The Beat of the Economic Heart: Joseph Schumpeter and Arthur Spiethoff on Business Cycles

The paper discusses the relationship between Arthur Spiethoff and Joseph A. Schumpeter, the men and their works. Had it not been for Spiethoff Schumpeter would in all probability have forever been lost to scientific work. It was Spiethoff who brought the Austrian back to academia and research after a sequence of serious mishaps in politics and banking. Spiethoff's contribution to an analysis of business cycles is then summarized and important similarities and some differences between it and Schumpeter's are pointed out. The view of Spiethoff and Schumpeter that cycles are endogenous and cannot possibly be eliminated without at the same time eliminating the dynamism of the capitalist economy is then couterposed with views of some of their contemporaries and particularly modern mainstream macroeconomics that this is not so.Schumpeter; Spiethoff; business cycles; innovations; creative destruction

The Contributions of Two Eminent Japanese Scholars on the Development of Economic Theories: Michio Morishima and Takashi Negishi

There can be no doubt that Michio Morishima and Takashi Negishi are two of the most important historians of economic thought of the recent past. Both authors contributed numerous papers and books to the subject, dealing with the works of major economists from the very inception of systematic economic thought at the time of the classical economists up until modern times. And both authors combined a vivid interest in modern economic theory with an interest in what past masters had to say. The paper assesses and compares the motivations of the two authors to engage in the history of economic theories, their similar, but different approaches to do historical research, and their achievements in this regard. Given the remarkable amount of work each one of them accomplished, the paper has to focus attention on a subset of the themes the two authors dealt with. The emphasis will be on (i) their treatment of the classical theories of value, distribution and capital accumulation, especially those of Adam Smith and David Ricardo, (ii) their discussion of the contributions of Karl Marx and some Marxists, (iii) their interpretation of some early and mature marginalist economists, especially Léon Walras, Eugen von Böhm-Bawerk and Knut Wicksell, and (iv) their views about the achievements of John Maynard Keynes. Given the intrinsic complexity of each of these themes, it goes without saying that the paper is bound to proceed largely in terms of synthetic statements.Negishi, Takashi; Morishima, Michio; general equilibrium; Marxist economics; trade; growth

Recursive Estimation of Orientation Based on the Bingham Distribution

Directional estimation is a common problem in many tracking applications. Traditional filters such as the Kalman filter perform poorly because they fail to take the periodic nature of the problem into account. We present a recursive filter for directional data based on the Bingham distribution in two dimensions. The proposed filter can be applied to circular filtering problems with 180 degree symmetry, i.e., rotations by 180 degrees cannot be distinguished. It is easily implemented using standard numerical techniques and suitable for real-time applications. The presented approach is extensible to quaternions, which allow tracking arbitrary three-dimensional orientations. We evaluate our filter in a challenging scenario and compare it to a traditional Kalman filtering approach

In Favor of Rigor and Relevance. A Reply to Mark Blaug

The paper discusses Mark Blaug’s recent criticisms of “Sraffian economics”. It is shown that none of the criticisms stand up to close examination. Blaug commits a number of elementary blunders and mistakes the mathematical form of an argument for its content. He variously contradicts himself and puts forward bold contentions that cannot be sustained. The paper concludes with an obvious plea for rigor and relevance.Piero Sraffa;Mark Blaug; General Equilibrium

Recursive Bayesian Filtering in Circular State Spaces

For recursive circular filtering based on circular statistics, we introduce a general framework for estimation of a circular state based on different circular distributions, specifically the wrapped normal distribution and the von Mises distribution. We propose an estimation method for circular systems with nonlinear system and measurement functions. This is achieved by relying on efficient deterministic sampling techniques. Furthermore, we show how the calculations can be simplified in a variety of important special cases, such as systems with additive noise as well as identity system or measurement functions. We introduce several novel key components, particularly a distribution-free prediction algorithm, a new and superior formula for the multiplication of wrapped normal densities, and the ability to deal with non-additive system noise. All proposed methods are thoroughly evaluated and compared to several state-of-the-art solutions

Efficient Evaluation of the Probability Density Function of a Wrapped Normal Distribution

The wrapped normal distribution arises when a the density of a one-dimensional normal distribution is wrapped around the circle infinitely many times. At first look, evaluation of its probability density function appears tedious as an infinite series is involved. In this paper, we investigate the evaluation of two truncated series representations. As one representation performs well for small uncertainties whereas the other performs well for large uncertainties, we show that in all cases a small number of summands is sufficient to achieve high accuracy

Unscented Orientation Estimation Based on the Bingham Distribution

Orientation estimation for 3D objects is a common problem that is usually tackled with traditional nonlinear filtering techniques such as the extended Kalman filter (EKF) or the unscented Kalman filter (UKF). Most of these techniques assume Gaussian distributions to account for system noise and uncertain measurements. This distributional assumption does not consider the periodic nature of pose and orientation uncertainty. We propose a filter that considers the periodicity of the orientation estimation problem in its distributional assumption. This is achieved by making use of the Bingham distribution, which is defined on the hypersphere and thus inherently more suitable to periodic problems. Furthermore, handling of non-trivial system functions is done using deterministic sampling in an efficient way. A deterministic sampling scheme reminiscent of the UKF is proposed for the nonlinear manifold of orientations. It is the first deterministic sampling scheme that truly reflects the nonlinear manifold of the orientation