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Intergenerational Mobility

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Human Capital TheoryReturns to Education (Mincer Equation)→
mobility Chetty opportunity inequality Great-Gatsby-curve

Core Idea

Intergenerational mobility measures the extent to which children's economic outcomes are independent of their parents' — the degree to which a person's position in the income distribution is determined by their own effort and ability versus their family background. The intergenerational elasticity (IGE) of income measures the correlation between parents' and children's earnings, with higher values indicating less mobility. The US has relatively low mobility (IGE ≈ 0.4-0.5) compared to Nordic countries (IGE ≈ 0.2). Chetty et al.'s work using IRS tax records revealed enormous geographic variation in mobility within the US, with local factors like school quality, social capital, and neighborhood characteristics explaining much of the variation. The "Great Gatsby curve" (Corak) documents a cross-country correlation between inequality and immobility, suggesting that higher inequality reduces intergenerational mobility.

Explainer

The promise of meritocracy — that your economic position should reflect your talent and effort, not your parents' bank account — is central to the social contract in market economies. Intergenerational mobility research tests whether this promise is being kept. The answer, across developed countries, is: imperfectly, with enormous variation across places, time periods, and institutional contexts.

The intergenerational elasticity of income is the standard summary measure. Estimated from the regression of children's log earnings on parents' log earnings (typically measured at comparable ages, mid-career), it captures how much of a parent's relative income position is transmitted to the next generation. The US IGE of 0.4-0.5 is strikingly high compared to Nordic countries (0.15-0.25), meaning that family background matters roughly twice as much in the US as in Scandinavia. Canada, Germany, and France fall between these extremes. These differences persist after controlling for measurement issues (lifecycle bias, attenuation from transitory income shocks), suggesting they reflect genuine institutional differences.

The mechanisms of intergenerational transmission are multiple and interacting. Genetic inheritance of traits correlated with earnings (cognitive ability, personality) accounts for some persistence, though behavioral genetics estimates suggest this explains perhaps 30-40% of the IGE. The remainder reflects environmental transmission: wealthier parents provide better nutrition, healthcare, neighborhoods, schools, social networks, information about navigating institutions, and direct financial transfers. They also transmit aspirations, attitudes toward education, and cognitive stimulation through home environments. Disentangling these mechanisms is crucial for policy: genetic transmission is not amenable to policy intervention, while environmental transmission can be addressed through early childhood programs, school quality improvement, and neighborhood investment.

Chetty's research program, leveraging the universe of US tax records, transformed the field by moving from national averages to granular geographic data. The Opportunity Atlas shows upward mobility (the expected income rank of children born to 25th-percentile parents) for every census tract in America. The variation is enormous: in the highest-mobility tracts, low-income children reach the middle class at rates comparable to Denmark; in the lowest-mobility tracts, they remain stuck in poverty at rates worse than any national average. The five factors most correlated with high mobility — less residential segregation, less inequality, better schools, more social capital, and more stable families — point toward specific, place-based policy targets.

The Great Gatsby curve — the cross-country correlation between income inequality and intergenerational persistence — suggests that inequality and immobility are structurally linked, not independent phenomena. High inequality means more distance between income levels, making it harder for disadvantaged children to bridge the gap. It also means more segregation of residential neighborhoods, schools, and social networks by income, reducing the cross-class interactions that facilitate upward mobility. If this relationship is causal (and Chetty's within-US evidence supports this), then rising inequality is not just a distributional concern but a mobility concern — it is pulling up the ladder for the next generation.

Practice Questions 3 questions

Prerequisite Chain

Understanding Zero → The Number Zero → Counting to Five → Counting to 10 → Counting to 20 → Counting a Set of Objects Up to 20 → Cardinality: The Last Number Counted → Matching Numerals to Quantities → Subitizing Small Quantities → Addition Within 10 → Number Bonds to 10 → Addition Within 20 → Doubles and Near Doubles → Doubles Facts Within 10 → Near Doubles Facts Within 20 → Mental Math Strategies for Addition → Mental Math: Adding and Subtracting Tens → Addition Within 100 → Repeated Addition as Multiplication → Multiplication as Equal Groups → Multiplication: Arrays → Basic Multiplication Facts (0s, 1s, 2s, 5s, 10s) → Multiplication Facts Within 100 → Division as Equal Sharing → Division as Grouping (Measurement Division) → Division: Grouping (Repeated Subtraction) Model → Division: Fair Sharing Model → Division as Equal Sharing → Division as Grouping → Basic Division Facts → Division Facts Within 100 → Multiplication and Division Fact Families → Relationship Between Multiplication and Division → Division Facts as Inverse of Multiplication → Remainders and Quotients in Division → Division Word Problems → Multi-Step Word Problems → Solving Multi-Step Word Problems → Multiplication Word Problems → Division Word Problems → Introduction to Long Division → Factors and Multiples → Prime and Composite Numbers → Equivalent Fractions → Relating Fractions and Decimals → Decimal Place Value → Integers and the Number Line → Comparing and Ordering Integers → Absolute Value → Adding Integers → Subtracting Integers → Multiplying Integers → Dividing Integers → Unit Rates → Proportions → Percent Concept → Converting Between Fractions, Decimals, and Percents → Operations with Rational Numbers → Two-Step Equations → Solving Multi-Step Equations → Equations with Variables on Both Sides → Angle Pairs: Complementary, Supplementary, and Vertical → Parallel Lines and Transversals → Corresponding Angles → Alternate Interior Angles → Triangle Angle Sum Theorem → Exterior Angle Theorem → Triangle Inequality Theorem → Similar Triangles: AA Similarity → Similar Triangles: SSS and SAS Similarity → Proportions in Similar Triangles → Right Triangle Trigonometry Introduction → Sine, Cosine, and Tangent Ratios → Trigonometric Ratios Review → Radian Measure → Converting Between Degrees and Radians → The Unit Circle → Graphing Sine and Cosine → Graphing Tangent and Reciprocal Trigonometric Functions → Derivatives of Trigonometric Functions → Antiderivatives → Indefinite Integrals → Basic Integration Rules → Riemann Sums → Definite Integral Definition → Probability Density Functions and Continuous Distributions → Cumulative Distribution Functions → Continuous Random Variables → Probability Density Functions → Expected Value → Weak Law of Large Numbers → Probability Axioms and Rules → Conditional Probability → Independence of Events → Sampling Distributions → Standard Error of Estimators → Hypothesis Testing: Framework and Logic → P-values and Statistical Significance → Effect Size and Practical Significance → Hypothesis Testing: Framework and Logic → Z-Tests and T-Tests for Means → One-Sample Z-Test for Means → One-Sample and Two-Sample T-Tests → Inference in Linear Regression → Prediction Intervals in Regression → Linear Regression Basics → Residuals and Goodness of Fit (R²) → Simple (Bivariate) OLS Regression → Classical OLS Assumptions (Gauss-Markov) → Returns to Education (Mincer Equation) → Intergenerational Mobility

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