America Under Fire: An Analysis of Gun Violence in the United States and the Link to Weak Gun Laws

In 2013, the Center for American Progress conducted a study to assess the correlation between the relative strength or weakness of a state's gun laws, as measured by the Law Center to Prevent Gun Violence, and rates of gun violence in the state across 10 categories of gun violence or gun-related crimes. Consistent with the research, the CAP study found a strong correlation between strong gun laws and lower rates of gun violence.In the 3.5 years since that study, a number of things have changed that warrant revisiting that research. Many states have acted to strengthen their gun laws: Since the mass shooting at Sandy Hook Elementary School, eight states have enacted laws to require universal background checks—bringing the total number of states that have enacted such laws to 18—and 20 states have strengthened their laws to help keep guns out of the hands of domestic abusers. Unfortunately, other states have taken the opposite approach, loosening laws regarding where guns may be carried and weakening or eliminating concealed carry permit requirements. In addition, improvements made in the collection of data relating to gun violence now allow more precise tracking of events such as mass shootings and fatal shootings by law enforcement officers.In this report, the authors revisit CAP's 2013 analysis with a revised methodology, some new categories of gun violence, and updated state grades from the Law Center to Prevent Gun Violence. The report provides a state ranking across key indicators of gun violence, then uses these rankings to calculate an overall Gun Violence Index score for each state. Using this score, the authors assessed the correlation between the rate of overall gun violence in the state and the relative strength or weakness of each state's gun laws

Pennsylvania Under the Gun: 5 Measures of Gun Violence in the Keystone State

This issue brief explores five aspects of gun violence in Pennsylvania that are especially alarming, unusual, or above the national average:1. Pennsylvania's rate of gun homicides is among the highest in the nation, particularly in communities of color.2. Pennsylvania law enforcement officers are killed with guns at an exceptionally high rate.3. More Pennsylvanians are killed by gun violence than in car accidents annually.4. Pennsylvania is a top supplier of crime guns recovered in other states.5. Pennsylvania women are killed with guns wielded by intimate partners at a high rate

Virginia Under the Gun

This issue brief provides additional context about what is at stake as Virginia voters con-sider which leaders they want to represent them in Richmond. It discusses four aspects of gun violence and gun-related crime in Virginia that are exceptional, unique, or above the national average:1. More Virginians are killed annually by gunfire than in car accidents.2. Virginia is one of the top exporters of crime guns.3. Women are killed with guns by intimate partners at a high rate in Virginia.4. Virginia has been disproportionately affected by mass shootings

Stolen Guns in America

In the early morning hours of July 5, 2017, New York Police Department officer Miosotis Familia was ambushed as she sat in a marked NYPD command truck with her partner while providing additional security to a Bronx neighborhood after Fourth of July festivities. In an attack that police officials described as an assassination, Officer Familia was fatally shot in the head with a gun that had been stolen in Charleston, West Virginia, four years earlier. Less than a month earlier on the other side of the country, a UPS driver in San Francisco shot and killed three co-workers and injured two others using a gun that had been stolen in Utah. The shooter was also armed with a gun that had been stolen in Napa County, California.Stolen guns pose a significant risk to community safety. Whether stolen from a gun store or an individual gun owner's collection, these guns often head straight into the illegal underground gun market, where they are sold, traded, and used to facilitate violent crimes. Gun theft is not a minor problem in the United States. According to data from the Federal Bureau of Investigation (FBI), during the four-year period from 2012 to 2015, nearly half a billion dollars' worth of guns were stolen from individuals nationwide, amounting to an estimated 1.2 million guns. Twenty-two thousand guns were stolen from gun stores during this same period. A gun is stolen in the U.S. every two minutes.This problem does not affect all states equally. The rate and volume of guns stolen from both gun stores and private collections vary widely from state to state. From 2012 through 2015, the average rate of the five states with the highest rates of gun theft from private owners—Tennessee, Arkansas, South Carolina, Oklahoma, and Alabama—was 13 times higher than the average rate of the five states with the lowest rates—Hawaii, Connecticut, Rhode Island, New York, and Massachusetts. Similarly, from 2012 through 2016, the average rate of the five states with the highest rates of guns stolen from gun stores was 18 times higher than the average rate the five states with the lowest rates.Gun owners and dealers have a substantial responsibility to take reasonable measures to protect against theft and help ensure that their guns do not become part of this illegal inventory. This report analyzes data from the FBI and the Bureau of Alcohol, Tobacco, Firearms and Explosives (ATF) to provide state-by-state data on the frequency with which guns are stolen from licensed gun dealers and individual gun owners in communities across the country. It then offers a number of policy solutions to help prevent future gun thefts

Predicting Daily Probability Distributions Of S&P500 Returns

Most approaches in forecasting merely try to predict the next value of the time series. In contrast, this paper presents a framework to predict the full probability distribution. It is expressed as a mixture model: the dynamics of the individual states is modeled with so-called "experts" (potentially nonlinear neural networks), and the dynamics between the states is modeled using a hidden Markov approach. The full density predictions are obtained by a weighted superposition of the individual densities of each expert. This model class is called "hidden Markov experts". Results are presented for daily S&P500 data. While the predictive accuracy of the mean does not improve over simpler models, evaluating the prediction of the full density shows a clear out-of-sample improvement both over a simple GARCH(1,l) model (which assumes Gaussian distributed returns) and over a "gated experts" model (which expresses the weighting for each state non-recursively as a function of external inputs). Several interpretations are given: the blending of supervised and unsupervised learning, the discovery of hidden states, the combination of forecasts, the specialization of experts, the removal of outliers, and the persistence of volatility.Information Systems Working Papers Serie

A First Application of Independent Component Analysis to Extracting Structure from Stock Returns

This paper discusses the application of a modern signal processing technique known as independent component analysis (ICA) or blind source separation to multivariate financial time series such as a portfolio of stocks. The key idea of ICA is to linearly map the observed multivariate time series into a new space of statistically independent components (ICs). This can be viewed as a factorization of the portfolio since joint probabilities become simple products in the coordinate system of the ICs. We apply ICA to three years of daily returns of the 28 largest Japanese stocks and compare the results with those obtained using principal component analysis. The results indicate that the estimated ICs fall into two categories, (i) infrequent but large shocks (responsible for the major changes in the stock prices), and (ii) frequent smaller fluctuations (contributing little to the overall level of the stocks). We show that the overall stock price can be reconstructed surprisingly well by using a small number of thresholded weighted ICs. In contrast, when using shocks derived from principal components instead of independent components, the reconstructed price is less similar to the original one. Independent component analysis is a potentially powerful method of analyzing and understanding driving mechanisms in financial markets. There are further promising applications to risk management since ICA focuses on higher-order statistics.Information Systems Working Papers Serie

Enhancement of and interference among higher order multipole transitions in molecules near a plasmonic nanoantenna

Spontaneous emission of quantum emitters can be modified by engineering their optical environment. This allows a resonant nanoantenna to significantly modify the radiative properties of a quantum emitter. In this article, we go beyond the common electric dipole approximation for the molecular electronic transition and take light-matter coupling through higher order multipoles into account. We investigate, by means of theory and numerical simulations, a strong enhancement of the magnetic dipole and electric quadrupole emission channels of a molecule adjacent to a plasmonic patch nanoantenna. While this on its own had been considered, the assumption in prior work usually has been that each molecular transition is dominated only by one of those multipolar emission channels. This leads naturally to the notion of discussing the modified emission in terms of a modified local density of states defined for each specific multipolar transition. In reality, this restricts the applicability of the approach, since specific molecular transitions occur via multiple multipolar pathways that have to be considered all at once. Here, we introduce a framework to study interference effects between higher order transitions in molecules by (a) a rigorous quantum-chemical calculation of their multipolar moments and (b) by a consecutive investigation of the transition rate upon coupling to an arbitrarily shaped nanoantenna. Based on that formalism we predict interference effects between these transition channels. This allows for a strong suppression of radiation by exploiting destructive interference. Our work suggests that placing a suitably chosen molecule at a well defined position and at a well defined orientation relative to a nanoantenna can fully suppress the transition probability.Comment: 30 pages, 8 figure