867 resultados para Doing (almost) nothing
Resumo:
The paper reports a study of children's attitudes to school based on a questionnaire survey of 845 pupils in their first year of secondary school in England, together with interviews with a sample of the children. A clearly structured set of attitudes emerged from a factor analysis which showed a distinction between instrumental and affective aspects of attitudes but also dimensions within these, including a sense of teacher commitment and school as a difficult environment. Virtually all children had a strong sense of the importance of doing well at school. However, a substantial minority were not sure that they would stay on after 16. There were few differences between boys and girls or between children from different socio-economic backgrounds but children planning to leave at 16 enjoyed school less and were less sure that it had anything to offer them. There was an almost universal commitment to the value of education but, for a minority, an ambivalence about the experience and relevance of schooling for them.
Resumo:
This paper provides a generalisation of the structural time series version of the Almost Ideal Demand System (AIDS) that allows for time-varying coefficients (TVC/AIDS) in the presence of cross-equation constraints. An empirical appraisal of the TVC/AIDS is made using a dynamic AIDS with trending intercept as the baseline model with a data set from the Italian Household Budget Survey (1986-2001). The assessment is based on four criteria: adherence to theoretical constraints, statistical diagnostics on residuals, forecasting performance and economic meaningfulness. No clear evidence is found for superior performance of the TVC/AIDS, apart from improved short-term forecasts.
Resumo:
Conventional seemingly unrelated estimation of the almost ideal demand system is shown to lead to small sample bias and distortions in the size of a Wald test for symmetry and homogeneity when the data are co-integrated. A fully modified estimator is developed in an attempt to remedy these problems. It is shown that this estimator reduces the small sample bias but fails to eliminate the size distortion.. Bootstrapping is shown to be ineffective as a method of removing small sample bias in both the conventional and fully modified estimators. Bootstrapping is effective, however, as a method of removing. size distortion and performs equally well in this respect with both estimators.
Resumo:
A Bayesian method of estimating multivariate sample selection models is introduced and applied to the estimation of a demand system for food in the UK to account for censoring arising from infrequency of purchase. We show how it is possible to impose identifying restrictions on the sample selection equations and that, unlike a maximum likelihood framework, the imposition of adding up at both latent and observed levels is straightforward. Our results emphasise the role played by low incomes and socio-economic circumstances in leading to poor diets and also indicate that the presence of children in a household has a negative impact on dietary quality.