Simulation Models in Economics: Issues, Design, and Implementation

1. Simulation Models in Economics: Issues, Design, and Implementation Sherman Robinson International Food Policy Research Institute (IFPRI)

2. Outline • Simulation models: • Types • issues • design • Implementation • Impact model • CGE models • Estimation and validation

3. 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

4. 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

5. 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

6. “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

7. 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

8. 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

9. 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

10. 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”

11. 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?)

12. 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

13. 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

14. 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

15. 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

16. 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

17. 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

19. 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

21. 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.

22. 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

24. 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

25. 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

26. 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.

27. 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)

28. 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)

29. Factor markets Factor market functioning Segmentation Wage determination What do we want to capture? Economywide Environment • Structural features • Binding macro constraints • General Equilibrium effects • Heterogeneity • Human and physical capital • Demographic Composition • Preferences • Access to Markets Households

30. 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

31. 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)

32. 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

33. Stylized Model Structure Factor Domestic Private Savings Markets Factor Wages Costs Gov. Savings & Rents Taxes Intermediate Input Cost Sav./Inv. Households Government Activities Transfers Private Government Consumption Investment Consumption Demand Commodity Markets Sales Exports Imports Foreign Transfers Rest of the Foreign Savings World

34. SAM Structure

35. 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

40. 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