991 resultados para Budget Committee


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Medhurst, J. (2004). 'You say a minority, sir, we say a nation': The Pilkington Committee on Broadcasting (1960-62) and Wales. Welsh History Review. 22(2), pp.109-136. RAE2008

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Smoking is an expensive habit. Smoking households spend, on average, more than $US1000 annually on cigarettes. When a family member quits, in addition to the former smoker's improved long-term health, families benefit because savings from reduced cigarette expenditures can be allocated to other goods. For households in which some members continue to smoke, smoking expenditures crowd-out other purchases, which may affect other household members, as well as the smoker. We empirically analyse how expenditures on tobacco crowd-out consumption of other goods, estimating the patterns of substitution and complementarity between tobacco products and other categories of household expenditure. We use the Consumer Expenditure Survey data for the years 1995-2001, which we complement with regional price data and state cigarette prices. We estimate a consumer demand system that includes several main expenditure categories (cigarettes, food, alcohol, housing, apparel, transportation, medical care) and controls for socioeconomic variables and other sources of observable heterogeneity. Descriptive data indicate that, comparing smokers to nonsmokers, smokers spend less on housing. Results from the demand system indicate that as the price of cigarettes rises, households increase the quantity of food purchased, and, in some samples, reduce the quantity of apparel and housing purchased.

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The effectiveness of corporate governance mechanisms has been a subject of academic research for many decades. Although the large majority of corporate governance studies prior to mid 1990s were based on data from developed market economies such as the U.S., U.K. and Japan, in recent years researchers have begun examining corporate governance in transition economies. A comparison of China and India offers a unique environment for analyzing the effectiveness of corporate governance. First, both countries state-owned enterprise (SOE) reform strategies hinges on the Modern Enterprise System characterized by the separation of ownership and control. Ownership of an SOE’s assets is distributed among the government, institutional investors, managers, employees, and private investors. Effective control rights are assigned to management, which generally has a very small, or even nonexistent ownership stake. This distinctive shareholding structure creates conflict of interest not only between management (insiders) and outside investors but also between large shareholders and minority investors. Moreover, because both governments desire to retain some control—in part through partial retained ownership of commercialized SOEs, further conflicts arise between politicians and firms. Second, directors in publicly listed firms in both countries are predominantly drawn from institutions with significant non-market objectives: the government and other state enterprises, particularly in China, and extended families, particularly in India. As a result, the effectiveness of internal governance mechanisms, such as the number of independent directors on the board and the number of independent supervisors on the supervisory committee, are likely to be quiet limited, although this has yet to be fully evaluated. Third, because of the political nature of the privatization process itself, typical external governance mechanisms, such as debt (in conjunction with appropriate bankruptcy procedures), takeover threats, legal protection of investors, product market competition, etc., have not been effective. Bank loans have traditionally been viewed as grants from the state designed to bail out failing firms. State-owned banks retain monopoly or quasi-monopoly positions in the banking sector and profit is not their overriding objective. If political favor is deemed appropriate, subsidized loans, rescheduling of overdue debt or even outright transfer of funds can be arranged with SOEs (soft budget constraints). In addition, a market for private, non-bank debt is limited in India and has yet to be established China. There is no active merger or takeover activity in Chinese stock markets to discipline management. Information available in the capital markets is insufficient to keep at arm’s length of the corporate decisions. In light of the above peculiarities, China and India share many of the typical institutional characteristics as a transition economy, including poor legal protection of creditors and investors, the absence of an effective takeover market, an underdeveloped capital market, a relative inefficient banking system and significant interference of politicians in firm management. Su (2005) finds that the extent of political interference, managerial entrenchment and institutional control can help explain corporate dividend policies and post-IPO financing choices in this situation. Allen et al. (2005) demonstrate that standard corporate governance mechanisms are weak and ineffective for publicly listed firms while alternative governance mechanisms based on reputation and relationship have been remarkably effective in the private sector. Because the peculiarities are significant in this context, the differences in the political-economies of the two countries are likely to be evident in such relational terms. In this paper we explore the peculiarities of corporate governance in this transitional environment through a systematic examination of certain aspects of these reputational and relationship dimensions. Utilising the methods of social network analysis we identify the inter-organisational relationships at board level formed by equity holdings and by shared directors. Using data drawn from the Orbis database we map these relations among the 3700 largest firms in India and China respectively and identify the roles played in these relational networks by the particularly characteristic institutions in each case. We find greatly different social network structures in each case with some support in these relational dimensions for their distinctive features of governance. Further, the social network metrics allow us to considerably refine proxies for political interference, managerial entrenchment and institutional control used in earlier econometric analysis.

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Mechanistic models such as those based on dynamic energy budget (DEB) theory are emergent ecomechanics tools to investigate the extent of fitness in organisms through changes in life history traits as explained by bioenergetic principles. The rapid growth in interest around this approach originates from the mechanistic characteristics of DEB, which are based on a number of rules dictating the use of mass and energy flow through organisms. One apparent bottleneck in DEB applications comes from the estimations of DEB parameters which are based on mathematical and statistical methods (covariation method). The parameterisation process begins with the knowledge of some functional traits of a target organism (e. g. embryo, sexual maturity and ultimate body size, feeding and assimilation rates, maintenance costs), identified from the literature or laboratory experiments. However, considering the prominent role of the mechanistic approach in ecology, the reduction of possible uncertainties is an important objective. We propose a revaluation of the laboratory procedures commonly used in ecological studies to estimate DEB parameters in marine bivalves. Our experimental organism was Brachidontes pharaonis. We supported our proposal with a validation exercise which compared life history traits as obtained by DEBs (implemented with parameters obtained using classical laboratory methods) with the actual set of species traits obtained in the field. Correspondence between the 2 approaches was very high (>95%) with respect to estimating both size and fitness. Our results demonstrate a good agreement between field data and model output for the effect of temperature and food density on age-size curve, maximum body size and total gamete production per life span. The mechanistic approach is a promising method of providing accurate predictions in a world that is under in creasing anthropogenic pressure.

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Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates, consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuel combustion and cement production (E-FF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (E-LUC), mainly deforestation, are based on combined evidence from land-cover-change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (G(ATM)) is computed from the annual changes in concentration. The mean ocean CO2 sink (S-OCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in S-OCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (S-LAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO2, and land-cover-change (some including nitrogen-carbon interactions). We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as +/- 1 sigma, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2004-2013), E-FF was 8.9 +/- 0.4 GtC yr(-1), E-LUC 0.9 +/- 0.5 GtC yr(-1), G(ATM) 4.3 +/- 0.1 GtC yr(-1), S-OCEAN 2.6 +/- 0.5 GtC yr(-1), and S-LAND 2.9 +/- 0.8 GtC yr(-1). For year 2013 alone, E-FF grew to 9.9 +/- 0.5 GtC yr(-1), 2.3% above 2012, continuing the growth trend in these emissions, E-LUC was 0.9 +/- 0.5 GtC yr(-1), G(ATM) was 5.4 +/- 0.2 GtC yr(-1), S-OCEAN was 2.9 +/- 0.5 GtC yr(-1), and S-LAND was 2.5 +/- 0.9 GtC yr(-1). G(ATM) was high in 2013, reflecting a steady increase in E-FF and smaller and opposite changes between S-OCEAN and S-LAND compared to the past decade (2004-2013). The global atmospheric CO2 concentration reached 395.31 +/- 0.10 ppm averaged over 2013. We estimate that E-FF will increase by 2.5% (1.3-3.5 %) to 10.1 +/- 0.6 GtC in 2014 (37.0 +/- 2.2 GtCO(2) yr(-1)), 65% above emissions in 1990, based on projections of world gross domestic product and recent changes in the carbon intensity of the global economy. From this projection of E-FF and assumed constant E-LUC for 2014, cumulative emissions of CO2 will reach about 545 +/- 55 GtC (2000 +/- 200 GtCO(2)) for 1870-2014, about 75% from E-FF and 25% from E-LUC. This paper documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this living data set (Le Quere et al., 2013, 2014). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2014).

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Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates as well as consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover-change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO2, and land-cover change (some including nitrogen–carbon interactions). We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2005–2014), EFF was 9.0 ± 0.5 GtC yr−1, ELUC was 0.9 ± 0.5 GtC yr−1, GATM was 4.4 ± 0.1 GtC yr−1, SOCEAN was 2.6 ± 0.5 GtC yr−1, and SLAND was 3.0 ± 0.8 GtC yr−1. For the year 2014 alone, EFF grew to 9.8 ± 0.5 GtC yr−1, 0.6 % above 2013, continuing the growth trend in these emissions, albeit at a slower rate compared to the average growth of 2.2 % yr−1 that took place during 2005–2014. Also, for 2014, ELUC was 1.1 ± 0.5 GtC yr−1, GATM was 3.9 ± 0.2 GtC yr−1, SOCEAN was 2.9 ± 0.5 GtC yr−1, and SLAND was 4.1 ± 0.9 GtC yr−1. GATM was lower in 2014 compared to the past decade (2005–2014), reflecting a larger SLAND for that year. The global atmospheric CO2 concentration reached 397.15 ± 0.10 ppm averaged over 2014. For 2015, preliminary data indicate that the growth in EFF will be near or slightly below zero, with a projection of −0.6 [range of −1.6 to +0.5] %, based on national emissions projections for China and the USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the global economy for the rest of the world. From this projection of EFF and assumed constant ELUC for 2015, cumulative emissions of CO2 will reach about 555 ± 55 GtC (2035 ± 205 GtCO2) for 1870–2015, about 75 % from EFF and 25 % from ELUC. This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set (Le Quéré et al., 2015, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2015).

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The 2007/2008 annual report of the Queen's EAP Steering Committee.

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Background: TORCH (Towards a Revolution in COPD Health) is an international multicentre, randomised, placebo-controlled clinical trial of inhaled fluticasone propionate/salmeterol combination treatment and its monotherapy components for maintenance treatment of moderately to severely impaired patients with chronic obstructive pulmonary disease (COPD). The primary outcome is all-cause mortality. Cause-specific mortality and deaths related to COPD are additional outcome measures, but systematic methods for ascertainment of these outcomes have not previously been described. Methods: A Clinical Endpoint Committee (CEC) was tasked with categorising the cause of death and the relationship of deaths to COPD in a systematic, unbiased and independent manner. The key elements of the operation of the committee were the use of predefined principles of operation and definitions of cause of death and COPD-relatedness; the independent review of cases by all members with development of a consensus opinion; and a substantial infrastructure to collect medical information. Results: 911 deaths were reviewed and consensus was reached in all. Cause-specific mortality was: cardiovascular 27%, respiratory 35%, cancer 21%, other 10% and unknown 8%. 40% of deaths were definitely or probably related to COPD. Adjudications were identical in 83% of blindly re-adjudicated cases ( = 0.80). COPD-relatedness was reproduced 84% of the time ( = 0.73). The CEC adjudication was equivalent to the primary cause of death recorded by the site investigator in 52% of cases. Conclusion: A CEC can provide standardised, reliable and informative adjudication of COPD mortality that provides information which frequently differs from data collected from assessment by site investigators.