turning statistics into knowledge: use and misuse of indicators and models data day geneva may 18th

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

Data DayGeneva May 18th

• Modeling: Partial vs General equilibrium

• The importance of estimation

• Indices

Turning statistics into knowledge 2



• Indices


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).

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.



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.



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


Adding apples and oranges….Adding apples and oranges….

Apples Oranges Fruits

Pw

Pw+TaPw+Tf

• 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 =

Q

P


Pw+ta


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.




• Indices


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


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




• Indices


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.


Indices

Problems:• Modeling versus estimation of weights of

different components (or subjective versus objective criteria)

• Based on theory, not hand-waving (World Bank’s OTRI versus IMF’s old TRI)

• Rankings and the importance of measurement error (OTRI versus TRI or Doing Business)


Concluding remarks

• Keep it simple and transparent• Don’t trust your guts: estimate everything you

can!• Pay attention to measurement error• Compare relative policy shocks not absolute

numbers


turning statistics into knowledge: use and misuse of indicators and models data day geneva may 18th

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