The Risk of Social Security Benefit Rule Changes: Some International Evidence

Against a background of projections of sharply increasing elderly dependency rates, workers in the major industrial economies are apprehensive that their social security benefit entitlements will be cut before or after they retire, leaving them with inadequate retirement income. This paper looks at recent benefit rule changes in the G7 countries to see what can be learned about such political risk in PAYG pension systems. From this small sample, I find that projections of rising costs under current rules are inducing reforms, and that these reforms often have a major impact on the present discounted value of promised benefits for middle-aged and younger workers. Usually, however, the benefits of the retired and those nearing retirement are protected. The phasing in of benefit cuts raises the question as to why younger workers are willing to take significant cuts in their implicit wealth while protecting the currently old. One possible answer is explored through a simple model: these workers fear even larger cuts in their benefits if the tax burden on future workers rises too high.

Selecting Economic Immigrants: An Actuarial Approach

There is growing international interest in a Canadian-style points system for selecting economic immigrants. Although existing points systems have been influenced by the human capital literature, the findings have traditionally been incorporated in an ad hoc way. This paper explores a formal method for designing a points system based on a human capital earnings regression for predicting immigrant economic success. The method is implemented for Canada using the IMDB, a remarkable longitudinal database that combines information on immigrants’ characteristics at landing with their subsequent income performance as reported on tax returns. We demonstrate the feasibility of the method by developing an illustrative points system. We also explore how the selection system can be improved by incorporating additional information such as country-of origin characteristics and intended occupations. We discuss what our findings imply for the debate about the relative merits of points- and employment-based systems for selecting economic immigrants.Immigrant selection, Points system, Human capital, Earnings prediction

Birds of a Feather - Better Together? Exploring the Optimal Spatial Distribution of Ethnic Inventors

We examine how the spatial and social proximity of inventors affects knowledge flows, focusing especially on how the two forms of proximity interact. We develop a knowledge flow production function (KFPF) as a flexible tool for modeling access to knowledge and show that the optimal spatial concentration of socially proximate inventors in a city or nation depends on whether spatial and social proximity are complements or substitutes in facilitating knowledge flows. We employ patent citation data, using same-MSA and co-ethnicity as proxies for spatial and social proximity, respectively, to estimate the key KFPF parameters. Although co-location and co-ethnicity both predict knowledge flows, the marginal benefit of co-location is significantly less for co-ethnic inventors. These results imply that dispersion of socially proximate individuals is optimal from the perspectives of the city and the economy. In contrast, for socially proximate individuals themselves, spatial concentration is preferred - and the only stable equilibrium.

Superhuman science: How artificial intelligence may impact innovation

New product innovation in fields like drug discovery and material science can be characterized as combinatorial search over a vast range of possibilities. Modeling innovation as a costly multi-stage search process, we explore how improvements in Artificial Intelligence (AI) could affect the productivity of the discovery pipeline in allowing improved prioritization of innovations that flow through that pipeline. We show how AI aided prediction can increase the expected value of innovation and can increase or decrease the demand for downstream testing, depending on the type of innovation, and examine how AI can reduce costs associated with well-defined bottlenecks in the discovery pipeline. Finally, we discuss the critical role that policy can play to mitigate potential market failures associated with access to and provision of data as well as the provision of training necessary to more closely approach the socially optimal level of productivity enhancing innovations enabled by this technology

Brain Drain or Brain Bank? The Impact of Skilled Emigration on Poor-Country Innovation

The development prospects of a poor country depend in part on its capacity for innovation. The productivity of its innovators depends in turn on their access to technological knowledge. The emigration of highly skilled individuals weakens local knowledge networks (brain drain), but may also help remaining innovators access valuable knowledge accumulated abroad (brain bank). We develop a model in which the size of the optimal innovator diaspora depends on the competing strengths of co-location and diaspora effects for accessing knowledge. Then, using patent citation data associated with inventions from India, we estimate the key co-location and diaspora parameters; the net effect of innovator emigration is to harm domestic knowledge access, on average. However, knowledge access conferred by the diaspora is particularly valuable in the production of India's most important inventions as measured by citations received. Thus, our findings imply that the optimal emigration level may depend, at least partly, on the relative value resulting from the most cited compared to average inventions.

microRNAs may sharpen spatial expression patterns

The precise layout of gene expression patterns is a crucial step in development. Formation of a sharp boundary between high and low expression domains requires a genetic mechanism which is both sensitive and robust to fluctuations, a demand that may not be easily achieved by morphogens alone. Recently it has been demonstrated that small RNAs (and, in particular, microRNAs) play many roles in embryonic development. While some RNAs are essential for embryogenesis, others are limited to fine-tuning a predetermined gene expression pattern. Here we explore the possibility that small RNAs participate in sharpening a gene expression profile that was crudely established by a morphogen. To this end we study a model where small RNAs interact with a target gene and diffusively move from cell to cell. Though diffusion generally smears spatial expression patterns, we find that intercellular mobility of small RNAs is actually critical in sharpening the interface between target expression domains in a robust manner. We discuss the applicability of our results, as examples, to the case of leaf polarity establishment in maize and Hox patterning in the early {\it Drosophila} embryo. Our findings point out the functional significance of some mechanistic properties, such as mobility of small RNAs and the irreversibility of their interactions. These properties are yet to be established directly for most classes of small RNAs. An indirect yet simple experimental test of the proposed mechanism is suggested in some detail