Relative wage movements and the distribution of consumption

We analyze how relative wage movements across birth cohorts and education groups during the 1980s affected the distribution of household consumption. The analysis integrates the labor economics literature on time variation in the wage structure with the consumption insurance literature. In contrast to previous tests of consumption insurance, we examine the impact of systematic, publicly observable shifts in the hourly wage structure. To circumvent the extreme scarcity of longitudinal data with high quality information on both consumption and labor market outcomes, we draw upon the best available cross-sectional data sources to construct synthetic panel data on consumption, labor supply and wages. We find that low-frequency movements in the cohort-education structure of pre-tax hourly wages drove large changes in the distribution of household consumption. The results constitute a spectacular failure of the consumption insurance hypothesis, and one that is not explained by existing theories of informationally constrained optimal consumption allocations. We also develop a procedure for assessing the welfare consequences of deviations from full consumption insurance and, in particular, from the failure to insulate the consumption distribution from relative wage shifts across cohort-education groups. For a coefficient of relative risk aversion equal to two, fully insulating households from group-specific endowment variation would raise welfare by an amount equivalent to a uniform 2.7% consumption increase

Relative wage movements and the distribution of consumption

The authors analyze how relative wage movements among birth cohorts and education groups affected the distribution of household consumption and economic welfare. Their empirical work draws on the best available cross-sectional data sets to construct synthetic panel data on U.S. consumption, labor supply, and wages during the 1980s. The authors find that low-frequency movements in the cohort-education structure of pretax hourly wages among men drove large changes in the distribution of household consumption. The results constitute a spectacular failure of between-group consumption insurance, a failure not explained by existing theories of informationally constrained optimal consumption behavior

Correspondence: Reply to ‘Reassessing the contribution of natural gas to US CO2 emission reductions since 2007’

Our recent study in this journal quantified the drivers of US CO2 emissions between 1997 and 2013, with particular focus on the decline in emissions after 2007. Based on our findings, we argued that economic recession was more important than substitution of natural gas for coal in the power sector. In their comment, Kotchen and Mansur reevaluate and reinterpret our results to challenge this conclusion. Because their calculations, using two alternative methods, are consistent with our findings, here we respond to their alternative interpretation

Biotic analogies for self-organising cities

Nature has inspired generations of urban designers and planners in pursuit of harmonious and functional built environments. Research regarding self-organisation has encouraged urbanists to consider the role of bottom-up approaches in generating urban order. However, the extent to which self-organisation-inspired approaches draw directly from nature is not always clear. Here, we examined the biological basis of urban research, focusing on self-organisation. We conducted a systematic literature search of self-organisation in urban design and biology, mapped the relationship between key biological terms across the two fields and assessed the quality and validity of biological comparisons in the urban design literature. Finding deep inconsistencies in the mapping of central terms between the two fields, a preponderance for cross-level analogies and comparisons that spanned molecules to ecosystems, we developed a biotic framework to visualise the analogical space and elucidate areas where new inspiration may be sought

Black hole collision with a scalar particle in four, five and seven dimensional anti-de Sitter spacetimes: ringing and radiation

In this work we compute the spectra, waveforms and total scalar energy radiated during the radial infall of a small test particle coupled to a scalar field into a $d$-dimensional Schwarzschild-anti-de Sitter black hole. We focus on $d=4, 5$ and 7, extending the analysis we have done for $d=3$. For small black holes, the spectra peaks strongly at a frequency $\omega \sim d-1$, which is the lowest pure anti-de Sitter (AdS) mode. The waveform vanishes exponentially as $t \to \infty$, and this exponential decay is governed entirely by the lowest quasinormal frequency. This collision process is interesting from the point of view of the dynamics itself in relation to the possibility of manufacturing black holes at LHC within the brane world scenario, and from the point of view of the AdS/CFT conjecture, since the scalar field can represent the string theory dilaton, and 4, 5, 7 are dimensions of interest for the AdS/CFT correspondence.Comment: 16 pages, 13 figures. Published versio

Multiagent Negotiation for Fair and Unbiased Resource Allocation

This paper proposes a novel solution for the n agent cake cutting (resource allocation) problem. We propose a negotiation protocol for dividing a resource among n agents and then provide an algorithm for allotting portions of the resource. We prove that this protocol can enable distribution of the resource among n agents in a fair manner. The protocol enables agents to choose portions based on their internal utility function, which they do not have to reveal. In addition to being fair, the protocol has desirable features such as being unbiased and verifiable while allocating resources. In the case where the resource is two-dimensional (a circular cake) and uniform, it is shown that each agent can get close to l/n of the whole resource

Accuracy and Limitations of Fitting and Stereoscopic Methods to Determine the Direction of Coronal Mass Ejections from Heliospheric Imagers Observations

Using data from the Heliospheric Imagers (HIs) onboard STEREO, it is possible to derive the direction of propagation of coronal mass ejections (CMEs) in addition to their speed with a variety of methods. For CMEs observed by both STEREO spacecraft, it is possible to derive their direction using simultaneous observations from the twin spacecraft and also, using observations from only one spacecraft with fitting methods. This makes it possible to test and compare different analyses techniques. In this article, we propose a new fitting method based on observations from one spacecraft, which we compare to the commonly used fitting method of Sheeley et al. (1999). We also compare the results from these two fitting methods with those from two stereoscopic methods, focusing on 12 CMEs observed simultaneously by the two STEREO spacecraft in 2008 and 2009. We find evidence that the fitting method of Sheeley et al. (1999) can result in significant errors in the determination of the CME direction when the CME propagates outside of 60deg \pm 20 deg from the Sun-spacecraft line. We expect our new fitting method to be better adapted to the analysis of halo or limb CMEs with respect to the observing spacecraft. We also find some evidence that direct triangulation in the HI fields-of-view should only be applied to CMEs propagating approximatively towards Earth (\pm 20deg from the Sun-Earth line). Last, we address one of the possible sources of errors of fitting methods: the assumption of radial propagation. Using stereoscopic methods, we find that at least seven of the 12 studied CMEs had an heliospheric deflection of less than 20deg as they propagated in the HI fields-of-view, which, we believe, validates this approximation.Comment: 17 pages, 6 figures, 2 tables, accepted to Solar Physic

A two-step learning approach for solving full and almost full cold start problems in dyadic prediction

Dyadic prediction methods operate on pairs of objects (dyads), aiming to infer labels for out-of-sample dyads. We consider the full and almost full cold start problem in dyadic prediction, a setting that occurs when both objects in an out-of-sample dyad have not been observed during training, or if one of them has been observed, but very few times. A popular approach for addressing this problem is to train a model that makes predictions based on a pairwise feature representation of the dyads, or, in case of kernel methods, based on a tensor product pairwise kernel. As an alternative to such a kernel approach, we introduce a novel two-step learning algorithm that borrows ideas from the fields of pairwise learning and spectral filtering. We show theoretically that the two-step method is very closely related to the tensor product kernel approach, and experimentally that it yields a slightly better predictive performance. Moreover, unlike existing tensor product kernel methods, the two-step method allows closed-form solutions for training and parameter selection via cross-validation estimates both in the full and almost full cold start settings, making the approach much more efficient and straightforward to implement