How many ways can you look at a proportion?: cross-community vote transfers in Northern Ireland after the Belfast Agreement

Summary.  The single transferable vote is a method of election that allows voters to mark candidates in order of preference. Votes that are not required to elect a candidate are passed to the next candidate in the voter's order of preference. Results of this kind of election give us data about the degree to which voters of a given persuasion are willing to pass their vote to a candidate of a different persuasion. Measures of voters' willingness to pass a vote to a candidate of a different persuasion are of particular interest in places such as Northern Ireland, where communities differ by religion and national aspiration, and agreed new political institutions are based on cross-community power-sharing. How we quantify this voting data may depend on the questions that we want to answer, of course. But, to understand changes in how the voter orders her or his preference, one may need to ask several questions, and to quantify the results of the election in more than one way.     

RANDOMISATION AND THE 1975 SENATE BALLOT DRAW

“So the last shall be first, and the first last; for many be called, but few chosen.” Matthew 20:16 The “random” draw for positions on the Senate ballot papers in the 1975 election resulted in an apparently non-random ordering, to the possible advantage of one particular party. This paper assesses the statistical significance of the 1975 draw and looks at possible causes of the evident non-randomness. A simplified yet realistic mathematical model is used to describe conditions under which the so-called donkey vote can have an effect on the final outcome of the election, thereby confirming the widely-held belief that the order of parties on the Senate ballot paper is relevant. We examine other Senate elections between 1949 and 1983 for the existence of relevant non-randomness similar to the 1975 result. Finally, we report briefly on our submission to the 1983 Joint Select Committee on Electoral Reform, which led to an improvement in the randomisation procedure.     

A STATISTICAL MODEL FOR DUPLICATE TOURNAMENTS IN GAMES OF LUCK AND SKILL

Many games played between two contestants start with a random deal, which introduces luck from the deal. The concept of ‘duplication’, commonly employed in Bridge tournaments, can be used to nullify that luck in a tournament. This paper poses a model for the contest between any two players and analyses the model for a tournament which employs the duplication principle. Two example tournaments on a new game are analysed.     

中国金融风险周期监测与央行货币政策非对称性效果识别

本文采用时变参数因子增广向量自回归模型（TVP-FAVAR）,并基于动态模型平均法测度了金融子系统变量的时变权重,通过加权计算得到我国金融风险周期指数（FRI）。然后改进构建了分区制货币政策模型系统,并采用逻辑平滑转换向量自回归模型（LST-VAR）研究了高低区制下,价格型和数量型货币政策对金融风险的传导效应,在此基础上,设计并测度了我国货币政策的时滞效应。研究发现,我国金融风险具有明显的两区制特征,样本区间内FRI大多时期处于低风险区制,而高风险区制的时间段与国内外重大金融风险事件相吻合。两种紧缩的货币政策均有利于抑制金融风险及其波动,且在高风险区制的抑制效应更为显著。对于货币政策时滞效应,数量型货币政策对金融风险的抑制作用大于价格型货币政策,但2008、2012和2015年三个高金融风险期的时滞效应均较小。最后,根据研究结果提出相应政策建议。     

The Promise of Prediction Contests

This article examines the prediction contest as a vehicle for aggregating the opinions of a crowd of experts. After proposing a general definition distinguishing prediction contests from other mechanisms for harnessing the wisdom of crowds, we focus on point-forecasting contests—contests in which forecasters submit point forecasts with a prize going to the entry closest to the quantity of interest. We first illustrate the incentive for forecasters to submit reports that exaggerate in the direction of their private information. Whereas this exaggeration raises a forecaster's mean squared error, it increases his or her chances of winning the contest. And in contrast to conventional wisdom, this nontruthful reporting usually improves the accuracy of the resulting crowd forecast. The source of this improvement is that exaggeration shifts weight away from public information (information known to all forecasters) and by so doing helps alleviate public knowledge bias. In the context of a simple theoretical model of overlapping information and forecaster behaviors, we present closed-form expressions for the mean squared error of the crowd forecasts which will help identify the situations in which point forecasting contests will be most useful.     

Identifying Structural Models of Committee Decisions With Heterogeneous Tastes and Ideological Bias

In practice, members of a committee often make different recommendations despite a common goal and shared sources of information. We study the nonparametric identification and estimation of a structural model, where such discrepancies are rationalized by the members’ unobserved types, which consist of ideological bias while weighing different sources of information, and tastes for multiple objectives announced in the policy target. We consider models with and without strategic incentives for members to make recommendations that conform to the final committee decision. We show that pure-strategy Bayesian Nash equilibria exist in both cases, and that the variation in common information recorded in the data helps us to recover the distribution of private types from the members’ choices. Building on the identification result, we estimate a structural model of interest rate decisions by the Monetary Policy Committee (MPC) at the Bank of England. We find some evidence that the external committee members are less affected by strategic incentives for conformity in their recommendations than the internal members. We also find that the difference in ideological bias between external and internal members is statistically insignificant. Supplementary materials for this article are available online.     

Power-law scaling behavior analysis of financial time series model by voter interacting dynamic system

We investigate the power-law scaling behaviors of returns for a financial price process which is developed by the voter interacting dynamic system in comparison with the real financial market index (Shanghai Composite Index). The voter system is a continuous time Markov process, which originally represents a voter's attitude on a particular topic, that is, voters reconsider their opinions at times distributed according to independent exponential random variables. In this paper, the detrended fluctuation analysis method is employed to explore the long range power-law correlations of return time series for different values of parameters in the financial model. The findings show no indication or very weak long-range power-law correlations for the simulated returns but strong long-range dependence for the absolute returns. The multiplier distribution is studied to demonstrate directly the existence of scale invariance in the actual data of the Shanghai Stock Exchange and the simulation data of the model by comparison. Moreover, the Zipf analysis is applied to investigate the statistical behaviors of frequency functions and the distributions of the returns. By a comparative study, the simulation data for our constructed price model exhibits very similar behaviors to the real stock index, this indicates somewhat rationality of our model to the market application.     

Polling opinions in the 2005 election

The winners of the General Election in May were not the political parties but the opinion pollsters, says Paul Baines . After 1992, when most pollsters predicted a hung parliament rather than a Conservative win, and 2001, when they overestimated the Labour lead, the 2005 election result was awaited by many pollsters with trepidation. Would their final eve-of-poll results be accurate or not?     

Was the conservative majority predictable?

Canada's $41{\rm st}$ national general election saw the Conservative Party increase its seat count from 143 to 166, thus giving it a majority of the national parliament's 308 seats. By contrast, nearly all of the pre‐election seat count forecasts predicted a Conservative minority only. We examine the extent to which simple statistical models could or could not have predicted the Conservative majority prior to the election. We conclude that, by using data from the previous (2008) election appropriately, the Conservative majority should have been anticipated as the most likely outcome. The Canadian Journal of Statistics 39: 721–733; 2011. © 2011 Statistical Society of Canada     

Spatial modelling of the two‐party preferred vote in Australian federal elections: 2001–2016

We examine the relationships between electoral socio‐demographic characteristics and two‐party preferences in the six Australian federal elections held between 2001 and 2016. Socio‐demographic information is derived from the Australian Census which occurs every 5 years. Since a census is not directly available for each election, an imputation method is employed to estimate census data for the electorates at the time of each election. This accounts for both spatial and temporal changes in electoral characteristics between censuses. To capture any spatial heterogeneity, a spatial error model is estimated for each election, which incorporates a spatially structured random effect vector. Over time, the impact of most socio‐demographic characteristics that affect electoral two‐party preference do not vary, with age distribution, industry of work, incomes, household mobility and relationships having strong effects in each of the six elections. Education and unemployment are among those that have varying effects. All data featured in this study have been contributed to the eechidna R package (available on CRAN).     

Dynamic Bayesian analysis for irregularly and incompletely observed contingency tables

Pre-election surveys are usually conducted several times to forecast election results before the actual voting. It is common that each survey includes a substantial number of non-responses and that the successive survey results are seen as a stochastic multinomial time series evolving over time. We propose a dynamic Bayesian model to examine how multinomial time series evolve over time for the irregularly observed contingency tables and to determine how sensitively the dynamic structure reacts to an unexpected event, such as a candidate scandal. Further, we test whether non-responses are non-ignorable to determine if non-responses need to be imputed for better forecast. We also suggest a Bayesian method that overcomes the boundary solution problem and show that the proposed method outperforms the previous Bayesian methods. Our dynamic Bayesian model is applied to the two pre-election surveys for the 2007 Korea presidential candidate election and for the 1998 Ohio general election.     

Ties in one block comparison experiments: a generalization of the Mallows–Bradley–Terry ranking model

This study is concerned with the extension of the Mallows–Bradley–Terry ranking model for one block comparison consisting of all the items of interest to situations which allow an expression of no preference. We consider a modification of the Mallows–Bradley–Terry ranking model by introducing an additional parameter, called an index of discrimination, in the model. This permits ties in the model. The maximum likelihood estimates of the parameters are found using a Maximization–Minimization algorithm: the evaluation of the mathematical expectations involved in the log-likelihood equation is obtained by generating samples of Monte Carlo Markov chain from the stationary distribution. In addition, a simulation study for asymptotic properties assessment has been made. The proposed method is applied to analyze data election.     

基于LSTAR模型的中国股市泡沫风险识别

本文在非线性模型框架下拟合中国主要股价指数的真实数据生成过程,并提出股市泡沫风险识别方法,较Phillips et al.（2011）提出的上确界单位根(SADF)方法具备更好的效果,能够精准预判股市泡沫风险进而为防范化解金融风险的政策措施提供参考。实证检验发现,主要股价指数的波动均存在逻辑平滑转换自回归(LSTAR)模型描述的非线性特征,自推出以来,四大股价指数均存在泡沫风险,上证指数存在六个主要的持续期,深圳成指存在四个主要的持续期,沪深300指数存在两个主要持续期,而创业板指数存在三个持续期。总体来看,创业板指数的泡沫生成时间会先于其它三大指数,可以作为预警中国股票市场泡沫风险的先行指标,且2015年7月之后的中国股票市场并不存在泡沫风险。     

Inference and rare event simulation for stopped Markov processes via reverse-time sequential Monte Carlo

We present a sequential Monte Carlo algorithm for Markov chain trajectories with proposals constructed in reverse time, which is advantageous when paths are conditioned to end in a rare set. The reverse time proposal distribution is constructed by approximating the ratio of Green’s functions in Nagasawa’s formula. Conditioning arguments can be used to interpret these ratios as low-dimensional conditional sampling distributions of some coordinates of the process given the others. Hence, the difficulty in designing SMC proposals in high dimension is greatly reduced. Empirically, our method outperforms an adaptive multilevel splitting algorithm in three examples: estimating an overflow probability in a queueing model, the probability that a diffusion follows a narrowing corridor, and the initial location of an infection in an epidemic model on a network.     

非线性协整检验与“费雪效应”机制分析

本文分别在线性Engle-Granger协整模型和非线性指数平滑迁移自回归误差修正模型 (ESTAR-ECM) 的框架下,对我国名义利率与通货膨胀率序列进行了长期均衡关系的检验。发现线性协整模型不能捕捉到我国名义利率与通货膨胀率的长期均衡关系,而对于ESTAR-ECM模型,无论利用商业银行1年期贷款利率还是7天期银行间同业拆借利率作为名义利率的代理变量,均证实名义利率与通货膨胀率具有长期稳定的均衡关系,表明“费雪效应”在我国是成立的。但由于“费雪效应”系数小于1,表明名义利率与通货膨胀率之间仅存在弱的“费雪效应”。其意义在于,我国利率政策对稳定通胀预期、抑制通货膨胀具有一定的正面效应,但由于利率对通货膨胀反应不足,导致完全依靠利率政策控制目前较高的通货膨胀有一定的困难。     

提高排污费能促进企业创新吗?——兼论对我国环保税开征的启示

考虑到我国2018年首征的环保税是由原排污费采取“税负平移”方式改制而成,本文以国发〔2007〕15号文颁布实施后各省级政府陆续调整二氧化硫(SO2)排污费标准为准实验;以2005-2014 年深沪股市重污染行业的上市公司为研究样本;采用双重差分方法(DID)研究了SO2排污费标准提高带来的企业创新效应,并以此探讨对环保税政策的相关启示。研究发现:排污费征收标准的提高总体上抑制了企业创新,然而当环保税税额提高到一定程度,环保税征收可促进企业进行技术创新。由此对我国环保税改革的启示在于,需进一步提高我国现行环保税税率并出台相应的配套政策。本文主要创新点在于通过外生政策冲击并采用DID 模型,相对有效处理了环境规制强度与企业创新之间的内生性问题,研究结论对由原排污费改制而来的我国环保税的进一步完善具有相应的政策指导意义。     

关联方增信与资产证券化信用风险溢价——基于底层资产风险的统计分析

本文着眼于企业资产支持证券(ABS)市场的信用风险溢价,探讨关联方增信的效果。研究表明,采用关联方增信的ABS风险溢价较高;当同一主体先前发行的ABS评级上调时,新发行ABS的风险溢价会因为采用关联方增信而升高。本文进一步探究了产生上述现象的原因,一方面,关联方增信使得集团内部风险集聚;另一方面,企业的道德风险使得原ABS的评级上调成为反映新ABS底层资产质量变差的负面信号,从而影响投资者的定价判断。本研究揭示了关联方增信可能存在的道德风险问题。通过分析ABS丰富的底层资产统计特征,本文发现集团风险集聚导致ABS的底层资产质量下降,进而提高了企业的融资成本。本文建议监管机构可以通过适当限制关联方增信或加强监管的方式保障我国企业资产证券化市场的健康持续发展。     

Non-nested model selection based on the quantiles and it’s application in time series

We consider the problem of model selection based on quantile analysis and with unknown parameters estimated using quantile leasts squares. We propose a model selection test for the null hypothesis that the competing models are equivalent against the alternative hypothesis that one model is closer to the true model. We follow with two applications of the proposed model selection test. The first application is in model selection for time series with non-normal innovations. The second application is in model selection in the NoVas method, short for normalizing and variance stabilizing transformation, forecast. A set of simulation results also lends strong support to the results presented in the paper.     

税收激励如何影响企业创新?——来自固定资产加速折旧政策的经验证据

本文借助财税〔2014〕75号、〔2015〕106号文件推出固定资产加速折旧政策这一“准自然 实验”来识别税收激励与企业创新的因果关系。利用我国上市公司2010—2017年的专利申请、终止、引用信息和财务报表数据,基于双重差分模型回归发现:数量维度上,固定资产加速折旧政策显著增加了企业研发投入和专利申请量;质量维度上,高创新含量的发明申请增长幅度大于“短平快”的实用新型和外观设计专利申请,企业专利结构改善。固定资产加速折旧政策还显著减少了授权专利的未到期终止数量、提高了发明申请的平均被引次数。拓展检验显示,该政策显著提升了处理组企业的盈利绩效与资本市场价值,且对民营企业(融资约束较重)与高资本密集度行业(加速折旧的潜在收益较大)的激励更大。研究结论表明,减税降费能够激励企业创新“提质增效”、助推我国经济高质量发展。     

Cox模型和寿险退保研究中的比例危险性

利用生存分析研究寿险退保问题是一个很好的工具，因为可以将寿险保单的持续期（persistency duration）视为生存期长，而将保单的退保或失效看作一个“保单生命”的结束，这其中的保单退保或失效就成为生存研究的目标事件。而导致保单失效的因素会有很多，只有通过利用Cox比例危险模型拟合寿险退保数据以分析影响客户退保的原因，并在对Cox模型的比例危险假设进行检验时，发现部分影响因素并不遵守此前提条件，从而推理得到这些影响因素在不同的时间段对客户退保的影响方式不同。也就是说，其影响有短期效应和长期效应之分。