It is not just about paying your dues: Impact of generational cohort on active and passive union participation

The lack of a validated measure of active–passive union participation and a dearth of research into the relationship between generational cohort and union participation challenge union leaders to develop policies and practices to facilitate union renewal. We address these issues by (a) developing a multidimensional measure of union participation that captures both active and passive components, (b) using structural equation modelling to validate the measure within a nomological framework, and (c) investigating the impact of generational cohort on all paths in our framework. Data from members of a large American union confirm that generational cohort influences how union members participate in their union. The two‐factor measure developed in this study facilitates research into antecedents and outcomes of passive and active union participation. Our findings should also prove useful to unions seeking to increase participation within their membership, academics researching unions and generational cohort, and human resource practitioners operating in unionised environments.     

Time series copulas for heteroskedastic data

We propose parametric copulas that capture serial dependence in stationary heteroskedastic time series. We suggest copulas for first‐order Markov series, and then extend them to higher orders and multivariate series. We derive the copula of a volatility proxy, based on which we propose new measures of volatility dependence, including co‐movement and spillover in multivariate series. In general, these depend upon the marginal distributions of the series. Using exchange rate returns, we show that the resulting copula models can capture their marginal distributions more accurately than univariate and multivariate generalized autoregressive conditional heteroskedasticity models, and produce more accurate value‐at‐risk forecasts.     

Green Public Procurement: A Neglected Tool in the European Green Deal Toolbox?

Intereconomics - Public procurement amounts to around 14% of European Union GDP and, given this size, could well represent an important tool to foster the green transition. However, green public...     

Stock market volatility forecasting: Do we need high-frequency data?

The general consensus in the volatility forecasting literature is that high-frequency volatility models outperform low-frequency volatility models. However, such a conclusion is reached when low-frequency volatility models are estimated from daily returns. Instead, we study this question considering daily, low-frequency volatility estimators based on open, high, low, and close daily prices. Our data sample consists of 18 stock market indices. We find that high-frequency volatility models tend to outperform low-frequency volatility models only for short-term forecasts. As the forecast horizon increases (up to one month), the difference in forecast accuracy becomes statistically indistinguishable for most market indices. To evaluate the practical implications of our results, we study a simple asset allocation problem. The results reveal that asset allocation based on high-frequency volatility model forecasts does not outperform asset allocation based on low-frequency volatility model forecasts.     

Broadcasting and Sport

The broadcasting of sport is heavily regulated. Our main findingis that common trends, and differences, in the quality, quantity,and price of televised sport across Europe and USA cannot beadequately explained without reference to policy interventionsby national and supranational government, and by competitionand regulatory authorities. These interventions have a significantimpact on the organization and governance of sports, as wellas the structure of broadcasting markets and the conduct ofbroadcasting companies. Foreclosure of broadcasting marketsthrough exclusive, long-term contracts, bundling and verticalintegration, access of viewers to major sporting events, andcollective selling stand out as the most significant policyissues. We conclude by noting a number of policy implications.     

An Illuminating Exchange The Construction of Social Reality

A BSTRACT . In his The Construction of Social Reality , Searle presents an account of rights, responsibilities, obligations, duties, and similar entities in terms of the formula X counts as Y in context C , where " X " refers in the simplest case to some physical object or event and " Y " to the result of imposing upon X some deontic power or function. Smith attempts to show the limitations of this formula, focusing especially on the examples of contested property rights (where C is not uniquely defined), and of money in bank accounts and other phenomena (where no physical X -term is available). Searle responds to these criticisms, above all by pointing to the fact that some of the problems Smith raises are to be addressed not by an ontological analysis of social reality but rather through legal or political means.     

The Law and Economics of Marriage Contracts

Growth in property ownership has raised the stakes in the distribution of financial assets on divorce. Given high risks of marital failure, this has stimulated the demand for private ordering through enforceable marriage contracts. This paper surveys the existing law and economics literature and legal practice to consider the state of knowledge on the economic theory, scope and limits of written nuptial agreements.     

Economic Development Indicators as Determinants of Medal Winning at the Sydney Olympics: An Extreme Bounds Analysis

This paper examines the variables that determine the performance of countries at the Olympic Games as measured by a weighted sum of the medals won at the Sydney 2000 Games. While previous studies have identified the importance of a country's economic size and the resources available to sport, this paper examines nine more variables including the number of athletes representing each nation and some development indicators. Based on 2310 regressions, both traditional and restricted extreme bounds analysis show that only two variables are robust: the number of athletes and national expenditure on health. Thus, the final model recognises four explanatory variables that include these two as well as GDP and population.