models of large dimensions. A comprehensive forecasting exercise involving TVP-VARs of different dimensions establishes the usefulness of the proposed approach.
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Time-lapse crosshole ground-penetrating radar (GPR) data, collected while infiltration occurs, can provide valuable information regarding the hydraulic properties of the unsaturated zone. In particular, the stochastic inversion of such data provides estimates of parameter uncertainties, which are necessary for hydrological prediction and decision making. Here, we investigate the effect of different infiltration conditions on the stochastic inversion of time-lapse, zero-offset-profile, GPR data. Inversions are performed using a Bayesian Markov-chain-Monte-Carlo methodology. Our results clearly indicate that considering data collected during a forced infiltration test helps to better refine soil hydraulic properties compared to data collected under natural infiltration conditions
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This paper develops a methodology to estimate the entire population distributions from bin-aggregated sample data. We do this through the estimation of the parameters of mixtures of distributions that allow for maximal parametric flexibility. The statistical approach we develop enables comparisons of the full distributions of height data from potential army conscripts across France's 88 departments for most of the nineteenth century. These comparisons are made by testing for differences-of-means stochastic dominance. Corrections for possible measurement errors are also devised by taking advantage of the richness of the data sets. Our methodology is of interest to researchers working on historical as well as contemporary bin-aggregated or histogram-type data, something that is still widely done since much of the information that is publicly available is in that form, often due to restrictions due to political sensitivity and/or confidentiality concerns.
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BACKGROUND: Certolizumab pegol (Cimzia, CZP) was approved for the treatment of Crohn's disease (CD) patients in 2007 in Switzerland as the first country worldwide. This prospective phase IV study aimed to evaluate the efficacy and safety of CZP over 26 weeks in a multicenter cohort of practice-based patients. METHODS: Evaluation questionnaires at baseline, week 6, and week 26 were completed by gastroenterologists in hospitals and private practices. Adverse events were evaluated according to World Health Organization (WHO) guidelines. RESULTS: Sixty patients (38F/22M) were included; 53% had complicated disease (stricturing or penetrating), 45% had undergone prior CD-related surgery. All patients had prior exposure to systemic steroids, 96% to immunomodulators, 73% to infliximab, and 43% to adalimumab. A significant decrease of the Harvey-Bradshaw Index (HBI) was observed under CZP therapy (12.2 ± 4.9 at week 0 versus 6.3 ± 4.7 at week 6 and 6.7 ± 5.3 at week 26, both P < 0.001). Response and remission rates were 70% and 40% (week 6) and 67% and 36%, respectively (week 26). The complete perianal fistula closure rate was 36% at week 6 and 55% at week 26. The frequency of adverse drug reactions attributed to CZP was 5%. CZP was continued in 88% of patients beyond week 6 and in 67% beyond week 26. CONCLUSIONS: In a population of CD patients with predominantly complicated disease behavior, CZP proved to be effective in induction and maintenance of response and remission. This series provides the first evidence of CZP's effectiveness in perianal fistulizing CD in clinical practice.
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The use of Geographic Information Systems has revolutionalized the handling and the visualization of geo-referenced data and has underlined the critic role of spatial analysis. The usual tools for such a purpose are geostatistics which are widely used in Earth science. Geostatistics are based upon several hypothesis which are not always verified in practice. On the other hand, Artificial Neural Network (ANN) a priori can be used without special assumptions and are known to be flexible. This paper proposes to discuss the application of ANN in the case of the interpolation of a geo-referenced variable.
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The effects of azadirachtin A, a tetranortriterpenoid from the neem tree Azadirachta indica J., on both development and interaction between Trypanosoma cruzi, the causative agent of Chagas' disease, and its vector Rhodnius prolixus were studied. Given through a blood meal, a dose-rsponse relationship of azadirachtin was established using antifeedant effect and ecdysis inhibition as effective parameters. A singlo dose of azadirachtin A was able to block the onset of mitosis in the epidermis and ecdysteroid titers in the hemnolymph, determined by radioimmuneassay, were too low for an induction of ecadysis. The survival of T. cruzi was also studied in R. prolixus treated with the drug. If the trypomastigotes were fed in presence of azadirachtin A the number of parasites drastically decreased. If the drug was applied after infection of the bug with T. cruzi, the parasite was still abolished from the gut. If the insect was pretreated with azadirachtin A before infection the same observation was obtained. A single dose of azadirachtin A was enough for a permanent resistance of the insect host against its reinfection with T. cruzi and for blocking the ecdysis for a long time. The effects of azadirachtin A on the hormonal balance of the host and growth inhibition of the parasite will be discussed on the basis of the present results.
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Proallatotoxins, and particularly preconcenes, are exceptionally promising models for studying Rhodnius prolixus physiology and for comparison with other natural compounds with anti-hormonal activities. Effects of preconcenes on feeding, development and reproduction of R. prolixus are being detailed. The precocenes reveal significant effects on feeding, moulting cycle (inducing precocious metamorphosis and ecdysial stasis), and reproduction of these insect. The mechanism of action of proallatotoxins was discussed based on the corpus allatum cytotoxic effect and on the ecdysteroid biosynthesis in prothoracic glands and ovaries. Further studies of these compounds on R. prolixus are need and will hopefully reveal other unesplored points regarding the action of the proallatotoxins on insects.
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BACKGROUND AND AIMS: In critically ill patients, fractional hepatic de novo lipogenesis increases in proportion to carbohydrate administration during isoenergetic nutrition. In this study, we sought to determine whether this increase may be the consequence of continuous enteral nutrition and bed rest. We, therefore, measured fractional hepatic de novo lipogenesis in a group of 12 healthy subjects during near-continuous oral feeding (hourly isoenergetic meals with a liquid formula containing 55% carbohydrate). In eight subjects, near-continuous enteral nutrition and bed rest were applied over a 10 h period. In the other four subjects, it was extended to 34 h. Fractional hepatic de novo lipogenesis was measured by infusing(13) C-labeled acetate and monitoring VLDL-(13)C palmitate enrichment with mass isotopomer distribution analysis. Fractional hepatic de novo lipogenesis was 3.2% (range 1.5-7.5%) in the eight subjects after 10 h of near continuous nutrition and 1.6% (range 1.3-2.0%) in the four subjects after 34 h of near-continuous nutrition and bed rest. This indicates that continuous nutrition and physical inactivity do not increase hepatic de novo lipogenesis. Fractional hepatic de novo lipogenesis previously reported in critically ill patients under similar nutritional conditions (9.3%) (range 5.3-15.8%) was markedly higher than in healthy subjects (P<0.001). These data from healthy subjects indicate that fractional hepatic de novo lipogenesis is increased in critically ill patients.