Os dois métodos e o núcleo duro da teoria econômica

While methodological sciences have no object and are supposed to adopt a hypothetical-deductive method, substantive sciences including economics should use an empirical or historical-deductive method. The great classical economists and Keynes did that and were able to develop open models explaining how equally open economic systems work. Thus, the hard core of relevant economics is formed by the classical microeconomics and the classical theory of capitalist economic growth, and by Keynesian macroeconomics. In contrast, neoclassical economist aiming to build a mathematical science wrongly adopted the hypothetical-deductive method, and came to macroeconomic and growth models that do not have practical use in policymaking. The exception is Marshall's microeconomics that does not provide a model of real economic systems, but is useful to the analysis of markets.

Ciência econômica e modelos de explicação científica: retomando a questão

Economic science and scientific explanation models. Economics was born under the sign of methodological vagueness. The first author who tried to solve the question (John Stuart Mill) asserted that it is a kind of knowledge that uses the abstract (direct deductive) method but also that it is an exception because for all other phenomena in the field of moral science the correct method is the inverse deductive or historical method. On the other side, functionalist explanations that are condemned by the scientific precepts of economics are present in the science since its beginning with Adam Smith. Economics went ahead without worriment about these methodological issues but this indefiniteness has never gone off stage. Since the start of XXI century new facts are emerging. Developments in Psychology are giving a new breath to Friedman's point of view and seem to fortify the mainstream (Rogebert e Nordberg, 2005), whereas unfolding in complexity science promises to throw it down and put in its place another kind of explanation borrowed from Biology (Beinhocker, 2006). All this stimulates to retake the question. We do this here, under a critical vision, taking the taxonomy of scientific explanations framed by modern positivism.

A taxa de câmbio real e a restrição externa: uma proposta de releitura com elasticidades endógenas

This paper investigates a topic of the agenda about growth models, emphasizing the elaboration of an external constrained model with endogenous elasticity, with an emphasis on real exchange rate level as main tool for the economic development. The model is anchored in Kaldor, Thirlwall and Barbosa Filho's models and it will demonstrate that external constraint changes in the course of time.

From restrained golden age to creeping platinum age: A periodization of Latin American development in the Robinsonian tradition

ABSTRACTThis paper analyzes Joan Robinson's growth model, and then adapted in order to provide an exploratory taxonomy of Growth Eras. The Growth Eras or Ages were for Robinson a way to provide logical connections among output growth, capital accumulation, the degree of thriftiness, the real wage and illustrate a catalogue of growth possibilities. This modified taxonomy follows the spirit of Robinson's work, but it takes different theoretical approaches, which imply that some of her classifications do not fit perfectly the ones here suggested. Latin America has moved from a Golden Age in the 1950s and 1960s, to a Leaden Age in the 1980s, having two traverse periods, one in which the process of growth and industrialization accelerated in the late 1960s and early 1970s, which is here referred to as a Galloping Platinum Age, and one in which a process of deindustrialization, and reprimarization and maquilization of the productive structure took place, starting in the 1990s, which could be referred to as a Creeping Platinum Age.

Use of Poisson spatiotemporal regression models for the Brazilian Amazon Forest: malaria count data

INTRODUCTION: Malaria is a serious problem in the Brazilian Amazon region, and the detection of possible risk factors could be of great interest for public health authorities. The objective of this article was to investigate the association between environmental variables and the yearly registers of malaria in the Amazon region using Bayesian spatiotemporal methods. METHODS: We used Poisson spatiotemporal regression models to analyze the Brazilian Amazon forest malaria count for the period from 1999 to 2008. In this study, we included some covariates that could be important in the yearly prediction of malaria, such as deforestation rate. We obtained the inferences using a Bayesian approach and Markov Chain Monte Carlo (MCMC) methods to simulate samples for the joint posterior distribution of interest. The discrimination of different models was also discussed. RESULTS: The model proposed here suggests that deforestation rate, the number of inhabitants per km², and the human development index (HDI) are important in the prediction of malaria cases. CONCLUSIONS: It is possible to conclude that human development, population growth, deforestation, and their associated ecological alterations are conducive to increasing malaria risk. We conclude that the use of Poisson regression models that capture the spatial and temporal effects under the Bayesian paradigm is a good strategy for modeling malaria counts.

Calibration of the century, apsim and ndicea models of decomposition and n mineralization of plant residues in the humid tropics

The aim of this study was to calibrate the CENTURY, APSIM and NDICEA simulation models for estimating decomposition and N mineralization rates of plant organic materials (Arachis pintoi, Calopogonium mucunoides, Stizolobium aterrimum, Stylosanthes guyanensis) for 360 days in the Atlantic rainforest bioma of Brazil. The models´ default settings overestimated the decomposition and N-mineralization of plant residues, underlining the fact that the models must be calibrated for use under tropical conditions. For example, the APSIM model simulated the decomposition of the Stizolobium aterrimum and Calopogonium mucunoides residues with an error rate of 37.62 and 48.23 %, respectively, by comparison with the observed data, and was the least accurate model in the absence of calibration. At the default settings, the NDICEA model produced an error rate of 10.46 and 14.46 % and the CENTURY model, 21.42 and 31.84 %, respectively, for Stizolobium aterrimum and Calopogonium mucunoides residue decomposition. After calibration, the models showed a high level of accuracy in estimating decomposition and N- mineralization, with an error rate of less than 20 %. The calibrated NDICEA model showed the highest level of accuracy, followed by the APSIM and CENTURY. All models performed poorly in the first few months of decomposition and N-mineralization, indicating the need of an additional parameter for initial microorganism growth on the residues that would take the effect of leaching due to rainfall into account.

Liming in Agricultural Production Models with and Without the Adoption of Crop-Livestock Integration

ABSTRACT Perennial forage crops used in crop-livestock integration (CLI) are able to accumulate large amounts of straw on the soil surface in no-tillage system (NTS). In addition, they can potentially produce large amounts of soluble organic compounds that help improving the efficiency of liming in the subsurface, which favors root growth, thus reducing the risks of loss in yield during dry spells and the harmful effects of “overliming”. The aim of this study was to test the effects of liming on two models of agricultural production, with and without crop-livestock integration, for 2 years. Thus, an experiment was conducted in a Latossolo Vermelho (Oxisol) with a very clayey texture located in an agricultural area under the NTS in Bandeirantes, PR, Brazil. Liming was performed to increase base saturation (V) to 65, 75, and 90 % while one plot per block was maintained without the application of lime (control). A randomized block experimental design was adopted arranged in split-plots and four plots/block, with four replications. The soil properties evaluated were: pH in CaCl2, soil organic matter (SOM), Ca, Mg, K, Al, and P. The effects of liming were observed to a greater depth and for a long period through mobilization of ions in the soil, leading to a reduction in SOM and Al concentration and an increase in pH and the levels of Ca and Mg. In the first crop year, adoption of CLI led to an increase in the levels of K and Mg and a reduction in the levels of SOM; however, in the second crop year, the rate of decline of SOM decreased compared to the decline observed in the first crop year, and the level of K increased, whereas that of P decreased. The extent of the effects of liming in terms of depth and improvement in the root environment from the treatments were observed only partially from the changes observed in the chemical properties studied.

Simulation of growth and development of irrigated cowpea in Piauí State by CROPGRO model

The objective of this work was to adapt the CROPGRO model, which is part of the DSSAT system, for simulating the cowpea (Vigna unguiculata) growth and development under soil and climate conditions of the Baixo Parnaíba region, Piauí State, Brazil. In the CROPGRO, only input parameters that define crop species, cultivars, and ecotype were changed in order to characterize the cowpea crop. Soil and climate files were created for the considered site. Field experiments without water deficit were used to calibrate the model. In these experiments, dry matter (DM), leaf area index (LAI), yield components and grain yield of cowpea (cv. BR 14 Mulato) were evaluated. The results showed good fit for DM and LAI estimates. The medium values of R² and medium absolute error (MAE) were, respectively, 0.95 and 264.9 kg ha-1 for DM, and 0.97 and 0.22 for LAI. The difference between observed and simulated values of plant phenology varied from 0 to 3 days. The model also presented good performance for yield components simulation, excluding 100-grain weight, for which the error ranged from 20.9% to 34.3%. Considering the medium values of crop yield in two years, the model presented an error from 5.6%.

Simulation of soybean growth and yield under northeastern Amazon climatic conditions

The objective of this work was to parameterize, calibrate, and validate a new version of the soybean growth and yield model developed by Sinclair, under natural field conditions in northeastern Amazon. The meteorological data and the values of soybean growth and leaf area were obtained from an agrometeorological experiment carried out in Paragominas, PA, Brazil, from 2006 to 2009. The climatic conditions during the experiment were very distinct, with a slight reduction in rainfall in 2007, due to the El Niño phenomenon. There was a reduction in the leaf area index (LAI) and in biomass production during this year, which was reproduced by the model. The simulation of the LAI had root mean square error (RMSE) of 0.55 to 0.82 m² m-2, from 2006 to 2009. The simulation of soybean yield for independent data showed a RMSE of 198 kg ha-1, i.e., an overestimation of 3%. The model was calibrated and validated for Amazonian climatic conditions, and can contribute positively to the improvement of the simulations of the impacts of land use change in the Amazon region. The modified version of the Sinclair model is able to adequately simulate leaf area formation, total biomass, and soybean yield, under northeastern Amazon climatic conditions.

Growth of Crassostrea gasar cultured in marine and estuary environments in Brazilian waters

The objective of this work was to evaluate the growth of the mangrove oyster Crassostrea gasar cultured in marine and estuarine environments. Oysters were cultured for 11 months in a longline system in two study sites - São Francisco do Sul and Florianópolis -, in the state of Santa Catarina, Southern Brazil. Water chlorophyll-α concentration, temperature, and salinity were measured weekly. The oysters were measured monthly (shell size and weight gain) to assess growth. At the end of the culture period, the average wet flesh weight, dry flesh weight, and shell weight were determined, as well as the distribution of oysters per size class. Six nonlinear models (logistic, exponential, Gompertz, Brody, Richards, and Von Bertalanffy) were adjusted to the oyster growth data set. Final mean shell sizes were higher in São Francisco do Sul than in Florianópolis. In addition, oysters cultured in São Francisco do Sul were more uniformly distributed in the four size classes than those cultured in Florianópolis. The highest average values of wet flesh weight and shell weight were observed in São Francisco do Sul, whereas dry flesh weight did not differ between the sites. The estuary environment is more promising for the cultivation of oysters.

Modeling growth and yield of loblolly pinestands under intensive management

Abstract:The objective of this work was to develop and validate a prognosis system for volume yield and basal area of intensively managed loblolly pine (Pinus taeda) stands, using stand and diameter class models compatible in basal area estimates. The data used in the study were obtained from plantations located in northern Uruguay. For model validation without data loss, a three-phase validation scheme was applied: first, the equations were fitted without the validation database; then, model validation was carried out; and, finally, the database was regrouped to recalibrate the parameter values. After the validation and final parameterization of the models, a simulation of the first commercial thinning was carried out. The developed prognosis system was precise and accurate in estimating basal area production per hectare or per diameter classes. There was compatibility in basal area estimates between diameter class and whole stand models, with a mean difference of -0.01 m2ha-1. The validation scheme applied is logic and consistent, since information on the accuracy and precision of the models is obtained without the loss of any information in the estimation of the models' parameters.

Kinetic measurements during transient film growth on zinc

The electrochemical behaviour of zinc has been extensively studied in alkaline and acid media, but only a few studies have been reported in neutral solutions, particularly in deaerated media. Zinc passivation in neutral medium and the effect of the ClO4- ion on the nucleation and growth of the passive layer is studied in this paper by a transient technique at different electrolyte concentrations and applied potentials. ZnO growth rate was shown to decrease with increasing electrolyte concentration. Moreover, passive layer growth occurred followed by pitting nucleation and growth. Film growth and pit nucleation are explained by means of the Macdonald and Engell-Stolica models.

Use data from permanent sampling points in growth and yield modeling

This study was carried to evaluate the efficiency of the Bitterlich method in growth and yield modeling of the even-aged Eucalyptus stands. 25 plots were setup in Eucalyptus grandis cropped under a high bole system in the Central Western Region of Minas Gerais, Brazil. The sampling points were setup in the center of each plot. The data of four annual mesurements were colleted and used to adjust the three model types using the age, the site index and the basal area as independent variables. The growths models were fitted for volume and mass of trees. The efficiency of the Bitterlich method was confirmed for generating the data for growth and yield modeling.

Mathematical modeling applied to the growth of tilapia in net cages in the sub middle of the São Francisco river

This study aimed to apply mathematical models to the growth of Nile tilapia (Oreochromis niloticus) reared in net cages in the lower São Francisco basin and choose the model(s) that best represents the conditions of rearing for the region. Nonlinear models of Brody, Bertalanffy, Logistic, Gompertz, and Richards were tested. The models were adjusted to the series of weight for age according to the methods of Gauss, Newton, Gradiente and Marquardt. It was used the procedure "NLIN" of the System SAS® (2003) to obtain estimates of the parameters from the available data. The best adjustment of the data were performed by the Bertalanffy, Gompertz and Logistic models which are equivalent to explain the growth of the animals up to 270 days of rearing. From the commercial point of view, it is recommended that commercialization of tilapia from at least 600 g, which is estimated in the Bertalanffy, Gompertz and Logistic models for creating over 183, 181 and 184 days, and up to 1 Kg of mass , it is suggested the suspension of the rearing up to 244, 244 and 243 days, respectively.