947 resultados para Growth Models (economics)
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Double Degree. A Work Project presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA- School of Business and Economics and a Masters Degree in Management from Louvain School of Management
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The real convergence hypothesis has spurred a myriad of empirical tests and approaches in the economic literature. This Work Project intends to test for real output and growth convergence in all N(N-1)/2 possible pairs of output and output growth gaps of 14 Eurozone countries. This paper follows a time-series approach, as it tests for the presence of unit roots and persistence changes in the above mentioned pairs of output gaps, as well as for the existence of growth convergence with autoregressive models. Overall, significantly greater evidence has been found to support growth convergence rather than output convergence in our sample.
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Kinetic models have a great potential for metabolic engineering applications. They can be used for testing which genetic and regulatory modifications can increase the production of metabolites of interest, while simultaneously monitoring other key functions of the host organism. This work presents a methodology for increasing productivity in biotechnological processes exploiting dynamic models. It uses multi-objective dynamic optimization to identify the combination of targets (enzymatic modifications) and the degree of up- or down-regulation that must be performed in order to optimize a set of pre-defined performance metrics subject to process constraints. The capabilities of the approach are demonstrated on a realistic and computationally challenging application: a large-scale metabolic model of Chinese Hamster Ovary cells (CHO), which are used for antibody production in a fed-batch process. The proposed methodology manages to provide a sustained and robust growth in CHO cells, increasing productivity while simultaneously increasing biomass production, product titer, and keeping the concentrations of lactate and ammonia at low values. The approach presented here can be used for optimizing metabolic models by finding the best combination of targets and their optimal level of up/down-regulation. Furthermore, it can accommodate additional trade-offs and constraints with great flexibility.
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The use of genome-scale metabolic models has been rapidly increasing in fields such as metabolic engineering. An important part of a metabolic model is the biomass equation since this reaction will ultimately determine the predictive capacity of the model in terms of essentiality and flux distributions. Thus, in order to obtain a reliable metabolic model the biomass precursors and their coefficients must be as precise as possible. Ideally, determination of the biomass composition would be performed experimentally, but when no experimental data are available this is established by approximation to closely related organisms. Computational methods however, can extract some information from the genome such as amino acid and nucleotide compositions. The main objectives of this study were to compare the biomass composition of several organisms and to evaluate how biomass precursor coefficients affected the predictability of several genome-scale metabolic models by comparing predictions with experimental data in literature. For that, the biomass macromolecular composition was experimentally determined and the amino acid composition was both experimentally and computationally estimated for several organisms. Sensitivity analysis studies were also performed with the Escherichia coli iAF1260 metabolic model concerning specific growth rates and flux distributions. The results obtained suggest that the macromolecular composition is conserved among related organisms. Contrasting, experimental data for amino acid composition seem to have no similarities for related organisms. It was also observed that the impact of macromolecular composition on specific growth rates and flux distributions is larger than the impact of amino acid composition, even when data from closely related organisms are used.
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Dissertação de mestrado em Bioquímica (área de especialização em Biomedicina)
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Plaice (Pleuronectes platessa, L.) and dab (Limanda limanda, L.) are among the most abundant flatfishes in the north-eastern Atlantic region and the dominant species in shallow coastal nursery grounds. With increasing pressures on commercial flatfish stocks in combination with changing coastal environments, better knowledge of population dynamics during all life stages is needed to evaluate variability in year-class strength and recruitment to the fishery. The aim of this research was to investigate the complex interplay of biotic and abiotic habitat components influencing the distribution, density and growth of plaice and dab during the vulnerable juvenile life stage and to gain insight in spatial and temporal differences in nursery habitat quality along the west coast of Ireland. Intraspecific variability in plaice diet was observed at different spatial scales and showed a link with condition, recent growth and morphology. This highlights the effect of food availability on habitat quality and the need to consider small scale variation when attempting to link habitat quality to feeding, growth and condition of juvenile flatfish. There was evidence of trophic, spatial and temporal resource partitioning between juvenile plaice and dab allowing the co-existence of morphologically similar species in nursery grounds. In the limited survey years there was no evidence that the carrying capacity of the studied nursery grounds was reached but spatial and interannual variations in fish growth indicated fluctuating environments in terms of food availability, predator densities, sediment features and physico-chemical conditions. Predation was the most important factor affecting habitat quality for juvenile plaice and dab with crab densities negatively correlated to fish condition whereas shrimp densities were negatively associated with densities of small-sized juveniles in spring. A comparison of proxies for fish growth showed the advantage of Fulton’s K for routine use whereas RNA:DNA ratios proved less powerful when short-term environmental fluctuations are lacking. This study illustrated how distinct sets of habitat features can drive spatial variation in density and condition of juvenile flatfish highlighting the value of studying both variables when modeling habitat requirements. The habitat models generated in this study also provide a powerful tool to predict potential climate and anthropogenic impacts on the distribution and condition of juveniles in flatfish nurseries. The need for effective coastal zone management was emphasized to ensure a sustainable use of coastal resources and successful flatfish recruitment to the fishery.
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The age, growth, maturity and population dynamics of lemon sole (Microstomus kitt), captured off the west coast of Ireland (ICES division Vllb), were determined for the period November 2000 to February 2002. The maximum age recorded was 14 years. Males of the population were dominated by 4 year olds, while females were dominated by 5 year olds. Females dominated the sex ratio in the overall sample, each month sampled, at each age and from 22cm in total length onwards (when N > 20). Possible reasons for the dominance of females in the sex ratio are discussed. Three models were used to obtain the parameters of the von Bertalanfly growth equation. These were the Ford-Walford plot (Beverton and Holt 1957), the Gulland and Holt plot (1959) and the Rafail (1973) method. Results of the fitted von Bertalanffy growth curves showed that female lemon sole o f f the west coast of Ireland grew faster than males and attained a greater size. Male and female lemon sole mature from 2 years of age onwards. There is evidence in the population o f a smaller asymptotic length (L«, = 34.47cm), faster growth rate (K = 0.1955) and younger age at first maturity, all of which are indicative o f a decrease in population size, when present results are compared to data collected in the same area 22 years earlier. Results of the yield per recruit curve indicate that lemon sole are currently being over-fished o f f the west coast of Ireland. Problems of selectivity within the sampling method, particularly at the discarding stage, may have influenced the outcome of results of the models used in the assessment of this stock. Therefore, additional/future work on this species should include catch data which incorporates discards and not landings data alone.
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Ecological economics is a recently developed field, which sees the economy as a subsystem of a larger finite global ecosystem. Ecological economists question the sustainability of the economy because of its environmental impacts and its material and energy requirements, and also because of the growth of population. Attempts at assigning money values to environmental services and losses, and attempts at correcting macroeconomic accounting, are part of ecological economics, but its main thrust is rather in developing physical indicators and indexes of sustainability. Ecological economists also work on the relations between property rights and resource management, they model the interactions between the economy and the environment, they study ecological distribution conflicts, they use management tools such as integrated environmental assessment and multi-criteria decision aids, and they propose new instruments of environmental policy.
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We study the relation between public capital, employment and growth under different assumptions concerning wage formation. We show that public capital increases economic growth, and that, if there is wage inertia, employment positively depends on both economic growth and public capital.
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This paper studies the effects of different types of research policy on economic growth. We find that while tax incentives to private research, public funding of private projects, and basic research performed at public institutions have unambiguously positive effects on economic growth, performing applied research at public institutions could have negative growth effects. This is due to the large crowding out of private research caused by public R\&D when it competes with private firms in the "patent race". Concerning the effects of these policies on welfare, it is found that research policy can either improve or reduce consumer welfare depending on the characteristics of the policy and that an excessively high research subsidy will reduce it.
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This paper presents an endogenous growth model in which the research activity is financed by intermediaries that are able to reduce the incidence of researcher's moral hazard. It is shown that financial activity is growth promoting because it increases research productivity. It is also found that a subsidy to the financial sector may have larger growth effects than a direct subsidy to research. Moreover, due to the presence of moral hazard, increasing the subsidy rate to R\&D may reduce the growth rate. I show that there exists a negative relation between the financing of innovation and the process of capital accumulation. Concerning welfare, the presence of two externalities of opposite sign steaming from financial activity may cause that the no-tax equilibrium provides an inefficient level of financial services. Thus, policies oriented to balance the effects of the two externalities will be welfare improving.
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The objective of this paper is to measure the impact of different kinds of knowledge and external economies on urban growth in an intraregional context. The main hypothesis is that knowledge leads to growth, and that this knowledge is related to the existence of agglomeration and network externalities in cities. We develop a three-tage methodology: first, we measure the amount and growth of knowledge in cities using the OCDE (2003) classification and employment data; second, we identify the spatial structure of the area of analysis (networks of cities); third, we combine the Glaeser - Henderson - De Lucio models with spatial econometric specifications in order to contrast the existence of spatially static (agglomeration) and spatially dynamic (network) external economies in an urban growth model. Results suggest that higher growth rates are associated to higher levels of technology and knowledge. The growth of the different kinds of knowledge is related to local and spatial factors (agglomeration and network externalities) and each knowledge intensity shows a particular response to these factors. These results have implications for policy design, since we can forecast and intervene on local knowledge development paths.