Post #2

In the first stage of my research, I went one-by-one through some of the existing economic studies that statistically and empirically evaluated the effects of right-to-carry, shall-issue, and concealed handgun permit laws on crime rates in the United States over the past several decades. My main takeaway from this initial stage of research was that there is a lack of consensus among the research community on the effects that these laws have on crime in our country.

Over the past few weeks, I have been comparing my notes on the different studies in an attempt to understand why researchers using the exact same data sets have reached such contradictory conclusions. While it has been difficult to fully understand some of the advanced statistical methods that the researchers use in their studies (I’ve only taken one stats class), I was still able to gain great clarity on why this type of research is so difficult and why reaching complete consensus among the research community on the effects of gun laws is nearly impossible.

To begin with, gun control is a highly polarizing subject that has dominated political discourse for many years, and partisan tensions around this issue have only been heightened by recent mass shootings. Even though the focus of my project has nothing to do with politics, it is important to note that researchers may not all be completely unbiased. Looking into the backgrounds of some of the researchers, I have found that many of them have direct political affiliations to pro-gun or anti-gun advocacy groups and could therefore have agendas of their own. It isn’t difficult for researchers to slightly tweak models in order to get results that are more in line with their own beliefs.

Another reason that evaluating the effects of gun laws on crime rates in the United States is so difficult has to do with the assumptions that researchers are making. In order to assess the impact of a gun law, researchers have to create counterfactual outcomes (for example, what the crime rate in Virginia would have been if a shall issue law wasn’t enacted). These counterfactual outcomes are necessary for statistical comparison, and in order to reach these outcomes, researchers need to make assumptions across space and time. There is little consensus among researchers about a credible set of assumptions, and since slight modification of assumptions can lead to drastically different results, it is understandable why researchers reach such different conclusions.

Lastly, the statistical models and methodologies have varied greatly from study to study, which also accounts for the great variety of conclusions. Researchers have to make many decisions on which confounding variables they adjust for and which they ignore. For example, one study uses cluster adjustments to correct for serial correlation, while another chooses to completely ignore serial correlation; these two studies reached opposite conclusions on the effect that right-to-carry laws had on crime rates.

Now that I have gone through all of my sources and compared them, I will begin writing my research paper over the next few weeks. Hopefully, I will be able to consolidate my ideas into a strong end product and clearly articulate what I have learned over the past few months!