Simulation Models in Economics:
Issues, Design, and
Implementation
Sherman Robinson
International Food Policy Research
Institute (IFPRI)
Outline
• Simulation models:
– Types
– issues
– design
– Implementation
• Impact model
• CGE models
• Estimation and validation
2
Simulation Models
• Long history in economics
– Econometric Models used in “simulation mode”
– Models designed for simulation
• Level of aggregation
– World models
– Country models
– Regional/sub-regional models
– Enterprise/farm models
3
Types of Simulation Models
• Stylized: “putting numbers to theory”
– Small, focused models—close to theory
• Applied
– Larger, more detail (including institutions)
– Broader range of issues
• Policy models
– Explicit links between policy parameters and
economic outcomes
4
Types of Simulation Models
•
•
•
•
“Reduced form” versus “structural”
Dynamic versus static
Partial versus general equilibrium
Coverage
– household/village/region/country/globe
• Domain of application
– “Universe” of the model
5
“Reduced Form” Models
• Vague theoretical specification of relationships
among variables
– Econometric estimation: hypothesis testing
– Unidentified/unidentifiable structural model
• Simulation mode: forecasting
– E.g., macroeconometric models
– Goal is to forecast endogenous variables, given
projections of exogenous variables
– Less interested in “how” the economy works
6
Structural Models
• Goal is to simulate “how” the economy works
– “Counterfactual” analysis: “What if” scenarios
– Controlled experiments: parameters/policies
• causal chains/large numbers
• Model elements
– Specify agents, technology, markets, institutions,
signals, motivation, and behavior
– “Domain” of the model
7
Structural Models
• Model elements: structural models
– Agents interacting, usually across markets
– Specification of agent behavior
– Specify institutional structure
– Notions of equilibrium
• Partial versus general equilibrium
• Static versus dynamic
8
Structural Models
• Partial equilibrium: commodity models
– Single market models
– Multimarket models
• Economywide models
– “Economy” may vary in size and domain
– Macro models
– General equilibrium models
– Microsimulation household models
9
Structural Models
• In a structural model, must specify:
– Agents (producers, households)
• Economic actors in the model
– Motivation (profit maximizing producers, utility
maximizing consumers)
– Signals (prices in markets)
– Institutional structure (competitive markets)
• “Rules of the game”
10
Structural Models
• Describe agent behavior mathematically
– Producers: supply behavior
• Production/cost functions, profit maximization
– Input demand (K, L, Land, intermediate inputs)
• Supply curves (marginal cost function?)
– Consumers: demand behavior
• Utility functions, utility maximization
– Income, expenditure equations
• Demand curves (Marshallian?)
11
Deep/Shallow Structural Models
• “Deep” structural models
– explicit description of agent behavior
– Utility functions, production/cost functions
– Relevant factor and commodity markets
• “Shallow” structural models
– Supply/demand functions which summarize agent
behavior (“reduced form” equations)
– Only loosely based on theory
12
Structural Models
• Agent based models:
– Opportunity, motive, ability
– Not enough to describe operation of the economy
• Additional “constraints” on the economy
– System constraints
• Supplies of primary factors (land, labor, capital)
– Equilibrium conditions
• Supply-demand balance in all markets
13
Structural Models
• Market equilibrium: how markets work
– Equilibrium conditions
• Supply = demand
– Equilibrating mechanisms
• Price responsive supply and demand functions
• International trade
– Equilibrating variables
• Commodity and factor prices, domestic and global
14
Market Equilibrium in Models
• A descriptive feature: If market clearing is a
reasonable assumption, then we can use the
specification to describe a realistic result
– Solve for market-clearing prices in the model,
which then correspond to actual prices
• No need to specify the exact process by which
markets equilibrate, just the result
– Powerful tool to simplify structural models
15
Partial Equilibrium Models
• Single commodity or multimarket
– Do not cover the entire economy
• Supply and demand curves
– Linear or nonlinear, loosely based on theory
– Expenditure functions may or may not be based on
demand theory
– “Shallow” structural models: reduced form equations
16
Simulation Models: Issues
• Growth and structural change
– Investment/education
– Role of trade
– Productivity growth
– Agriculture/water/land
– Industrialization
• Long-run development strategies
18
Simulation Models : Issues
• Macro shocks and structural adjustment
• Income distribution
– Long run: poverty and growth
– Short run: impact of macro adjustment
• Fiscal policy
– Tax system design and/or reform
– Government expenditure policy
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Simulation Models : Issues
• Globalization
– Trade policy reform: GATT/WTO
– Regional trade agreements
• Customs unions: EU, Mercosur
• FTA’s: NAFTA, bilaterals, etc.
• Preferential access: Cotonou, EBA, AGOA,etc
– Domestic policy reforms and trade system
• Impact of OECD agricultural policies
20
Simulation Models: Issues
• Energy
– Energy “system” and the economy
– Oil price shocks
– Biofuels
• Environment/climate change
– Costs of environmental policy
– Climate change: mitigation/adaptation
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Model Design: Aggregation
• Macro (aggregates: C, I, G, E, M)
– Macroeconometric models
– Asset markets and financial variables
• Micro (household/firm/farm analysis)
– Microsimulation models
• Mezzo (sectors: multi-market and CGE)
– Structure of production, employment, trade, etc.
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Implementation: Construction
• Explicit mathematical statement of theoretical
model
– Specify functional forms, endogenous variables,
parameters, and exogenous variables
– Transforms inputs to outputs
• Computer code: modeling languages
– GAMS, Matlab, Mathematica, Stella, Vensim,
system dynamics
23
Implementation: Validation
• Validation is linked to issues to be analyzed
– Focus of the model application
– Intended “domain of applicability” of the model
• Need to “test” the model with historical data
relevant to its domain of applicability
– How well does the model “explain” past events?
– How well does it capture the important causal
chains? Validity of the underlying deep/shallow
structural model
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Multi-Market: IMPACT Model
• Impact is a suite of models:
– Core Impact multi-market global trade model
– “Water" model of FPU river basins,
– “Water stress" model that converts hydrological
output into yield shocks
– Crop models
– Biofuels, livestock, and fish models
– Links to GCM climate change models
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Economywide CGE Models
• “General equilibrium”: many markets, factors
and commodities
– Simultaneous equilibrium across inter-dependent
markets
• “Behavior” consistent with general
equilibrium theory
– Deep structural relations
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CGE Model Design: Theory
• Walras-neoclassical-structuralist-Keynes:
theoretical roots
– Role of product and factor markets
– Role of assets and financial markets
• Dynamic versus static
– Time horizon: short, medium, long
– Notion of equilibrium: flows and stocks
• Rational expectations, forward looking, etc.
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CGE Models
• Numerical application of the Walrasian general
equilibrium model
– Market economy where a many agents maximize their
objective functions (utility or profit) subject to their constraints
(budget or technology)
– Single-period, static model
• Equilibrium model
– No global objective function
– Optimizing, price-responsive behavior of individual actors
– Complete specification of both supply and demand sides of all
markets (goods and factors)
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Background
• Johansen 1960: MSG Model of Norway
– Still used for planning and forecasting
• 1970s: Confined mostly to universities and
research institutes
• 1980s and beyond: wider use (including
government agencies in many countries)
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What do we want to capture?
Economywide
Environment
Factor markets
Households
Structural features
Binding macro constraints
General Equilibrium effects
Factor market functioning
Segmentation
Wage determination
Heterogeneity
Human and physical capital
Demographic Composition
Preferences
Access to Markets
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Typical CGE Model Features
• Simulation model
– No forecasting or macro cyclical analysis
• “Micro-macro” model in structure
– Explicit specification of micro/agent behavior
– Simultaneous economywide and micro outcomes
• Set up in “real” terms:
– No asset markets,
– Money is neutral,
– Decisions are a function of relative prices
• Representative household assumption
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CGE Models
• Actors: producers, consumers, government,
rest of the world
• Motivation: profit maximization, utility
maximization
• Institutions and signals: competitive markets
and prices
• Agent constraints: technology, factor
endowments (budget constraints)
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CGE Models
• System constraints:
– Resources (land, labor, capital),
– International: foreign trade balance
• Equilibrium conditions:
– Supply-demand balance in all markets
– Macro balances: government, savings-investment,
foreign trade balance
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Stylized Model Structure
Factor
Markets
Factor
Costs
Activities
Sales
Domestic Private Savings
Wages
& Rents
Intermediate
Input Cost
Gov. Savings
Taxes
Households
Government
Sav./Inv.
Transfers
Commodity
Markets
Exports
Imports
Rest of the
World
Private
Consumption
Government
Consumption
Investment
Demand
Foreign Transfers
Foreign Savings
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SAM Structure
Expenditures
Receipts
Activities
Market
sales
Domestic
Institutions
Home consumption
Intermediate
Commodities
inputs
Transactions
costs
Final
market
demands
Factors
Domestic
Institutions
Activities
Factors
Value
added
Taxes
Rest of
World
Totals
Commodities
Tariffs,
Taxes
Income,
Taxes
Rest of
World
Activity
income
Exports
Commodity
demand
Transfers
Factor
income
Transfers,
Transfers,
Taxes,
Savings
Savings
Commodity
supply
Institution
income
Foreign
exchange
outflow
Imports
Activity
spending
Totals
Factor
spending
Institution
spending
Foreign
exchange
inflow
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Solving CGE Models
• Direct approaches
– Scarf algorithm
– Log linearization (Johansen, Orani, GTAP)
– Simultaneous nonlinear equations
• Scarf algorithm.
• Tâtonnement algorithms
• Newton techniques (GAMS)
• Optimization methods
– Negishi Theorem (Ginsburgh-Waelbroeck-Keyzer)
– Nonlinear programming problem (NLP)
– Shadow prices = market prices
36
Calibration of CGE Models
• Equivalent to a “backward” solution of the
model in order to determine the set of
parameter values consistent with the initial
structure of the economy.
• Assume that the initial data (e.g., SAM)
represent an equilibrium model solution.
– Share parameters from SAM data.
– Elasticity parameters from other sources.
37
Estimation and Validation
• Define “domain of applicability” of model
• Econometric models: simultaneous estimation
and validation
– Sample data used for both parameter estimation and
within-sample “prediction” of endogenous variables
(validation). With lots of data, one can save some data
for separate validation exercise.
• Notion of “information” for estimation and
validation
38
Estimation and Validation
• Structural versus reduced-form models
– “Deep” behavioral parameters for structural
simulation models
• Tastes, technology, and institutions
– Issue of use of prior information about parameters
in estimation
• Separation of estimation and validation
• Not enough data to do both simultaneously
• Need to use variety of information
39
Estimation and Validation
• Estimation using MaxEnt econometrics
– Zellner: “Efficient” information processing rule.
Use all, but only, the information available. Do not
assume information you do not have.
– Use of prior information on parameters
• Bayesian in spirit, but not formal Bayesian estimation
• Distinction between “precision” and “prediction”
– Tradeoffs, different from classical regression analysis
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Conclusion
• Gap between theory and empirical
implementation has narrowed
• Simulation models are widely used, and will
become even more common
• Advances in econometrics applicable to
structural parameter estimation:
– Information theoretic estimation methods
41