977 resultados para Index numbers (Economics)


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Individual well-being is multidimensional and various aspects of the quality of life need to be jointly considered in its measurement. The axiomatic literature on the subject has proposed many indices of multidimensional poverty and deprivation and explored the properties that are at the basis of these measures. The purpose of this chapter is to add intertemporal considerations to the analysis of material deprivation. We employ the EU-SILC panel data set, which includes information on different aspects of well-being over time. EU countries are compared based on measures that take this additional intertemporal information into consideration. Journal of Economic Literature Classi cation No.: D63.

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This document describes the data collection and use for the computation of rankings within RePEc (Research Papers in Economics). This encompasses the determination of impact factors for journals and working paper series, as well as the ranking of authors, institutions and geographic regions. The various ranking methods are also compared, using a snapshot of the data.

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With the globalization of economic activity, the relative weight of foreign trade in national economic activities has increased, and the question of how to measure trends in the value and quantity of international trade has become an important issue for policy-makers and economists. This paper compares the chain-linked indices formulated by Masato Kuroko, based on HS this fiscal year for individual industry categories and countries with chain-linked indices based on SITC-R1 codes, in order to study how changes in the quality composition of the same products, which cannot be considered using unit value indices based on SITC-R1 codes, can be considered using unit value indices based on the more detailed HS product classifications.

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Made-up set; title supplied.

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This dissertation studies environmental regulation issues in the hog production industry as well as forces behind the reorganization of the industry during the past two decades. Federal and State-level environmental regulations imposed on U.S. hog production during the year 2003 are examined in Chapter 1. Based on the number of regulations passed by the Federal government and states, the 2003 regulatory index is constructed. The regulatory stringency index suggests that state-level regulations vary across states and have increased over the years. In addition, state-level regulations are more stringent than federal regulations. Chapter 2 develops an empirically implementable theoretical model which allows us to investigate the long-run effects of environmental regulations on the U.S. hog industry. Hog feeding operations (HFOs) are divided into large feeding operations (LHFOs) and small feeding operations (SHFOs). The impact of the presence of a large number of LHFOs on the entry and exit of CHFOs is also examined. Results of this study suggest that: Increased state-level regulation stringency significantly lowers the output of SHFOs; increased state-level regulation stringency significantly lowers the output of LHFOs; increased state-level regulation stringency significantly lowers the number of SHFOs; SHFO output rises significantly in states that have a greater number of LHFOs; LHFO output rises significantly in states that have a greater number of LHFOs; the number of SHFOs significantly increases in states that have a greater numbers of LHFOs; regulation increases the average SHFO size; and regulation decreases the average LHFO size. Chapter 3 examines the importance of input availability, market attractiveness, agglomeration economies and environmental regulations on the reorganization of U.S. hog production for a panel of 22 U.S. hog producing states which include, Northern states, Southern states and Midwest states for the period 1994-2006. Results from this study suggest that: Hog production in a state is positively affected by hog production in a nearby state, confirming the presence of agglomeration economies; Environmental regulations and high corn price have negative effects on state-level U.S. hog production; High hog prices, and favorable labor cost, and land values attract hog production; and transportation cost has no effect on hog production. Advisors: Azzeddine Azzam and Karina Schoengold

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This research primarily represents a contribution to the lobbying regulation research arena. It introduces an index which for the first time attempts to measure the direct compliance costs of lobbying regulation. The Cost Indicator Index (CII) offers a brand new platform for qualitative and quantitative assessment of adopted lobbying laws and proposals of those laws, both in the comparative and the sui generis dimension. The CII is not just the only new tool introduced in the last decade, but it is the only tool available for comparative assessments of the costs of lobbying regulations. Beside the qualitative contribution, the research introduces an additional theoretical framework for complementary qualitative analysis of the lobbying laws. The Ninefold theory allows a more structured assessment and classification of lobbying regulations, both by indication of benefits and costs. Lastly, this research introduces the Cost-Benefit Labels (CBL). These labels might improve an ex-ante lobbying regulation impact assessment procedure, primarily in the sui generis perspective. In its final part, the research focuses on four South East European countries (Slovenia, Serbia, Montenegro and Macedonia), and for the first time brings them into the discussion and calculates their CPI and CII scores. The special focus of the application was on Serbia, whose proposal on the Law on Lobbying has been extensively analysed in qualitative and quantitative terms, taking into consideration specific political and economic circumstances of the country. Although the obtained results are of an indicative nature, the CII will probably find its place within the academic and policymaking arena, and will hopefully contribute to a better understanding of lobbying regulations worldwide.

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"August, 1916."

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Shipping list no.: 93-0196-P.

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This paper considers the history of the cluster concept in urban economic geography, and its relationship to recent debates about creative cities. It then looks at the role that universities can play in the development of a creative cluster, as well as some of the potential pitfalls.

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The New Zealand creative sector was responsible for almost 121,000 jobs at the time of the 2006 Census (6.3% of total employment). These are divided between • 35,751 creative specialists – persons employed doing creative work in creative industries • 42,300 support workers - persons providing management and support services in creative industries • 42,792 embedded creative workers – persons engaged in creative work in other types of enterprise The most striking feature of this breakdown is the fact that the largest group of creative workers are employed outside the creative industries, i.e. in other types of businesses. Even within the creative industries, there are fewer people directly engaged in creative work than in providing management and support. Creative sector employees earned incomes of approximately $52,000 per annum at the time of the 2006 Census. This is relatively uniform across all three types of creative worker, and is significantly above the average for all employed persons (of approximately $40,700). Creative employment and incomes were growing strongly over both five year periods between the 1996, 2001 and 2006 Censuses. However, when we compare creative and general trends, we see two distinct phases in the development of the creative sector: • rapid structural growth over the five years to 2001 (especially led by developments in ICT), with creative employment and incomes increasing rapidly at a time when they were growing modestly across the whole economy; • subsequent consolidation, with growth driven by more by national economic expansion than structural change, and creative employment and incomes moving in parallel with strong economy-wide growth. Other important trends revealed by the data are that • the strongest growth during the decade was in embedded creative workers, especially over the first five years. The weakest growth was in creative specialists, with support workers in creative industries in the middle rank, • by far the strongest growth in creative industries’ employment was in Software & digital content, which trebled in size over the decade Comparing New Zealand with the United Kingdom and Australia, the two southern hemisphere nations have significantly lower proportions of total employment in the creative sector (both in creative industries and embedded employment). New Zealand’s and Australia’s creative shares in 2001 were similar (5.4% each), but in the following five years, our share has expanded (to 5.7%) whereas Australia’s fell slightly (to 5.2%) – in both cases, through changes in creative industries’ employment. The creative industries generated $10.5 billion in total gross output in the March 2006 year. Resulting from this was value added totalling $5.1b, representing 3.3% of New Zealand’s total GDP. Overall, value added in the creative industries represents 49% of industry gross output, which is higher than the average across the whole economy, 45%. This is a reflection of the relatively high labour intensity and high earnings of the creative industries. Industries which have an above-average ratio of value added to gross output are usually labour-intensive, especially when wages and salaries are above average. This is true for Software & Digital Content and Architecture, Design & Visual Arts, with ratios of 60.4% and 55.2% respectively. However there is significant variation in this ratio between different parts of the creative industries, with some parts (e.g. Software & Digital Content and Architecture, Design & Visual Arts) generating even higher value added relative to output, and others (e.g. TV & Radio, Publishing and Music & Performing Arts) less, because of high capital intensity and import content. When we take into account the impact of the creative industries’ demand for goods and services from its suppliers and consumption spending from incomes earned, we estimate that there is an addition to economic activity of: • $30.9 billion in gross output, $41.4b in total • $15.1b in value added, $20.3b in total • 158,100 people employed, 234,600 in total The total economic impact of the creative industries is approximately four times their direct output and value added, and three times their direct employment. Their effect on output and value added is roughly in line with the average over all industries, although the effect on employment is significantly lower. This is because of the relatively high labour intensity (and high earnings) of the creative industries, which generate below-average demand from suppliers, but normal levels of demand though expenditure from incomes. Drawing on these numbers and conclusions, we suggest some (slightly speculative) directions for future research. The goal is to better understand the contribution the creative sector makes to productivity growth; in particular, the distinctive contributions from creative firms and embedded creative workers. The ideas for future research can be organised into the several categories: • Understanding the categories of the creative sector– who is doing the business? In other words, examine via more fine grained research (at a firm level perhaps) just what is the creative contribution from the different aspects of the creative sector industries. It may be possible to categorise these in terms of more or less striking innovations. • Investigate the relationship between the characteristics and the performance of the various creative industries/ sectors; • Look more closely at innovation at an industry level e.g. using an index of relative growth of exports, and see if this can be related to intensity of use of creative inputs; • Undertake case studies of the creative sector; • Undertake case studies of the embedded contribution to growth in the firms and industries that employ them, by examining taking several high performing noncreative industries (in the same way as proposed for the creative sector). • Look at the aggregates – drawing on the broad picture of the extent of the numbers of creative workers embedded within the different industries, consider the extent to which these might explain aspects of the industries’ varied performance in terms of exports, growth and so on. • This might be able to extended to examine issues like the type of creative workers that are most effective when embedded, or test the hypothesis that each industry has its own particular requirements for embedded creative workers that overwhelms any generic contributions from say design, or IT.

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Much research has investigated the differences between option implied volatilities and econometric model-based forecasts. Implied volatility is a market determined forecast, in contrast to model-based forecasts that employ some degree of smoothing of past volatility to generate forecasts. Implied volatility has the potential to reflect information that a model-based forecast could not. This paper considers two issues relating to the informational content of the S&P 500 VIX implied volatility index. First, whether it subsumes information on how historical jump activity contributed to the price volatility, followed by whether the VIX reflects any incremental information pertaining to future jump activity relative to model-based forecasts. It is found that the VIX index both subsumes information relating to past jump contributions to total volatility and reflects incremental information pertaining to future jump activity. This issue has not been examined previously and expands our understanding of how option markets form their volatility forecasts.

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Estimates of the half-life to convergence of prices across a panel of cities are subject to bias from three potential sources: inappropriate cross-sectional aggregation of heterogeneous coefficients, presence of lagged dependent variables in a model with individual fixed effects, and time aggregation of commodity prices. This paper finds no evidence of heterogeneity bias in annual CPI data for 17 U.S. cities from 1918 to 2006, but correcting for the “Nickell bias” and time aggregation bias produces a half-life of 7.5 years, shorter than estimates from previous studies.