Does Prior Banking Experience Matter? Differences of the Banked and Unbanked in Individual Development Accounts

Using data from the 4-year American Dream Demonstration, this study compares saving performance and program participation of banked (n = 1,538) and unbanked participants (n = 466) enrolled in 14 IDA programs. The study shows banked participants had $2.74 higher average monthly net deposit (p < 0.05); 5% higher deposit frequency (p < 0.001); and 42% less odds of drop out than unbanked participants (p < 0.001). Moreover, program characteristics such as financial education, monthly saving targets, peer group meetings, and direct deposit are important predictors of program performances. Individual characteristics such as race/ethnicity, home ownership, and income are significantly associated with program performance.     

The importance of sector‐stereotypical images in relation to job pursuit intentions

This study broadens the concept of employer image and demonstrates the relevance of applicants’ sector image when looking for employment in either nonprofit or for‐profit organizations. We apply the Stereotype Content Model to conceptualize image through perceived competence and warmth and use multilevel analyses on data from final‐year Master’s students. Results show the importance of the sector‐stereotypical image and are partially in line with our hypotheses. Job pursuit intentions for specific organizations are predicted by both the organizations’ as well as the respective sectors’ perceived warmth and competence. Pursuit intentions for the for‐profit sector are predicted only by the image of that sector. However, the intention to pursue employment in the nonprofit sector is predicted by both its competence and warmth as well as by the perceived warmth of its organizations. These findings are discussed in view of a trickle‐down effect and compared to previous findings on sector image among consumers.     

The Influence of Parental Financial Socialization on Youth’s Financial Behavior: Evidence from Ghana

How youth manage their money may influence their transitions to adulthood. This may be particularly true for youth in sub-Saharan Africa (SSA), where many youth and young adults lack access to economic opportunities. Parental financial socialization is associated with youth financial knowledge, attitudes, and behavior in research studies conducted mostly in the US, yet little is known about the financial lives of youth living in SSA. Propensity score analysis and robust standard errors with multiple regression were used to examine the relationship between parental financial socialization and youth financial behaviors among a sample of 3,623 youth ages 12–19 and a parent or other adult guardian living in eight out of 10 regions of Ghana. Findings indicated that both parent- and youth-perceived parental financial socialization was a strong and consistent predictor of youth financial behaviors, as was receipt of earned income. Practitioners interested in empowering youth through financial education and inclusion programs might consider how to involve parents and other family members in programs and capitalize on opportunities for youth to have some earned income while they learn how to manage money.     

COMMON COMPONENTS OF RISK AND UNCERTAINTY ATTITUDES ACROSS CONTEXTS AND DOMAINS: EVIDENCE FROM 30 COUNTRIES

Attitudes towards risk and uncertainty have been indicated to be highly context‐dependent, and to be sensitive to the measurement technique employed. We present data collected in controlled experiments with 2,939 subjects in 30 countries measuring risk and uncertainty attitudes through incentivized measures as well as survey questions. Our data show clearly that measures correlate not only within decision contexts or measurement methods, but also across contexts and methods. This points to the existence of one underlying “risk preference”, which influences attitudes independently of the measurement method or choice domain. We furthermore find that answers to a general and a financial survey question correlate with incentivized lottery choices in most countries. Incentivized and survey measures also correlate significantly between countries. This opens the possibility to conduct cultural comparisons on risk attitudes using survey instruments.     

The Partisan Impact of Congressional Redistricting: The Case of Texas, 2001–2003*

Objective. In this article we assess the partisan effects of five plans proposed by Republican state legislators during Texas' 2003 congressional redistricting. Methods. Using the JudgeIt statistical program developed by Gelman and King (2001) , and data provided by the Texas Legislative Council, we assess the bias, responsiveness, and the probability that the Democratic Party wins each district for each plan. Results. All five Republican plans, including the one enacted, are strongly biased in favor of the Republican Party. Conclusions. Texas' Democratic legislators were wise to use every parliamentary maneuver available to block the enactment of a new congressional map. Beyond affecting the partisan makeup of the Texas delegation, Texas' redistricting has national implications because it adds to the GOP's narrow majority in the U.S. House of Representatives.     

Socio‐Emotional Context and Adolescents' Decision Making: The Experience of Regret and Relief After Social Comparison

Many studies indicate that adolescents are hypersensitive to rewards in salient socio‐emotional contexts. However, little is known about adolescents' sensitivity to complex negative emotions. To study the development of the ability to experience regret and relief, children, adolescents, and young adults performed a gambling task in a socio‐emotional context of competition, in which they were informed that their outcome would be compared with that of a competitor. The context of competition impacted the feelings of regret and relief in adolescents. When adolescents experienced an initial negative outcome, their feeling of relief was reinforced. However, they did not seem to experience regret in the social context of competition. These results provide a possible explanation for adolescents' enhanced risk seeking.     

Measuring poverty without the Mortality Paradox

Under income-differentiated mortality, poverty measures reflect not only the “true” poverty, but, also, the interferences or noise caused by the survival process at work. Such interferences lead to the Mortality Paradox: the worse the survival conditions of the poor are, the lower the measured poverty is. We examine several solutions to avoid that paradox. We identify conditions under which the extension, by means of a fictitious income, of lifetime income profiles of the prematurely dead neutralizes the noise due to differential mortality. Then, to account not only for the “missing” poor, but, also, for the “hidden” poverty (premature death), we use, as a fictitious income, the welfare-neutral income, making indifferent between life continuation and death. The robustness of poverty measures to the extension technique is illustrated with regional Belgian data.     

An approach to learning from both good and poor factory performance in a Kanban-based just-in-time production system

In a JIT manufacturing environment it may be desirable to learn from an archived history of data that contains information that reflects less than optimal factory performance. The purpose of this paper is to use rule induction to predict JIT factory performance from past data that reflects both poor (saturated or starved) and good (efficient) factory performance. Inductive learning techniques have previously been applied to JIT production systems (Markham et al. , Computers and Industrial Engineering, 34 , 717-726, 1998; Markham et al. , International Journal of Manufacturing Technology Management, 11 (4), 239-246, 2000), but these techniques were only applied to data sets that reflected a well-performing factory. This paper presents an approach based on inductive learning in a JIT manufacturing environment that (1) accurately classifies and predicts factory performance based on shop factors, and (2) identifies the important relationships between the shop factors that determine factory performance. An example application is presented in which the classification and regression tree (CART) technique is used to predict saturated, starved or efficient factory performance based on dynamic shop floor data. This means that the relationship between the variables that cause poor factory performance can be discovered and measures to assure efficient performance can then be taken.     

Generalized Linear Models with a Small Scale Parameter

We propose a study of asymptotic properties in an extension of the Nelder-Wedderburn generalized linear models (GLM) and we apply the results to a model choice in Mandel's models of analysis of variance (ANOVA). This study concerns the behaviour of the maximum likelihood estimators (MLE) when the scale parameter of the GLM tends to zero. Finally, to allow the use of our results, we give some specifications of this limit in three cases of the GLM.