Victory margins and the paradox of voting

This paper addresses a simple question: why do people vote? Though simple, this question remains unanswered despite the considerable attention it has received. In this paper, I show that purely rational–instrumental factors explain a large fraction of turnout variations, provided that the effect of the margin of victory on implemented policy is considered. I extend Myerson's models of elections based on Poisson games, and show that, when platforms are responsive to vote shares, the predictions of the model become consistent with several stylized facts, including the secular fall in turnout rates in the US.     

Estimating the Size of a Criminal Population from Police Records Using the Truncated Poisson Regression Model

The truncated Poisson regression model is used to arrive at point and interval estimates of the size of two offender populations, i.e. drunk drivers and persons who illegally possess firearms. The dependent capture–recapture variables are constructed from Dutch police records and are counts of individual arrests for both violations. The population size estimates are derived assuming that each count is a realization of a Poisson distribution, and that the Poisson parameters are related to covariates through the truncated Poisson regression model. These assumptions are discussed in detail, and the tenability of the second assumption is assessed by evaluating the marginal residuals and performing tests on overdispersion. For the firearms example, the second assumption seems to hold well, but for the drunk drivers example there is some overdispersion. It is concluded that the method is useful, provided it is used with care.     

Modelling soccer matches using bivariate discrete distributions with general dependence structure

In this paper copulas are used to generate bivariate discrete distributions. These distributions are fitted to soccer data from the English Premier League. An interesting aspect of these data is that the primary variable of interest, the discrete pair shots-for and shots-against, exhibits negative dependence; thus, in particular, we apply bivariate Poisson-related distributions that allow such dependence. The paper focuses on Archimedian copulas, for which the dependence structure is fully determined by a one-dimensional projection that is invariant under marginal transformations. Diagnostic plots for copula fit based on this projection are adapted to deal with discrete variables. Covariates relating to within-match contributions such as numbers of passes and tackles are introduced to explain variability in shot outcomes. The results of this analysis would appear to support the notion that playing the 'beautiful game' is an effective strategy—more passes and crosses contribute to more effective play and more shots on the goal.     

Valuing Food Store Access: Policy Implications for the Food Stamp Program

Food stamp recipients may lack access to larger stores, reducing the availability of nutritious food. Reliance on smaller stores may have undesirable impacts. Policy alternatives include limiting food stamp redemption to larger stores and subsidizing store development. I estimate that limiting redemption to supermarkets and grocery stores, or supermarkets alone, results in losses ranging from $499.2 million to $1.05 billion, or $1.17 billion to $2.44 billion (respectively) annual loss in food stamp recipient welfare nationwide. The impact of improving access is also significant, ranging from $333.6 million to $931.2 million.     

基于截尾分布理论预测开放式基金大额赎回量

提出了开放式基金的巨额赎回量和大额赎回量的概念，将复合泊阿松分布和截尾分布理论运用在大额赎回量概率计算之中，得到了计算公式。由于开放式基金流动性风险主要来自于大额赎回量，因此使用截尾分布方法预测未来近期的大额赎回量更合适。推导出了正态分布下大额赎回量的期望和方差计算公式。为基金管理人合理规避这种流动性风险提供了一种预测方法。     

How does news sentiment affect the states of Japanese stock return volatility?

This paper examines the impact of public news sentiment on the volatility states of firm-level returns on the Japanese Stock market. We firstly adopt a novel Markov Regime Switching Long Memory GARCH (MRS-LMGARCH), which is employed to estimate the latent volatility states of intraday stock return. By using the RavenPack Dow Jones News Analytics database, we fit discrete choice models to investigate the impact of news sentiment on changes of volatility states of the constituent stocks in the TOPIX Core 30 Index. Our findings suggest that news occurrence and sentiment, especially those of macro-economic news, are a key factor that significantly drives the volatility state of Japanese stock returns. This provides essential information for traders of the Japanese stock market to optimize their trading strategies and risk management plans to combat volatility.     

Estimation in the generalized Poisson model via robust testing

An estimation method is presented which compromises robust efficiency with computational feasibility in the case of the generalized Poisson model. The formal setup is built on flexible nonparametric extensions of the underlying model. The estimation efficiency is expressed via minimax properties of tests resulting from expansions of estimators. The nonparametric neighborhoods related to the proposed score function are exemplified and a real data case is analysed. The resulting method balances several qualitative features of statistical inference: strong differentiability (asymptotic derivations are more accurate), efficiency and natural model extension (quality of formal basic assumptions).     

基于网格技术的城市公共汽车到站时刻预测研究

在介绍了网格技术的含义和基础知识后,结合我国目前公共汽车预测研究的现状,设计了基于网格技术的城市公共汽车到站时间的预测系统,并对其进行了详细的设计。     

“Itô's Lemma” and the Bellman Equation for Poisson Processes: An Applied View

Using the Hamilton-Jacobi-Bellman equation, we derive both a Keynes-Ramsey rule and a closed form solution for an optimal consumption-investment problem with labor income. The utility function is unbounded and uncertainty stems from a Poisson process. Our results can be derived because of the proofs presented in the accompanying paper by Sennewald (2006). Additional examples are given which highlight the correct use of the Hamilton-Jacobi-Bellman equation and the change-of-variables formula (sometimes referred to as ``Itô's Lemma'') under Poisson uncertainty.     

THE JOINT ARRIVAL AND DEPARTURE PROCESS FOR THE M/M/l QUEUE

We consider the M/M/1-queue and derive an explicit expression for the joint distribution of the number of arrivals and the number of departures in [0, t), given the number of customers initially present. The derivation is almost purely combinatorial, it avoids the use of generating functions, and immediately yields a simple probabilistic interpretation of the result.