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Convergence Scenarios: an Overview

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Approach represented by papers such as Barro and Sala-i-Martin (1992) ... Based on closed economy growth models in Solow/Swan tradition. Or Ramsey/Cass/Koopmans ... – PowerPoint PPT presentation

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Title: Convergence Scenarios: an Overview


1
Convergence Scenariosan Overview
  • Jonathan Temple
  • (University of Bristol)

2
Classical Convergence
  • Approach represented by papers such as Barro and
    Sala-i-Martin (1992) and Mankiw, Romer and Weil
    (1992)
  • Based on closed economy growth models in
    Solow/Swan tradition
  • Or Ramsey/Cass/Koopmans
  • Adds assumptions about world growth

3
Some Basics
  • Predicts countries converge in growth rates
  • But income levels differ in steady-state
  • This is because steady-state determinants vary
    across countries
  • Most familiar investment, population growth
  • These determinants treated as exogenous

4
A Key Strength
  • A key strength of the approach is to recognise
    that, in principle
  • there is no reason why most countries cannot
    become rich
  • So future may not look like the past
  • Viewpoint differs from non-economists

5
Empirical Findings
  • Wide variety of convergence estimates
  • Recent work suggests rates are slow
  • So countries spend a lot of time away from
    steady-state
  • Some evidence suggests clubs
  • But a lot of uncertainty (small N)
  • and asking wrong question?

6
This is the Wrong Approach!
  • Bad approach for emissions scenarios
  • Estimated convergence rate is (implicitly) an
    average
  • Taken across different countries/regions
  • Regressions weight countries equally
  • Effectively small countries (sub-Saharan Africa)
    carry much more weight

7
The Wrong Approach, Part II
  • Approach treats countries as closed
  • These economies evolve independently
  • For empirical purposes, treats steady-state
    determinants as exogenous
  • Rules out feedback from growth
  • How to relax these assumptions?

8
Possible Feedback Mechanisms
  • Endogenous world growth
  • Geography and market access
  • Demography
  • Endogenous institutions
  • Financial development
  • Equipment prices
  • Energy prices
  • Feedback from climate

9
Endogenous World Growth
  • Clear externalities in knowledge
  • Powerful effects of scale in endogenous growth
    models
  • World population of researchers expanding rapidly
    (India, China?)
  • Will only be offset if research process is
    becoming more difficult

10
Geography and Market Access
  • Recent work in trade emphasizes role of spatial
    location and market access
  • Suggests multiple equilibria at level of world
    regions
  • Fast growth in specific regions will change
    patterns of market access
  • Hence feedback from regional growth

11
Demography
  • Crucial for emissions scenarios to build in
    endogenous demography
  • Offsetting effects rising longevity versus
    fertility transition
  • Quantity/quality trade-off models predict human
    capital accumulation rise
  • Importance of policies in China, India

12
Endogenous Institutions
  • Work such as AJR (AER 2001) suggests institutions
    crucial to steady-state GDP
  • Strong correlations between institution indices
    and levels of GDP
  • Endogenous democratization
  • might reduce forecast dispersion?
  • Less risk of civil war as income rises?

13
Growth and Finance
  • Much work links growth to financial development
  • Development of banks endogenous to income level
  • Then stock markets
  • Financial globalization relevant to convergence
    (e.g. FDI flows)

14
Equipment Price Effects
  • Why does real investment differ?
  • Work such as Hsieh/Klenow suggests relative price
    of equipment crucial
  • Evidence suggests this price much higher in poor
    countries
  • Can be expected to fall as part of convergence
    process?

15
Energy Price Effects
  • Price of energy unlikely to be independent of
    global convergence
  • May feedback into world growth
  • This effect will also tend to reduce dispersion
    of emissions scenarios, relative to dispersion of
    GDP scenarios

16
Global Warming Feedbacks
  • Central point endogenous climate
  • So different convergence scenarios may have
    feedbacks via climate
  • For example, agriculture, water stress
  • Changes in infrastructure, global distribution of
    population, etc.

17
How to Model All These Effects?
  • Full structural model very complex
  • So best approach may be reduced-form
  • Aggregate major regions
  • Consider different convergence behaviour in each
  • But build in virtuous circle effects as a
    reduced-form
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