968 resultados para Richards’ growth models
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Long-run economic growth arouses a great interest since it can shed light on the income-path of an economy and try to explain the large differences in income we observe across countries and over time. The neoclassical model has been followed by several endogenous growth models which, contrarily to the former, seem to predict that economies with similar preferences and technological level, do not necessarily tend to converge to similar per capita income levels. This paper attempts to show a possible mechanismthrough which macroeconomic disequilibria and inefficiencies, represented by budget deficits, may hinder human capital accumulation and therefore economic growth. Using a mixed education system, deficit is characterized as a bug agent which may end up sharply reducing the resources devoted to education and training. The paper goes a step further from the literature on deficit by introducing a rich dynamic analysis of the effects of a deficit reduction on different economic aspects.Following a simple growth model and allowing for slight changes in the law of human capital accumulation, we reach a point where deficit might sharply reduce human capital accumulation. On the other hand, a deficit reduction carried on for a long time, taking that reduction as a more efficient management of the economy, may prove useful in inducing endogenous growth. Empirical evidence for a sample of countries seems to support the theoretical assumptions in the model: (1) evidence on an inverse relationship betweendeficit and human capital accumulation, (2) presence of a strongly negative associationbetween the quantity of deficit in the economy and the rate of growth. They may prove a certain role for budget deficit in economic growth
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[cat] Els models de creixement amb aprenentatge suposen que el coneixement après en producció es transmet de forma lliure i instantània a tota l'economia. En con- seqüència, l'economia presenta economies d'escala creixents i el creixement de la productivitat (TFP) és endògena. No obstant, el supòsit de difusió instantània del coneixement és poc realista. La difusió del coneixement necessita temps i algun canal de transmissió. En aquest article suposem que el coneixement es transmet amb la contractació de treballadors nous (learning-by-hiring). En el nostre model la difusió instantània i lliure de coneixement pot ocórrer només dins d'un sector. La difusió de coneixement entre sectors pot ocórrer només a través de la mobilitat de treballadors, i per tant, el mercat de treball determina el nivell i la taxa de creixement de productivitat (TFP). Estudiem com els costos de mobilitat laboral modifiquen l'equilibri sota dos escenaris: creixement endogen i exogen. A més, demostrem que d'altres ineficiències del mercat laboral, com són les taxes o els costos de cerca, poden reduir la mobilitat laboral, i per tant, modificar la TFP.
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[cat] Els models de creixement amb aprenentatge suposen que el coneixement après en producció es transmet de forma lliure i instantània a tota l'economia. En con- seqüència, l'economia presenta economies d'escala creixents i el creixement de la productivitat (TFP) és endògena. No obstant, el supòsit de difusió instantània del coneixement és poc realista. La difusió del coneixement necessita temps i algun canal de transmissió. En aquest article suposem que el coneixement es transmet amb la contractació de treballadors nous (learning-by-hiring). En el nostre model la difusió instantània i lliure de coneixement pot ocórrer només dins d'un sector. La difusió de coneixement entre sectors pot ocórrer només a través de la mobilitat de treballadors, i per tant, el mercat de treball determina el nivell i la taxa de creixement de productivitat (TFP). Estudiem com els costos de mobilitat laboral modifiquen l'equilibri sota dos escenaris: creixement endogen i exogen. A més, demostrem que d'altres ineficiències del mercat laboral, com són les taxes o els costos de cerca, poden reduir la mobilitat laboral, i per tant, modificar la TFP.
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Graphical tracking is a technique for crop scheduling where the actual plant state is plotted against an ideal target curve which encapsulates all crop and environmental characteristics. Management decisions are made on the basis of the position of the actual crop against the ideal position. Due to the simplicity of the approach it is possible for graphical tracks to be developed on site without the requirement for controlled experimentation. Growth models and graphical tracks are discussed, and an implementation of the Richards curve for graphical tracking described. In many cases, the more intuitively desirable growth models perform sub-optimally due to problems with the specification of starting conditions, environmental factors outside the scope of the original model and the introduction of new cultivars. Accurate specification for a biological model requires detailed and usually costly study, and as such is not adaptable to a changing cultivar range and changing cultivation techniques. Fitting of a new graphical track for a new cultivar can be conducted on site and improved over subsequent seasons. Graphical tracking emphasises the current position relative to the objective, and as such does not require the time consuming or system specific input of an environmental history, although it does require detailed crop measurement. The approach is flexible and could be applied to a variety of specification metrics, with digital imaging providing a route for added value. For decision making regarding crop manipulation from the observed current state, there is a role for simple predictive modelling over the short term to indicate the short term consequences of crop manipulation.
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Current forest growth models and yield tables are almost exclusively based on data from mature trees, reducing their applicability to young and developing stands. To address this gap, young European beech, sessile oak, Scots pine and Norway spruce trees approximately 0 to 10 years old were destructively sampled in a range of naturally regenerated forest stands in Central Europe. Diameter at base and height were first measured in situ for up to 175 individuals per species. Subsequently, the trees were excavated and dry biomass of foliage, branches, stems and roots was measured. Allometric relations were then used to calculate biomass allocation coefficients (BAC) and growth efficiency (GE) patterns in young trees. We found large differences in BAC and GE between broadleaves and conifers, but also between species within these categories. Both BAC and GE are strongly age-specific in young trees, their rapidly changing values reflecting different growth strategies in the earliest stages of growth. We show that linear relationships describing biomass allocation in older trees are not applicable in young trees. To accurately predict forest biomass and carbon stocks, forest growth models need to include species and age specific parameters of biomass allocation patterns.
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After more than forty years studying growth, there are two classes of growth models that have emerged: exogenous and endogenous growth models. Since both try to mimic the same set of long-run stylized facts, they are observationally equivalent in some respects. Our goals in this paper are twofold First, we discuss the time-series properties of growth models in a way that is useful for assessing their fit to the data. Second, we investigate whether these two models successfully conforms to U.S. post-war data. We use cointegration techniques to estimate and test long-run capital elasticities, exogeneity tests to investigate the exogeneity status of TFP, and Granger-causality tests to examine temporal precedence of TFP with respect to infrastructure expenditures. The empirical evidence is robust in confirming the existence of a unity long-run capital elasticity. The analysis of TFP reveals that it is not weakly exogenous in the exogenous growth model Granger-causality test results show unequivocally that there is no evidence that TFP for both models precede infrastructure expenditures not being preceded by it. On the contrary, we find some evidence that infras- tructure investment precedes TFP. Our estimated impact of infrastructure on TFP lay rougbly in the interval (0.19, 0.27).
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The initial endogenous growth models emphasized the importance of externaI effects in explaining sustainable growth across time. Empirically, this hypothesis can be confirmed if the coefficient of physical capital per hour is unity in the aggregate production function. Although cross-section results concur with theory, previous estimates using time series data rejected this hypothesis, showing a small coefficient far from unity. It seems that the problem lies not with the theory but with the techniques employed, which are unable to capture low frequency movements in high frequency data. This paper uses cointegration - a technique designed to capture the existence of long-run relationships in multivariate time series - to test the externalities hypothesis of endogenous growth. The results confirm the theory' and conform to previous cross-section estimates. We show that there is long-run proportionality between output per hour and a measure of capital per hour. U sing this result, we confmn the hypothesis that the implied Solow residual can be explained by government expenditures on infra-structure, which suggests a supply side role for government affecting productivity and a decrease on the extent that the Solow residual explains the variation of output.
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Initial endogenous growth models emphasized the importance of external effects and increasing retums in explaining growth. Empirically, this hypothesis can be confumed if the coefficient of physical capital per hour is unity in the aggregate production function. Previous estimates using time series data rejected this hypothesis, although cross-country estimates did nol The problem lies with the techniques employed, which are unable to capture low-frequency movements of high-frequency data. Using cointegration, new time series evidence confum the theory and conform to cross-country evidence. The implied Solow residual, which takes into account externaI effects to aggregate capital, has its behavior analyzed. The hypothesis that it is explained by government expenditures on infrasttucture is confIrmed. This suggests a supply-side role for government affecting productivity.
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The aim of this article is to assess the role of real effective exchange rate volatility on long-run economic growth for a set of 82 advanced and emerging economies using a panel data set ranging from 1970 to 2009. With an accurate measure for exchange rate volatility, the results for the two-step system GMM panel growth models show that a more (less) volatile RER has significant negative (positive) impact on economic growth and the results are robust for different model specifications. In addition to that, exchange rate stability seems to be more important to foster long-run economic growth than exchange rate misalignment
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How do the liquidity functions of banks affect investment and growth at different stages of economic development? How do financial fragility and the costs of banking crises evolve with the level of wealth of countries? We analyze these issues using an overlapping generations growth model where agents, who experience idiosyncratic liquidity shocks, can invest in a liquid storage technology or in a partially illiquid Cobb Douglas technology. By pooling liquidity risk, banks play a growth enhancing role in reducing inefficient liquidation of long term projects, but they may face liquidity crises associated with severe output losses. We show that middle income economies may find optimal to be exposed to liquidity crises, while poor and rich economies have more incentives to develop a fully covered banking system. Therefore, middle income economies could experience banking crises in the process of their development and, as they get richer, they eventually converge to a financially safe long run steady state. Finally, the model replicates the empirical fact of higher costs of banking crises for middle income economies.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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A utilização de funções matemáticas para descrever o crescimento animal é antiga. Elas permitem resumir informações em alguns pontos estratégicos do desenvolvimento ponderal e descrever a evolução do peso em função da idade do animal. Também é possível comparar taxas de crescimento de diferentes indivíduos em estados fisiológicos equivalentes. Os modelos de curvas de crescimento mais utilizados na avicultura são os derivados da função Richards, pois apresentam parâmetros que possibilitam interpretação biológica e portanto podem fornecer subsídios para seleção de uma determinada forma da curva de crescimento em aves. Também pode-se utilizar polinômios segmentados para descrever as mudanças de tendência da curva de crescimento animal. Entretanto, existem importantes fatores de variação para os parâmetros das curvas, como a espécie, o sistema de criação, o sexo e suas interações. A adequação dos modelos pode ser verificada pelos valores do coeficiente de determinação (R2), do quadrado médio do resíduo (QM res), do erro de predição médio (EPm), da facilidade de convergência dos dados e pela possibilidade de interpretação biológica dos parâmetros. Estudos envolvendo modelagem e descrição da curva de crescimento e seus componentes são amplamente discutidos na literatura. Porém, programas de seleção que visem a progressos genéticos para a forma da curva não são mencionados. A importância da avaliação dos parâmetros dos modelos de curvas de crescimento é ainda mais relevante já que os maiores ganhos genéticos para peso estão relacionados com seleção para pesos em idades próximas ao ponto de inflexão. A seleção para precocidade pode ser auxiliada com base nos parâmetros do modelo associados à variáveis que descrevem esta característica genética dos animais. Esses parâmetros estão relacionados a importantes características produtivas e reprodutivas e apresentam magnitudes diferentes, de acordo com a espécie, o sexo e o modelo utilizados na avaliação. Outra metodologia utilizada são os modelos de regressão aleatória, permitindo mudanças graduais nas covariâncias entre idades ao longo do tempo e predizendo variâncias e covariâncias em pontos contidos ao longo da trajetória estudada. A utilização de modelos de regressões aleatórias traz como vantagem a separação da variação da curva de crescimento fenotípica em seus diferentes efeitos genético aditivo e de ambiente permanente individual, mediante a determinação dos coeficientes de regressão aleatórios para esses diferentes efeitos. Além disto, não há necessidade de utilizar fatores de ajuste para a idade. Esta revisão teve por objetivos levantar os principais modelos matemáticos frequentistas utilizados no estudo de curvas de crescimento de aves, com maior ênfase nos empregados com a finalidade de estimar parâmetros genéticos e fenotípicos.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Includes bibliography
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Includes bibliography