Is Freedom Better?

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Why We Built This

Everyone has opinions about what makes societies thrive. Some say it's freedom. Others say it's equality. Many point to democracy. But what does the data actually show?

We wanted to cut through the noise and let the numbers speak. So we gathered data from 150+ countries and asked a simple question: which ideas actually correlate with people living better lives?

A Note on What This Can (and Can't) Tell Us

Let's be honest: correlation isn't causation. We can't prove that economic freedom causes better outcomes. We can't run experiments on entire nations or rewind history to test different policies.

But here's the thing — when you're studying something as complex as human societies, correlation is often the best tool we have. And when you see the same patterns showing up again and again, across different metrics, from different organizations, covering different aspects of life... that's worth paying attention to.

Think of this as a compass, not a GPS. It points in a direction, even if it can't tell you exactly how to get there.

How We Did It

1

Gather the Data

We pull fresh data from trusted sources — the World Bank, UN, Heritage Foundation, and others. No cherry-picking, no outdated numbers.

2

Match the Countries

We line up countries across all datasets. If a country doesn't have data for a specific metric, we leave it out of that comparison. Simple as that.

3

Crunch the Numbers

We calculate Pearson correlations — a standard way to measure how strongly two things move together. Higher number = stronger relationship.

4

Check Our Work

We test for statistical significance (p < 0.05). This tells us whether the pattern is real or just random noise. Spoiler: the patterns here are real.

Where the Data Comes From

We don't make anything up. Every number comes from established international organizations:

Reading the Numbers

Not sure what a correlation of 0.7 means? Here's a quick guide:

  • 0.7 - 1.0: Strong relationship (these two things really move together)
  • 0.4 - 0.6: Moderate relationship (there's definitely something here)
  • 0.1 - 0.3: Weak relationship (a hint, but not much to write home about)
  • Around 0: No relationship (these things don't seem connected)

For context: Jacob Cohen's landmark 1988 work established that in social science, r = 0.5 counts as a "large" effect (Cohen, 1988). Most published findings don't come close. The correlations here are above 0.5 — that's rare.

Talk to Us

Spotted a mistake? Have an idea? Just want to say hi? We're real people and we read every message. Drop us a line — we'd love to hear from you.