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Economic Growth and Income Distribution: Linking Macroeconomic Models with Household Surveys at the Global Level PowerPoint PPT Presentation


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Economic Growth and Income Distribution: Linking Macroeconomic Models with Household Surveys at the Global Level. Mauricio Bussolo, Rafael E. De Hoyos, and Denis Medvedev The World Bank Presented by: Francisco H. G. Ferreira (The World Bank) IARIW Conference 2008. Outline. Motivation

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Economic Growth and Income Distribution: Linking Macroeconomic Models with Household Surveys at the Global Level

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Economic Growth and Income Distribution: Linking Macroeconomic Models with Household Surveys at the Global Level

Mauricio Bussolo, Rafael E. De Hoyos, and

Denis Medvedev

The World Bank

Presented by:

Francisco H. G. Ferreira (The World Bank)

IARIW Conference 2008


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Outline

  • Motivation

  • Methodological Approach

    • Demographic and education projections

    • Sample re-weighting

    • The CGE

    • Microsimulations

  • Applications

    • Global Income Distribution in 2030

    • The Rise of China and India

    • Distributional Implications of Climate Change

  • Comments.


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    1.Motivation

    • To propose a modeling tool capable of forecasting changes in the global income distribution.

      • To generate “reasonable” predictions of how global inequality and poverty might change under different scenarios.

        • “Baseline” growth projections

        • Changes in trade agreements

        • Climate change


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    2.Methodological Approach

    • Use household surveys for 121 countries (90% of world population).

      • Project forward changes in demographic and educational structure (from “inertia”).

      • Project changes in occupational structure and incomes:

        • Taking account of (1) and

        • Forecasting changes in incomes and returns in each sector from estimates of productivity growth and changes in demand from a “Global CGE”.


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    The GIDD method:A “Global CGE-Microsimulation System”

    1

    2

    3

    4


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    Step 1: Demographic and Education Projections

    Age

    The changes in demographic structure are taken from WB or UN population projections

    Education

    Overall education attainments are assumed to be related with aging via a “pipeline” effect (Lutz and Goujon, 2001)

    2030

    2000


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    Step 2: Reweighting individual observations in the surveys

    • Organize sampling weights into a matrix of individuals by partition cells:

    • The demographic and educational projections generate the marginal “projected” densities:

    • System is under-identified. Can be solved in various ways, including

    Matrix of “n” individual sampling weights over “m” characteristics

    Population in Subgroup “m”


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    Step 3: The CGE

    • There are other changes in the economy, in addition to the age/education structure.

    • These are simulated through a (computable) general equilibrium model, which incorporates the population changes from Steps 1 and 2.

      • The World Bank’s global LINKAGE model

        • Production function is nested CES with five factors:

          Unskilled and skilled labor, capital, land, natural resources.

        • Demand structure modeled through an ELES, with cross-price and income elasticities.

        • Sector-specific productivity growth trends “calibrated to be consistent with historical evidence”


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    Step 4: Microsimulations

    • Once shocked with:

      • Age/demographic reweighting;

      • Sector and factor-specific productivity growth;

      • Any exogenous changes (in policy or climate)

  • The CGE generates a set of “aggregate” changes in linkage variables:

    • Worker reallocation flows

    • Changes in incomes

    • Changes in prices

  • These are translated to the counterfactual distributions in the surveys by:

    • Using probits to identify the most likely individuals to move sectors

    • Using sector-specific earnings equations to predict their earnings

    • Scaling resulting sector and skill gaps so that the changes in average gaps in the survey match the changes in average gaps in the CGE.

    • Making a final adjustment on overall levels of real aggregate per capita income


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    3.Applications

    • Global Income Inequality in 2030 (compared to 2000)

      • Forecast a decline in global income inequality…

      • …driven entirely by inter-country convergence.

      • “Global middle class” grows from 7.6% to 16.1% of world population.


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    3.Applications (ctd.)

    • The rising influence of China and India


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    3.Applications (ctd.)

    • Distributional Impacts of Climate Change

    • A “climate model” links carbon emissions to regional changes in temperatures.

    • Use estimates in Cline (2007) to map these changes onto changes in agricultural productivity. Feed these into agricultural production functions in the CGE.

    • Find (small) increases in global poverty and inequality.

    • Larger losses among “near poor”.


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    Comments

    • A plausible list of really difficult things to do in economics:

      • Measure global inequality

      • Account for general equilibrium effects of policy changes

      • Predict the future

    • This paper has it all!

    • That makes it very easy to criticize.

    • But if one accepts the premise that the ability to “predict” -obviously subject to great uncertainty - the plausible worldwide distributional implications of large shocks and policy changes in the future, then it is not easy to propose a clearly superior alternative to this.


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    Comments (ctd.)

    • My comments are mostly presentational:

      • Reconsider use of the Shorrocks (1982) between-group decomposition framework as a motivating device. After Steps 4 and 5, within-group inequality is no longer constant, as you currently appear to claim.

      • Consider an alternative notation to describe Step 2. I have a feeling that this can be written down just as formally, but more clearly.

      • Spend a little more time spelling out the micro-simulation stage, with examples.

      • While this is a nice conference paper, hard to think that publication won’t require two papers: one on the basic methodology, and other(s) on the applications.


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