Parental transfer of financial knowledge and later credit outcomes among low- and moderate-income homeowners

It is well established that acquiring financial skills during childhood is linked with better savings in adulthood. Little is known, however, about the relationship between parental teaching of money management early in life and children's financial outcomes in adulthood. This is particularly true for low- and moderate-income (LMI) households. Using data from Community Advantage Program survey data for 2,389 LMI homeowners, we find that adults who report receiving high levels of money-management teaching in childhood from their parents are associated with higher credit scores and lower credit card debt in adulthood. We also find that the level of parental financial teaching influences the relationship between children's later educational attainment and credit scores. These findings suggest implications for initiatives promoting financial capability for parents and children.     

Barely managing: Attitudes of information technology professionals on management technique

This paper presents findings from exploratory research into the attitudes of information technology (IT) professionals about the role management has played or could play in computing activities. It also looks at the subsidiary questions of what might be desirable preparation of managers for directing IT professionals, what the barriers to this are, and how this preparation might be stimulated. The paper is based on in-depth, ethnographic interviews conducted in 2001 with 30 IT professionals from both public and private sectors in New Mexico.     

Total least squares and bootstrapping with applications in calibration

The solution to the errors-in-variables problem computed through total least squares is highly nonlinear. Because of this, many statistical procedures for constructing confidence intervals and testing hypotheses cannot be applied. One possible solution to this dilemma is bootstrapping. A nonparametric bootstrap technique could fail. Here, the proper nonparametric bootstrap procedure is provided and its correctness is proved. On the other hand, a residual bootstrap is not valid and suitable in this case. The results are illustrated through a simulation study. An application of this approach to calibration data is presented.     

Identification and Inference With Many Invalid Instruments

We study estimation and inference in settings where the interest is in the effect of a potentially endogenous regressor on some outcome. To address the endogeneity, we exploit the presence of additional variables. Like conventional instrumental variables, these variables are correlated with the endogenous regressor. However, unlike conventional instrumental variables, they also have direct effects on the outcome, and thus are “invalid” instruments. Our novel identifying assumption is that the direct effects of these invalid instruments are uncorrelated with the effects of the instruments on the endogenous regressor. We show that in this case the limited-information-maximum-likelihood (liml) estimator is no longer consistent, but that a modification of the bias-corrected two-stage-least-square (tsls) estimator is consistent. We also show that conventional tests for over-identifying restrictions, adapted to the many instruments setting, can be used to test for the presence of these direct effects. We recommend that empirical researchers carry out such tests and compare estimates based on liml and the modified version of bias-corrected tsls. We illustrate in the context of two applications that such practice can be illuminating, and that our novel identifying assumption has substantive empirical content.     

The Working Families’ Tax Credit and Some European Tax Reforms in A Collective Setting

A framework for simplified implementation of the collective model of labor supply decisions is presented in the context of fiscal reforms in the UK. Through its collective form the model accounts for the well known problem of distribution between wallet and purse, a broadly debated issue which has so far been impossible to model due to the limitations of the unitary model of household behavior. A calibrated data set is used to model the effects of introducing two forms of the Working Families’ Tax Credit. We also summarize results of estimations and calibrations obtained using the same methodology on data from five other European countries. The results underline the importance of taking account of the intrahousehold decision process and suggest that who receives government transfers does matter from the point of view of labor supply and welfare of household members. They also highlight the need for more research into models of household behavior.

Collective Models of Labor Supply with Nonconvex Budget Sets and Nonparticipation: A Calibration Approach

We suggest a methodology to calibrate a collective model with household-specific bargaining rules and marriage-specific preferences that incorporate leisure externalities. The empirical identification relies on the assumption that some aspects of individual preferences remain the same after marriage, so that estimation on single individuals can be used. The procedure maps the complete Pareto frontier of each household in the dataset and we define alternative measures of a power index. The latter is then regressed on relevant bargaining factors, including a set of variables retracing the potential relative contributions of the spouses to household disposable income. In its capacity to handle complex budget sets and labor force participation decisions of both spouses, this framework allows the comparison of unitary and collective predictions of labor supply reactions and welfare changes entailed by fiscal reforms in a realistic setting (see Michal Myck et al., 2006; Denis Beninger et al., 2006).

A functional marked point process model for lupus data

Modelling for marked point processes is an important problem, but has received remarkably little attention in the statistical literature. The authors developed a marked point process model that incorporates the use of functional data analysis in a joint estimation of the frequency function of the point process and the intensity of the mark, with application to data from 22 lupus patients consisting of times of flares in symptom severity combined with a quantitative assessment of the severity. The data indicate that a rapid decrease in drug dose is significantly associated with a decrease in flare frequency. Experiments with simulated data designed to model the actual data further support this conclusion. The Canadian Journal of Statistics 40: 517–529; 2012 © 2012 Statistical Society of Canada