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What if everyone voted?

And what the answer tells us about voter suppression

G. Elliott Morris
Data journalist
The Economist

September 30, 2019

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What is a "data journalist"?

 

 

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What is a "data journalist"?

A "data journalist" is just like a "regular" journalist who relies on their own skills in empiricism to tell a story.

Process:

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What is a "data journalist"?

A "data journalist" is just like a "regular" journalist who relies on their own skills in empiricism to tell a story.

Process:

1. Find a story

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What is a "data journalist"?

A "data journalist" is just like a "regular" journalist who relies on their own skills in empiricism to tell a story.

Process:

1. Find a story

2. Find a data-driven angle in said story

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What is a "data journalist"?

A "data journalist" is just like a "regular" journalist who relies on their own skills in empiricism to tell a story.

Process:

1. Find a story

2. Find a data-driven angle in said story

3. Analyze data with statistics programs (Excel, STATA, Python, R)

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What is a "data journalist"?

A "data journalist" is just like a "regular" journalist who relies on their own skills in empiricism to tell a story.

Process:

1. Find a story

2. Find a data-driven angle in said story

3. Analyze data with statistics programs (Excel, STATA, Python, R)

4. Convey information (with words and graphics)

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What if everyone voted?

 

 

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Guiding questions

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Guiding questions

1. How many Democrats and Republicans are there?

Given data constraints, we're really asking: How many Clinton and Trump voters are there?

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Guiding questions

1. How many Democrats and Republicans are there?

Given data constraints, we're really asking: How many Clinton and Trump voters are there?

2. How are they distributed geographically?

The answer lets us assign Electoral College votes.

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Data

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Data

1. Cooperative Congressional Election Study (CCES): A survey of 64,000 Americans

Includes demographic data and 2016 vote choice for 40,000+ validated voters

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Data

1. Cooperative Congressional Election Study (CCES): A survey of 64,000 Americans

Includes demographic data and 2016 vote choice for 40,000+ validated voters

2. American Community Survey (ACS): A Census Bureau survey of 175,000 Americans

Includes the same demographic data as the CCES 32,640 “cells”

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Method

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Method

1. Train a predictive model on CCES data

  • Multi-level logistic regression
  • Predict vote choice with: age, gender, race, education, region and interactions between them
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Method

1. Train a predictive model on CCES data

  • Multi-level logistic regression
  • Predict vote choice with: age, gender, race, education, region and interactions between them

2. Use the model to predict voting habits for every eligible American

Via “post-stratification” on the ACS

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ACS Post-stratification

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ACS Post-stratification

1. Each "type" of person gets their own "cell":

  • One cell for white men ages 18-30 without college degrees who live in the Northeast
  • Another for white men ages 18-30 without college degrees who live in the South
  • Another for non-white men ages 18-30 without college degrees who live in the Northeast
  • etc.
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ACS Post-stratification

1. Each "type" of person gets their own "cell":

  • One cell for white men ages 18-30 without college degrees who live in the Northeast
  • Another for white men ages 18-30 without college degrees who live in the South
  • Another for non-white men ages 18-30 without college degrees who live in the Northeast
  • etc.

2. We know how many voters in that "cell" live in each state

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ACS Post-stratification

1. Each "type" of person gets their own "cell":

  • One cell for white men ages 18-30 without college degrees who live in the Northeast
  • Another for white men ages 18-30 without college degrees who live in the South
  • Another for non-white men ages 18-30 without college degrees who live in the Northeast
  • etc.

2. We know how many voters in that "cell" live in each state

3. So we can say that x and y% of each "cell" vote for Clinton or Trump, then add up

  • For example, a Latino female age 18-30 with a college degree in Texas is 85% likely to vote for a Democrat for president (White man 65+ is 80% Republican)
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Results

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Results

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Results: If everyone voted

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What does this tell us about voter suppression?

 

 

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Voter suppression

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Voter suppression

- We can modify the percentage of each group that turns out to vote, then re-predict the election

  • What if only all whites vote?
  • All non-whites?
  • Whites without degrees? Etc.
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Voter suppression

- We can modify the percentage of each group that turns out to vote, then re-predict the election

  • What if only all whites vote?
  • All non-whites?
  • Whites without degrees? Etc.

- Democrats do better when non-whites turnout; Republicans have a vested interest in keeping turnout rates low

  • Especially in southern states with large minority populations
  • Their efforts to move voting locations off-campus—TX almost removed the FAC as a precinct after 2018—also have political consequences
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Suppression of white votes

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Suppression of non-white votes

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Considerations

What this doesn’t tell us:

  • That Clinton/Trump/Abrams/etc would have won if certain x, y or z restrictions had been put in place
  • Downstream effects (AKA party positions and coalition changes)

The balancing act:

  • There are a ton of white, non-college educated voters in the Midwest that tilt national scales if we increase turnout
    • Especially because increases in turnout are not uniform
    • And because of their geographic distribution, small relative increases in white turnout can tip the Electoral College to Republicans (see: 2016)
    • But on the other hand, some organizations are explicitly targeting non-whites and young voters for turnout purposes
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Thank you!

 

G. Elliott Morris

Data journalist, The Economist

Email: elliott@thecrosstab.com

Twitter: @gelliottmorris


These slides were made with the xaringan package for R from Yihui Xie. They are available online at https://www.thecrosstab.com/slides/2019-09-30-utaustin/

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What is a "data journalist"?

 

 

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