Reframing the History of the Competition Concept: Neoliberalism,Meritocracy, Modernity

This paper reframes the concept of competition, arguing that recent tendencies to frame it in the context of neoliberalism are too narrow to grasp its full significance. We need to see how it operates well beyond the capitalist economy, as a social and not just theoretical concept. I contextualise it in a deeper history, going back to the eighteenth century, beginning with an empirical examination of the development of the concept in English language dictionaries and encyclopaedias, using a method of ‘conceptual history’. I show how the concept, its grammatical forms, and characteristic associations have evolved substantially since the eighteenth century. This finding is placed in a broader explanatory context, arguing that it is the combined rise of a set of core institutions of modernity, not just capitalism but also democracy, adversarial law, science, and civil society, that deeply embeds competition in the modern world. The decline of aristocratic and religious authority, and the national subordination of martial power, opened the way for more ‘liberal’ forms of society in which authority is routinely contested through competition, across economy, politics, culture and beliefs. Appreciating this is a necessary step towards truly grappling with the effects of competition on modern life.     

Everyday Race: Millennials,Generation Z,and the Census

The census is a central feature of U.S. governance, providing important information regarding the U.S. population used to determine legislative representation and the allocation of federal funding. The count also involves a measure of race and ethnicity, however the sociopolitical construction of race means census categories have shifted throughout history. Existing data highlight how current classifications do not fully capture the identities of different groups; however, less is known about the views of young adults. Utilizing interview and journal data wherein 84 college students from the Millennial and Generation Z cohorts were asked to reflect on the 2010 and 2020 census race questions, our findings reveal a major gap between census classification and everyday experiences with racial categorization. Our study provides meaningful insights into how young adults think about the census race and ethnicity categories, with implications for future research and census collection.     

FORECASTING VOLATILITY IN THE PRESENCE OF MODEL INSTABILITY

Recent advances in financial econometrics have allowed for the construction of efficient ex post measures of daily volatility. This paper investigates the importance of instability in models of realised volatility and their corresponding forecasts. Testing for model instability is conducted with a subsampling method. We show that removing structurally unstable data of a short duration has a negligible impact on the accuracy of conditional mean forecasts of volatility. In contrast, it does provide a substantial improvement in a model's forecast density of volatility. In addition, the forecasting performance improves, often dramatically, when we evaluate models on structurally stable data.     

The Topology of Central Counterparty Clearing Networks and Network Stability

□ This paper derives a measure of central counterparty (CCP) clearing-network risk that is based on the probability that the maximum exposure (the N-th order statistic) of a CCP to an individual general clearing member is large. Our analytical derivation of this probability uses the theory of Laplace asymptotics, which is related to the large deviations theory of rare events. The theory of Laplace asymptotics is an area of applied probability that studies the exponential decay rate of certain probabilities and is often used in the analysis of the tails of probability distributions. We show that the maximum-exposure probability depends on the topology, or structure, of the clearing network. We also derive a CCP's Maximum-Exposure-at-Risk, which provides a metric for evaluating the adequacy of the CCP's and general clearing members’ loss-absorbing financial resources during rare but plausible market conditions. Based on our analysis, we provide insight into how clearing-network structure can affect the maximum-exposure risk of a CCP and, thereby, network stability. We show that the rate function (the exponential decay rate) of the maximum-exposure probability is informative and can be used to compare the relative maximum-exposure risks across different network configurations.