When being overpaid makes me feel good about myself: It depends on how the other feels

The present research examined whether the emotions of others (i.e., disappointment versus happiness with respect to a received outcome) influence own self-esteem when being overpaid. Results from two experiments demonstrated that participants reported higher performance self-esteem when the other expressed happiness rather than disappointment. This effect was only found in the condition where one was overpaid relative to the condition where one did not yet know one’s own outcome. In the second experimental study we further found that this interaction between the emotion of the other and the distribution situation only emerged among participants low (relative to high) in personal need for structure. Implications with respect to the relationship between overpayment and self-esteem and the interpersonal effects of emotions in this process are discussed.     

Perceived facilitators and barriers to saving among low-income youth

Asset-based social welfare programs focus on helping low- to moderate-income citizens to accumulate wealth in the form of homeownership, savings, small businesses, and higher education. Individual development accounts, savings accounts in which account holders’ deposits are matched, are a vehicle often used in these programs. In a national demonstration of individual development accounts for children (children's savings accounts), low-income youth were interviewed to learn what helped them to save and what made it difficult to save. We describe the young people's perceptions of these factors, and conclude with implications for policy and program design.     

A class of exponential-type ratio estimators of a general parameter

This paper addresses the problem of estimating a general parameter using information on an auxiliary variable X. We have suggested a class of exponential-type ratio estimators for the parameter and its properties are studied. It is identified that the estimators due to Upadhyaya et al. [Journal of Statistical Theory and Practice (2011), 5(2), 285–302] and Yadav and Kadilar [Revista Columbiana de Estadistica, (2013), 36(1), 145–152] are members of the proposed estimator. We have also shown that the suggested estimator is more efficient than the estimators of Upadhyaya et al. (2011 Upadhyaya, L.N., Singh, H.P., Chatterjee, S., Yadav, R. (2011). Improved ratio and product exponential type estimators. J. Stat. Theo. Pract. 5 (2): 285–302.[Taylor &; Francis Online] , [Google Scholar]) and Yadav and Kadilar (2013 Yadav, S.K., Kadilar, C. (2013). Improved exponential type ratio estimator of population variance. Revis. Colum. de Estadist. 36(1): 145–152. [Google Scholar]). Numerical illustration is provided in support of the present study.     

Linearity,symmetry, and equidistance in semantic differential scales for measuring images of self and images of others

ABSTRACT

Violations of linearity, symmetry, and equidistance of scale points in semantic differential scales may be due to respondents failing to figure out antonyms, to a positivity bias, or to respondents curtailing their reading the options. Multiple correspondence analysis on data provided by a randomized between-subjects experiment (split-ballot), using a web survey of 537 German residents, shows that bipolar semantic differential scales allow for linear measurement and conceal no positivity bias, and that using not suitable adjective pairs in semantic differential scales destroys symmetry.     

Adjustment for nonresponse with variables from different sources: Bias correction and precision loss,with application to the Swiss European Social Survey 2012

ABSTRACT

Adjustment for nonresponse should reduce the nonresponse bias without decreasing the precision of the estimates. Adjustment for nonresponses are commonly based on socio-demographic variables, although these variables may be poorly correlated with response propensities and with variables of interest. Such variables nevertheless have the advantage of being available for all sample units, whether or not they are participating in the survey. Alternatively, adjustment for nonresponse can be obtained from a follow-up survey aimed at sample units which did not participate in the survey and from which the variables are designed to be correlated with response propensities. However, information collected through these follow-up surveys is not available for people in the sample who participated neither in the survey nor in its nonresponse follow-up. These two sets of variables when used in a nonresponse model for the Swiss European Social Survey 2012 differ only slightly with regard to their effect on bias correction and on the precision of estimates. The variables from the follow-up are performing slightly better. In both cases, the adjustment for nonresponse performs poorly.     

Is the web a promising tool for data collection in developing countries? An analysis of the sample bias of 10 web and face-to-face surveys from Africa,Asia, and South America

Whereas the sample composition biases of web surveys have been discussed extensively for developed countries, studies for developing countries are scarce. This article helps to fill that gap by comparing similar non-probability-based web surveys (WEB) and probability-based face-to-face (F2F) surveys both to each other and to the labor force. An analysis of WageIndicator data on work and wages derived from surveys held in 2009–2013 in 10 developing countries (WEB-sample N = 9135; F2F-sample N = 14,659), shows that F2F samples resemble the labor force to a larger extent than web samples do. In both cases, individuals in their 20s and early 30s are overrepresented, and younger and older respondents are underrepresented. This trend is more pronounced in WEB than in F2F samples. However, the differences converge in countries with higher Internet usage. A comparison of the WEB and F2F samples shows that compositions differ greatly, with web respondents being younger, more often male, more often living alone, and higher educated, although these differences are smaller in countries with higher Internet usage. Given the cost differences between the two survey modes, one should nevertheless consider the potential of web surveys as an instrument to gain explorative insights, specifically when searching for individuals with particular characteristics.     

基于logistic模型的外来人口婚姻迁移的影响因素分析——以珠三角某地区为例

婚姻迁移是人口迁移的一个方面,且增多趋势愈见明显。动机研究是人口迁移相对集中的关注问题。但是关于以迁入地为基点对婚姻迁移的影响因素分析相对较少。本文试图以某地区为例,研究其外来人口中婚姻迁移行为发生的影响因素,主要包括个人、户籍、经济、就业和城市适应五大因素,并引入logistic模型对测量变量进行统计分析。结果表明,个人因素对婚姻迁移的贡献最大,除了就业因素外,其他因素的贡献相似。尤其指出的是随着外来人口的城市适应程度提高,婚姻迁移的可能性将会增加。由此说明,外来人口城市生活的再社会化程度将为他们的社会融合奠定基础。     

An integrative model of leadership behavior

Decades of questionnaire and interview studies have revealed various leadership behaviors observed in successful leaders. However, little is known about the actual behaviors that cause those observations. Given that lay observers are prone to cognitive biases, such as the halo effect, the validity of theories that are exclusively based on observed behaviors is questionable. We thus follow the call of leading scientists in the field and derive a parsimonious model of leadership behavior that is informed by established psychological theories. Building on the taxonomy of Yukl (2012), we propose three task-oriented behavior categories (enhancing understanding, strengthening motivation and facilitating implementation) and three relation-oriented behavior categories (fostering coordination, promoting cooperation and activating resources), each of which is further specified by a number of distinct behaviors. While the task-oriented behaviors are directed towards the accomplishment of shared objectives, the relation-oriented behaviors support this process by increasing the coordinated engagement of the team members. Our model contributes to the advancement of leadership behavior theory by (1) consolidating current taxonomies, (2) sharpening behavioral concepts of leadership behavior, (3) specifying precise relationships between those categories and (4) spurring new hypotheses that can be derived from existing findings in the field of psychology. To test our model as well as the hypotheses derived from this model, we advocate the development of new measurements that overcome the limitations associated with questionnaire and interview studies.     

The effect of cognitive diversity on the illusion of control bias in strategic decisions: An experimental investigation

By integrating cognitive diversity into debiasing literature, this paper contributes towards opening the black box of executive judgment. Based on information processing theory we investigate the role of cognitive diversity in strategic decision making. We apply a vignette-based experimental research design to examine the effect of cognitive diversity in teams on decision maker's illusion of control. The results of these experiments provide evidence for a positive influence of high cognitive diversity for debiasing judgment while similarly indicating no such effect for groups with low cognitive diversity. These findings suggest that group composition aspects can play an important role for improving judgment in decision making teams and open promising new avenues for studying debiasing in behavioral strategy research.     

On making causal claims: A review and recommendations

Social scientists often estimate models from correlational data, where the independent variable has not been exogenously manipulated; they also make implicit or explicit causal claims based on these models. When can these claims be made? We answer this question by first discussing design and estimation conditions under which model estimates can be interpreted, using the randomized experiment as the gold standard. We show how endogeneity – which includes omitted variables, omitted selection, simultaneity, common-method variance, and measurement error – renders estimates causally uninterpretable. Second, we present methods that allow researchers to test causal claims in situations where randomization is not possible or when causal interpretation could be confounded; these methods include fixed-effects panel, sample selection, instrumental variable, regression discontinuity, and difference-in-differences models. Third, we take stock of the methodological rigor with which causal claims are being made in a social sciences discipline by reviewing a representative sample of 110 articles on leadership published in the previous 10 years in top-tier journals. Our key finding is that researchers fail to address at least 66% and up to 90% of design and estimation conditions that make causal claims invalid. We conclude by offering 10 suggestions on how to improve non-experimental research.