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Libros sobre el tema "Population Growth Model"

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Publicado: 6 de septiembre de 2023

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1

Yeung, David. A stochastic growth model with endogenous population growth rate. Toronto: York University, 1985.

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2

M. C. M. de Gunst. A random model for plant cell population growth. [Amsterdam, the Netherlands]: Centrum voor Wiskunde en Informatica, 1989.

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3

The optimum growth rate for population in the neoclassical overlapping generations model. Frankfurt am Main: Peter Lang, 2007.

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4

Brylinsky, M. Development of a computer simulation model of a cultured blue mussel (Mytilus edulis) population. Moncton, N.B: Dept. of Fisheries and Oceans, Science Branch, Gulf Region, 1991.

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5

Ratner, Svetlana, Liliya Nazarova, Kasiya Kirdasinova y Anna Karapetyan. Circular model of economic growth: experience, opportunities and barriers. ru: INFRA-M Academic Publishing LLC., 2022. http://dx.doi.org/10.12737/1893194.

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The concept of a circular (or circular/closed cycle) economy is quite new for the Russian scientific literature on economics and management. Having originated initially in countries experiencing serious resource constraints and (or) acute environmental problems, a few months ago it seemed to be a curious idea for Russia, allowing in the long term to achieve simultaneous preservation and even an increase in economic growth rates without the concomitant increase in the expenditure of natural resources and the inevitably associated increase in the burden on the environment. However, the dramatically changed economic situation due to unprecedented sanctions pressure, the freezing of the country's financial resources and the destruction of a huge number of production chains forces us to take a fresh look at the concept of a circular economy and shift the focus of research on its possible practical applications from environmental aspects to such topical economic aspects as creating new jobs, products and services, preserving the quality of life of the population while decrease in purchasing power, etc. A feature of the monograph is the focus on new opportunities for economic growth that the circular economy provides, even in conditions of severe resource (including financial) constraints. It is intended for students, masters, postgraduates, researchers, as well as practitioners from the field of management with modern circular business models and methods of organizing production and consumption processes according to the circular type.
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6

Filling up America: An economic-demographic model of population growth and distribution in the nineteenth-century United States. Greenwich, Conn: JAI Press, 1986.

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7

Associates, Dick Conway &. Puget Sound subarea forecasts: Model calibration and forecasts. [Seattle?: Puget Sound Regional Council?, 1992.

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8

Theory of population and economic growth. Oxford: Blackwell, 1986.

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9

Golosov, Mikhail. Efficiency with endogenous population growth. Cambridge, MA: National Bureau of Economic Research, 2004.

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10

Golosov, Mikhail. Efficiency with endogenous population growth. [Minneapolis, MN]: Federal Reserve Bank of Minneapolis, Research Dept., 2004.

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11

Golosov, Mikhail. Efficiency with endogenous population growth. Cambridge, Mass: National Bureau of Economic Research, 2004.

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12

Lakshmana, C. M. Changing child population: Growth, trends and levels in Karnataka. Bangalore: Institute for Social and Economic Change, 2008.

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13

Institute for Social and Economic Change., ed. Changing child population: Growth, trends and levels in Karnataka. Bangalore: Institute for Social and Economic Change, 2008.

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14

Optimal economic growth and non-stable population. Berlin: Springer-Verlag, 1989.

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15

Planning, Maryland Office of. Managing Maryland's growth: Models and guidelines : sizing and shaping growth areas. [Baltimore, MD]: Maryland Office of Planning, 1998.

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16

Chamon, Marcos. Economic transformation, population growth, and long-run world income distribution. [Washington, D.C.]: International Monetary Fund, Research Dept., 2006.

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17

Chamon, Marcos. Economic transformation, population growth and the long-run world income distribution. Cambridge, Mass: National Bureau of Economic Research, 2006.

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18

Jones, Charles I. Population and ideas: A theory of endogenous growth. Cambridge, MA: National Bureau of Economic Research, 1997.

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19

Chi-Hsien, Tuan y Yü Ching-yüan 1937-, eds. Population control in China: Theory and applications. New York: Praeger, 1985.

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20

1955-, Bloom David E. y National Bureau of Economic Research., eds. Does age structure forecast economic growth? Cambridge, Mass: National Bureau of Economic Research, 2007.

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21

Galor, Oded. Population, technology, and growth: From the Malthusian regime to the demographic transition. Cambridge, MA: National Bureau of Economic Research, 1998.

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22

Nowlan, David M. The effect of downtown population growth on commuting trips: Some recent Toronto experience. [Toronto]: Program in Planning, University of Toronto, 1990.

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23

Hazan, Moshe. Child labor, fertility, and economic growth. [Jerusalem]: The Maurice Falk Institute for Economic Research in Israel, 1999.

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24

Williamson, Jeffrey G. Growth, distribution and demography: Some lessons from history. Cambridge, MA: National Bureau of Economic Research, 1997.

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25

Sonja, Munz y Gács Vera, eds. Fertility and prosperity: Links between demography and economic growth. München: Ifo Institute for Economic Research at the University of Munich, Dept. of Social Policy and Labour Markets, 2008.

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26

Henry, Mullally, ed. Urban evolution: Studies in the mathematical ecology of cities. Oxford [Oxfordshire]: Oxford University Press, 1985.

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27

Capital accumulation and economic growth in a small open economy. Cambridge: Cambridge University Press, 2009.

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28

Ehrlich, Isaac. Endogenous fertility, mortality, and economic growth: Can a malthusian framework account for the conflicting historical trends in population? Cambridge, MA: National Bureau of Economic Research, 2005.

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29

S, Madheswaran, ed. Technological progress, scale effect, and total factor productivity growth in Indian cement industry: Panel estimation of stochastic production frontier. Bangalore: Institute for Social and Economic Change, 2009.

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30

Keyfitz, Nathan y David P. Smith. Mathematical demography: Selected papers. Editado por Wachter Kenneth W. editor y Le Bras, Hervé, 1943- editor. Berlin: Springer, 2013.

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31

Portugali, Juval. Complexity Theories of Cities Have Come of Age: An Overview with Implications to Urban Planning and Design. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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32

V, Bazarov B., ed. Problemnye regiony resursnogo tipa: Aziatskai︠a︡ chastʹ Rossii. Novosibirsk: Izd-vo Sibirskogo otd-nii︠a︡ Rossiĭskoĭ akademii nauk, 2005.

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33

Gruescu, Sandra. Population Ageing and Economic Growth: Education Policy and Family Policy in a Model of Endogenous Growth. Springer London, Limited, 2007.

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34

Population Ageing and Economic Growth: Education Policy and Family Policy in a Model of Endogenous Growth (Contributions to Economics). Physica-Verlag Heidelberg, 2006.

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35

Whitmore, Harland William. World Economy, Population Growth, and the Global Ecosystem: A Unified Theoretical Model of Interdependent Dynamic Systems. Palgrave Macmillan, 2010.

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36

Whitmore, H. World Economy, Population Growth, and the Global Ecosystem: A Unified Theoretical Model of Interdependent Dynamic Systems. Palgrave Macmillan Limited, 2007.

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37

The World Economy, Population Growth, and the Global Ecosystem: A Unified Theoretical Model of Interdependent Dynamic Systems. Palgrave Macmillan, 2007.

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38

Whitmore, H. The World Economy, Population Growth, and the Global Ecosystem: A Unified Theoretical Model of Interdependent Dynamic Systems. Palgrave Macmillan, 2008.

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39

Cuenco, Michael L. A model of fish bioenergetics and growth at the organismal and population levels in laboratory and pond environments. 1985.

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40

Economic Analyses Using The Overlapping Generations Model And General Equilibrium Growth Accounting For The Japanese Economy Population Agriculture And Economic Development. World Scientific Publishing Co Pte Ltd, 2014.

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41

Pandey, Himanshu. Population Growth and Migration Models. Radha Publications, 1993.

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42

Faust, Lisa J., Claudine André, Raphaël Belais, Fanny Minesi, Zjef Pereboom, Kerri Rodriguez y Brian Hare. Bonobo population dynamics: Past patterns and future predictions for the Lola ya Bonobo population using demographic modelling. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198728511.003.0018.

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Wildlife sanctuaries rescue, rehabilitate, reintroduce and provide life-long care for orphaned and injured animals. Understanding a sanctuary’s population dynamics—patterns in arrival, mortality and projected changes in population size—allows careful planning for future needs. Building on previous work on the population dynamics of chimpanzees (Pan troglodytes) in sanctuaries of the Pan African Sanctuary Alliance (PASA; Faust et al. 2011), this chapter extends analyses to the only PASA bonobo sanctuary. Its authors analysed historic demographic patterns and projected future population dynamics using an individual-based demographic model. The population has been growing at 6.7 per cent per year, driven by arrivals of new individuals (mean = 5.5 arrivals per year). Several model scenarios projecting varying arrival rates, releases and breeding scenarios clarify potential future growth trajectories for the sanctuary. This research illustrates how data on historic dynamics can be modelled to inform future sanctuary capacity and management needs. Les sanctuaires de faune secourent, réhabilitent, réintroduisent, et fournissent des soins pour toute la vie aux animaux orphelins et blessés. Comprendre les dynamiques de la population d’un sanctuaire—les motifs d’arrivée, mortalité, et de changements projetés de la taille de la population—permet une planification prudente pour les nécessités du futur. En se basant sur le travail déjà fait sur les dynamiques de la population chimpanzé (Pan troglodytes) dans les sanctuaires du Pan African Sanctuary Alliance (PASA; Faust et al. 2011), nous étendons notre analyse au seul sanctuaire bonobo par PASA. Nous avons analysé les motifs démographiques historiques et avons projeté les futures dynamiques de la population en utilisant un modèle démographique basé sur l’individu. La population augmente de 6.7 per cent par an, poussée par l’arrivée de nouveaux individus (moyenne = 5.5 arrivées par an). Plusieurs scénarios modèles montrent une trajectoire de potentielle croissance pour le sanctuaire. Cette recherche illustre comment modeler les données sur les dynamiques historiques pour informer la capacité future du sanctuaire et les besoins gestionnaires.
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43

Weber, Lars. Demographic Change and Economic Growth: Simulations on Growth Models. Springer London, Limited, 2010.

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44

Weber, Lars. Demographic Change and Economic Growth: Simulations on Growth Models. Brand: Physica, 2012.

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45

Gruescu, Sandra. Population Ageing and Economic Growth. Springer, 2008.

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46

Salverda, Wiemer y Stefan Thewissen. How Has the Middle Fared in the Netherlands? A Tale of Stagnation and Population Shifts. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198807032.003.0009.

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This chapter sets out how inequality and real incomes across the distribution evolved in the Netherlands from the late 1970s through the economic Crisis. Inequality grew, though not dramatically, while wages showed remarkably little real increase. This meant that real income increases for households relied for the most part on the growth in female labour-force participation and in dual-income couples. The chapter highlights the major changes in population and household structures that underpinned the observed changes in household incomes at different points in the distribution. It also sets out key features of the institutional structures in the labour market and broader welfare state, and the centrality of the priority given to wage moderation and the maintenance of competitiveness in the growth model adopted throughout the period.
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47

Weber, Lars. Demographic Change and Economic Growth. Springer, 2010.

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48

Imhoff, E. van. Optimal Economic Growth and Non-Stable Population. Springer London, Limited, 2012.

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49

Demographic Change And Economic Growth Simulations On Growth Models. Physica-Verlag HD, 2010.

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50

Gelfand, Alan y Sujit K. Sahu. Models for demography of plant populations. Editado por Anthony O'Hagan y Mike West. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198703174.013.17.

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This article discusses the use of Bayesian analysis and methods to analyse the demography of plant populations, and more specifically to estimate the demographic rates of trees and how they respond to environmental variation. It examines data from individual (tree) measurements over an eighteen-year period, including diameter, crown area, maturation status, and survival, and from seed traps, which provide indirect information on fecundity. The multiple data sets are synthesized with a process model where each individual is represented by a multivariate state-space submodel for both continuous (fecundity potential, growth rate, mortality risk, maturation probability) and discrete states (maturation status). The results from plant population demography analysis demonstrate the utility of hierarchical modelling as a mechanism for the synthesis of complex information and interactions.
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