Ecological inference techniques: an empirical evaluation using data describing gender and voter turnout at New Zealand elections, 1893–1919

Summary.  The difference, if any, between men's and women's voting patterns is of particular interest to historians of gender and politics. For elections that were held before the introduction of opinion surveying in the 1940s, little data are available with which to estimate such differences. We apply six methods for ecological inference to estimate men's and women's voting rates in New Zealand (NZ), 1893–1919. NZ is an interesting case-study, since it was the first self-governing country where women could vote. Furthermore, NZ officials recorded the voting rates of men and women at elections, making it possible to compare estimates produced by methods for ecological inference with known true values, thus testing the efficacy of different methods for ecological inference for this data set. We find that the most popular methods for ecological inference, namely Goodman's ecological regression and King's parametric method, give poor estimates, as does the much debated neighbourhood method. However, King's non-parametric method, Chambers and Steel's semiparametric method and the Steel, Beh and Chambers homogeneous approach all gave good estimates that were close to the known values, with the homogeneous approach performing best overall. The success of these methods in this example suggests that ecological inference may be a viable option when investigating gender and voting. Moreover, researchers using ecological inference in other fields may do well to consider a range of statistical methods. This work is a significant NZ contribution to historical politics and the first quantitative contribution, in the area of NZ gender and politics.     

Block thresholding wavelet regression using SCAD penalty

This paper concerns wavelet regression using a block thresholding procedure. Block thresholding methods utilize neighboring wavelet coefficients information to increase estimation accuracy. We propose to construct a data-driven block thresholding procedure using the smoothly clipped absolute deviation (SCAD) penalty. A simulation study demonstrates competitive finite sample performance of the proposed estimator compared to existing methods. We also show that the proposed estimator achieves optimal convergence rates in Besov spaces.     

二维平衡单水平轮换模式设计研究

现行的轮换样本调查使用各种类型的单水平轮换模式,在西方各国均得到了广泛应用,但是也存在着一系列问题。因此,通过对各种类型的轮换模式进行统一,并进行系统化、理论化研究,最终得出了二维平衡单水平轮换模式设计方法,并对其应用优势进行了总结。这套设计方法不仅将轮换模式设计与后续的估计方法研究统一起来,而且还能够削减各类轮换偏差的负面影响,并能准确度量轮换样本之间的相关关系,最终得出更加准确的连续性抽样估计量。     

Construct redundancy in leader behaviors: A review and agenda for the future

Leadership remains a popular and heavily researched area in the social sciences. Such popularity has led to a proliferation of new constructs within the leadership domain. Here, we argue that such construct proliferation without pruning is unhealthy and violates the principle of parsimony. Our purpose was to examine construct redundancy via a comprehensive review of task-oriented, relational, passive, and inspirational leader behaviors as well as values-based and moral leadership behaviors. Our findings, as indexed via meta-analytic correlations, reveal that construct redundancy remains problematic for the leadership literature. In addition, many of the values-based and moral behavior models correlated heavily with constructs traditionally examined as outcome variables (e.g., trust, LMX, justice). Implications for future research are discussed in regards to construct redundancy and how to avoid endogeneity bias in primary studies in the leadership literature.     

Investigating recruitment and completion mode biases in online and door to door electronic surveys

Electronically assisted survey techniques offer several advantages over traditional survey techniques. However, they can also potentially introduce biases, such as coverage biases and measurement error. The current study compares the relative merits of two survey distribution and completion modes: email recruitment with internet completion; and door to door recruitment with either tablet or internet completion. Presentation mode is held constant so that we are able to separate the impacts of recruitment mode and completion mode on responses. Recruitment mode appeared to influence both response rates and which socio-demographic groups were represented. However, the difference between the two recruitment modes was relatively small. Completion mode appeared to have little or no impact on responses although it did influence completion times. The email distributed survey performed better with regard to time costs and the number of respondents obtained. Differences between the two survey modes appeared to be largely due to recruitment method rather than completion mode.     

Control variables and causal inference: a question of balance

A common motivation for adding control variables to statistical models is to reduce the potential for spurious findings when analyzing non-experimental data and to thereby allow for more reliable causal inferences. However, as I show here, unless all potential confounding factors are included in an analysis (which is unlikely to be achievable with most real-world data-sets), adding control variables to a model in many circumstances can make estimated effects of the variable(s) of interest to the researcher on the dependent variable less accurate. Due to this fact, in some circumstances omitting control variables, even those that affect the dependent variable and are correlated with the variable(s) of interest, may allow for more accurate estimates of the effect(s) of the variable(s) of interest.     

APPROXIMATING VOLATILITIES BY ASYMMETRIC POWER GARCH FUNCTIONS

ARCH/GARCH representations of financial series usually attempt to model the serial correlation structure of squared returns. Although it is undoubtedly true that squared returns are correlated, there is increasing empirical evidence of stronger correlation in the absolute returns than in squared returns. Rather than assuming an explicit form for volatility, we adopt an approximation approach; we approximate the γth power of volatility by an asymmetric GARCH function with the power index γ chosen so that the approximation is optimum. Asymptotic normality is established for both the quasi-maximum likelihood estimator (qMLE) and the least absolute deviations estimator (LADE) in our approximation setting. A consequence of our approach is a relaxation of the usual stationarity condition for GARCH models. In an application to real financial datasets, the estimated values for γ are found to be close to one, consistent with the stylized fact that the strongest autocorrelation is found in the absolute returns. A simulation study illustrates that the qMLE is inefficient for models with heavy-tailed errors, whereas the LADE is more robust.     

台湾股票指数期货的日内价格发现机制研究

通过使用 Hasbrouck,以及 Gonzalo 和 Granger 的价格发现模型,研究了新加坡衍生产品交易所和台湾期货交易所共同上市的台湾股票指数期货在两家交易所的信息传递效率,分析了上市相似指数期货合约的各个交易所间信息传递的机制.研究结果表明,两种台湾股票指数期货和它们的标的资产之间存在着一个共因子,而且新加坡交易所的摩根台指期货合约在价格发现的过程中起到了主导作用.究其根本,新加坡相对宽松的监管制度决定了它能够更有效地进行市场交易制度改革,从而占据价格发现的主体地位.对于存在竞争的交易所来讲,监管环境是决定其价格功能发挥的一个重要的因素.     

Increasing minority employment: Are you ready to recruit?

To increase employment from desired race or gender groups, employers nearly always first turn to recruiting from outside their organization. But a few years after such initiatives are undertaken, diversity numbers typically remain low or even decrease, turnover among recruits from the sought‐after groups is high, and the efforts are threatened by their recurrent cost. Employers need to break this fruitless cycle by thinking more strategically. Without an inclusive organizational climate that retains and fully utilizes minority employees after hire, simply recruiting more such employees will not lead to sustainable changes in workforce demographics. Drawing on empirical research, this paper describes six “red flags” that identify workplaces not ready to recruit. Only after organizational changes address the deficiencies identified by the red flags will the time for minority recruitment be at hand. But by then special focused recruitment may not be necessary; when employers change their workplace cultures to become truly inclusive, word gets around.     

The Validity of Social Media–Based Career Information

The use of social media expands the availability and sources of career information. However, the authorship of this information has changed from traditional print media and multimedia sources created by experts to social media–based career information created by the users themselves. Although variability in career information validity has been an issue for some time, rapid growth in the use of social media creates some unique challenges. The ease with which social media–based career information can spread creates the potential for rapid widespread dissemination of disinformation and biased perceptions. Potential sources of invalidity include intentional bias (with or without profit motive), unintentional bias, restricted range of experience, out‐of‐date information, popularity bias, similarity bias, and context deficiency. The authors examine potential sources of social media–based career information invalidity and suggest implications for practice to help individuals make the best use of such information.