Money, Political Ambition, and the Career Decisions of Politicians

In this paper we assess the impact of a variety of policies that may influence the career decisions of members of the U.S. Congress, using the empirical framework of Diermeier, Keane and Merlo (2005). These policies alter incentives to run for re-election, run for higher office or leave Congress, by altering wages, nonpecuniary rewards and career prospects (both in and out of Congress). We find that reducing the relative wage of politicians would substantially reduce the duration of congressional careers. Notably, however, the effect varies considerably across different types of politicians. A reduction in the congressional wage would disproportionately induce exit from Congress by “skilled” politicians, Democrats, politicians who were relatively young when first elected, and those without pre-congressional political experience. Interestingly, however, it would not cause the type of politicians who most value legislative accomplishments (“achievers”) to disproportionately exit Congress. Thus, wage reductions would not reduce the “quality” composition of Congress in this sense. Term limits also have similar effects on achievers and non-achievers. However, we find that term limits would disproportionately induce members of the majority party to exit Congress. This has the interesting implication that term limits make it more difficult to sustain substantial congressional majorities over time. We do find three types of policies that disproportionately induce nonachievers to leave Congress: (i) elimination of seniority as a determinant of key committee assignments, (ii) restricting private sector employment after leaving Congress, and (iii) reducing the seniority advantage in elections.politicians, political careers, monetary and non-monetary incentives, U.S. Congress

Money, Political Ambition, and the Career Decisions of Politicians, Second Version

In this paper we assess the impact of a variety of policies that may influence the career decisions of members of the U.S. Congress, using the empirical framework of Diermeier, Keane and Merlo (2005). These policies alter incentives to run for re-election, run for higher office or leave Congress, by altering wages, non-pecuniary rewards and career prospects (both in and out of Congress). We find that reducing the relative wage of politicians would substantially reduce the duration of congressional careers. Notably, however, the effect varies considerably across different types of politicians. A reduction in the congressional wage would disproportionately induce exit from Congress by “skilled” politicians, Democrats, and politicians who were relatively young when first elected. Interestingly, however, it would not cause the type of politicians who most value legislative accomplishments (“achievers”) to disproportionately exit Congress. Thus, wage reductions would not reduce the “quality” composition of Congress in this sense. Term limits also have similar effects on achievers and non-achievers. However, we find that term limits would disproportionately induce members of the majority party to exit Congress. This has the interesting implication that term limits make it more difficult to sustain substantial congressional majorities over time. We do find three types of policies that disproportionately induce non-achievers to leave Congress: (i) elimination of seniority as a determinant of key committee assignments, (ii) restricting private sector employment after leaving Congress, and (iii) reducing the seniority advantage in elections.politicians, political careers, monetary and non-monetary incentives, U.S. Congress

What Accounts for the Decline in Crime?

In this paper we analyze recent trends in aggregate property crime rates in the United States. We propose a dynamic equilibrium model which guides our quantitative investigation of the major determinants of observed patterns of crime. Our main findings can be summarized as follows. First, the model is capable of reproducing the drop in crime between 1980 and 1996. Second, the most important factors that account for the observed decline in property crime are the higher apprehension probability, the stronger economy, and the aging of the population. Third, the effect of unemployment on crime is negligible. Fourth, the increased inequality prevented an even larger decline in crime. Overall, our analysis can account for the behavior of the time series of property crime rates over the past quarter century.PROPERTY CRIME; INEQUALITY; DYNAMICS

Symmetry breaking: A tool to unveil the topology of chaotic scattering with three degrees of freedom

We shall use symmetry breaking as a tool to attack the problem of identifying the topology of chaotic scatteruing with more then two degrees of freedom. specifically we discuss the structure of the homoclinic/heteroclinic tangle and the connection between the chaotic invariant set, the scattering functions and the singularities in the cross section for a class of scattering systems with one open and two closed degrees of freedom.Comment: 13 pages and 8 figure

Spatial clustering of mental disorders and associated characteristics of the neighbourhood context in Malmö, Sweden, in 2001

Study objective: Previous research provides preliminary evidence of spatial variations of mental disorders and associations between neighbourhood social context and mental health. This study expands past literature by (1) using spatial techniques, rather than multilevel models, to compare the spatial distributions of two groups of mental disorders (that is, disorders due to psychoactive substance use, and neurotic, stress related, and somatoform disorders); and (2) investigating the independent impact of contextual deprivation and neighbourhood social disorganisation on mental health, while assessing both the magnitude and the spatial scale of these effects. Design: Using different spatial techniques, the study investigated mental disorders due to psychoactive substance use, and neurotic disorders. Participants: All 89 285 persons aged 40–69 years residing in Malmö, Sweden, in 2001, geolocated to their place of residence. Main results: The spatial scan statistic identified a large cluster of increased prevalence in a similar location for the two mental disorders in the northern part of Malmö. However, hierarchical geostatistical models showed that the two groups of disorders exhibited a different spatial distribution, in terms of both magnitude and spatial scale. Mental disorders due to substance consumption showed larger neighbourhood variations, and varied in space on a larger scale, than neurotic disorders. After adjustment for individual factors, the risk of substance related disorders increased with neighbourhood deprivation and neighbourhood social disorganisation. The risk of neurotic disorders only increased with contextual deprivation. Measuring contextual factors across continuous space, it was found that these associations operated on a local scale. Conclusions: Taking space into account in the analyses permitted deeper insight into the contextual determinants of mental disorders

Integrating Superconductive and Optical Circuits

We have integrated on oxidized silicon wafers superconductive films and Josephson junctions along with sol-gel optical channel waveguides. The fabrication process is carried out in two steps that result to be solid and non-invasive. It is demonstrated that 660 nm light, coupled from an optical fibre into the channel sol-gel waveguide, can be directed toward superconducting tunnel junctions whose current-voltage characteristics are affected by the presence of the radiation. The dependence of the change in the superconducting energy gap under optical pumping is discussed in terms of a non-equilibrium superconductivity model.Comment: Document composed of 7 pages of text and 3 figure

Higgs ultraviolet softening

We analyze the leading effective operators which induce a quartic momentum dependence in the Higgs propagator, for a linear and for a non-linear realization of electroweak symmetry breaking. Their specific study is relevant for the understanding of the ultraviolet sensitivity to new physics. Two methods of analysis are applied, trading the Lagrangian coupling by: i) a "ghost" scalar, after the Lee-Wick procedure; ii) other effective operators via the equations of motion. The two paths are shown to lead to the same effective Lagrangian at first order in the operator coefficients. It follows a modification of the Higgs potential and of the fermionic couplings in the linear realization, while in the non-linear one anomalous quartic gauge couplings, Higgs-gauge couplings and gauge-fermion interactions are induced in addition. Finally, all LHC Higgs and other data presently available are used to constrain the operator coefficients; the future impact of $pp\to\text{4 leptons}$ data via off-shell Higgs exchange and of vector boson fusion data is considered as well. For completeness, a summary of pure-gauge and gauge-Higgs signals exclusive to non-linear dynamics at leading-order is included.Comment: 31 pages, 3 figures, 7 table

Deep Reinforcement Learning for Black-box Testing of Android Apps

The state space of Android apps is huge, and its thorough exploration during testing remains a significant challenge. The best exploration strategy is highly dependent on the features of the app under test. Reinforcement Learning (RL) is a machine learning technique that learns the optimal strategy to solve a task by trial and error, guided by positive or negative reward, rather than explicit supervision. Deep RL is a recent extension of RL that takes advantage of the learning capabilities of neural networks. Such capabilities make Deep RL suitable for complex exploration spaces such as one of Android apps. However, state-of-the-art, publicly available tools only support basic, Tabular RL. We have developed ARES, a Deep RL approach for black-box testing of Android apps. Experimental results show that it achieves higher coverage and fault revelation than the baselines, including state-of-the-art tools, such as TimeMachine and Q-Testing. We also investigated the reasons behind such performance qualitatively, and we have identified the key features of Android apps that make Deep RL particularly effective on them to be the presence of chained and blocking activities. Moreover, we have developed FATE to fine-tune the hyperparameters of Deep RL algorithms on simulated apps, since it is computationally expensive to carry it out on real apps