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The influence of firearms on violent crime in the United States has sparked a significant amount of public discussion. It would seem that there are sufficient research arguing both sides (namely, that the legislation has been successful and that it has not been effective), making it possible for anybody to cherry pick a study to support their position. A visualization in this piece, however, provides a different takeaway from the ultimate result.
The purpose of these articles is to do an analysis of the effects that the legislation had within the relevant time period for the data that was available. This research includes graphic representations to help readers comprehend whether or not the right-to-carry statute has resulted in a reduction in violent crime. In the next section, Panel Regression will be used to provide an estimate of the effect that the right-to-carry statute has had on the rate of violent crime.
Gun control and gun decontrol are two of the most prominent schools of thought about how to reduce gun-related crime. Gun control advocates contend that effective measures to curb the availability of weapons on the market should take the form of appropriate government regulations. On the other hand, supporters of looser gun control argue that people will be better able to defend themselves, their property, and their communities if they are allowed a greater degree of personal autonomy in matters pertaining to firearms. More specifically, they believe that every citizen should be allowed the right to own and carry a firearm, with only minimal restrictions. The assumption that individuals who plan to do damage will be dissuaded from doing so if they believe that possible victims of gun violence are likely to have the capacity of defending themselves and, as a result, perhaps causing injury to the potential offender is at the core of the reasoning put out by proponents of loosening restrictions on the ownership and use of firearms.
A balanced panel of statistics on gun violence in all 50 states of the United States, plus the District of Columbia (for a total of 51 states), broken down by year from 1977 to 1999 is presented in Guns.

Understanding the dataset
Dependent Variable: crime
A Dictionary of Data: The data consists of a balanced panel of all 50 states in the United States, as well as the District of Columbia (making a total of 51 “states”), arranged chronologically by year from 1977 to 1999. Each observation represents a different state in a particular year. In all, there are 51 states, which multiplied by 23 years equals 1173 observations.

Analysis
Before any data analysis the data must be prepared to check if there is existing missing values or which value/variable can be used as target/dependent variables. Using the automatic data preparation from spss the following table if formed for a given linear regression preceeding
Panel regression techniques will be utilized in this section to explain the change in the rate of violent crime dependent on variables such as the imprisonment rate, the right-to-carry statute, and population.

During the entire period under observation, right-to-carry laws were in place in only 29 out of the 51 states.
Only four of these 29 states had a statute that allowed citizens to carry concealed firearms when the observation period began.
In the second part of the monitoring period, more than half of the states had actually implemented the legislation.
The states that have not passed a right-to-carry legislation at all during the analyzed time period are referred to as non-shall states, while those that have done so at least once during the period in question are referred to as shall states.
Insights gained by analyzing Graph 2: The trend of the average violent rate over time in shall states and non-shall states is comparable to the “overall average violent crime rate,” and there has been neither an increase nor a drop in the average crime rate in shall states over the course of the years.
Initial Hypothesis: This graph does not provide sufficient evidence since there is no clear delineation between the average violent crime rate before and after the implementation of shall law in shall states.

In places where the legislation has been enacted, the crime rate is broken down into two categories: before and after the implementation of the law, as shown in Graph 3 (which tests Hypothesis I).
For example, if the law was first implemented in state “1” in the year 1990, then the average rate of violence in state “1” before 1990 will be referred to as the “shall states avg. violence rate before shall intro,” while the average rate of violence in state “1” after 1990 will be referred to as the “shall states avg. violence rate after shall intro.”

The “Shall states avg. violence rate before shall intro” will be 0 for years beginning in 1997 since 1997 was the final year in the observed period in which shall legislation was implemented.

The information that can be gleaned from Graph above reveals that the trend of “shall states avg. murder rate after shall intro” has grown throughout the years.
Despite the fact that this demonstrates that laws have not been effective in reducing the crime rate, it is possible that this is due to the fact that states that adopted shall laws during the earlier part of the observation period have a lower average violent crime rate than states that implemented the law during the later part of the observation period.

Graph below; Do the states that adopted the legislation during the first half of the observation period have a lower average violent rate than the states that implemented the right-to-carry statute during the second portion?
The data for the states in which the legislation has been passed have been divided into many buckets according to the year in which the law was passed, and each bucket contains the previous five years’ worth of information.

(77–80), (81–85), and (86–90) have a lower average crime rate than states that have established shall legislation in (91–95), (96–100), which demonstrates that states that have adopted the law during the early time of the observation had a lower average violent crime rate than states that implemented the rule during the later period of the study.
None of the graphs shown up to this point have provided any conclusive information about the efficiency of the legislation. It’s possible that if “Graph above” was broken up into many subgraphs, each of which showed a distinct trend, we’d have a better grasp of the data.

Graph below (Split of Graph above): Assuming that four states had enacted the shall legislation in the period between 1977 and 1980, the graph below analyzes the average violent crime rate in those four states after the implementation of the law (i.e from 80 to 99).

conclusions drawn from Graph above It has been noticed that the average violent rate has dropped in places where the legislation has been adopted over a variety of time periods. This demonstrates that the right-to-carry statute has been beneficial in reducing the amount of violent crime that occurs.
This is merely a graphical depiction, and there are a variety of other reasons that might be contributing to a lower or higher incidence of violent crime.

The above graph shows the crime rate against the male variable which shows that the number of crimes reduces due to reduce in the number of male population in a given state.
The above graphs from a linear regression analysis proves that the rate of crime increases with each year which shows that by increase in population the rate of crime increases.

Conclusion
The estimate of the “Fixed Effects with Entity-Fixed and Time-Fixed” model and the “Fixed Effects with Entity-Fixed” model both indicate that having a right-to-carry law results in a lower rate of violent crime than not having a right-to-carry legislation, but the difference is less than 4 percent.
This is also consistent with the conclusions from analysis, which said that “right-to-carry legislation has proven successful in effectively lowering the rate of violent crime.” Other studies have shown that an increase in the availability of firearms leads to an increase in the number of robberies (burglary rate).
Only the rate of violent crimes is examined in this research.

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