2005年-世界发展银行全球_Simulating_the_Poverty_Impact_of_Macroeconomic_Shocks_and_Policies_25页_370kb

Summary of "Simulating the Poverty Impact of Macroeconomic Shocks and Policies"

Core Content

This paper presents a stylized simulation framework that integrates a general equilibrium model of an open economy with a Lorenz model of the size distribution of economic welfare. The framework is designed to assess the poverty and distributional impacts of macroeconomic shocks and policies, particularly in the context of developing countries. It emphasizes the importance of considering both aggregate economic performance and distributional effects in policy analysis, as these are often interdependent and have significant implications for poverty reduction.

The paper explores three main types of macroeconomic shocks and policies:

1. Dutch disease
2. Changes in terms of trade
3. Budgetary policy

The simulation approach is based on a two-sector model of an open economy, where one sector produces an export good and the other produces a domestic good used for both intermediate and final consumption. The model incorporates factor demand equations, import and export price equations, and household income equations to capture the interaction between macroeconomic variables and welfare distribution.

Main Views and Key Points

1. Macroeconomic Shocks and Poverty

• Aggregate effects of shocks (e.g., oil price increases) may not be significant, but distributional and structural impacts can be substantial.
• These distributional impacts are crucial for understanding poverty dynamics and for informing policy decisions.
• Policy instruments such as exchange rates, tariffs, subsidies, and trade liberalization have implications for fiscal and monetary policies.

2. Modeling Approach

• The paper proposes a general equilibrium framework that combines macroeconomic variables with micro-level welfare distribution.
• Three approaches are discussed for analyzing distributional impacts:
  • Standard representative household (RH) approach
  • Extended representative household (ERH) approach
  • Microsimulation approach
• The ERH approach is emphasized, using a Lorenz curve to link functional distribution to size distribution of welfare.

3. Lorenz Curve and Poverty Measures

• The Lorenz curve is used to represent the cumulative share of welfare received by the poorest portion of the population.
• It allows for the recovery of income distribution and density functions, which are essential for computing poverty indicators.
• The Foster-Greer-Thorbecke (FGT) family of poverty measures can be derived from the Lorenz curve and the mean income of the distribution.

4. Quadratic Lorenz Curve

• A quadratic Lorenz function is used to model the distribution of welfare.
• The function is defined with parameters $e$, $m$, $n$, and $r$, which are estimated through regression analysis.
• The paper provides calibrated parameters for the model based on Social Accounting Matrix (SAM) data, highlighting the labor and capital intensity of the two sectors.

5. Numerical Implementation

• The model is calibrated using base year data and SAM.
• The SAM is used to represent the circular flow of economic activity, including production, consumption, trade, and income distribution.
• Household data are simulated using beta distribution to generate unit record data for rural and urban populations.

6. Policy Implications

• The interdependence between macroeconomic variables and distributional outcomes is a key feature of the model.
• Government redistribution of tax revenue is a central component of the model, with rural households receiving 60% of transfers and urban households receiving 40%.
• The model assumes that rural households receive 20% of the trade balance, while urban households receive 80%.

Key Information

• The general equilibrium model is adapted from Devarajan, Lewis, and Robinson (1990).
• The Lorenz model is used to simulate poverty implications by capturing the distributional effects of shocks and policies.
• The two-sector model includes:
  • Export sector: Labor-intensive
  • Domestic sector: Capital-intensive
• The elasticity of substitution is assumed to be:
  • 0.5 for intermediate goods
  • 2.0 for final goods
• The SAM is used to represent the base year equilibrium, with the government account excluded in the base case.
• Calibrated parameters are derived from SAM data and used to estimate the functional distribution of income.
• The poverty line and distributional parameters are essential for computing poverty measures.
• The model is flexible and can be applied to various macroeconomic shocks and policies to simulate their poverty and inequality impacts.

Conclusion

The paper argues that a general equilibrium framework with Lorenz-based distributional analysis is necessary to understand the structural and distributional implications of macroeconomic shocks and policies. It highlights the importance of accounting for heterogeneity among stakeholders and the interdependence of policy instruments. The framework is designed to be analytically robust and numerically implementable, enabling policy simulations and poverty assessments in developing countries.