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Economics 175: Income Inequality – Lecture 1 Notes

Course Mechanics

  • Empirical Assignment: 10%
  • Pop Quizzes: 7 quizzes total, 10%; Best 5 of 7 count
  • In-Class Group Debates: 4 debates, 40% total
  • Midterm: 15%
  • Final Exam: 25%

Course Overview

  • Five components of the course:
    • Political Philosophy: Should we care about inequality and is there a role for government involvement in reduction of inequality?
    • Measurement of Inequality: Inequality of what?
    • Theory
    • Data
    • Economics of Inequality
  • Historical Evolution of Inequality
    • Wage Inequality
    • Capital Income Inequality
    • Wage Share of Income
  • Economic Policies Used to Mitigate Inequality
  • Political Economy: Why do different countries have different amounts of inequality? (incomplete slide)

Inequality of What?

  • Central question: What do we care about?
  • Much research focuses on income, especially wage income — why?
    • Wealth and Consumption are hard to tax and hard to measure
    • Wage income is easiest to measure

Inequality of What? (Continued)

  • Reiterates: What do we care about?
  • Emphasis on income/wage income as the primary focus due to measurability and policy relevance

How are Incomes Compared Across Countries

  • Problem: Incomes are measured in different currencies
  • Solution 1 (illustrative): Convert incomes into a common currency using the current exchange rate
  • Example: The average person in the U.S. has an income of US$66,000/year. The average person in Colombia receives 28.5 million pesos/year. Who earns more?

Exchange Rate Conversion

  • Example: British Pound vs U.S. Dollar
  • Exchange rate given: 1.34 rac{ ext{ extdollar}}{ ext{£}}
  • Are you richer with £35,000 or $40,000?
  • Convert £35,000 to dollars: 35{,}000 imes 1.34 = 46{,}900
  • Result: $46,900 > $40,000; you would be better off with £35,000 in this exchange-rate frame

Income Comparisons Across Countries (Conceptual)

  • Real-world complication: Prices differ across countries; goods are cheaper in developing countries (especially non-tradables like housing and transportation)
  • Therefore, simple currency conversion can misstate living standards
  • Solution concept: Purchasing Power Parity (PPP) adjusted incomes
  • PPP adjustment idea: Use a representative basket of goods to compare cost of living across countries
  • PPP example: If a basket costs US$100 in the U.S. but only 14 Pesos in Mexico, then adjust incomes by the price ratio: multiply incomes in Mexico by $US100 / 14 Pesos
  • General PPP formula (illustrative):
    • ext{PPP-adjusted income} = ext{Nominal income} imes rac{P{ ext{US basket}}}{P{ ext{country basket}}}
    • In the example: ext{Adjusted income in Mexico} = ext{Income}_{ ext{Mexico}} imes rac{100}{14}

World Incomes (PPP-adjusted)

  • Data source: Penn World Tables
  • PPP-adjusted incomes for 185 countries
  • Presentation focuses on three groups: top, middle, and bottom per capita incomes
  • Emphasis on cross-country comparison using PPP to account for price level differences

Top to Bottom Ratios

  • Example ratios (PPP-adjusted):
    • Qatar (Rank 1) / Democratic Republic of the Congo (Rank 185) = 177
    • US (Rank 13) / Niger (Rank 180) = 59
    • Top 10 average / Bottom 10 average = 86,946 / 1,131 ≈ 76

Richest People (Forbes 2025) – Top 10

  • 1) Elon Musk — United States — Tesla, SpaceX — Automotive — ~342 ext{ B}
  • 2) Mark Zuckerberg — United States — Facebook — Technology — (rank/wealth shown as part of list)
  • 3) Jeff Bezos — United States — Amazon — Technology/Commerce — (wealth shown as part of list)
  • 4) Larry Ellison — United States — Oracle — Technology — ~216 ext{ B}
  • 5) Bernard Arnault & family — France — LVMH — Fashion & Retail — ~192 ext{ B}
  • 6) Warren Buffett — United States — Berkshire Hathaway — Finance & Investments — ~178 ext{ B}
  • 7) Larry Page — United States — Google (Alphabet) — Technology/Internet — ~154 ext{ B}
  • 8) Sergey Brin — United States — Google (Alphabet) — Technology/Internet — ~138 ext{ B}
  • 9) Amancio Ortega — Spain — Zara — Fashion & Retail — ~124 ext{ B}
  • 10) Steve Ballmer — United States — Microsoft — Technology — ~118 ext{ B}

Richest People (Forbes 2025) – 11 to 20

  • 11) Rob Walton & family — United States — Walmart — Fashion & Retail — ~110 ext{ B}
  • 12) Jim Walton & family — United States — Walmart — Fashion & Retail — ~109 ext{ B}
  • 13) Bill Gates — United States — Microsoft — Technology — ~108 ext{ B}
  • 14) Michael Bloomberg — United States — Bloomberg LP — Finance & Investments — ~105 ext{ B}
  • 15) Alice Walton — United States — Walmart — Fashion & Retail — ~101 ext{ B}
  • 16) Jensen Huang — United States — NVIDIA — Semiconductors/Technology — ~98.7 ext{ B}
  • 17) Michael Dell — United States — Dell Technologies — Technology/Computers — ~97.7 ext{ B}
  • 18) Mukesh Ambani — India — Reliance Industries — Diversified — ~92.5 ext{ B}
  • 19) Carlos Slim Helu & family — Mexico — América Móvil — Telecom — ~82.5 ext{ B}
  • 20) Francoise Bettencourt Meyers & family — France — L’Oréal — Fashion & Retail (Cosmetics) — ~81.6 ext{ B}

Richest People (Forbes 2025) – 21 to 40 (selected)

  • 21+) Values listed across slides for 21–40 include: Jim (and family), etc., with net wealth in the range of ~$80–$110B for the mid-teens and lower billions for others; the slide provides a continued list with entries such as Rob Walton, Jim Walton, Bill Gates, Michael Bloomberg, Alice Walton, Jensen Huang, Michael Dell, Mukesh Ambani, Carlos Slim Helu, Francoise Bettencourt Meyers among others.

Richest People in the World – 11 to 20 (Alternative view)

  • Page 21 provides a similar 11–20 listing with the same names and wealth figures as above, reinforcing the dispersion of wealth among the global top 20
  • Example figures (as shown):
    • Rob Walton & family — United States — Walmart — Fashion & Retail — 110 ext{ B}
    • Jim Walton & family — United States — Walmart — Fashion & Retail — 109 ext{ B}
    • Bill Gates — United States — Microsoft — Technology — 108 ext{ B}
    • Michael Bloomberg — United States — Bloomberg LP — Finance & Investments — 105 ext{ B}
    • Alice Walton — United States — Walmart — Fashion & Retail — 101 ext{ B}
    • Jensen Huang — United States — NVIDIA — Technology/ Semiconductors — 98.7 ext{ B}
    • Michael Dell — United States — Dell Technologies — Technology/Computers — 97.7 ext{ B}
    • Mukesh Ambani — India — Reliance Industries — Diversified — 92.5 ext{ B}
    • Carlos Slim Helu & family — Mexico — América Móvil — Telecom — 82.5 ext{ B}
    • Francoise Bettencourt Meyers & family — France — L’Oréal — Fashion & Retail — 81.6 ext{ B}

Income Inequality in the United States (Top World Incomes Database)

  • Time series of shares for top groups in the U.S.:
    • Top 0.01% Share, Top 0.1% Share, Top 1% Share, Top 10% Share
  • 1970: 0.01% = 1.15%, 0.1% = 3.41%, 1% = 10.70%, 10% = 33.35%
  • 1980: 0.01% = 1.16%, 0.1% = 3.43%, 1% = 10.42%, 10% = 33.84%
  • 1990: 0.01% = 2.45%, 0.1% = 5.97%, 1% = 14.71%, 10% = 38.76%
  • 2000: 0.01% = 3.44%, 0.1% = 7.73%, 1% = 17.34%, 10% = 42.73%
  • 2007: 0.01% = 3.68%, 0.1% = 8.34%, 1% = 18.38%, 10% = 44.04%
  • 2010: 0.01% = 3.67%, 0.1% = 8.12%, 1% = 17.89%, 10% = 43.81%
  • 2023: 0.01% = 4.72%, 0.1% = 9.93%, 1% = 20.73%, 10% = 46.76%

Income Inequality in Norway (Top World Incomes Database)

  • Time series for Norway: top shares over selected years
  • 1980s: multiple rows show different shares, but the intended trend shows a rise in top shares over time and subsequent changes by 2023
  • 1980: 0.90% (top 0.01%), 2.46% (top 0.1%), 7.26% (top 1%), 26.45% (top 10%)
  • 1990: 2.50% (top 0.01%), 5.43% (top 0.1%), 12.23% (top 1%), 31.60% (top 10%)
  • 2000: 2.53% (top 0.01%), 5.62% (top 0.1%), 12.84% (top 1%), 32.83% (top 10%)
  • 2007: 2.29% (top 0.01%), 5.17% (top 0.1%), 12.05% (top 1%), 31.81% (top 10%)
  • 2023: 1.07% (top 0.01%), 3.12% (top 0.1%), 9.34% (top 1%), 30.61% (top 10%)

Global Income Distribution Visuals (Summary of Slides 19–24)

  • Page 19: Graph comparing top 0.1% and top 10% income shares for USA vs Sweden; highlights that the USA has higher top shares, Sweden lower – illustrates country differences in top-end concentration
  • Page 23: Our recent history – Figure 4: Change in real income between 1988 and 2008 at various percentiles of global income distribution (in 2005 international dollars)
    • Real income growth varies across percentiles; higher percentiles tend to show larger absolute gains
  • Page 24: The elephant curve of global inequality and growth, 1980-2016
    • Real income growth per adult (%):
    • Bottom 50% captured 12% of total growth
    • Rise of emerging countries
    • Squeezed bottom 90% in the US & Western Europe
    • Top 1% captured 27% of total growth
    • Visualizes that the global top benefited more from growth, while the bottom half captured a small share
  • Overall interpretation: globalization and growth have been uneven; gains concentrated among the global elite, with notable improvements for many in emerging economies

Summary Slide: Key Takeaways

  • Types of Inequality: Income, Wealth, Consumption, Lifetime Consumption, Happiness
  • Focus will be largely on within-country inequality, though cross-country inequality is large
  • Price differences matter when comparing incomes across countries; PPP adjustments help address this
  • The world distribution has seen growth in the bottom, but the top 5% have grown substantially; the upper middle class in developed countries has experienced sluggish growth

Reading for Next Lecture

  • John Stuart Mill, Utilitarianism, pp. 1-26
  • John Roemer, Free to Lose, pp. 14-27