An agent-based approach to value theory and wealth distribution in economics

Any attempt to model an economy requires foundational assumptions about the relations between prices, values and the distribution of wealth. These assumptions exert a profound influence over the results of any model. Unfortunately, there are few areas in economics as vexed as the theory of value. I argue in this paper that the fundamental problem with past theories of value is that it is simply not possible to model the determination of value, the formation of prices and the distribution of income in a real economy with analytic mathematical models. All such attempts leave out crucial processes or make unrealistic assumptions which significantly affect the results. There have been two primary approaches to the theory of value. The first, associated with classical economists such as Ricardo and Marx were substance theories of value, which view value as a substance inherent in an object and which is conserved in exchange. For Marxists, the value of a commodity derives solely from the value of the labour power used to produce it - and therefore any profit is due to the exploitation of the workers. The labour theory of value has been discredited because of its assumption that labour was the only ‘factor’ that contributed to the creation of value, and because of its fundamentally circular argument. Neoclassical theorists argued that price was identical with value and was determined purely by the interaction of supply and demand. Value then, was completely subjective. Returns to labour (wages) and capital (profits) were determined solely by their marginal contribution to production, so that each factor received its just reward by definition. Problems with the neoclassical approach include assumptions concerning representative agents, perfect competition, perfect and costless information and contract enforcement, complete markets for credit and risk, aggregate production functions and infinite, smooth substitution between factors, distribution according to marginal products, firms always on the production possibility frontier and firms’ pricing decisions, ignoring money and credit, and perfectly rational agents with infinite computational capacity. Two critical areas include firstly, the underappreciated Sonnenschein-Mantel- Debreu results which showed that the foundational assumptions of the Walrasian general-equilibrium model imply arbitrary excess demand functions and therefore arbitrary equilibrium price sets. Secondly, in real economies, there is no equilibrium, only continuous change. Equilibrium is never reached because of constant changes in preferences and tastes; technological and organisational innovations; discoveries of new resources and new markets; inaccurate and evolving expectations of businesses, consumers, governments and speculators; changing demand for credit; the entry and exit of firms; the birth, learning, and death of citizens; changes in laws and government policies; imperfect information; generalized increasing returns to scale; random acts of impulse; weather and climate events; changes in disease patterns, and so on. The problem is not the use of mathematical modelling, but the kind of mathematical modelling used. Agent-based models (ABMs), objectoriented programming and greatly increased computer power however, are opening up a new frontier. Here a dynamic bargaining ABM is outlined as a basis for an alternative theory of value. A large but finite number of heterogeneous commodities and agents with differing degrees of market power are set in a spatial network. Returns to buyers and sellers are decided at each step in the value chain, and in each factor market, through the process of bargaining. Market power and its potential abuse against the poor and vulnerable are fundamental to how the bargaining dynamics play out. Ethics therefore lie at the very heart of economic analysis, the determination of prices and the distribution of wealth. The neoclassicals are right then that price is the enumeration of value at a particular time and place, but wrong to downplay the critical roles of bargaining, power and ethics in determining those same prices.

Application of power functions to chromatographic data for the enhancement of signal to noise ratios and separation resolution

Chromatographic detection responses are recorded digitally. A peak is represented ideally by a Guassian distribution. Raising a Guassian distribution to the power ‘n’ increases the height of the peak to that power, but decreases the standard deviation by √n. Hence there is an increasing disparity in detection responses as the signal moves from low level noise, with a corresponding decrease in peak width. This increases the S/N ratio and increases peak to peak resolution. The ramifications of these factors are that poor resolution in complex chromatographic data can be improved, and low signal responses embedded at near noise levels can be enhanced. The application of this data treatment process is potentially very useful in 2D-HPLC where sample dilution occurs between dimension, reducing signal response, and in the application of post-reaction detection methods, where band broadening is increased by virtue of reaction coils. In this work power functions applied to chromatographic data are discussed in the context of (a) complex separation problems, (b) 2D-HPLC separations, and (c) post-column reaction detectors.

Distribution of Gaba in the nerve ganglia of haliotis asinina linnaeus

Gamma-aminobutyric acid (GABA) is a major neurotransmitter and effective settlement inducer in abalone aquaculture. This study aimed to explore the distribution of GABA within neural tissues of Haliotis asinina. Gamma-aminobutyric acid was found in neuronal cell type 1 of 3 major ganglia (i.e., cerebral, pleuropedal, and visceral ganglia) of both sexes. The distribution of GABA-immunoreactive (-ir) cells in the cerebral ganglion was concentrated mostly in the cortex region of the dorsal horn, whereas it was scattered throughout the pleuropedal ganglion, with more in the upper half. Gamma-aminobutyric acid-ir nerve fibers were found throughout the neuropils of the ganglia. The visceral ganglion had the least numbers of GABA-ir neurons compared with the other 2 ganglia. The cells were distributed mainly in the dorsal horn. We also observed GABA to be colocalized with 2 other neurotransmitters: serotonin (5-HT) and dopamine (DA). In the cerebral ganglion, fluorescence double staining of GABA and 5-HT, and GABA and DA showed immunoreactivity in separate cells and was also colocalized in the same cells. In the pleuropedal ganglion, the staining pattern was similar to the cerebral ganglion, but positive-staining cells were less numerous. In the visceral ganglion, GABA and DA, and GABA and 5-HT were colocalized in the same cell types. Overall, we found that GABAergic cells were most numerous in the cerebral ganglion of H. asinina. Further studies are required to determine the functions of these neurotransmitters in relation to their distribution.

Neuronal classification and distribution in the central nervous system of the female mud crab, Scylla olivacea

The mud crab, Scylla olivacea, is one of the most economically valuable marine species in Southeast Asian countries. However, commercial cultivation is disadvantaged by reduced reproductive capacity in captivity. Therefore, an understanding of the general and detailed anatomy of central nervous system (CNS) is required before investigating the distribution and functions of neurotransmitters, neurohormones, and other biomolecules, involved with reproduction. We found that the anatomical structure of the brain is similar to other crabs. However, the ventral nerve cord (VNC) is unlike other caridian and dendrobrachiate decapods, as the subesophageal (SEG), thoracic and abdominal ganglia are fused, due to the reduction of abdominal segments and the tail. Neurons in clusters within the CNS varied in sizes, and we found that there were five distinct size classes (i.e., very small globuli, small, medium, large, and giant). Clusters in the brain and SEG contained mainly very small globuli and small-sized neurons, whereas, the VNC contained small-, medium-, large-, and giant-sized neurons. We postulate that the different sized neurons are involved in different functions. Microsc. Res. Tech. 77:189–200, 2014. © 2013 Wiley Periodicals, Inc.

Investigation of progress of reactions and evolution of radial heterogeneity in the initial stage of thermal stabilization of PAN precursor fibres

The relationship between process parameters and structural transformations in the fibres at each stage of the carbon fibre manufacturing process play a crucial role in developing high performance carbon fibres. Here we report a systematic method which uses the combination of Taguchi approach and scientific evaluation techniques to establish these relationships for the initial stage of thermal stabilization. Density, cyclization index and fraction of reacted nitriles of a precursor containing acrylonitrile, methacrylate and itaconic acid (AN/MA/IA) were used to assess the progress of stabilization in the fibres with respect to various combinations of process parameters. The extent of progress of stabilization improved with increase in temperature (from 225 to 235 °C) and time (from 12 to 24 min) whereas an opposite trend was observed with increase in the tension on the fibres from (1600-2550 cN). According to optical microscopy, radial heterogeneity was observed in the fibres treated at 235 °C. Interestingly, we were able to identify the existence of heterogeneous modulus distribution from skin to core of the precursor fibres which was further transferred to treated fibres. The overall radial modulus of treated fibres was higher than the precursor fibres. In contrast to the literature, the fracture morphology of the fibre samples indicated that initiation of crack is caused by surface defects rather than radial heterogeneity.