The Saving for Every Child Program in Israel: an overview of a universal asset-building policy

ABSTRACT

In 2017, the Israeli government implemented a universal child development account programme – the Saving for Every Child Program (SECP) – which establishes a personal savings account for every Israeli child and provides monthly deposits until the child turns 18. The SECP has the potential to provide substantial assets when children reach adulthood, but the benefits depend on parents’ investment choices. The unique programme’s nature presents opportunities to learn from its implementation. This paper provides a comprehensive overview of the SECP, its legislative history, early findings from its implementation, and recommendations that may improve programme participation and outcomes across population groups.     

Socioeconomic Status,Gender Inequality and Women's Mental Health: Some Findings from the Canberra Mental Health Survey

Data from the Canberra Mental Health Survey are utilized to answer questions concerning the mental health status of women (especially married women). Using the Langner Scale as the main index it is shown that there is a complex relationship between the socio-economic status of a married woman's occupation, and the status of her husband's job. It is also shown that there is an association between sex, marital status and mental health that runs in the direction of Jessie Bernard's summary ‘marriage is good for men, but not for women’.     

Did tax incentives play any part in increased giving?

Since 2000, increased taxation incentives along with other measures have been used by the government to encourage philanthropy in Australia. Since the new incentives were introduced, claimed gift tax deductions have increased. However, generally, donors are not aware of the new tax incentives for giving and in any case they report that their motivation for giving is not primarily, if at all, to obtain tax incentives. This article examines this paradox and seeks some possible explanations.     

Partnerships, Power and the "New" Politics of Community Participation in British Health Care

Multi–sectoral approaches to health improvement in its broadest sense have entailed an emphasis by the British government upon partnership working in and around community involvement in planning processes. New service planning and delivery organizations in the health service—primary care groups and primary care trusts—thus have to ensure that public and patient involvement strategies reflect a coordinated, if not integrated, multi–sectoral approach to such involvement. But how are these enforced partnership arrangements shaping the approach taken by primary care groups and trusts to the issue of public and patient involvement? More particularly, is the traditional dominance of health service managers and the medical profession in decision–making processes under challenge? This article draws on a study of primary care groups and trusts in three districts in order to gauge perceptions and calculations with regard to partnerships for involvement. Results appear to suggest that health service managers and practitioners continue to exercise considerable influence in comparison to that of patients and citizens. But, if the findings are viewed in the broader contexts of government managerialist strategies of surveillance and accountability and the growth of service–user and advocacy organizations, partnerships may offer significant scope for “lay” challenges to managerial and medical power.     

Quantifying Quality: Can Quantitative Data (“Metrics”) Explain the 2001 RAE Ratings for Social Policy and Administration?

This paper finds that around 80 per cent of the differences in the ratings awarded in the 2001 RAE for social policy may be “explained” using half a dozen pieces of quantitative data. Social policy excellence—as judged by peer review—is associated with the award of doctorates, the amount of money raised, publications in a particular (if broad) range of journals and books by major publishers, and being large. Even taking account of differences on all these factors, the analysis found that new universities fared worse than their quantitative data would suggest. It is argued that quantitative data should play a larger role in decisions about research quality, aiding equity and transparency.     

The Significance of Living Together and Importance of Marriage in Same-Sex Couples

Because marriage has been denied to same-sex couples, it is likely that the meaning and significance ascribed to non-marital cohabitation may be unique. Further, it is unclear whether same-sex couples view marriage as important to their relationships, and if they do, why. Using qualitative data from 526 individuals in cohabiting same-sex relationships across 47 states, we explored (1) the meaning and significance of cohabitation and (2) the perceived importance of legal marriage to the relationship. Participants viewed cohabitation as significant, most commonly because it indicates long-term commitment, provides emotional support, makes the couple a family, and allows them to share life together. Marriage was perceived as important to a majority (90%), most commonly because it confers financial and legal benefits, relational legitimacy, and demonstrates the same commitment as different-sex couples. Overall, findings highlight the symbolic significance of cohabitation and importance of access to legal marriage to adults in same-sex relationships.     

A new estimator of proportion with a linear function using data from two-decks randomized response model

A new estimator for estimating the proportion of a potentially sensitive attribute in survey sampling has been introduced by solving a linear equation. The proposed estimator has been compared with the estimator proposed by Odumade and Singh (2009) with equal protection to all of the respondents. The asymptotic properties of the proposed estimator are investigated through exact numerical illustrations for different choices of parameters. A non randomized response approach has been suggested. A scope for further research has also been pointed out.     

A Full Bayesian Non-parametric Analysis Involving a Neutral to the Right Process

Implementation of a full Bayesian non-parametric analysis involving neutral to the right processes (apart from the special case of the Dirichlet process) has been difficult for two reasons: first, the posterior distributions are complex and therefore only Bayes estimates (posterior expectations) have previously been presented; secondly, it is difficult to obtain an interpretation for the parameters of a neutral to the right process. In this paper we extend Ferguson & Phadia (1979) by presenting a general method for specifying the prior mean and variance of a neutral to the right process, providing the interpretation of the parameters. Additionally, we provide the basis for a full Bayesian analysis, via simulation, from the posterior process using a hybrid of new algorithms that is applicable to a large class of neutral to the right processes (Ferguson & Phadia only provide posterior means). The ideas are exemplified through illustrative analyses.     

A Bayesian approach to non-parametric monotone function estimation

Summary.  The paper proposes two Bayesian approaches to non-parametric monotone function estimation. The first approach uses a hierarchical Bayes framework and a characterization of smooth monotone functions given by Ramsay that allows unconstrained estimation. The second approach uses a Bayesian regression spline model of Smith and Kohn with a mixture distribution of constrained normal distributions as the prior for the regression coefficients to ensure the monotonicity of the resulting function estimate. The small sample properties of the two function estimators across a range of functions are provided via simulation and compared with existing methods. Asymptotic results are also given that show that Bayesian methods provide consistent function estimators for a large class of smooth functions. An example is provided involving economic demand functions that illustrates the application of the constrained regression spline estimator in the context of a multiple-regression model where two functions are constrained to be monotone.