Colorado Republican Federal Campaign Committee v. Federal Election Commission: Maintaining What Remains of the Federal Election Campaign Act Through Constitutional Compromise

This Note will discuss the Court\u27s reasoning and holding in Colorado Republican. Additionally, this Note will discuss how the Court distinguished independent and coordinated campaign expenditures that were first established in Buckley v. Valeo. Finally, this Note will discuss why the Court did not address whether limitations on coordinated expenditures for political parties are protected by the First Amendment

Complex Systems and Applied Linguistics

With this monograph, Diane Larsen-Freeman and Lynne Cameron unveil a complex systems approach to applied linguistics in the first book-length introduction to the topic. Stirrings of a shift in this direction have begun to appear in Larsen-Freeman’s publications this past decade (e.g., 1997, 2002). Expanding on those early papers, this work is intended “to open the conversation” (Larsen-Freeman & Cameron, 2008, p. 255) about complex systems among applied linguists; however, it is not intended to be the last word. As such, it is a rich introduction for teachers, researchers, and students who want to foreground a dynamic worldview in their theory and method for understanding complex systems. This book begins a new chapter in the intellectual history of applied linguistics by repositioning our understandings and making change central. At the very least, the development of a complex systems approach to applied linguistics at the hands of two well-respected applied linguists, each with distinguished publications records, is cause enough to engage with its ideas

Longevity risks and capital markets: The 2010-2011 update

This Special Issue of Geneva Papers on Risk and Insurance - Issues and Practice contains 10 contributions to the academic literature all dealing with longevity risk and capital markets. Draft versions of the papers were presented at Longevity Six: The Sixth International Longevity Risk and Capital Markets Solutions Conference that was held in Sydney on 9-10 September 2010. It was hosted by the Australian Institute for Population Ageing Research, the Australian School of Business and the University of New South Wales. It was sponsored by PricewaterhouseCoopers, Australian Prudential Regulation Authority (APRA), Coventry Capital, Swiss Re, and Institute of Actuaries of Australia.Longevity Risk; Capital Market

Characterization of small molecules inhibiting the pro-angiogenic activity of the zinc finger transcription factor Vezf1

Discovery of inhibitors for endothelial-related transcription factors can contribute to the development of anti-angiogenic therapies that treat various diseases, including cancer. The role of transcription factor Vezf1 in vascular development and regulation of angiogenesis has been defined by several earlier studies. Through construction of a computational model for Vezf1, work here has identified a novel small molecule drug capable of inhibiting Vezf1 from binding to its cognate DNA binding site. Using structure-based design and virtual screening of the NCI Diversity Compound Library, 12 shortlisted compounds were tested for their ability to interfere with the binding of Vezf1 to DNA using electrophoretic gel mobility shift assays. We identified one compound, T4, which has an IC50 of 20 μM. Using murine endothelial cells, MSS31, we tested the effect of T4 on endothelial cell viability and angiogenesis by using tube formation assay. Our data show that addition of T4 in cell culture medium does not affect cell viability at concentrations lower or equal to its IC 50 but strongly inhibits the network formation by MSS31 in the tube formation assays. Given its potential efficacy, this inhibitor has significant therapeutic potential in several human diseases

Longevity risk and the econometric analysis of mortality trends and volatility

Working paper - Australian School of Business Research Paper No. 2009ACTL08Longevity risk and the modeling of trends and volatility for mortality improvement has attracted increased attention driven by ageing populations around the world and the expected financial implications. The original Lee-Carter model that was used for longevity risk assessment included a single improvement factor with differential impacts by age. Financial models that allow for risk pricing and risk management have attracted increasing attention along with multiple factor models. This paper investigates trends, including common trends through co-integration, and the factors driving the volatility of mortality using principal components analysis for a number of developed countries including Australia, England, Japan, Norway and USA. The results demonstrate the need for multiple factors for modeling mortality rates across all these countries. The basic structure of the Lee-Carter model can not adequately model the random variation and the full risk structure of mortality changes. Trends by country are found to be stochastic. Common trends and co-integrating relationships are found across ages highlighting the benefits from modeling mortality rates as a system in a Vector-Autoregressive (VAR) model and capturing long run equilibrium relationships in a Vector Error-Correction Model (VECM) framework.Longevity risk and the modeling of trends and volatility for mortality improvement has attracted increased attention driven by ageing populations around the world and the expected financial implications. The original Lee-Carter model that was used for longevity risk assessment included a single improvement factor with differential impacts by age. Financial models that allow for risk pricing and risk management have attracted increasing attention along with multiple factor models. This paper investigates trends, including common trends through co-integration, and the factors driving the volatility of mortality using principal components analysis for a number of developed countries including Australia, England, Japan, Norway and USA. The results demonstrate the need for multiple factors for modeling mortality rates across all these countries. The basic structure of the Lee-Carter model can not adequately model the random variation and the full risk structure of mortality changes. Trends by country are found to be stochastic. Common trends and co-integrating relationships are found across ages highlighting the benefi ts from modeling mortality rates as a system in a Vector-Autoregressive (VAR) model and capturing long run equilibrium relationships in a Vector Error-Correction Model (VECM) framework

Financial Innovation for an Aging World

Over the last half-century, around the world, many nations have seen plummeting fertility rates and mounting life expectancies. These two factors are the engine behind unprecedented global aging. In this paper, we explore how the demographic transition may influence financial markets and, in turn, how financial market innovation might help resolve concerns flowing from global aging trends. We first provide context by reviewing the economics, finance, and insurance-related literature on how global aging patterns may influence capital markets. We then turn to insurance markets, and discuss a range of products and policies, including both retail and wholesale financial offerings for various forms of life annuities, long-term care benefits, reverse mortgages, securitization of longevity risk, inflation-protected assets, reinsurance, guarantees, derivative contracts on residential property price indices, mortality swaps and longevity derivative contracts. We also indicate how new public-private partnerships might be beneficial in enhancing the future environment for old-age risk management.

Model Risk, Mortality Heterogeneity, and Implications for Solvency and Tail risk

Mortality models used to assess longevity risk and retirement funding have been extended to stochastic models with trends and systematic risk. Systematic risk cannot be readily diversified in an insurance pool or pension fund. It is an important factor in assessing solvency and highlighting the tail risk in longevity insurance and pension products. Idiosyncratic risk can be diversified in typical pool sizes, although less effectively at the older ages. Mortality heterogeneity is not usually taken into account in stochastic mortality models. This is a mortality risk that reduces the effectiveness of idiosyncratic mortality risk pooling. Heterogeneity has been modeled with frailty models and more recently with Markov multiple state ageing models. This paper overviews recent developments in models for mortality heterogeneity and uses a model calibrated to both population mortality and health condition data to consider the impact of model risk and heterogeneity in assessing solvency and tail risk for longevity risk products

Modeling mortality with a bayesian vector autoregression

Paper presented at Strathmore International Math Research Conference on July 23 - 27, 2012Mortality risk models have been developed to capture trends and common factors driving mortality improvement. Multiple factor models take many forms and are often developed and fitted to older ages. In order to capture trends from young ages it is necessary to take into account the richer age structure of mortality improvement from young ages to middle and then into older ages. The Heligman and Pollard (1980) model is a parametric model which captures the main features of period mortality tables and has parameters that are interpreted according to age range and effect on rates. Although time series techniques have been applied to model parameters in various parametric mortality models, there has been limited analysis of parameter risk using Bayesian techniques. This paper uses a Bayesian Vector Autoregressive (BVAR) model for the parameters of the Heligman-Pollard model and fits the model to Australian data. As VARmodels allow for dependence between the parameters of the Heligman-Pollard model they are flexible and better reflect trends in the data, giving better forecasts of the parameters. Forecasts can readily incorporate parameter uncertainty using the models. Bayesian Vector Autoregressive (BVAR) models are shown to significantly improve the forecast accuracy of VAR models for mortality rates based on Australian data. The Bayesian model allows for parameter uncertainty, shown to be a significant component of total risk.Mortality risk models have been developed to capture trends and common factors driving mortality improvement. Multiple factor models take many forms and are often developed and fitted to older ages. In order to capture trends from young ages it is necessary to take into account the richer age structure of mortality improvement from young ages to middle and then into older ages. The Heligman and Pollard (1980) model is a parametric model which captures the main features of period mortality tables and has parameters that are interpreted according to age range and effect on rates. Although time series techniques have been applied to model parameters in various parametric mortality models, there has been limited analysis of parameter risk using Bayesian techniques. This paper uses a Bayesian Vector Autoregressive (BVAR) model for the parameters of the Heligman-Pollard model and fits the model to Australian data. As VARmodels allow for dependence between the parameters of the Heligman-Pollard model they are flexible and better reflect trends in the data, giving better forecasts of the parameters. Forecasts can readily incorporate parameter uncertainty using the models. Bayesian Vector Autoregressive (BVAR) models are shown to significantly improve the forecast accuracy of VAR models for mortality rates based on Australian data. The Bayesian model allows for parameter uncertainty, shown to be a significant component of total risk

Corporate interest rate risk management with derivatives in Australia: empirical results

Financial and insurance theories explain that large widely-held corporations manage corporate risks if doing so is costective to reduce frictional costs such as taxes, agency costs and financial distress costs. A large number of previous empirical studies, most in the U.S., have tested the hypotheses underlying corporate risk management with financial derivative instruments. In order to quantify corporate hedge demand, most previous studies have used the ratio of principal notional amount of derivatives to company size, although they recognize that company size is not an appropriate proxy for financial risk. This paper analyzes the interest-rate-risk hedge demand by Australian companies, measured through the ratio of principal notional amount of interest rate derivatives to interest-rate-riskbearing liabilities. Modern panel data methods are used, with two panel data sets from 1998 to 2003 (1102 and 465 observations, respectively). Detailed information about interest-rate-risk exposures was available after manual data collection from financial annual reports, which was only possible due to specific reporting requirements in Australian accounting standards. Regarding the analysis of the extent of hedge, our measurement of interest-rate-risk exposures generates some significant results di erent from those found in previous studies. For example, this study shows that total leverage (total debt ratio) is not significantly important to interest-rate-risk hedge demand and that, instead, this demand is related to the specific risk exposure in the interest bearing part of the firms liabilities. This study finds significant relations of interest-rate-risk hedge to company size, floating-interest-rate debt ratio, annual log returns, and company industry type (utilities and non-banking financial institutions)