Turning statistics into knowledge: use and misuse of indicators and models

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Turning statistics into knowledge use and misuse
of indicators and models

• Data Day
• Geneva May 18th

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• Modeling Partial vs General equilibrium
• The importance of estimation
• Indices

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• Modeling Partial vs General equilibrium
• The importance of estimation
• Indices

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Modeling Partial versus General equilibrium

• Definitions
• Partial equilibrium implies that we only consider
  a few markets at a time and we do not close the
  models by including all economic interactions
  across sectors (e.g., SMART, GSIM in WITS or
  TRITS at the World Bank).
• In a general equilibrium setup all markets are
  simultaneously modeled and interact with each
  other (e.g., GTAP developed at Purdue University).

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Why partial equilibrium?

• Advantages
• Minimal data requirement. We can take advantage
  of rich WITS datasets. Crucial if question is
  about
• Bolivia or Uruguay and not the Rest of South
  America
• Soya exports and not Other cereals
• Results of the trade model will feed poverty
  analysis. Households produce corn or soya, not
  cereals. Heterogeneity of impacts may be lost
  in a more aggregate general equilibrium model.

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Why partial equilibrium?

• More Advantages
• Allows analysis of Doha negotiations more
  accurately
• In the WTO countries negotiate bound tariffs, not
  applied (tariff overhang in many regions)
• Applied and bound tariffs are very different
  within HS 10 Cereals. General equilibrium
  approach will miss this.

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Why partial equilibrium?

• More Advantages
• Transparency
• Modeling is straightforward and results can be
  easily explain. No black box.
• Easy to implement
• Excel sheet/SMART/GSIM
• Solves aggregation bias

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Adding apples and oranges.
P
Pwta
PwTa
PwTf
Pw
Q
Apples
Oranges
Fruits

• No welfare cost associated with Ta apples
  import demand is perfectly inelastic. No tariff
  on oranges. So no welfare cost associated with
  fruit protection.
• Aggregation bias suggests welfare loss

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Why partial equilibrium?

• Disadvantages
• One has information only on a pre-determined
  number of economic variables (partial model of
  the economy)
• One may miss important feedbacks
• E.g., Labor market constraints. (But if you know
  they are there you can model them)
• Can be very sensitive to a few (badly estimated)
  elasticities.

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• Modeling Partial vs General equilibrium
• The importance of estimation
• Indices

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The importance of estimation

• Ex-post
• One can estimate the impact of a certain policy
  reform on exports, trade creation, diversion, GDP
  growth, productivity and with a bit of modeling
  utility (e.g., gravity equation)
• Ex-ante
• One should estimate the critical parameters of
  the modeling exercise (elasticities, economies of
  scale, etc..). Otherwise
• Harris (1984) versus Head and Ries (1999)
• World Bank (2001) versus Hoekman et al (2004)
• GEP(2001) versus common sense
• Importance of comparing relative and not absolute
  results

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But why do simulation results differ?

• Scenarios are not the same
• Full versus partial
• Different base years (benchmarks)
• Mixing with other reforms (fiscal policy, trade
  facilitation)
• Data are not the same
• GTAP data is standard, but PTAs, NTBs..
• Parameters (elasticities) are not the same
• Modeling assumptions differ
• Perfect versus imperfect competition
• Flexible versus rigid labor markets
• Endogeneity of TFP to trade openness

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• Modeling Partial vs General equilibrium
• The importance of estimation
• Indices

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Indices between analysis and narrative

• According to statisticians what cannot be
  counted does not count, but do indicators try
  to count what cannot be counted?
• Composite indices are good for
• Narrative
• And advocacy of particular reform/policy
• Decision making process if based on policies
  rather than outcomes, and aggregated using a
  proper technique.

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Indices

• Problems
• Modeling versus estimation of weights of
  different components (or subjective versus
  objective criteria)
• Based on theory, not hand-waving (World Banks
  OTRI versus IMFs old TRI)
• Rankings and the importance of measurement error
  (OTRI versus TRI or Doing Business)

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Concluding remarks

• Keep it simple and transparent
• Dont trust your guts estimate everything you
  can!
• Pay attention to measurement error
• Compare relative policy shocks not absolute
  numbers