Why indifference is the best reaction to President Obama’s executive actions on guns.

The recent executive actions on gun control announced by President Obama have been met with both applause and criticism. Any response other than indifference is probably an overreaction, writes Matthew Lang. If the President’s actions are eventually carried out, background checks will rise as more private firearm sellers become legally viewed as dealers. The increase in background checks is unlikely to have any effect on gun-related deaths. Instead, he argues, President Obama’s announcement will most likely increase the number of firearms purchased by gun advocates, as is typically the case whenever gun owners perceive a possible threat to the Second Amendment. According to recent research, firearm-related deaths are unlikely to respond to an increase in the number of guns per household. Reducing gun violence will take more than redefining what it means to be a firearms dealer

Tighter gun laws may lead to fewer suicides

Monthly firearm background checks have been recorded in every US state since 1998, making it possible to explore whether changes in the availability of firearms in a state are related to its suicide rate. This relationship has been difficult to research in the past, as the fraction of suicides using firearms are a commonly used measure of firearms. Matthew Lang finds that increases in state background checks are associated with slight increases in the total suicide rate, suggesting that the increased availability of particular suicide method can lead to more suicides

This year has seen a massive surge in gun purchases in both Republican and Democratic states

Past research has shown that when Republicans are afraid for their safety, or when they are concerned about gun laws being tightened, they buy more guns. In new research which uses background checks as a stand-in for gun sales, Matthew Lang determines that there have been eight million ‘extra’ gun sales in both Republican and Democratic states in 2020 compared to previous years. Using Google Trends data, he finds that this surge in gun buying is likely to be linked to many Americans’ growing fears about their personal safety

Congress’ new firearm legislation may do little to stop mass shootings but may mark a turning point in addressing gun violence

Following mass shootings in Buffalo, New York and Uvalde, Texas, the US Congress proposed and passed the first meaningful firearms legislation in decades, the Bipartisan Safer Communities Act. Matthew Lang gives an overview of the bill’s provisions, including enhancements to background checks, red flag laws, and greater investment for mental health services and school safety. He writes that while the legislation may do little to reduce the number of mass shootings, it may mark a turning point, breaking the long-standing Congressional deadlock on measures to address gun violence

Streamlining Missing Data Analysis by Aggregating Multiple Imputations at the Data Level: A Monte Carlo Simulation to Assess the Tenability of the SuperMatrix Approach

A Monte Carlo Simulation Study was conducted to assess the tenability of a novel treatment of missing data. Through aggregating multiply-imputed data sets prior to model estimation, the proposed technique allows researchers to reap the benefits of a principled missing data tool (i.e., multiple imputation), while maintaining the simplicity of complete case analysis. In terms of the accuracy of model fit indices derived from confirmatory factor analyses, the proposed technique was found to perform universally better than a naive ad hoc technique consisting of averaging the multiple estimates of model fit derived from a traditionally conceived implementation of multiple imputation. However, the proposed technique performed considerably worse in this task than did full information maximum likelihood (FIML) estimation. Absolute fit indices and residual based fit indices derived from the proposed technique demonstrated an unacceptable degree of bias in assessing direct model fit, but incremental fit indices led to acceptable conclusions regarding model fit. Chi-squared difference values derived from the proposed technique were unbiased across all study conditions (except for those with very poor parameterizations) and were consistently more accurate than such values derived from the ad hoc comparison condition. It was also found that Chi-squared difference values derived from FIML-based models were negatively biased to an unacceptable degree in any conditions with greater than 10% missing. Implications, limitations and future directions of the current work are discussed

MIBEN: Robust Multiple Imputation with the Bayesian Elastic Net

Correctly specifying the imputation model when conducting multiple imputation remains one of the most significant challenges in missing data analysis. This dissertation introduces a robust multiple imputation technique, Multiple Imputation with the Bayesian Elastic Net (MIBEN), as a remedy for this difficulty. A Monte Carlo simulation study was conducted to assess the performance of the MIBEN technique and compare it to several state-of-the-art multiple imputation methods

Quantifying the latitudinal representivity of in situ solar wind observations

Advanced space-weather forecasting relies on the ability to accurately predict near-Earth solar wind conditions. For this purpose, physics-based, global numerical models of the solar wind are initialized with photospheric magnetic field and coronagraph observations, but no further observation constraints are imposed between the upper corona and Earth orbit. Data assimilation (DA) of the available in situ solar wind observations into the models could potentially provide additional constraints, improving solar wind reconstructions, and forecasts. However, in order to effectively combine the model and observations, it is necessary to quantify the error introduced by assuming point measurements are representative of the model state. In particular, the range of heliographic latitudes over which in situ solar wind speed measurements are representative is of primary importance, but particularly difficult to assess from observations alone. In this study we use 40+ years of observation-driven solar wind model results to assess two related properties: the latitudinal representivity error introduced by assuming the solar wind speed measured at a given latitude is the same as that at the heliographic equator, and the range of latitudes over which a solar wind measurement should influence the model state, referred to as the observational localisation. These values are quantified for future use in solar wind DA schemes as a function of solar cycle phase, measurement latitude, and error tolerance. In general, we find that in situ solar wind speed measurements near the ecliptic plane at solar minimum are extremely localised, being similar over only 1° or 2° of latitude. In the uniform polar fast wind above approximately 40° latitude at solar minimum, the latitudinal representivity error drops. At solar maximum, the increased variability of the solar wind speed at high latitudes means that the latitudinal representivity error increases at the poles, though becomes greater in the ecliptic, as long as moderate speed errors can be tolerated. The heliospheric magnetic field and solar wind density and temperature show very similar behaviour

Engineering estimates versus impact evaluation of energy efficiency projects: Regression discontinuity evidence from a case study

Energy efficiency upgrades have been gaining widespread attention across global channels as a cost-effective approach to addressing energy challenges. The cost-effectiveness of these projects is generally predicted using engineering estimates pre-implementation, often with little ex post analysis of project success. In this paper, for a suite of energy efficiency projects, we directly compare ex ante engineering estimates of energy savings to ex post econometric estimates that use 15-minute interval, building-level energy consumption data. In contrast to most prior literature, our econometric results confirm the engineering estimates, even suggesting the engineering estimates were too modest. Further, we find heterogeneous efficiency impacts by time of day, suggesting select efficiency projects can be useful in reducing peak load