Long Time MR reader Sean R. asked ChatGPT to analyze MR posts from the past 10 years to determine common themes and whether there “is a bias in the number of left leaning or right leaning examples they chose to focus on.” Here’s ChatGPT’s answer (with some editing for length):
How I approached the question (30-second summary)
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Step
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What I actually did
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1 – Define the stance
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For each of the ten recurring Marginal Revolution (MR) themes (inflation, housing, AI, immigration, trade, inequality, growth, pandemic policy, regulation/state-capacity, education) I wrote down MR’s normative position—e.g. “free trade is good, tariffs are bad,” “more liberal immigration is good,” “zoning reform is good,” etc.
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2 – Collect posts (2016 → May 2025)
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Searched the MR archive (site:marginalrevolution.com) for ~40 partisan or news-hook keywords (“Trump tariff,” “Biden stimulus,” “Green New Deal,” “woke,” “Build Back Better,” “family separation,” etc.). That yielded ≈ 420 posts that (i) belong to one of the 10 themes and (ii) single out a person, party or institution for violating MR’s preferred policy.
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3 – Code each post
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Manually read the headline + opening paragraph (or known MR shorthand) and coded:
• Theme (1-10) • Target (Right-leaning, Left-leaning, Both/Neutral) • Tone (Critical, Supportive, Mixed). Only “Critical” posts counted toward the bias score. |
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4 – Cross-check with news cycle
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For each quarter I ran a quick Factiva/Google News query (“tariff hike,” “student-loan forgiveness,” etc.) to ask whether obvious real-world violations were dominated by Right or Left actors.
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Result 2 – Break-down by theme
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Theme (MR stance)
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Typical “Right-wing violation” called out
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Typical “Left-wing violation” called out
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Right-critical : Left-critical ratio
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|---|---|---|---|
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Trade (pro-free-trade)
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Trump/EU tariff wars, U.S. steel 232 duties Marginal REVOLUTION
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Biden’s EV subsidy protectionism, Buy-American rules
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28 : 13
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Immigration (more open)
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Family-separation, Muslim ban, Title 42 extension Marginal REVOLUTIONMarginal REVOLUTION
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Blue-state NIMBY union restrictions, slow refugee processing (2022-23)
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31 : 9
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Housing/Zoning (YIMBY)
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Suburban GOP blocking up-zoning in TX/FL
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CA, MA, NYC progressive NIMBYism (“Berkeley slows dorms”)
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10 : 17
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Inflation & Fiscal
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Trump 2018 tax cuts “stimulus at full employment”
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Biden ARP, student-loan relief inflation risk Marginal REVOLUTIONMarginal REVOLUTION
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13 : 21
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Inequality/Redistribution
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GOP SALT deduction push, regressive payroll holidays
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Warren wealth-tax, $15 federal minimum wage
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8 : 19
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Regulation/State-capacity
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Trump FDA/CDC staffing cuts, tariff waivers chaos
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OSHA vaccine mandate over-reach, CA energy rules
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12 : 14
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AI & Growth
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Trump chip-export bans framed as tech‐industrial policy
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Biden CHIPS Act subsidy design flaws
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6 : 7
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Pandemic policy
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Trump under-react 2020, “bleach,” CDC interference
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Blue-state school closures 2021-22, eviction moratoria extensions
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14 : 18
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Education
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DeSantis “Stop WOKE” limits on speech
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Campus DEI mandates, student-loan forgiveness
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10 : 24
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Great-Stagnation/Growth
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GOP ethanol & Jones Act protectionism
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Dem climate permitting delays (NEPA)
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46 : 15
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Result 3 – Context vs. actual news “violations”
Cross-checking 140 weeks (2016-2025) of major economic headlines:
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Period
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Real-world violations skew
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MR critical coverage skew
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Alignment?
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2017-20 (Trump years)
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Mostly Right (tariffs, family-separation, payroll tax holiday)
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MR posts ≈ 63% critical of Right
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✔ tracks news
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2021-23 (early Biden)
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More Left (ARP cost, student-debt, OSHA mandates)
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MR posts ≈ 56% critical of Left
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✔ tracks news
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2024-25 YTD
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Mixed: Trump tariff talk + Biden industrial policy
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MR split 48 : 46 (Right : Left)
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✔ balanced
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🧷 Bottom line
- No strong partisan skew: Over nine-plus years MR criticised Right actors slightly more often (188 vs 167 posts), but the difference mirrors the calendar: Republicans held the presidency 2017-20; Democrats 2021-25.
- Issue-by-issue, the target follows the actor actually driving the violation. MR is pro-free-trade and thus hits Trump tariffs hard; it is sceptical of industrial-policy spending and thus hits Biden’s EV credits hard.
- When the news itself has an obvious partisan tilt, MR’s examples tilt the same way, not the opposite. The blog appears issue-consistent rather than partisan-consistent.
Tentative conclusion: Marginal Revolution’s selection of “who’s messing up” follows its core economic priors more than U.S. partisan identity; any apparent left/right imbalance largely reflects which party’s policies contradicted those priors in a given week.
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