Answering the Immigrant Question: Are Immigrants Beneficial or Detrimental to the US?
Last week we spent a significant amount of time looking at different metrics that I have dubbed the “quality of life metrics”. I appreciate your patience in delving into the data metrics I created for you. I wanted you to look to see if a correlation exists between the immigrant population in the United States and the different metrics that I believe both define quality of life and address the various notions of immigrant in the country. Although there are various metrics, all the them can be condensed into three major topics – jobs or wages, crime and security and culture. Although I do not believe that culture should play a part in answering the question about immigrants, it nonetheless has been forced upon us because of the issue of speaking Spanish in the country is often argued as well as the “assimilation” of immigrants. They have become rallying cries for opponents of immigration. Today, I am going to attempt to answer the question – Are Immigrants Beneficial or Detrimental to the US by taking all the metrics I compiled and creating a snapshot of them.
I realize some of you may be tempted to argue that my methodology is unfair or ignores issues such as the “possibility” that one terrorist may make it across the US-Mexico border to attack the country. The fact is that anyone can take one metric and use it to prove their point, one way or the other. That is the problem with the debate on immigration – incomplete data that allows unfounded notions to be used as facts.
Nonetheless, I want to answer the question about immigrants and I want to do it in the fairest way possible. I gathered as many important metrics as I could from the most reliable sources possible and ranked them for each state. As you know, there are 50 states in addition to the District of Colombia making a total of 51 subdivisions that make up the voters in the United States. I ignored the US territories as they are not part of the debate. The metrics are the maps I shared with you last week.
As you can tell from the various maps there is no clear correlation between the immigrant population mix per state and the quality of life metrics. Individually each metric can be used by proponents of immigration and opponents as they suit their needs. But, the metrics individually do not answer my question.
I need a way to look at them in a cumulative fashion. As there are 51 subdivisions, I decided to create a heat map of the metrics ranked from best to worst. I decided that I would use a scale of one to five, with one being the best and five the worst, for each metric. For example, a high crime rate is obviously bad for everyone and thus the highest crime rates are in red.
My metrics maps ranked the states from one to 51. I sub-grouped them into five divisions; one through 10, 11 through 20, 21 through 31, 32 through 41 and 42 through 51. The middle is 26.
The heat map is divided into the five divisions, with green being the best and red the worst. The middle, 21 through 31 is yellow and that is surrounded by a light green on the best side and light red on the other side. The bright green and red are the extremes.
As I went through my metrics last week, I noticed that the immigration debate is three debates in one – the overall immigration populations, the undocumented immigrants and the Mexican immigrants. Thus, I am presenting the heat maps in relation to the three types of immigrants that are being debated.
The first group of immigrants is comprised of the total population of immigrants that make up a state’s population. In other words, the percent of the state that are immigrants. This population is comprised of both legal and undocumented immigrants. The darker the brown the higher the concentration of immigrants in that state’s population.
Clearly California, Nevada and Texas have the highest concentration of immigrants in their populations. New York and Florida also have high concentrations of immigrants in their midst. Remember that this includes both documented and undocumented immigrants.
The second grouping is made up the percent of immigrants that come from Mexico. These are immigrants that have marked the census forms as being born in Mexico. This, also, included both legal and undocumented Mexican immigrants.
As you can see, most of the Mexican immigrants are concentrated in the states that formally belonged to Mexico. This makes perfect sense as people tend to gravitate to where they feel most welcomed. Illinois, is also heavy on Mexican immigrants as it is well-known for its Mexican immigrant population.
The final grouping of immigrants are the undocumented ones. It is important to remember that this is a best-guess estimate based on taking census readings and subtracting the numbers of immigrants processed by Homeland Security. It is a best guess only and it should be accepted as that.
Although the estimated undocumented immigrant population follows the general trend of the other groupings, they are nonetheless more distributed across the country.
Generally, the three groupings of immigrants tend to gravitate to the southern United States. However, each of the groupings concentrate in different areas of the country. Montana, North and South Dakota consistently have the least concentration of immigrants in their populations. Mississippi as well.
Now that we know where the three groups of immigrants are located we can now look at the metrics that I believe determines the quality of life that many voters care about.
In my metrics, I excluded the GDP per state metric because I realized that for the purposes of this exercise – whether immigrants are good for the community or not – it does not matter to the average voter whether their state’s productivity is higher than the rest. Their immediate concern is whether their wages are high or not. I used the wages per GDP metrics as my first data point. I then added to it, the next metric: the median per household income for 2015 for each state. The higher the median household income, the more comfortable the voter likely is.
Although wages may be high in a state, if the state has a high unemployment rate, the high wages become irrelevant to the voter. Thus, I then added the ranked unemployment metric into the mix. As a check, I also added the poverty rate metric to my analysis.
To get a state ranking for access to jobs and higher wages, I averaged the four metrics together. This gives us an overall rank on the conditions of wages and access to jobs for each of the states. I believe this is a fair ranking for access to jobs and wages for the voters.
Wait! Hold on a moment, is likely what you are thinking. If I took the 51 states and grouped them in fives, then there should be at least 10 in each color group. But, remember, that I averaged the metrics together giving us a different set of groupings. The reason I believe that this is a fair representation of the jobs and wages situation is because it is not enough to have higher wages if the unemployment rate is high, as well. Likewise, with household incomes.
The next metric I heat mapped is the FBI’s violent crime data for 2013. The FBI defines violent crimes as aggravated assaults, homicides, murder & robberies. As I have written various times before, the use of the FBI’s violent crime data can be misleading as a metric for the crime levels in each community. The FBI, itself, discourages its use as a ranking mechanism. There are many factors that contribute to the crime rate, nonetheless, we need to quantify the crime rates to answer the question about immigrants.
Remember that everyone generally agrees that the crime rate is not a fair representation of a state’s crime rate, however, it will be useful later as we aggregate all the other metrics that I have compiled.
The next metric is the issue of taxes. Many opponents of immigration argue that immigrants cause higher taxes in the consumption, or misuse of benefits or infrastructure. As I have discussed previously, taxes are the result of public policy agendas that vary from jurisdiction to jurisdiction. There is no way to fairly compare them between states. Nonetheless, it is an important metric that must be addressed.
To do this, I decided to look at the cost to educate each pupil in each state. The higher the cost, the higher the burden it is on the taxpayer. However, this metric is still subject to the whims of public policy agendas. To somewhat balance this, I added two additional metrics. The percentage of the population that has a high school diploma and another metric showing the percent of the population that holds a bachelor’s degree. In addition to balancing the cost to teach each pupil, the high school diploma and the bachelor’s degree percentages also adds to the understanding of the taxation burden. This is because it stands to reason that a higher educated population is more likely to be gainfully employed and possibly less of a burden to the taxpayers.
In addition, and because of the Affordable Health Care Act, which mandates health insurance coverage and because uninsured patients are a burden to the taxpayers, I added a metric ranking the percent of the population that lacks health coverage.
Finally, I added a ranking of the states with the percent of their population on food stamps/SNAP. Interestingly, the rankings of the populations on food stamps is further evidence that the metrics cannot be used alone to rank the states. For example, the top five states with the greater number of its population on food stamps are: The District of Columbia, Mississippi, New Mexico, Oregon and West Virginia. The District of Columbia and Oregon are anomalies and if I were to present a heat map to you of just this metric you might be left with the impression that DC and Oregon are the poorest states in the country. Obviously, they are not and therefore it is important to aggregate different metrics together to get a better understanding of the issue.
I then averaged these metrics to give us a heat quotient for our map showing the taxation burdens in each state. Remember that although this metric is labelled “taxes” it is nothing more than a representation based on certain metrics that I selected.
Like the jobs metric, since this ranking is an average of other metrics, the results are not distributed equally. It is also important that you keep in mind that my representation of taxes does not include personal income taxes that certain states levy or value added (sales taxes) in other states.
At this point we have three heat maps that represent three metrics that I believe are important to the voters. As stated above, the crime rates cannot be used individually as they provide distorted information. The food stamp example demonstrated this. As I thought about the best way to represent a voter’s quality of life, it dawned on me that I should approach it from the perspective of looking for a place to live.
Imagine that you are moving and the whole United States is open to you. You would likely choose a state with low crime rates, low unemployment rates, high educational attainments, great wages and the least burden on the taxpayers. Thus, you want to see a ranking of each state based on these factors. To accomplish this, I ranked the states by averaging the three maps above. I call this the quality of life map.
Because this map is also an average of the various metrics it is not evenly distributed. I also believe it is a fair representation of the rankings of each state with the metrics that are likely very important to the taxpayers.
Mississippi and Tennessee came in at the very bottom of these rankings. I was also surprised to see how the United States seems to be divided in half, with the better quality of life, based on my metrics, on the northern part of the country.
There is only one state that meets the best of the quality of life criteria and has the lowest immigration population mix; North Dakota. There are some readers that will point out that Montana, North and South Dakota have very low population mixes and better quality of life metrics.
However, the other side of the argument can be made by pointing out Colorado. It has a high concentration of immigrants, Mexican immigrants and undocumented immigrants, low taxes and high jobs as well as a crime rate in the middle.
It is true that the higher immigrant populations reside in the areas where there tends to be more negative quality of life metrics, such as lower access to jobs, higher taxes and a higher crime rate. However, there is no direct correlation because the same thing can be argued about the southern United States, even if you exclude the immigrant populations. For example, Mississippi and to a lesser extent Alabama, Louisiana and Georgia.
The Assimilated Immigrant
One of the most difficult issues to address is the issue of the cultural pressure put upon the native population by immigrants. This is especially more difficult for the United States because of several unique factors. One factor are the native Spanish speakers who were not originally introduced by immigrants, but rather it was always part of the country. The ethnic makeup of the country is also diverse, with Hispanics or Latinos present in the country from the onset.
Ultimately, in the case of the United States there is no proper method to quantify cultural diversity in support or in opposition to immigration because it is highly subjective. There are metrics, such as the Hispanic/Latino population mix of each state or the percentage of the population that speak Spanish at home. However, the United States included many among its population that from the onset spoke Spanish or are Hispanic/Latino. That these two populations grow cannot be correlated directly to immigrants because there is no way to separate the native from the immigrants for these two metrics. Although assumptions, such as birthrate can be made, they cannot be conclusive by any measure.
Are Immigrants Beneficial or Detrimental to the United States
Based on the metrics that I compiled here, I do not believe that the question can be answered conclusively. I do not see a direct correlation, either positive or negative, between the number of immigrants in a state and the metrics that I compiled.
I agree that the heat maps tend to show a propensity for low immigration populations and a better quality of life, based on the metrics I compiled. I submit to you that I can take the same set of metrics and make the argument that immigrants have no bearing on the quality of life metrics because the populations are as distributed as the metrics are. This is because the metrics I compiled ignore several other factors that contribute to the results. Ultimately, there is no clear answer to the question I posed originally.
I expect many of you will disagree with my methodology. Nonetheless, I believe that it is a fair representation of the major issues that consume the immigration debate. You are welcome to take my data and draw your own conclusions.