988 resultados para composite index


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We examine whether a three-regime model that allows for dormant, explosive and collapsing speculative behaviour can explain the dynamics of the S&P 500. We extend existing models of speculative behaviour by including a third regime that allows a bubble to grow at a steady rate, and propose abnormal volume as an indicator of the probable time of bubble collapse. We also examine the financial usefulness of the three-regime model by studying a trading rule formed using inferences from it, whose use leads to higher Sharpe ratios and end of period wealth than from employing existing models or a buy-and-hold strategy.

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China is a large country characterized by remarkable growth and distinct regional diversity. Spatial disparity has always been a hot issue since China has been struggling to follow a balanced growth path but still confronting with unprecedented pressures and challenges. To better understand the inequality level benchmarking spatial distributions of Chinese provinces and municipalities and estimate dynamic trajectory of sustainable development in China, I constructed the Composite Index of Regional Development (CIRD) with five sub pillars/dimensions involving Macroeconomic Index (MEI), Science and Innovation Index (SCI), Environmental Sustainability Index (ESI), Human Capital Index (HCI) and Public Facilities Index (PFI), endeavoring to cover various fields of regional socioeconomic development. Ranking reports on the five sub dimensions and aggregated CIRD were provided in order to better measure the developmental degrees of 31 or 30 Chinese provinces and municipalities over 13 years from 1998 to 2010 as the time interval of three “Five-year Plans”. Further empirical applications of this CIRD focused on clustering and convergence estimation, attempting to fill up the gap in quantifying the developmental levels of regional comprehensive socioeconomics and estimating the dynamic convergence trajectory of regional sustainable development in a long run. Four clusters were benchmarked geographically-oriented in the map on the basis of cluster analysis, and club-convergence was observed in the Chinese provinces and municipalities based on stochastic kernel density estimation.

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Achieving sustainable urban development is identified as one ultimate goal of many contemporary planning endeavours and has become central to formulation of urban planning policies. Within this concept, land-use and transport integration is highlighted as one of the most important and attainable policy objectives. In many cities, integration is embraced as an integral part of local development plans, and a number of key integration principles are identified. However, the lack of available evaluation methods to measure extent of urban sustainability levels prevents successful implementation of these principles. This paper introduces a new indicator-based spatial composite indexing model developed to measure sustainability performance of urban settings by taking into account land-use and transport integration principles. Model indicators are chosen via a thorough selection process in line with key principles of land-use and transport integration. These indicators are grouped into categories and themes according to their topical relevance. These indicators are then aggregated to form a spatial composite index to portray an overview of the sustainability performance of the pilot study area used for model demonstration. The study results revealed that the model is a practical instrument for evaluating success of local integration policies and visualizing sustainability performance of built environments and useful in both identifying problematic areas as well as formulating policy interventions.

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Millions of crabs are sorted and discarded in freezing conditions each year in Alaskan fisheries for Tanner crab (Chionoecetes bairdi) and snow crab (C. opilio). However, cold exposures vary widely over the fishing season and among different vessels, and mortalities are difficult to estimate. A shipboard experiment was conducted to determine whether simple behavioral observations can be used to evaluate crab condition after low-temperature exposures. Crabs were systematically subjected to cold in seven different exposure treatments. They were then tested for righting behavior and six different ref lex actions and held to monitor mortality. Crabs lost limbs, showed ref lex impairment, and died in direct proportion to increases in cold exposure. Righting behavior was a poor predictor of mortality, whereas reflex impairment (scored as the sum of reflex actions that were lost) was an excellent predictor. This composite index could be measured quickly and easily in hand, and logistic regression revealed that the relationship between reflex impairment and mortality correctly predicted 80.0% of the mortality and survival for C. bairdi, and 79.4% for C. opilio. These relationships provide substantial improvements over earlier approaches to mortality estimation and were independent of crab size and exposure temperature.

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The stock index futures was introduced in Malaysia in December 1995 with the launching of the futures contract on the Kuala Lumpur Stock Exchange Composite Index. Due to its recentness in the country, many issues pertaining to this equity derivatives instrument have not been explored. Thus, the development of stock index futures opens many opportunities for research in this area. This study examines the temporal relationship between the price of the Kuala Lumpur Stock Exchange Composite Index futures contract (FKLI) and its underlying stock index, the Kuala Lumpur Stock Exchange Composite Index (KLSE CI). The five-year period under study is split into three subperiods to observe the price co-movement pattern under different volatility levels. The study finds that futures market tends to lead the spot market by one day during the periods of stable market, and there is a mixed lead-lag relationship between the two markets during the period of highly volatile market.

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This article evaluates the robustness of rankings obtained from composite indices that combine information from two or more components via a weighted sum. It examines the empirical prevalence of robust comparisons using the method proposed by Foster et al. (2010). Indices examined are the Human Development Index (HDI), the Index of Economic Freedom (IEF), and the Environmental Performance Index (EPI). Key theoretical results demonstrate links between the prevalence of robust comparisons, Kendall’s tau rank correlation coefficient, and statistical association across components. Implications for redundancy among index components are also examined.

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In the paper, we construct a composite indicator to estimate the potential of four Central and Eastern European countries (the Czech Republic, Hungary, Poland and Slovakia) to benefit from productivity spillovers from foreign direct investment (FDI) in the manufacturing sector. Such transfers of technology are one of the main benefits of FDI for the host country, and should also be one of the main determinants of FDI incentives offered to investing multinationals by governments, but they are difficult to assess ex ante. For our composite index, we use six components to proxy the main channels and determinants of these spillovers. We have tried several weighting and aggregation methods, and we consider our results robust. According to the analysis of our results, between 2003 and 2007 all four countries were able to increase their potential to benefit from such spillovers, although there are large differences between them. The Czech Republic clearly has the most potential to benefit from productivity spillovers, while Poland has the least. The relative positions of Hungary and Slovakia depend to some extent on the exact weighting and aggregation method of the individual components of the index, but the differences are not large. These conclusions have important implications both the investment strategies of multinationals and government FDI policies.

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In the paper, we construct a composite indicator to estimate the potential of four Central and Eastern European countries (the Czech Republic, Hungary, Poland and Slovakia) to benefit from productivity spillovers from foreign direct investment (FDI) in the manufacturing sector. Such transfers of technology are one of the main benefits of FDI for the host country, and should also be one of the main determinants of FDI incentives offered to investing multinationals by governments, but they are difficult to assess ex ante. For our composite index, we use six components to proxy the main channels and determinants of these spillovers. We have tried several weighting and aggregation methods, and we consider our results robust. According to the analysis of our results, between 2003 and 2007 all four countries were able to increase their potential to benefit from such spillovers, although there are large differences between them. The Czech Republic clearly has the most potential to benefit from productivity spillovers, while Poland has the least. The relative positions of Hungary and Slovakia depend to some extent on the exact weighting and aggregation method of the individual components of the index, but the differences are not large. These conclusions have important implication both the investment strategies of multinationals and government FDI policies.

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We investigate whether the levels of a stock market index contain any evidence of a behavioural bias depending on the proximity of the index level to 'psychological barriers'. These are certain index levels (usually in multiples of 100) at which the market tends to stick before breaking out either up or down. Extant behavioural finance literature has attributed this to investors' subjective perception of 'something special' about certain index levels where in fact no rational economic basis exists for such a perception. We carry out an empirical analysis of the NASDAQ Composite index and find that barrier effects are indeed present in that stock index. We employ simulation analysis to validate of our obtained results.

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This paper identifies transport disadvantage using a 7 day activity-travel diary data from two rural case study areas. A composite participation index (PI) measure was developed for this study based on six indices measuring elements of travel and activity participation. Using the index the paper then goes on to compare these results, with the results obtained from other more traditional indicators used to identify transport disadvantage. These indicators are related to the size of activity space such as unique network distance travelled, number of unique locations visited, activity space area, activity duration, and fullness (shape) of activity spaces. The weaknesses of these indicator based measures are that: firstly, they do not take into account the relativity of the measure between different areas i.e. travel distance in terms of the wider context of available activities within an area; and secondly, these indicators are multi-dimensional and each represents a different qualitative aspect of travel and activity participation. As a result, six individual indices were developed to overcome these problems. These include: participation count index, participation length index, participation area index, participation duration index, participation type index, and participation frequency index. These are then aggregated to assess the relative performance in terms of these different indices and identify the nature of transport disadvantage. GIS was used to visualise individual travel patterns and to derive scores for both the indicator based measures and the index based measures. Factor analysis was conducted to derive weights of the individual indices to form the composite index measure. From this analysis, two intermediate indices were also derived using the underlying factors of the data related to these indices. Using the scores of all these measures, multiple regression analyses were conducted to identify patterns of transport disadvantage.

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Objective: To examine the association between individual- and neighborhood-level disadvantage and self-reported arthritis. Methods: We used data from a population-based cross-sectional study conducted in 2007 among 10,757 men and women ages 40–65 years, selected from 200 neighborhoods in Brisbane, Queensland, Australia using a stratified 2-stage cluster design. Data were collected using a mail survey (68.5% response). Neighborhood disadvantage was measured using a census-based composite index, and individual disadvantage was measured using self-reported education, household income, and occupation. Arthritis was indicated by self-report. Data were analyzed using multilevel modeling. Results: The overall rate of self-reported arthritis was 23% (95% confidence interval [95% CI] 22–24). After adjustment for sociodemographic factors, arthritis prevalence was greatest for women (odds ratio [OR] 1.5, 95% CI 1.4–1.7) and in those ages 60–65 years (OR 4.4, 95% CI 3.7–5.2), those with a diploma/associate diploma (OR 1.3, 95% CI 1.1–1.6), those who were permanently unable to work (OR 4.0, 95% CI 3.1–5.3), and those with a household income <$25,999 (OR 2.1, 95% CI 1.7–2.6). Independent of individual-level factors, residents of the most disadvantaged neighborhoods were 42% (OR 1.4, 95% CI 1.2–1.7) more likely than those in the least disadvantaged neighborhoods to self-report arthritis. Cross-level interactions between neighborhood disadvantage and education, occupation, and household income were not significant. Conclusion: Arthritis prevalence is greater in more socially disadvantaged neighborhoods. These are the first multilevel data to examine the relationship between individual- and neighborhood-level disadvantage upon arthritis and have important implications for policy, health promotion, and other intervention strategies designed to reduce the rates of arthritis, indicating that intervention efforts may need to focus on both people and places.

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During the last several decades, the quality of natural resources and their services have been exposed to significant degradation from increased urban populations combined with the sprawl of settlements, development of transportation networks and industrial activities (Dorsey, 2003; Pauleit et al., 2005). As a result of this environmental degradation, a sustainable framework for urban development is required to provide the resilience of natural resources and ecosystems. Sustainable urban development refers to the management of cities with adequate infrastructure to support the needs of its population for the present and future generations as well as maintain the sustainability of its ecosystems (UNEP/IETC, 2002; Yigitcanlar, 2010). One of the important strategic approaches for planning sustainable cities is „ecological planning‟. Ecological planning is a multi-dimensional concept that aims to preserve biodiversity richness and ecosystem productivity through the sustainable management of natural resources (Barnes et al., 2005). As stated by Baldwin (1985, p.4), ecological planning is the initiation and operation of activities to direct and control the acquisition, transformation, disruption and disposal of resources in a manner capable of sustaining human activities with a minimum disruption of ecosystem processes. Therefore, ecological planning is a powerful method for creating sustainable urban ecosystems. In order to explore the city as an ecosystem and investigate the interaction between the urban ecosystem and human activities, a holistic urban ecosystem sustainability assessment approach is required. Urban ecosystem sustainability assessment serves as a tool that helps policy and decision-makers in improving their actions towards sustainable urban development. There are several methods used in urban ecosystem sustainability assessment among which sustainability indicators and composite indices are the most commonly used tools for assessing the progress towards sustainable land use and urban management. Currently, a variety of composite indices are available to measure the sustainability at the local, national and international levels. However, the main conclusion drawn from the literature review is that they are too broad to be applied to assess local and micro level sustainability and no benchmark value for most of the indicators exists due to limited data availability and non-comparable data across countries. Mayer (2008, p. 280) advocates that by stating "as different as the indices may seem, many of them incorporate the same underlying data because of the small number of available sustainability datasets". Mori and Christodoulou (2011) also argue that this relative evaluation and comparison brings along biased assessments, as data only exists for some entities, which also means excluding many nations from evaluation and comparison. Thus, there is a need for developing an accurate and comprehensive micro-level urban ecosystem sustainability assessment method. In order to develop such a model, it is practical to adopt an approach that uses a method to utilise indicators for collecting data, designate certain threshold values or ranges, perform a comparative sustainability assessment via indices at the micro-level, and aggregate these assessment findings to the local level. Hereby, through this approach and model, it is possible to produce sufficient and reliable data to enable comparison at the local level, and provide useful results to inform the local planning, conservation and development decision-making process to secure sustainable ecosystems and urban futures. To advance research in this area, this study investigated the environmental impacts of an existing urban context by using a composite index with an aim to identify the interaction between urban ecosystems and human activities in the context of environmental sustainability. In this respect, this study developed a new comprehensive urban ecosystem sustainability assessment tool entitled the „Micro-level Urban-ecosystem Sustainability IndeX‟ (MUSIX). The MUSIX model is an indicator-based indexing model that investigates the factors affecting urban sustainability in a local context. The model outputs provide local and micro-level sustainability reporting guidance to help policy-making concerning environmental issues. A multi-method research approach, which is based on both quantitative analysis and qualitative analysis, was employed in the construction of the MUSIX model. First, a qualitative research was conducted through an interpretive and critical literature review in developing a theoretical framework and indicator selection. Afterwards, a quantitative research was conducted through statistical and spatial analyses in data collection, processing and model application. The MUSIX model was tested in four pilot study sites selected from the Gold Coast City, Queensland, Australia. The model results detected the sustainability performance of current urban settings referring to six main issues of urban development: (1) hydrology, (2) ecology, (3) pollution, (4) location, (5) design, and; (6) efficiency. For each category, a set of core indicators was assigned which are intended to: (1) benchmark the current situation, strengths and weaknesses, (2) evaluate the efficiency of implemented plans, and; (3) measure the progress towards sustainable development. While the indicator set of the model provided specific information about the environmental impacts in the area at the parcel scale, the composite index score provided general information about the sustainability of the area at the neighbourhood scale. Finally, in light of the model findings, integrated ecological planning strategies were developed to guide the preparation and assessment of development and local area plans in conjunction with the Gold Coast Planning Scheme, which establishes regulatory provisions to achieve ecological sustainability through the formulation of place codes, development codes, constraint codes and other assessment criteria that provide guidance for best practice development solutions. These relevant strategies can be summarised as follows: • Establishing hydrological conservation through sustainable stormwater management in order to preserve the Earth’s water cycle and aquatic ecosystems; • Providing ecological conservation through sustainable ecosystem management in order to protect biological diversity and maintain the integrity of natural ecosystems; • Improving environmental quality through developing pollution prevention regulations and policies in order to promote high quality water resources, clean air and enhanced ecosystem health; • Creating sustainable mobility and accessibility through designing better local services and walkable neighbourhoods in order to promote safe environments and healthy communities; • Sustainable design of urban environment through climate responsive design in order to increase the efficient use of solar energy to provide thermal comfort, and; • Use of renewable resources through creating efficient communities in order to provide long-term management of natural resources for the sustainability of future generations.

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In recent years a number of urban sustainability assessment frameworks are developed to better inform policy formulation and decision-making processes. This paper introduces one of these attempts in developing a comprehensive assessment tool—i.e., Micro-level Urban-ecosystem Sustainability IndeX (MUSIX). Being an indicator-based indexing model, MUSIX investigates the environmental impacts of land-uses on urban sustainability by measuring urban ecosystem components in local scale. The paper presents the methodology of MUSIX and demonstrates the performance of the model in a pilot test-bed—i.e., in Gold Coast, Australia. The model provides useful insights on the sustainability performance of the test-bed area. The parcel-scale findings of the indicators are used to identify local problems considering six main issues of urban development—i.e., hydrology; ecology; pollution; location; design, and; efficiency. The composite index score is used to propose betterment strategies to guide the development of local area plans in conjunction with the City's Planning Scheme. In overall, this study has shown that parcel-scale environmental data provides an overview of the local sustainability in urban areas as in the example of Gold Coast, which can also be used for setting environmental policy, objectives and targets.