Trade, Standards and the WTO
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Transcript Trade, Standards and the WTO
General Equilibrium Modelling
and Trade Policy Analysis
Marco Fugazza
DITC, UNCTAD
15 September 2006
Outline
• Why are economic models needed?
• What kinds of models are commonly used for trade
policy analysis?
• Basics of CGE Modelling
• What is involved in a policy simulation?
• What should we know of trade liberalization CGE
simulations?
• An Application
• How can modeling better assist policy making?
2
Why are economic
models needed?
3
Why are economic models needed?
•
1. “Without theory, practice is but routine born of habit.”
•
2. “(S)He who loves practice without theory is like the sailor
who boards ship without a rudder and compass and never knows
where he may cast.“
3.
“Being denied a sufficiently secure experimental base, economic
theory has to adhere to the rules of logical discourse and must
renounce the facility of internal inconsistency. A deductive
structure that tolerates a contradiction does os under the penalty
of being useless since any statement can be derived flawlessly and
immediately from that contradiction. In its mathematical form,
economic theory is open to an efficient scrutinity for logical
errors.”
•
4. “In attempting to answer the question ‘Could it be true?’, we
learn a good deal about why it might not be true.”
4
•
1. “Without theory, practice is but routine born of habit.” ~
Louis Pasteur
•
2. “(S)He who loves practice without theory is like the sailor
who boards ship without a rudder and compass and never knows
where he may cast.“ ~ Leonardo da Vinci
•
3. “Being denied a sufficiently secure experimental base,
economic theory has to adhere to the rules of logical discourse
and must renounce the facility of internal inconsistency. A
deductive structure that tolerates a contradiction does os under
the penalty of being useless since any statement can be derived
flawlessly and immediately from that contradiction. In its
mathematical form, economic theory is open to an efficient
scrutinity for logical errors.” ~ Gérard Debreu (Nobel Prize
winner,1983)
•
4. “In attempting to answer the question ‘Could it be true?’, we
learn a good deal about why it might not be true.” ~ Kenneth
Arrow (Nobel Prize winner, 1972)
5
Why are economic models needed?
•
The use of economic models should help improve
policymaking. How?
1. They provide a theoretically consistent framework for
analyzing trade policy questions
2. Models can provide a handle on complicated questions
3. Models can help give greater intellectual support for a
chosen trade policy
4. The use of models can provide a common “language”
for policy discourse or debate
5. But models should complement rather than substitute
for policy making
6
Models commonly used
for trade policy analysis
7
Models used for trade policy analysis
• Simulation models: they help answer “What if” types of
questions (+ projections): Partial Equilibrium Models,
General Equilibrium models
• Econometric Models :
– gravity models: reduced form: can be used to establish
whether certain economic variables have an effect on a
variable of interest (Does GSP increase trade?)
– Macro-econometric models: tools for projections of
aggregates but no info on the industrial structure of the
economy + may lack micro-foundations
• Simulation (econometric) models are deterministic
8
(stochastic)
A Partial Equilibrium Analysis
Price
Impact of wheat market on
rest of the economy can be
neglected
DS
Pw(1+t)
Pw
DD
Wheat
9
A General Equilibrium Analysis
spending on goods and services
Savings
Investments
goods and services
Households
Firms
Factor services of production
exports
imports
FDI
Factor incomes
REST OF THE WORLD
10
GE or PE analysis?
• Nature of policy change
– Does it cut across many markets or sectors?
• Potential impact of change
– Are there economy-wide impacts?
• Constraints imposed by availability of data and resources
(financial and skills)
– PE data and models: free
– CGE data: single country (SAM) could be free,
multiple country (GTAP: from $ 360 to $ 4600)
– CGE models: free (GTAP) but may need software for
mathematical programming to run (LINKAGE,
MIRAGE)
11
Basics of CGE Modelling
12
A Typology of CGE Modeling
Static: regions, sectors, factors,
economic agents
+ set of economic behaviors &
relationships
Micro-Simulation Models:
representative
agents hypothesis
“removed”
Dynamic=Static features
+ explicit inter-temporal features
13
CGE Standard Model Elements I
• Input Output Economics & SAMs
• Behavioral Relationships/ Agents
– Supply
– Demand
– Trade
•
•
•
•
Government
Pricing and Imperfect substitutes
Policy – tax equivalents
Closure
–
–
–
–
Accounting identities
Endogenous/exogenous variables
Macroeconomic assumptions
Exchange rate determination
• Solution
– Equilibrium
– Linearization
– Percent change variables
14
CGE Standard Model Elements II
• Calibration/Benchmarking
• Aggregation
– Agents
– Goods/Sectors
• Experiments
– Welfare Measures
– Projections
– What if
• Extensions
– Imperfect Competition, IRS
– Product Differentiation
– Dynamics
• Results Comparisons
15
Input-Output economics & SAMs
• Production= Intermediates + Value Added
• Production= Intermediate demand + Final
Demand
• +
• Macroeconomic accounting identities to
capture income flows, tax incidence, trade and
payments, and savings-investment balances
• = > SAMs capture `circular flow’ of income
and expenditure
16
Input-Output economics & SAMs
spending on goods and services
Savings
Investments
goods and services
Households
Firms
Factor services of production
exports
imports
FDI
Factor incomes
REST OF THE WORLD
17
Input-Output economics & SAMs
• Whether neoclassical, strucuralist, neoKeynesian, or Monetarist, a CGE modeler must
respect accounting identities and equilibrium
conditions. Hence, most applied work is based
on a social accounting matrix to benchmark
(calibrate) a model and to represent relevant
accounting identities.
• SAMs capture equilibrium conditions
• Walras’ law applies
18
Decision Making and Institutions
• Linkages in SAMs are accounted for by
modelling the decision-making process of the
firm, the consumer, as well as other economic
agents and institutions: production and demand
structure
• Trade results from that decision-making
processes and their interaction with
institutions:
•
Production- Exports +
Imports=Consumption
19
Closing the Model
• Need to define a numéraire (walras law allows
to “drop” one market)
• Assumption about the adjustment mechanism
in factor and commodity markets
• Macro closure
– Macro accounting balance (gvt expenditure and
deficit; aggregate saving and investment; balance
of trade and -real- exchange rate)
– Macro adjustment mechanism (exogenously
determined)
20
Closing the Model
• Johansen closure: investment is exogenous and
consumption is the adjustment variable
• Keynesian closure: nominal wage is fixed and
employment is the adjustment variable (unemployment)
• Kaldorian closure: wages could be less or equal to the
marginal product of labor (exploitation of labor model)
• Classical closure: prices and wages are the adjustment
variables (constant employment) and investment becomes
endogenous and adjusts to total savings available
• Foreign borrowing (Robinson): trade balance is
endogenous, current account and hence net capital
inflows are the adjustment variable
21
Beyond the Standard Model
• Economies of scale, monopolistic competition and
differentiated products
• Institutional features of a particular economy (e.g. tax
collection costs)
• Specific features of a policy instrument
• Increase effort on estimation of substitution elasticities
• Dynamics to account for dynamic aspects (policy
credibility; capital accumulation; FDI; knowledge
accumulation and spillovers) and adjustment
• Account for the extensive margin of trade (the “small22
shares” issue)
CGE Dynamic Models
• Recursive:
– solves annually
– Current economic conditions (e.g. the
availability of capital) are dependent on past
outcomes but are unaffected by forward
looking expectations
– Linked with a macro econometric to include
exogenously projected changes in demographic
trends or in technology: baseline scenario
– Impact of policy change is given with respect
to the baseline scenario (sector specific TFP
and real GDP growth are solved endogenously)
23
CGE Dynamic Models
• Forward looking:
– Ramsey model, OLG, Infinite lived consumer
with financial market
– No extensive baseline scenario: trade
performance-productivity linkage + gvt
investment on infrastructure and TFP linkage +
investment in education and labor productivity
linkage
– Could account for transitionary disequilibrium
states (true adjustment process?)
24
Micro-Macro Models
• Combination of a Micro Simulation model (base on
Household surveys: fiscal and labor) and a CGE model
• Ideal to assess the impact of macroeconomic (trade)
policies and shocks on poverty/ inequality: MAMS
(maquette for MDG simulation)
• Two types of combination:
– Fully-integrated: the household model built directly
into the CGE : CGE model with heterogeneous agents
(high complexity)
– Sequential (top-down): CGE simulation results are
passed on to an household model (macro and micro
need not to be reconciled but possible lack of
25
coherence)
Micro Simulation Models
• Micro-accounting models: “the day after” approach
– Capture 1st order effects
– No behavioral response
• Behavioral Models
– Capture 2nd order effects
– Behavioral response
– Reduced form or Structural
• Dynamic versus Static models
– Dynamic is usually associated with aging of
information
– Dynamic could be behavioral
26
What is involved in a
policy simulation?
27
What is involved in a policy
simulation?
Economy before
trade policy change
Policy
change
Economy after
trade policy change
Difference between the two is attributed to
policy change
28
What is needed for a policy
simulation?
Inputs
MODEL / Closure
Outputs
29
What are the inputs?
• Baseline data:
– trade flows
– levels of protection
– input-output structure: national income aggregates
• Measure of responsiveness of economic agents
to price changes (i.e. elasticities)
• Policy - negotiating scenario
– Sectors (Agriculture, NAMA, etc.)
– Depth of liberalization
30
What are the Outputs?
• Configuration of the economy after policy change
• Overall income gains/losses from policy change
• Sources of income gain
– Sectoral (agriculture vs. NAMA)
– Policy instrument (market access or domestic
support)
• Winners or losers (at the country level)
• Changes in pattern and volume of trade and income
• “Story” to explain how inputs and model combine to
determine the output/outcome
31
Tracing Differences in Results
• Deterministic – outcome is completely determined by
choice of inputs and model (no “residuals”)
Inputs +
MODEL
Outputs
Differences in simulation results = differences in choice of
inputs and model/closure
“Story” must explain why the choice of inputs and model is
appropriate/optimal for the policy question of interest
32
Towards an “objective”
look at trade liberalization
CGE simulations
33
Doha Round CGE Simulations
•
•
•
•
•
Common results:
Multilateral liberalization is beneficial at the
global level
There are potential gains for developing
countries
Developing countries own liberalization is an
important source of their gains
Removing subsidies may damage net food
importer countries
34
Doha Round CGE Simulations
•
Results differ among studies on how gains are
redistributed
•
1. What share of the benefits goes to developing
countries?
2. What share comes from agriculture
liberalization? From NAMA?
•
35
What are the gains for developing
countries?
Full liberalization scenario. Million $ 1997
2500
2000
1500
1000
46%
30%
55%
21%
Carnegie, 2006
World Bank,
2006
World
Bank,2003
Michigan
Model, 2003
500
0
Developing countries
Developed Countries
36
What share of the gains comes
from agriculture liberalization ?
Results based on the full liberalization scenario
100%
80%
60%
40%
20%
0%
-20%
Carnagie, 2006
Agriculture
World Bank,
2006
World Bank,
2003
Manufacturing
Michigan
Model, 2003
Services
37
How important are assumptions?
• Examine one scenario with differing
assumptions
• Scenario 50% cut in all tariffs and subsidies
– Standard closure
– Fixed trade balance
– Fixed wages (unskilled unemployment) in
developing countries
– Double trade elasticities (substituability
between domestic and foreign products)
38
Global welfare
by closure
300
250
200
$b 150
100
50
0
Standard
TB
2xArm
Labour
Scenario
Source: UNCTAD
39
Fixed Trade Balance
Welfare compared with standard closure
50
40
Japan
30
20
$b 10
0
-10
B
Z
M
R
T
U
E
E
C
M
L
A
SE
A
X
M
E
A
B
R
IN
V
D
O
O
R
USA
K
JP
N
E
U
25
-30
D
-20
Scenario
Source: UNCTAD
40
Trade elasticities
Welfare compared with standard closure
35
Japan
30
25
20
$b
15
10
B
Z
M
R
T
U
E
E
C
M
L
A
SE
A
M
E
A
B
R
D
IN
V
D
O
O
R
K
JP
N
E
U
25
0
X
5
Scenario
Source: UNCTAD
41
Fixed wages
Welfare compared with standard closure
90
China
80
70
$b
60
50
40
B
Z
M
R
T
U
E
E
C
M
L
A
SE
A
M
E
A
B
R
D
IN
V
D
O
O
R
K
JP
N
E
U
25
10
0
X
30
20
Scenario
Source: UNCTAD
42
Other assumptions we ignore
•
•
•
•
•
CRTS
Perfect competition
Static/dynamic
Technology
Productivity
• Key elasticities e.g. K/L substitutability
• Aggregation
43
An Application: The
potential for SouthSouth Trade
44
Setting a Policy Simulation
• Qualifying the general issue of interest: “what
is at stake ?” analysis
• Choice of aggregation
• Model specification and Closure
• Choice of scenario to be simulated
• Presentation of the results
• Interpretation of the results
45
What is at stake?
Trade weighted average applied tariffs (inc. preferences) by development status
Developed
Developing
Least developed
%
%
%
Developed
2.1
9.2
11.1
Developing
3.9
7.2
14.4
Least developed 3.1
7.2
8.3
Total
8.1
13.6
Source
2.9
Source: Computed from TRAINS/WITS (2004)
46
Aggregation
• South-South trade is the focus:
– keep as many southern countries as possible (21)
– Identify those sectors with the highest protection
among developing countries (20) and/or with little
access to norther markets
– Adjust the country-groups selection in accordance
• General hints:
– Aggregation is usually 20*20 (max 30*30)
– Different aggregations affect differently the level of
protection an distortion that will characterize the
simulation exercise (could hide/highlight gains and
losses ) and thus the expected gains from the policy
simulation
47
Model and Closure
• Model characteristics are likely to depend on your CGE
skills
• Standard GTAP is widely used but more and more
imperfect competition in manufactures
• Still prevalence of static models because of high
computational resources required for the baseline
scenario in recursive models
• No a priori concerning the favorite closure
• With a focus on developing countries fixed wage
(flexible employment) for unskilled labor could be
sensible
• Standard non-standard: fixed trade balance for all
countries but the USA
48
Choice of Scenario
• Pre-simulation to account for the aging of data and
policy (e.g. China accession to the WTO, end of ATC)
• Political Relevance: Potential of south-south trade
relevant in the context of GSTP negotiations (43
countries + opening to the group of 77 + China)
• If not related to “realistic” scenarios (Doha
negotiations) identify sector and country relevant
scenarios (manufactures, agriculture and overall
liberalization or tariff cuts/ across different regions)
• In general tariff cuts are simulated together with export
taxes and subsidies
• Compensation of changes in tariff revenues (e.g.
income is made endogenous) could be a major concern
for developing countries
49
Presentation of Results
• Present both absolute variations and proportional
variations with respect to relevant initial values
(welfare as a percentage of initial GDP)
• Present the results of the same scenario obtained with
at least one different closure from the favorite one
(annex)
• Results could be presented in aggregate form for sake
of clarity with reference o fully disaggregated results in
the text
• Present the results obtained in a benchmark simulation:
usually full trade liberalization
50
Interpretation of Results
• Are you sure you understand what is going on? (should be
the case if good preliminary analytical work done for
aggregation)
• Results are your “story” and must reflect a good coherence
between your scenario(s) and the various component of
your modeling approach
• Multiple scenarios and comparative analysis are less
sensible to modeling specificities: everything is relative
• Simulations of a specific agreement/policy scenario must
be based on the most “realistic” computational framework
• Make sure that what your telling is in line with your
assumptions (e.g. do not talk about changes in labor
demand when employment is assumed to be fixed)
51
How can modelling better assist
policy making?
• A. Improving data
–
–
–
–
–
–
trade transaction costs
more disaggregated sectors
better disaggregation of regions/countries
protection in services
TNC activities: FDI vs. Outsourcing
Households surveys to account for poverty and
inequality impact
52
.... Cont’d
• B. Improving modelling of:
–
–
–
–
–
Better treatment of services
Adjustment costs
Functioning of factor (labour) markets
Tariff revenue implications of trade liberalization
Extensive margin of trade (potential for
diversification + productivity gains)
• C. Improving confidence in simulation results
– Sensitivity analyses: within and across models
– Ex-post verifications
– Use also focused models
53
References
“Demystifying Modelling Methods for Trade Policy”, Roberta Piermartini and
Robert Teh, Discussion Paper No. 10, World Trade Organization, Geneva,
Switzerland, September 2005
(http://onlinebookshop.wto.org/shop/article_details.asp?Id_Article=661)
“Structure of GTAP” ,Thomas W. Hertel and Marinos E. Tsigas, Chapter 2 in
T.W. Hertel (ed.), Global Trade Analysis: Modeling and Applications,
Cambridge University Press, 1997.
(https://www.gtap.agecon.purdue.edu/resources/res_display.asp?RecordID=41
3)
Global Trade Analysis Project (GTAP):http://www.gtap.agecon.purdue.edu/
“LINKAGE Technical Reference Document”, Dominique van der
Mensbrugghe, DECPG, World Bank, December 2005
(http://siteresources.worldbank.org/INTPROSPECTS/Resources/33493454
1100792545130/LinkageTechNote.pdf)
References
Michigan Model of World Production and Trade:
http://www.fordschool.umich.edu/rsie/model/description.html
“Mirage, a Computable General Equilibrium model for Trade
Policy Analysis”, Bchir E., Y. Decreux, J-L. Guérin, S. Jean,
CEPPI
http://www.cepii.fr/anglaisgraph/workpap/pdf/2002/wp02-17.pdf
World Scan Dynamic Model of the World of the Netherlands
Bureau of Economic Policy analysis (CPB):
http://www.cpb.nl/nl/pub/bijzonder/20/bijz20_c.pdf
Harrison/Rutherford/Tarr Multi-Regional Global Trade Model:
http://dmsweb.badm.sc.edu/Glenn/ur_pub.htm
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