Research Methodology — Are Red or Blue States Better?

Introduction

Is conservative ideology better or worse than liberal ideology?

That’s a tough question!  But more or less, it’s what this study is proposing to answer.  Obviously, we have to get a lot more specific.  So let’s rephrase this research question as

Do Republican states do better or worse on what matters than Democrat states?

Again, a huge (and still fairly vague) question!  Why look at states?  Why look at political parties?  What makes a state Republican or Democrat?  What kinds of things “matter”?  What do you mean “better” or “worse”?  OK, OK, I’ll make it a little more specific

How do states who vote Republican in Presidential races compare on a range of non-controversial economic and quality of life indicators to states who vote Democrat?

Well, to parse apart any other ambiguities and learn how I went about answering this question, please check out the rest of this article.

Findings

You should totally read over the methodology I used, but I know a lot of readers just want to get to the results (or you can scroll back up after you’re done reading!)

Here are the four categories of indicators, a post for each:

Independent Variable

(Political Affiliation)

Causal Assumptions

This study uses voting patterns and political party affiliation as an indicator of political ideology and implemented policy, which it then correlates with economic and quality of life outcomes.

To connect all of this, three “common sense,” non-partisan assumptions are made about causality.

  1. Political affiliation causally affects implemented policies.
    1. In other words, states that vote more conservative end up having more conservative policies.
  2. Political affiliation is an indicator of culture.
    1. States that are more conservative culturally end up voting for more conservative representatives.
  3. Policy and culture causally affects outcomes.
    1. States with more conservative policies and culture will generally have different outcomes than states that are more liberal.

Of course causality is a whole big mess.  But these are all fairly common sense and strong assumptions about causality that both political parties can agree on.  So if you think the correlations this study finds are spurious, then you have to dismiss one of these fairly obvious facts.

Further, this study sets up temporal precedence.  Some have pointed out that it may be the case, for instance, that Blue states don’t become rich, but rich states become Blue?  Or maybe some other factor is causing both Blue-ness and rich-ness?  However, causal precedence accounts for this by first measuring A) the presumed cause before B) the presumed effect.  More specifically, I look at

  • A) 12 years of policy / culture (indicated by voting patterns), and then look at B) a specific outcome at the end of that period.

And I don’t look at

  • B) a history of a specific well being indicator and then track A) subsequent voting after that

Lastly, none of this is perfect.  Every study can only ever looks at correlation.  You can never measure causation.  But 1) claims about spurious correlation lead to absurd conclusions about commonly held beliefs and 2) this study accounts for causal precedence.

You may want to check out my article “How Correlation Does and Doesn’t Imply Causation” for more.

Unit of Analysis

The population of states were chosen instead of the population of counties for a few reasons.

  1. Good data sets are attainable for 100% of states on a wide variety of measures, but it’s nearly impossible to find such for even most counties on most measures.
  2. Data is not commensurable across counties but is more so when looking at the state level. It’s completely commensurable when comparing voting in the Presidential election.  In other words, what “conservative” or “liberal” means varies incredibly county to county.  The same when considering what a policies or ideology a “Republican” or “Democrat” might stand for.
  3. While there is great variation within states across counties, for instance, with the urban vs suburban vs rural divide, this pattern is virtually universal between states.
    1. In other words, a rural county in a Red State may be more conservative that an urban county in the same state.  However, this same general pattern is equally true for Blue States.
    2. Further, a rural county in a Red State is more conservative than a rural county in a Blue State.  The same goes for comparing “liberal-ness” of Red vs Blue suburban and urban counties.  Therefore, all things considered, Red States are more conservative than Blue States.

Presidential vs Gubernatorial Elections

Presidential election results were chosen over elections for the governor or other state legislators or officials as an indicator of a state’s political policies and culture for several reasons. Initially, the argument for preferring gubernatorial or other state elections makes sense since they have a larger and more direct influence on a state’s legislation.  However, the Presidential election 1) reflects more of the population and 2) uses the same definitions for “Democrat” and “Republican.”  More specifically,

  1. Americans are horrible at voting. Around 50% more people vote in the presidential elections compared to midterms (around 60% vs 40%, respectively).  Therefore, a state’s voting pattern for the president is much more representative of the political views of the state’s population, and therefore culture.
  2. A state may vote for a Republican President, but have a Democrat Governor. However, local party affiliation isn’t commensurable with national affiliation. For instance, some local Red State Democrats may be more right leaning than some local Blue State Republicans. Different states define “Republican” and “Democrat” very differently, locally speaking, compared to other states. However, when we look at who a state votes for in Presidential elections, every single state is talking about the exact same person and, more importantly, the exact same policy platform. Only using national elections is the data commensurable.
  3. Additionally, focusing on the last four Presidential elections takes advantage of comparing supporters of Trump, Obama, and Bush. This is a prominent national conversation.

Possible Categories of States

States are categorized as Red, Purple, or Blue.  In the last four elections, Red states voted mostly or always for Republican presidents and Blue states mostly or always for Democrats.  Purple states voted 50-50.

Dark and light Red and dark and light Blue, plus Purple, were initially used to categorize states, resulting in five categories.  However, this was reduced to three categories for simplicity’s sake in data analysis and ease in visually parsing apart the data.  However, each state was assigned a number, either 1, .5, 0, -.5, or -1, corresponding to these five “hues,” respectively.  If no strong trends emerge during data analysis, or if a future researcher has the time and energy to do so, the data set may be broken down into these five finer categories and re-analyzed.

 

Dependent Variable

(Quality of Life Indicators)

Finding Common Ground

Only indicators of economic and quality of life outcomes that are “non-controversial” or “common ground,” i.e. agreed upon as positive (or negative) indicators by both political parties, will be used.

Examples of controversial variables are abortion rates, marijuana use, immigration, climate change policy, evolution being taught in schools, or LGBTQ marriage.  Generally, Democrats and Republicans would disagree when assessing these as positive, negative, or neutral in terms of economics or quality of life.

The purpose of this is so that I can only include so many indicators and I don’t want there to be any squabbling about the results.

Additionally, widespread agreement on an indicator suggests that it is much more likely to be actually important, in terms of quality of life.  In comparison, it’s less likely that an indicator is actually important if there’s widespread disagreement about it, in which half of Americans are wrong.

Please note, especially if you’re a conservative leaning, that two conservative preferred indicators are included in the “controversial indicators” post.  Both are discussed in the next section and included because my conservative dad was adamant about it.

Examples of Indicators that were Excluded

*Note: A post will be created about these “Controversial Indicators” but they won’t be used to calculate Red vs Blue comparisons on the Economy, Crime, Society, or Health.

Single parent households with children is an interesting indicator and was explicitly rejected for two reasons.

  1. This indicator isn’t common ground. While it’s big for conservatives, liberals don’t particularly care about it.  As a guess, the difference might be rooted in ideologies regarding the value of father-led nuclear family.  Regardless, it’s the difference is so big that it’s even somewhat common for liberals to choose to have kids on their own.
  2. More importantly, neither liberal nor conservative voters care about this indicator in and of itself.  Single parents often nurture happy, healthy children without any problems.  Both sides instead care about things like child poverty/malnutrition or access to role models.  Stats like child poverty, household food insecurity, and high school graduation rates are already included in this study.
  3. There is also reason to assume that it’s better to be a single parent in a Democrat state than a Republican state.  For instance, assuming more/better welfare in Democrat states, it would be easier for poor single parents to avoid child malnutrition.  Assuming better public schools in Dem states, it’d be easier for kids to find additional role models.  (Note: While it’s assumed Rep states have closer knit communities, it’s also assumed that there’s more stigma against single moms).

Abortion rates is another notable indicator that was excluded.

  1. Abortion by state is hard to measure.  No other indicator assessed has such variety in state laws, stigma, and options for access (e.g. number of Planned Parenthood clinics).  The result is that many Red State citizens get abortions in Blue States where they legally are allowed to, face far fewer protesters, and can more easily access it.  Similarly, it is common that where there are harsher laws, greater stigma, and less legal access, residents are more likely to obtain illegal abortions, which are very difficult to count. The researcher could not find any data sets that even attempted to account for these factors, both of which likely deflate Red state numbers.
  2. While, this is an incredibly important indicator for many conservatives, many Democrats don’t see it as important at all.  This study aims to find common ground not just so we don’t squabble over what to include, but also because, generally speaking, if we both agree on it then it’s much more likely to actually be important.  While if we disagree, one of us is necessarily wrong. Is it the Dems?  or the Reps? I don’t want to include such in comparing party ideologies.
  3. If abortion is super important to you, then please keep it in mind!  However, you should take a look at other indicators of child well-being included in this study.  After all, kids don’t become less important after they’re born.
    1. Percent of Children in Poverty
    2. Infant Mortality rate,
    3. Divorce rate,
    4. Teen Birth rate, and
    5. Household Food Insecurity rate

Indicators were also excluded and deemed “controversial” if the best data sets I could find were, for example,

  1. For 2017 or earlier.
    1. The reason for this is because to misses a lot of the time being measured, ie the last 4 Presidential terms.
  2. Based on research conducted by a NGO, university, think tank, etc.
    1. The reason for this is that anything but an official (Republican) government agency data set might be seen as having a liberal bias.
    2. Examples of this include Census, CDC, HHS, and FBI.
  3. Skepticism about cherry picking indicators.
    1. For instance, I couldn’t find STD’s per capita by state, but did find data on some individual STD’s.  I then randomly chose two of the most well-known so that it didn’t look like I cherry picked the one STD that came out better for Democrats.
    2. Similarly, I couldn’t find good state data on welfare recipients across all/most programs. However, I did find good numbers for food stamps, but I excluded this indicator because I didn’t want it to look like I cherry picked this particular welfare program.

 

Data Analysis

Red States and Blue States will count for 1 for their respective category.  Purple states will count for 0 given that it’s equally likely, with the rough indicator used in this study, that the relevant policies would be either liberal or conservative leaning.  Are they following the general trend or an outlier?  Impossible to say without looking more into it.  In comparison, while it’s likely all Red States have some liberal leaning policies, and vice versa, Red State policies lean conservative.

Data will be analyzed in five ways, which be tallied together for an overall score for each indicator

  • Percent of the dominant political party in the top and bottom 5 (10% of) states.
    • These will be referred to as the “Failed” and “Model States,” respectively
    • A “Major Winner” will be at least 80% (4 out of 5, or 4:1) of states in the top 5
      • 60% (3 out of 5, or 3:2) is a “Minor Winner” given that just a single state flipping would completely change this result
      • For the bottom 5, the calculation’s the same, but the other color/party is the winner
      • Analyzing the difference in magnitude between states or weighting states as Dark or Light Red/Blue would allow better measuring and assessment in future studies.
    • Examples
      • “60% of Model States were Red, making Republicans the Minor Winner”
      • “80% of failed states were Blue, making Republicans the Major Winner”
  • Percent of the dominant political party in the top and bottom 15 (30% of) states.
    • This will be referred to as the “Good” and “Bad Basket”
    • A “Major Winner” will be at least 67% (10 out of 15, or 2:1) of states in the top 15
      • 53.3% or 60% (8 or 9 out of 15, or 8:7 or 3:2) of states is a “Minor Winner” given that just one or two states flipping would change this result
      • For the bottom 15, the calculation’s the same, but the other color/party is the winner
      • Analyzing the difference in magnitude between states or weighting states as Dark or Light Red/Blue would allow better measuring and assessment in future studies.
    • Examples
      • “53.3% of the good basket were Blue, making Democrats the Minor Winner”
      • “80% of the bad basket were Blue, making Republicans the Major Winner”
  • Percent of each political party better than the average for the US.
    • These will be referred to as “States that are Making America Great”
    • A “Major Winner” will be declared if the majority of one political party but a minority of the other is above the average for the US, with at least a 10 percentage point difference between them.
      • This is because a state from one group is more likely to raise up the US average, while a state from the other is more likely to pull it down
      • If one group has a higher percentage of states, but both groups have a majority or minority above the average, there will be a “Minor Winner”
      • Analyzing the difference in magnitude between states or weighting states as Dark or Light Red/Blue would allow better measuring and assessment in future studies.
    • Example
      • “60% of Blue states and 15% of Red states are making America great, making Democrats the Major Winner.”
  • Total Score / Winner for a specific Indicator
    • Points awarded
      • A Minor Win counts for 1 pt
      • A Major Win counts for 1.5 points
    • A party with the most points will be said to do Vastly, Clearly, or Slightly Better depending on their overall score from for the 5 possible wins discussed above.
      • Vastly Better – 6 to 7.5
      • Clearly Better – 4.5 to 5.5
      • Slightly Better – 3 to 4

 

My Background

My Research Background

My first masters was a research based Masters in Science in Comparative and International Education (basically “sociology of education”) degree from the University of Oxford.  A third of my coursework was in research methodology and my degree was awarded based on performance on a research based dissertation.  I wrote mine using data I collected during a month and a half of fieldwork in Bosnia.

I also took courses in research methodology and statistics during my second masters program for clinical social work at Columbia University.

Conflicts of Interest

I’m not getting paid for any of this, not even through any ad revenue.  Honestly, I’m just bored during the pandemic.  So I’m beholden to no financial incentives or agendas, except my own.

My agenda is to construct a study that conservatives will accept. To that end, much of the above was done to avoid claims of being biased, bending the results, etc.  For instance, I sought out a number of conservative family and friends to suggest indicators and discuss my methodology.

My Personal Bias & Politics

Full disclosure, I’m a Democrat and fairly liberal leaning myself.

However, I was raised very fundamentalist and conservative and identified with such into my early twenties.  I even voted for Bush the first time I cast my ballot in a Presidential race.  It wasn’t until the end of college – after learning about many of the statistics above! – that I became more left leaning.

Today I’m certainly left on the spectrum, but I’m also still notably moderate on a variety of issues.  In fact, I like to think of myself as a “European moderate.”

  1. For example, I believe that the US should move in the socialist direction, but will emphatically argue that capitalism has done a lot of good and should continue to be a substantive part of the economy. Every high income country, including the US, has some complicated mix of capitalism (read: run by the free market) and socialism (read: run by the government).
  2. Similarly, I’m also pro-choice, but think abortion in and of itself isn’t a good thing at all and empathize with many conservative arguments here
  3. I’m also strongly pro-racial justice, BLM, etc but also believe it’s important to have civil discussions, avoid labeling everyone as “racist,” and am proud of a lot of the unique American project

All this being said, I’ve included links to all of the data sets I’ve used, which are either the sources of the data or link to those sources.  So if you disagree, please check them out or find different data sets, and let me know!

7 responses to “Research Methodology — Are Red or Blue States Better?

  1. Sounds interesting! I guess the results will be in a future post?

    My initial concern is that I didn’t see you say anything about normalizing for money. So I fear you will wind up with a list of states rank-ordered roughly by, say, median income…but without being able to recognize that. It wouldn’t surprise me if rich states were both blue and had better quality of life metrics. But those would both just be causally independent expressions of being rich.

    Conversely, it seems possible that states with the highest peak population density might have worse crime rates, and in fact be blue, but without the blueness causing the crime.

    I’m sure you’ve anticipated such confounders. Just consider it an expression of interest.

    Best wishes!

    Liked by 1 person

    • Thanks Patrick!

      First, I’m almost done analyzing the data. I’ll publish each of the four main categories as I write them up.

      Second, I have a whole “Economics” category with eight indicators. So we’ll see how Blue or Red dominated they turn out to be! After all, conservatives argue that conservative economics is better economics.

      In addition, I’d argue that conservatives are much more likely to believe non-economic factors play an equally important role, like family and Christian values.

      Like

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