Children and Demand: Direct and Non-Direct Effects

This paper examines the effects of children on demands. We employ a French family expenditure survey that has a number of unusual features to explore the source of the correlation between children and demands. The first sample we use is of older households which has information on completed fertility. The second sample is of younger households for whom we have family background variables. We find that children are not exogenous for some goods. These findings cast doubt on the usual practice of identifying direct children effects with the coefficients on the children variables in demand equations.     

Lifting the Lid: Perspectives on and Activity within Student Supervision

Practice teaching is central to social work education. Significant changes have occurred in the past 10 years affecting social work education in Scotland. This article reports on the findings of a small-scale study involving the audio recording of supervision sessions and the interviewing of students and practice teachers engaged in a 65-day assessed placement. The research reveals a high level of congruence between students and practice teachers in perspectives on the supervisory relationship, confirms the findings of other studies concerning effective supervision and provides some vivid evidence of practice teacher and student activity within supervision perceived to be conducive to student learning. A specific finding was the association between the use of ‘exploring’ by practice teachers and students engaging in practice analysis. It is concluded that the changes affecting social work education over the past 10 years, on the evidence of this small sample, overall have had a positive impact on the supervisory relationship within practice learning. One area suggested for further study is the potential link between ‘expressing opinion’ by practice teachers and students within supervision and the development of evidence-based practice.     

Reports of Wins and Risk Taking: An Investigation of the Mediating Effect of the Illusion of Control

Two experiments examined the relationships between the knowledge that another person has won in a gamble, the illusion of control and risk taking. Participants played a computer-simulated French roulette game individually. Before playing, some participants learnt that another person won a large amount of money. Results from a first experiment (n = 24) validated a causal model where the knowledge of another person’s win increased the illusion of control, measured with betting times, expectancy and self-reports on scales, which in turn encourages risk taking. In the second experiment (n = 36), some participants were told the previous player acknowledged the win to be fortuitous. The suppression of the belief that the previous winner had himself exerted control over the outcome resulted in lower rates of risk-taking behaviors. This suggests that it was not the knowledge of another person’s win in itself that increased risk taking, but rather, the belief that the other person had some control over the gamble’s outcome. Theoretical implications for the study of social mechanisms involved in gambling behavior are discussed.     

Does the Representation of Household Behavior Matter for Welfare Analysis of Tax-benefit Policies? An Introduction

A widely shared intuition holds that individual control over money matters for the decision process within the household and the subsequent distribution of resources and welfare. As a consequence, there are good reasons to depart from the unitary model of the household and to explore the possibilities offered by models of the family accounting for several decision makers in the household and for the potential impact of tax reforms on the balance of power. This paper summarizes both the methodological and empirical findings presented in the next three papers of this special issue of the Review of the Economics of the Household. This series of contributions primarily entails a concrete comparison of the policy implications of the choice between the unitary and a particular multi-person representation: the collective representation. On the one hand, it suggests a methodology to implement the collective model of labor supply in a realistic context where participation is modeled together with working hours, and where the full tax-benefit system is accounted for. On the other hand, the empirical part relies on comprehensive simulations of tax reforms in Belgium, France, Germany, Italy, Spain, and the United Kingdom, and allows to quantify the distortions that may affect policy recommendations based on the unitary model.

Average and Quantile Effects in Nonseparable Panel Models

Nonseparable panel models are important in a variety of economic settings, including discrete choice. This paper gives identification and estimation results for nonseparable models under time‐homogeneity conditions that are like “time is randomly assigned” or “time is an instrument.” Partial‐identification results for average and quantile effects are given for discrete regressors, under static or dynamic conditions, in fully nonparametric and in semiparametric models, with time effects. It is shown that the usual, linear, fixed‐effects estimator is not a consistent estimator of the identified average effect, and a consistent estimator is given. A simple estimator of identified quantile treatment effects is given, providing a solution to the important problem of estimating quantile treatment effects from panel data. Bounds for overall effects in static and dynamic models are given. The dynamic bounds provide a partial‐identification solution to the important problem of estimating the effect of state dependence in the presence of unobserved heterogeneity. The impact of T, the number of time periods, is shown by deriving shrinkage rates for the identified set as T grows. We also consider semiparametric, discrete‐choice models and find that semiparametric panel bounds can be much tighter than nonparametric bounds. Computationally convenient methods for semiparametric models are presented. We propose a novel inference method that applies in panel data and other settings and show that it produces uniformly valid confidence regions in large samples. We give empirical illustrations.