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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.

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Prerequisite Chain

Understanding ZeroThe Number ZeroCounting to FiveCounting to 10Counting to 20Counting a Set of Objects Up to 20Cardinality: The Last Number CountedMatching Numerals to QuantitiesSubitizing Small QuantitiesAddition Within 10Number Bonds to 10Addition Within 20Doubles and Near DoublesDoubles Facts Within 10Near Doubles Facts Within 20Mental Math Strategies for AdditionMental Math: Adding and Subtracting TensAddition Within 100Repeated Addition as MultiplicationMultiplication as Equal GroupsMultiplication: ArraysBasic Multiplication Facts (0s, 1s, 2s, 5s, 10s)Multiplication Facts Within 100Division as Equal SharingDivision as Grouping (Measurement Division)Division: Grouping (Repeated Subtraction) ModelDivision: Fair Sharing ModelDivision as Equal SharingDivision as GroupingBasic Division FactsDivision Facts Within 100Multiplication and Division Fact FamiliesRelationship Between Multiplication and DivisionDivision Facts as Inverse of MultiplicationRemainders and Quotients in DivisionDivision Word ProblemsMulti-Step Word ProblemsSolving Multi-Step Word ProblemsMultiplication Word ProblemsDivision Word ProblemsIntroduction to Long DivisionFactors and MultiplesPrime and Composite NumbersEquivalent FractionsRelating Fractions and DecimalsDecimal Place ValueIntegers and the Number LineComparing and Ordering IntegersAbsolute ValueAdding IntegersSubtracting IntegersMultiplying IntegersDividing IntegersUnit RatesProportionsPercent ConceptConverting Between Fractions, Decimals, and PercentsOperations with Rational NumbersTwo-Step EquationsSolving Multi-Step EquationsEquations with Variables on Both SidesAngle Pairs: Complementary, Supplementary, and VerticalParallel Lines and TransversalsCorresponding AnglesAlternate Interior AnglesTriangle Angle Sum TheoremExterior Angle TheoremTriangle Inequality TheoremSimilar Triangles: AA SimilaritySimilar Triangles: SSS and SAS SimilarityProportions in Similar TrianglesRight Triangle Trigonometry IntroductionSine, Cosine, and Tangent RatiosTrigonometric Ratios ReviewRadian MeasureConverting Between Degrees and RadiansThe Unit CircleGraphing Sine and CosineGraphing Tangent and Reciprocal Trigonometric FunctionsDerivatives of Trigonometric FunctionsAntiderivativesIndefinite IntegralsBasic Integration RulesRiemann SumsDefinite Integral DefinitionProbability Density Functions and Continuous DistributionsCumulative Distribution FunctionsContinuous Random VariablesProbability Density FunctionsExpected ValueWeak Law of Large NumbersProbability Axioms and RulesConditional ProbabilityIndependence of EventsSampling DistributionsStandard Error of EstimatorsHypothesis Testing: Framework and LogicP-values and Statistical SignificanceEffect Size and Practical SignificanceHypothesis Testing: Framework and LogicZ-Tests and T-Tests for MeansOne-Sample Z-Test for MeansOne-Sample and Two-Sample T-TestsInference in Linear RegressionPrediction Intervals in RegressionLinear Regression BasicsResiduals and Goodness of Fit (R²)Simple (Bivariate) OLS RegressionClassical OLS Assumptions (Gauss-Markov)Returns to Education (Mincer Equation)Intergenerational Mobility

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