Annuities and Individual Welfare

This paper advances the theory of annuity demand. First, we derive sufficient conditions under which complete annuitization is optimal, showing that this well-known result holds true in a more general setting than in Yaari (1965). Specifically, when markets are complete, sufficient conditions need not impose exponential discounting, intertemporal separability or the expected utility axioms; nor need annuities be actuarially fair, nor longevity risk be the only source of consumption uncertainty. All that is required is that consumers have no bequest motive and that annuities pay a rate of return for survivors greater than those of otherwise matching conventional assets, net of administrative costs. Second, we show that full annuitization may not be optimal when markets are incomplete. Some annuitization is optimal as long as conventional asset markets are complete. The incompleteness of markets can lead to zero annuitization but the conditions on both annuity and bond markets are stringent. Third, we extend the simulation literature that calculates the utility gains from annuitization by considering consumers whose utility depends both on present consumption and a which they have become accustomed. The value of annuitization hinges critically on the size of the initial standard-of-living relative to wealth.

Neighbors Matter: Causal Community Effects and Stock Market Participation

This paper establishes a causal relation between an individual's decision of whether to own stocks and average stock market participation decision of the individual's community. We instrument for the average ownership of an individual's community with lagged average ownership of the states in which one's non-native neighbors were born. Combining this instrumental variables approach with controls for individual and community fixed effects, a broad set of time-varying individual and community controls, and state-by-year effects, rules out alternative explanations. To further establish that word-of-mouth communication drives this causal effect, we show that the results are stronger in more sociable communities.

The Geography of Stock Market Participation: The Influence of Communities and Local Firms

This paper is the first to investigate the importance of geography in explaining equity market participation. We provide evidence to support two distinct local area effects. The first is a community ownership effect, that is, individuals are influenced by the investment behavior of members of their community. Specifically, a ten percentage-point increase in equity market participation of the members of one's community makes it two percentage points more likely that the individual will invest in stocks. We find further evidence that the influence of community members is strongest for less financially sophisticated households and strongest within peer groups' as defined by age and income categories. The second is that proximity to publicly-traded firms also increases equity market participation. In particular, the presence of publicly-traded firms within 50 miles and the share of U.S. market value headquartered within the community are significantly correlated with equity ownership of individuals. These results are quite robust, holding up in the presence of a wide range of individual and community controls, instrumental variables estimation, the inclusion of individual fixed effects, and specification checks to rule out that the relations are driven solely by ownership of the stock of one's employer.

Applications of CFD and visualization techniques

In this paper, three applications are presented to illustrate current techniques for flow calculation and visualization. The first two applications use a commercial computational fluid dynamics (CFD) code, FLUENT, performed on a Cray Y-MP. The results are animated with the aid of data visualization software, apE. The third application simulates a particulate deposition pattern using techniques inspired by developments in nonlinear dynamical systems. These computations were performed on personal computers

How pharmacoepidemiology networks can manage distributed analyses to improve replicability and transparency and minimize bias

Several pharmacoepidemiology networks have been developed over the past decade that use a distributed approach, implementing the same analysis at multiple data sites, to preserve privacy and minimize data sharing. Distributed networks are efficient, by interrogating data on very large populations. The structure of these networks can also be leveraged to improve replicability, increase transparency, and reduce bias. We describe some features of distributed networks using, as examples, the Canadian Network for Observational Drug Effect Studies, the Sentinel System in the USA, and the European Research Network of Pharmacovigilance and Pharmacoepidemiology. Common protocols, analysis plans, and data models, with policies on amendments and protocol violations, are key features. These tools ensure that studies can be audited and repeated as necessary. Blinding and strict conflict of interest policies reduce the potential for bias in analyses and interpretation. These developments should improve the timeliness and accuracy of information used to support both clinical and regulatory decisions

Five minutes with Jeffrey C. Alexander: “Southern European countries are not just experiencing an economic crisis, but also an identity crisis”

Is there a ‘dark side’ to European modernity? As part of our ‘Thinkers on Europe’ series, EUROPP’s editors Stuart A Brown and Chris Gilson spoke to Jeffrey C. Alexander about his views on modernity, the European integration process, and the importance of cultural and political symbols to European democracy

Two-proton removal from 44 S and the structure of 42 Si

Newly published 42Si ?-ray spectra and a final-state-inclusive 42Si production cross section value, obtained in a higher-statistics intermediate-energy two-proton removal experiment from 44S, are considered in terms of the final-state-exclusive cross sections computed using proposed shell-model effective interactions for nuclei near N=28. Specifically, we give cross section predictions when using the two nucleon amplitudes of the two-proton overlaps 42Si(J?)| computed using the newly proposed sdpf-mu shell-model Hamiltonian. We show that these partial cross sections or their longitudinal momentum distributions should enable a less-tentative interpretation of the measured gamma-ray spectra and provide a more quantitative assessment of proposed shell-model Hamiltonians in this interesting and challenging region of the chart of nuclides. � 2013 American Physical Society