Classical, neoclassical and Austrian philosophy of economic science

In this paper apriorism has been examined, the main-stream philosophy of economic science. An essential element in apriorism is the idea that the economist should always start his analysis from a hard, solid core of assumptions, in which he can have great confidence. Since most aprioristic thinkers reflect to some extent the insights of Robbins, Menger and Mill, the latter have been considered rather extensively. Menger and Mill have virtually the same arguments for their almost identical hard core assumptions. It is partly a methodological argument: for a knowledge of the consequence of the various motives influencing human action, we must first know the consequences of each of these motives separately. Observation and/or introspection reveal to us what these motives are. In economics this amounts to the hard core assumption of an economic man striving efficiently towards his economic end. Robbins argues in a fundamentally different way, since his hard core contains almost universal facts of experience, present whenever human activity has an economic aspect. On the other had Mill and Robbins have almost identical views concerning the confrontation of deduced results with reality and the value of economic predictions. The aprioristic approach is said to disapprove of the usual practice of econometrics mainly because the latter does not base its theory on a set of assumptions that can be considered as a hard core within apriorism. The views of Robbins van Von Mises appear to confirm the idea that apriorism is incompatible with this usual practice.Economics ;

Multi-directional Geodesic Neural Networks via Equivariant Convolution

We propose a novel approach for performing convolution of signals on curved surfaces and show its utility in a variety of geometric deep learning applications. Key to our construction is the notion of directional functions defined on the surface, which extend the classic real-valued signals and which can be naturally convolved with with real-valued template functions. As a result, rather than trying to fix a canonical orientation or only keeping the maximal response across all alignments of a 2D template at every point of the surface, as done in previous works, we show how information across all rotations can be kept across different layers of the neural network. Our construction, which we call multi-directional geodesic convolution, or directional convolution for short, allows, in particular, to propagate and relate directional information across layers and thus different regions on the shape. We first define directional convolution in the continuous setting, prove its key properties and then show how it can be implemented in practice, for shapes represented as triangle meshes. We evaluate directional convolution in a wide variety of learning scenarios ranging from classification of signals on surfaces, to shape segmentation and shape matching, where we show a significant improvement over several baselines

Are the Determinants of Markup Size Industry-Specific? The Case of Slovenian Manufacturing Firms

The aim of this paper is to identify factors that affect the pricing policy in Slovenian manufacturing firms in terms of the markup size and, most of all, to explicitly account for the possibility of differences in pricing procedures among manufacturing industries. Accordingly, the analysis of the dynamic panel is carried out on an industry-by-industry basis, allowing the coefficients on the markup determinants to vary across industries. We find that the oligopoly theory of markup determination for the most part holds for the manufacturing sector as a whole, although large variability in markup determinants exists across industries within the Slovenian manufacturing. Our main conclusion is that each industry should be investigated separately in detail in order to assess the precise role of markup factors in the markup-determination process.Industry, Manufacturing, Markup determinants, Slovenia

On some methods of construction of invariant normalizations of lightlike hypersurfaces

The authors study the geometry of lightlike hypersurfaces on pseudo-Riemannian manifolds $(M, g)$ of Lorentzian signature. Such hypersurfaces are of interest in general relativity since they can be models of different types of physical horizons. For a lightlike hypersurface $V \subset (M, g)$ of general type and for some special lightlike hypersurfaces (namely, for totally umbilical and belonging to a manifold $(M, g)$ of constant curvature), in a third-order neighborhood of a point $x \in V$, the authors construct invariant normalizations intrinsically connected with the geometry of $V$ and investigate affine connections induced by these normalizations. For this construction, they used relative and absolute invariants defined by the first and second fundamental forms of $V$. The authors show that if $\dim M = 4$, their methods allow to construct three invariant normalizations and affine connections intrinsically connected with the geometry of $V$. Such a construction is given in the present paper for the first time. The authors also consider the fibration of isotropic geodesics of $V$ and investigate their singular points and singular submanifolds.Comment: LaTeX, 25 page

Contestability and sunk costs: An analysis of product R&D competition

The paper shows that Bertrand competition and contestability can be reconciled with sunk costs. When average total costs are constant over a range of output, marginal cost pricing does not conflict with the budget constraint faced by firms. Empirical observations support the notion of constant average total costs. When average total costs are constant, there is no trade-off between dynamic economies and static efficiency. The argument is applied to product R&D competition.industrial organization ;