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1. |
Record Nr. |
UNINA9910786883503321 |
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Titolo |
Capital for the future : : saving and investment in an interdependent world |
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Pubbl/distr/stampa |
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Washington, D.C., : , : World Bank, , [2013] |
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copyright 2013 |
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ISBN |
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Descrizione fisica |
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xv, 149 pages : illustrations (color), maps; ; 27 cm |
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Collana |
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Global development horizons, , 2221-8416 |
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Disciplina |
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Soggetti |
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Saving and investment |
Investments |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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Cover; Contents; Foreword; Acknowledgments; Abbreviations; OVERVIEW; Outlooks under the two scenarios; Figures; O.1 Future global saving and investment rates will remain fairly stable in the gradual convergence scenario, but this stability belies substantial shifts in the relative shares of developing and high-income countries; O.2 Developing countries will represent more than half of global capital stocks by 2030 in the gradual convergence scenario, compared with about a third in 2010; O.3 Increased earning power will be the greatest driver of saving by Mexican households |
O.4 Annual infrastructure needs over the next 20 years are likely to be greatest in East and South Asia O.5 By 2030, nearly half or more of gross capital inflows will likely go to developing countries; Modeling the global dynamics of investment, saving, and capital flows; O.6 Schematic diagram describing interactions between saving, investment demand, and investment financing; Note; References; CHAPTER 1: The Emerging Pattern of Global Investment; Changing patterns of investment worldwide |
1.1 Gross investment in developing countries has increased in absolute terms (panel a) and as a share of global investment (panel b)Boxes; 1.1 Different terms, different rates: Purchasing-power adjusted investment vs. investment expressed in national currency; B1.1.1 Differentials in investment rates (panel a) and capital-output ratios (panel b) are |
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greater when measured in PPP terms; 1.2 Developing countries' rising investment rates (panel a) and growing share of global output (panel b) have contributed to their increased share of investment in global output |
1.3 The rising share of developing countries' investment in global output is due to more than just changes in China and India 1.2 Investment booms are not always associated with sustained growth; 1.4 Investment rates among Sub-Saharan African countries of different income levels have followed distinct paths; Tables; B1.2.1 Investment booms have occurred in a broad range of developing and high-income countries; B1.2.1 Many countries experience weak growth following an investment boom |
1.5 Global manufacturing investment tends to be concentrated in lower-middle-income countries (panel a), with China currently accounting for the vast majority of investment in those countries (panel b)1.1 There is significant heterogeneity in marginal products of capital, at both economy wide and sectoral levels, across developing countries; 1.6 The public sector share of output is lower in high-income countries than in other country groups (panel a), but the public sector share of investment has converged among country groups (panel b) |
1.7 Private sector commitments to infrastructure have risen over time, both in major developing countries (panel a) and across most infrastructure subsectors (panel b) |
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Sommario/riassunto |
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The gradual acceleration of growth in developing countries is a defining feature of the past two decades. This acceleration came with major shifts in patterns of investment, saving, and capital flows. This second volume in the Global Development Horizons series analyzes these shifts and explores how they may evolve through 2030.Average domestic saving in developing countries stood at 34 percent of their GDP in 2010, up from 24 percent in 1990, while their investment was around 33 percent of their GDP in 2012, up from 26 percent. These trends in saving and investment, along with higher growth r |
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2. |
Record Nr. |
UNINA9910746093603321 |
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Autore |
Jastrzębska Agnieszka |
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Titolo |
Analysing Web Traffic : A Case Study on Artificial and Genuine Advertisement-Related Behaviour / / by Agnieszka Jastrzębska, Jan W. Owsiński, Karol Opara, Marek Gajewski, Olgierd Hryniewicz, Mariusz Kozakiewicz, Sławomir Zadrożny, Tomasz Zwierzchowski |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
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ISBN |
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Edizione |
[1st ed. 2023.] |
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Descrizione fisica |
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1 online resource (173 pages) |
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Collana |
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Studies in Big Data, , 2197-6511 ; ; 127 |
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Altri autori (Persone) |
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OwsińskiJ. W (Jan W.) |
OparaKarol |
GajewskiMarek |
HryniewiczOlgierd |
KozakiewiczMariusz |
ZadrożnySławomir |
ZwierzchowskiTomasz |
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Disciplina |
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Soggetti |
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Engineering - Data processing |
Computational intelligence |
Big data |
Data Engineering |
Computational Intelligence |
Big Data |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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The problem and its key characteristics -- The pragmatics of the data acquisition and assessment -- The proper representation: patterns, variables and their analysis -- Clustering analysis -- Building the classifiers -- The hybrid cluster-and-classify approach -- A summary view of the problem and its solution. |
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Sommario/riassunto |
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This book presents ample, richly illustrated account on results and experience from a project, dealing with the analysis of data concerning behavior patterns on the Web. The advertising on the Web is dealt with, and the ultimate issue is to assess the share of the artificial, automated |
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activity (ads fraud), as opposed to the genuine human activity. After a comprehensive introductory part, a full-fledged report is provided from a wide range of analytic and design efforts, oriented at: the representation of the Web behavior patterns, formation and selection of telling variables, structuring of the populations of behavior patterns, including the use of clustering, classification of these patterns, and devising most effective and efficient techniques to separate the artificial from the genuine traffic. A series of important and useful conclusions is drawn, concerning both the nature of the observed phenomenon, and hence the characteristics of the respective datasets, and theappropriateness of the methodological approaches tried out and devised. Some of these observations and conclusions, both related to data and to methods employed, provide a new insight and are sometimes surprising. The book provides also a rich bibliography on the main problem approached and on the various methodologies tried out. |
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