Harris-Todaro Model

📚 Harris-Todaro Model of Rural-Urban Migration — Notes (Corrected Version)

👤 Developed by: Michael Todaro

Focus: Explains rural-to-urban migration in developing countries, even in the presence of urban unemployment.

🎯 Core Idea

  • Extends the Lewis model by explaining why migration continues despite urban job scarcity.

  • Introduces the concept of expected urban income as the main driver of migration.

📌 Assumptions of the Model

  1. Two sectors: Rural (agriculture) and Urban (industry).

  2. Urban wages are higher and often institutionally fixed.

  3. Migration is rational and based on economic calculations.

  4. Migrants base their decision on expected income, not actual income.

  5. Expected urban income is a function of:

    • The urban wage.

    • The probability of employment.

  6. Migration continues until:

    Expected Urban Income=Rural Income\text{Expected Urban Income} = \text{Rural Income}Expected Urban Income=Rural Income

  7. Job probability is:

    LMLU\frac{L_M}{L_U}LU​LM​​

    where LML_MLM​ = urban jobs, LUL_ULU​ = total urban labour force.

📈 Mathematical Expression of Migration Decision

Migration will occur if:

E(WU)=(LMLU)⋅W‾M>WAE(W_U) = \left( \frac{L_M}{L_U} \right) \cdot \overline{W}_M > W_AE(WU​)=(LU​LM​​)⋅WM​>WA​

Where:

  • E(WU)E(W_U)E(WU​): Expected urban income

  • W‾M\overline{W}_MWM​: Fixed urban wage

  • WAW_AWA​: Rural income/wage

  • LML_MLM​: Number of urban employed

  • LUL_ULU​: Total urban labour force

📉 Urban Unemployment as Equilibrium

  • Migration continues until:

    E(WU)=WAE(W_U) = W_AE(WU​)=WA​

  • At this point, rural-urban expected incomes equalize and migration halts.

  • Despite urban unemployment, migration is economically rational.

🧠 Example

  • Urban wage = 100

  • Probability of job = 0.2

  • E(WU)=0.2×100=20E(W_U) = 0.2 \times 100 = 20E(WU​)=0.2×100=20

  • If rural wage = 50 → no migration

  • If probability increases to 0.6 → E(WU)=60>50E(W_U) = 60 > 50E(WU​)=60>50 → migration occurs

📊 Diagrammatic Explanation (Simplified)

  • AA′: Rural labour demand (downward sloping).

  • MM′: Urban labour demand (slopes down from right).

  • W̅_M: Urban wage (fixed above equilibrium).

  • qq′ curve: Shows where expected urban income equals rural income.

  • Point Z: Equilibrium → where migration stops.

❌ Criticisms

  1. Migrants may lack precise info on job probabilities.

  2. Many migrate after securing a job, invalidating the model’s assumption.

  3. Probability-based decision-making may not reflect reality.

  4. No policy solution offered for urban saturation.

  5. Ignores psychological, social, and non-economic factors.

✅ Relevance

  • Provides a realistic explanation of urban unemployment in developing countries.

  • Applies well to scenarios in India, Nigeria, Kenya, etc., where informal urban labour markets thrive.

⏳ 1-Minute Revision Summary

  • Migration continues despite unemployment if expected income in urban areas exceeds rural wages.

  • Expected income depends on urban wage × job probability.

  • Migration stops when expected urban income = rural income.

  • Explains urban unemployment equilibrium, a key feature of many LDCs.