Katrina\u27s Animal Legacy: The PETS Act

This article discusses issues related to the federal Pets Evacuation and Transportation Standards Act of 2006 (PETS Act), which was signed into law in the aftermath of Hurricane Katrina. Issues discussed in this article include: Various problems concerning animal evacuations and sheltering that Hurricane Katrina brought to light; Provisions of the PETS Act and related laws and policies which were developed in response to the tragedies brought about by Hurricane Katrina; and Strengths and weaknesses of the PETS Act and recommends next steps to improve implementation of the PETS Act

Quarantine Risk Analysis

Australia’s quarantine policy is based on the concept of manageable risk, which is underpinned by quarantine risk analysis, which this article examines with particular reference to recommendations of the 1996 Australian Quarantine Review. Quarantine risk assessment addresses disease concerns associated with any particular proposed import and may also require detailed examination of possible economic and environmental effects. The degree of quantification varies, and more quantitative approaches may be either deterministic or stochastic. Assessments consider both the probability of an event occurring and its consequences, including the direct economic effect of any introduction of an exotic disease.International Relations/Trade,

An empirical behavioral model of liquidity and volatility

We develop a behavioral model for liquidity and volatility based on empirical regularities in trading order flow in the London Stock Exchange. This can be viewed as a very simple agent based model in which all components of the model are validated against real data. Our empirical studies of order flow uncover several interesting regularities in the way trading orders are placed and cancelled. The resulting simple model of order flow is used to simulate price formation under a continuous double auction, and the statistical properties of the resulting simulated sequence of prices are compared to those of real data. The model is constructed using one stock (AZN) and tested on 24 other stocks. For low volatility, small tick size stocks (called Group I) the predictions are very good, but for stocks outside Group I they are not good. For Group I, the model predicts the correct magnitude and functional form of the distribution of the volatility and the bid-ask spread, without adjusting any parameters based on prices. This suggests that at least for Group I stocks, the volatility and heavy tails of prices are related to market microstructure effects, and supports the hypothesis that, at least on short time scales, the large fluctuations of absolute returns are well described by a power law with an exponent that varies from stock to stock

\u27Dear Colleague\u27 letter

\u27Dear Colleague\u27 letter for the September 2006 briefing on Children\u27s Well-Being and the Role of Workplace Flexibility for Parents event. Prepared on behalf of Workplace Flexibility 2010 by Senator Mike DeWine and Senator Christopher J. Dodd

An empirical behavioral model of price formation

Although behavioral economics has demonstrated that there are many situations where rational choice is a poor empirical model, it has so far failed to provide quantitative models of economic problems such as price formation. We make a step in this direction by developing empirical models that capture behavioral regularities in trading order placement and cancellation using data from the London Stock Exchange. For order placement we show that the probability of placing an order at a given price is well approximated by a Student distribution with less than two degrees of freedom, centered on the best quoted price. This result is surprising because it implies that trading order placement is symmetric, independent of the bid-ask spread, and the same for buying and selling. We also develop a crude but simple cancellation model that depends on the position of an order relative to the best price and the imbalance between buying and selling orders in the limit order book. These results are combined to construct a stochastic representative agent model, in which the orders and cancellations are described in terms of conditional probability distributions. This model is used to simulate price formation and the results are compared to real data from the London Stock Exchange. Without adjusting any parameters based on price data, the model produces good predictions for the magnitude and functional form of the distribution of returns and the bid-ask spread

Trust in justice and the legitimacy of legal authorities: topline findings from a European comparative study

Issues of public trust in justice and institutional legitimacy are becoming increasingly salient in debate about criminal justice across Europe. Legitimate authority can be defined as having three interlinked elements: (a) legality (acting according to the law); (b) shared values (values that are shared by those with authority and those subject to that authority); and (c) consent (the sense amongst the policed of a moral obligation to obey the authority). According to this definition, legitimacy is present not only when individuals recognise the authority of institutions and feel a corresponding duty of deference to them (consent); it is also present when individuals believe that justice institutions have a proper moral purpose (shared values), and that justice institutions follow their own rules as well as the rules that govern everyone in society (legality). With this definition in mind, we analyse in this chapter data from the fifth European Social Survey on relationships between public trust in justice institutions and public perceptions of the legitimacy of these institutions

Non-linear minimum variance estimation for discrete-time multi-channel systems

A nonlinear operator approach to estimation in discrete-time systems is described. It involves inferential estimation of a signal which enters a communications channel involving both nonlinearities and transport delays. The measurements are assumed to be corrupted by a colored noise signal which is correlated with the signal to be estimated. The system model may also include a communications channel involving either static or dynamic nonlinearities. The signal channel is represented in a very general nonlinear operator form. The algorithm is relatively simple to derive and to implement