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The theory of the monetary circuit, as developed in its most powerful form by Graziani (1989), has made a significant contribution to the analysis of credit money in Marxian economics. A key issue is the extent to which circuit theory fails to take into account the relationship between sectors producing capital and consumption goods. In Marx’s reproduction schema, how much money do capitalists need to advance in order for exchange between sectors to balance, and for the circuit to be closed? The purpose of this paper is to address this issue by examining different models of the monetary circuit, each of which has a textual grounding in Marx’s often contradictory musings in Capital, Volume 2.

Alongside alternative conceptions of the circuit of money, different interpretations exist about the role of the multiplier, which can be nested in Marx’s reproduction schema. The problem, from a Marxian point of view, is that in the existing literature investment is usually confined to the capital goods sector. It can be argued that Marx, for the most part, viewed investment as involving accumulation in both departments of production. Using a multiplier framework, derived from input-output technology, this wider treatment of investment is considered as an alternative way of modelling the circulation of money. In addition to contributing to Marxian analysis of the money circuit, this approach could also be more accessible to a wider Post Keynesian audience, since a scalar Keynesian multiplier is employed.

The malfunction variables of power stations are related to the areas of weather, physical structure, control and load behaviour. To predict temporal power failure is difficult due to their unpredictable characteristics. As high accuracy is normally required, the estimation of failures of short-term temporal prediction is highly difficult. This study presents a method for converting stochastic behaviour into a stable pattern, which can subsequently be used in a short-term estimator. For this conversion, K-means clustering is employed, followed by Long-Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) algorithms are used to perform the Short-term estimation. The environment, the operation and the generated signal factors are all simulated using mathematical models. Weather parameters and load samples have been collected as part of a data set. Monte-Carlo simulation using MATLAB programming has been used to conduct experimental estimation of failures. The estimated failures of the experiment are then compared with the actual system temporal failures and found to be in good match. Therefore, for any future power grid, there is a testbed ready to estimate the future failures.

The central hypothesis to be tested is the relevance of gold in the determination of the value of the US dollar as an international reserve currency after 1971. In the first section, the market value of the US dollar is analysed by looking at new forms of value (financial derivative products), the dollar as a safe haven, the choice of a standard of value and the role of special drawing rights in reforming the international monetary system. Based on dimensional analysis, the second section analyses the definition and meaning of a numéraire for international currency and the justification for a variable standard of value based on a commodity (gold). Then follows the theoretical foundation for the empirical and econometric analysis used later. The third section is devoted to the specification of an econometric model and a graphical analysis of the data. It is clear that an inverse relation exists between the value of the US dollar and the price of gold. The fourth section shows the estimations of the different specifications of the model including linear regression and cointegration analysis. The most important econometric result is that the null hypothesis is rejected in favour of a significant link between the price of gold and the value of the US dollar. There is also a positive relationship between gold price and inflation. An inverse statistically significant relation between gold price and monetary policy is shown by applying a dynamic model of cointegration with lags.

Some cycle routes have proved unpopular because at several points a cyclist has to stop or slow very appreciably. Cyclists are discouraged by the resulting extra journey time. Three alternative hypotheses are made for a cyclist's performance in response to an imposed stop. In all he brakes uniformly from a cruising speed. In one, this speed is a personal standard, and he accelerates uniformly to regain it. In the second, because his energy is used in accelerating, he has less to use in cruising. The third hypothesis is that a cyclist's power output in accelerating is the same as in cruising, except at very low speeds, so that he attains his normal cruising speed asymptotically.

Trials were conducted on a lightly trafficked 2.5-km circuit with seven roundabouts. Cyclists made at least two circuits each, one non-stop and one stopping at roundabouts. Pairs of times for each cyclist were compared with derivations from each hypothesis. It was found that the estimates derived from the second hypothesis were much closer to the trial times than those given by the others. The conclusion is that making an adult cyclist stop is equivalent to extending the journey time by as much as an extra 50 m, approximately, would take. In reckoning the lengths of routes in order to select one for development, an equivalent distance of about 50 m should be added for each stop or near stop, unless they are close together.

In antitrust class-action litigation, courts are increasingly unlikely to accept the presumption that all class members were harmed by price-fixing among a group of firms or by exclusionary behavior by a single firm. Econometric methods typically applied in antitrust and other settings estimate the average effect of the challenged conduct, but do not inform impact for individual class members. We present classwide econometric methods and statistical tests for detecting the existence (or lack thereof) of common impact and determining what proportion (if any) of the proposed class suffered injury in many class actions. We conclude that econometric tools can meaningfully inform the legal process, even when courts demand proof of common impact.

This paper focuses on two related questions at the intersection of antitrust and intellectual property law. First, under what circumstances must the holder of a patent or a copyright or the owner of a trade secret allow others to use that intellectual property? Second, under what circumstances can the holder of an intellectual property right use that right to make it difficult for another party to succeed in a related market? These questions have vexed antitrust and intellectual property scholars alike ever since the Federal Circuit ruled in 2000 that patent holders “may enforce the statutory right to exclude others from making, using, or selling the claimed invention free from liability under the antitrust laws,” a ruling that directly contradicted the Ninth Circuit ruling that antitrust liability could be imposed for almost identical conduct, depending on the motivations of the patent holder. The various proceedings in United States v. Microsoft only added fuel to the firestorm of controversy.After briefly retracing the jurisprudential path to see how this situation arose, we propose a solution that primarily involves a variation on the real property concept of adverse possession for the intellectual property space along with a slight extension of the Essential Facilities Doctrine for industries that exhibit network effects. We examine, both for firms with and without market power, how our proposal would resolve the situations presented by large fixed asset purchases, the introduction of entirely new products, and operating systems with network effects. We also demonstrate how our proposal could be applied in the European antitrust enforcement context.

The author presents new estimates of the probability weighting functions found in rank-dependent theories of choice under risk. These estimates are unusual in two senses. First, they are free of functional form assumptions about both utility and weighting functions, and they are entirely based on binary discrete choices and not on matching or valuation tasks, though they depend on assumptions concerning the nature of probabilistic choice under risk. Second, estimated weighting functions contradict widely held priors of an inverse-s shape with fixed point well in the interior of the (0,1) interval: Instead the author usually finds populations dominated by “optimists” who uniformly overweight best outcomes in risky options. The choice pairs used here mostly do not provoke similarity-based simplifications. In a third experiment, the author shows that the presence of choice pairs that provoke similarity-based computational shortcuts does indeed flatten estimated probability weighting functions.

The British North American colonies were the first western economies to rely on legislature-issued paper monies as an important internal media of exchange. This system arose piecemeal. In the absence of banks and treasuries that exchanged paper monies at face value for specie monies on demand, colonial governments experimented with other ways to anchor their paper monies to real values in the economy. These mechanisms included tax-redemption, land-backed loans, sinking funds, interest-bearing notes, and legal tender laws. I assess and explain the structure and performance of these mechanisms. This was monetary experimentation on a grand scale.

Mixed logit models can represent heterogeneity across individuals, in both observed and unobserved preferences, but require computationally expensive calculations to compute probabilities. A few methods for including error covariance heterogeneity in a closed form models have been proposed, and this paper adds to that collection, introducing a new form of a Network GEV model that sub-parameterizes the allocation values for the assignment of alternatives (and sub-nests) to nests. This change allows the incorporation of systematic (nonrandom) error covariance heterogeneity across individuals, while maintaining a closed form for the calculation of choice probabilities. Also explored is a latent class model of nested models, which can similarly express heterogeneity. The heterogeneous models are compared to a similar model with homogeneous covariance in a realistic scenario, and are shown to significantly outperform the homogeneous model, and the level of improvement is especially large in certain market segments. The results also suggest that the two heterogeneous models introduced herein may be functionally equivalent.