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Applied General Equilibrium Models I and II

Program

 

Class meeting

Dates: August 09 – December 06, 2022

Time: Tuesday, 14h00 to 17h50

Time zone: GMT-3:00 (Brasília)

 

Instructor: Eduardo A. Haddad

Prof. Haddad is Full Professor at the Department of Economics at the University of Sao Paulo, Brazil, where he directs the Regional and Urban Economics Lab (NEREUS). He also holds a position as Affiliate Research Professor at the Regional Economics Applications Laboratory – REAL – at the University of Illinois at Urbana-Champaign, USA. He is a Senior Fellow at the Policy Center for the New South, Rabat, Morocco.

Prof. Haddad has published widely in professional journals on regional and interregional input-output analysis, computable general equilibrium modeling, and various aspects of regional economic development in developing countries; he has also contributed with chapters in international books in the fields of regional science and economic development. His research focuses on large-scale modeling of multi-regional economic systems, with special interest in modeling integration applied to transportation, climate change and spatial interaction.

Prof. Haddad received his B.A. in Economics from the Federal University of Minas Gerais, Brazil, in 1993, and his Ph.D. in Economics from the University of Illinois at Urban-Champaign in 1997. In January-December 1998 he held a post-doctoral position at the University of Oxford. He has served as the president of the Brazilian Regional Science Association (2008-2010), and as the first president of the Regional Science Association of the Americas (2008-2010). He is now the Elect-President of the Regional Science Association International (RSAI). He was the Director of Research of the Institute of Economic Research Foundation – FIPE – from 2005 to 2013. He has spent the period January 2014 to June 2015 on sabbatical as a visitor at the Department of Economics (International Economics Section) at Princeton University, and at the Edward J. Bloustein School of Public Policy and Planning at Rutgers University. In 2017-2018, he was the Chairman of the Department of Economics at USP.

Full CV

 

Teaching assistant: Inácio F. Araújo

Dr. Araújo is a Post-Doc researcher at the Department of Economics and the Regional and Urban Economics Lab (NEREUS) at the University of Sao Paulo, Brazil. His major research interests lie in the field of regional analysis. He has experience in the implementation and application of economic models, especially input-output and computable general equilibrium models.

Full CV

 

Teaching assistant: Ademir A. M. Rocha

Ademir Rocha is a Ph.D. Candidate at the Department of Economics and researcher at the Regional and Urban Economics Lab (NEREUS) and Interdisciplinary Climate Investigation Center (INCLINE) at the University of São Paulo, Brazil. He has experience in the field of economic modeling and has published articles on the following topics: regional and urban economics, locational decision of economic agents, land use modeling and economics of climate change.

Full CV

 

Learning objectives

The course goals are:

  • To introduce students to the ideas and techniques of input-output analysis and computable general equilibrium modelling, and to equip them to start using operational models, adapting such models for their own simulations
  • To equip students to start using different methods in multisectoral and multirregional analysis
  • To develop skills that help analyzing development policies
  • To introduce students to some of the commonly-used tool kits in regional science that help understanding and interpreting the complexity of the spatial structure of sub-national economies

 

Readings

Textbooks:

Dervis, K., De Melo, J. and Robinson, S. (1982). General Equilibrium Models for Development Policy. Cambridge University Press.

Dixon, P. D., Jerie, M. and Rimmer, M. T. (2018). Trade Theory in Computsble General Equilibrium Models: Armington, Krugman and Melitz. Springer.

Dixon, P. B. and Jorgenson, D. W. (2013). Handbook of Computable General Equilibrium Modeling. Volumes 1A and 1B. North-Holland, Amsterdam.

Dixon, P. B., Parmenter, B. R., Sutton, J. and Vincent, D. P. (1982). ORANI: A Multisectoral Model of the Australian Economy. North-Holland, Amsterdam.

Dixon, P. B., Parmenter, B. R., Powell, A. A. and Wilcoxen, P. J. (1992). Notes and Problems in Applied General Equilibrium Economics. Advanced Textbooks in Economics 32, Eds. C. J. Bliss and M. D. Intriligator, North-Holland, Amsterdam.

Dixon, P. D. and Rimmer, M. T. (2002). Dynamic General Equilibrium Modelling for Forecasting and Policy: A Practical Guide and Documentation of MONASH. Amsterdam, North-Holland.

Ginsburgh V. and Keyzer M. (1997). The Structure of Applied General Equilibrium Models. The MIT Press, Cambridge.

Haddad, E. A. (1999). Regional Inequality and Structural Changes: Lessons from the Brazilian Economy. Ashgate, Aldershot.

Hertel, T. W. (1997). Global Trade Analysis: Modeling and Applications, Cambridge University Press.

Isard, W. et al. (1998). Methods of Interregional and Regional Analysis. Ashgate, Aldershot.

Miller, R.E. and Blair, P.D. (2009). Input-Output Analysis: Foundations and Extensions. Englewood Cliffs: Prentice-Hall.

Shoven, J. B. and Whalley, J. (1992). Applying General Equilibrium. Cambridge Surveys of Economic Literature. Cambridge University Press, Cambridge.

Complementary readings:

To be indicated by the instructor. A list of complementary readings will be available at the website of the course.

 

Link for class material distant access

Moodle: https://edisciplinas.usp.br/acessar/

NEREUS: http://www.usp.br/nereus/

 

Toolboxes of Input-Output Analysis

Análise de Insumo-Produto: Teoria e Aplicações no R (NEDUR-UFPR) – Link

ioanalysis: Input-Output Analysis in R (REAL-UIUC) – Link

PyIO: Python Module for Input-Output Analysis (REAL-UIUC) – Link

REAL I-O: Input-Output Operation Software (REAL-UIUC) – Link

 

Examination and grading

The final mark composition:

  • Final exam (course project): 60%
  • Continuous controls (homework): 30%
  • Assiduity and in-class participation: 10%

 

Homework and attendance

Some of the techniques used will be included in homework assignments, which should be delivered on previously established dates. While student cooperation is encouraged to resolve exercises, each student will have to submit his/her own answers. There will be quizzes throughout the course that will be part of the grading.

 

Late assignments

Regular attendance is expected as well as delivery of homework (quizzes, group exercises, presentations and simulation exercises). In addition, there will be an individual project at the end of each part of the course. The Final Exam will consist of a paper based on an application of an inter-regional input-output model (Part I), and an inter-regional CGE model (Part II).

 

Complementary activities

We may schedule eventual tutorial meetings outside regular course hours to discuss and carry-on hands-on applications of the concepts and techniques discussed in the sessions. Such activities may be complemented by the introduction of extensions of the basic models.

 

Course project

In previous editions of the course, we have developed with students applied models for different countries and regions: Greece (2017), Chile (2018), Colombia (2019), Brazilian Urban Areas and Paraguay (2020), and “Serra da Mantiqueira” (2021). The development of such models has relied on collaboration with scholars and institutions from those countries (e.g. Prof. Yannis Psycharis at Panteion University, the team led by Patricio Aroca at UAI, and Dr. Jaime Bonet and his research team at Banco de la República). In essence, they have helped us with the country’s data and we have developed the models. At the end of the course, students engaged in collaborative research projects using one of the models developed during the semester. Many of the projects the students worked on then became the basis for publications.

 

Course detailed outline

 

Part I: EAE6061 – Applied General Equilibrium Models I

 

Class #1 (August 09, 2022)

Topic: “General Equilibrium: Pure Theory, Applied Theory, and Practice”

Key learning outcome:

  • Intellectual legacy of general equilibrium theory and applied general equilibrium models
  • “Cournot’s Problem”

Manual chapters and readings:

Review (linear algebra) – Miller and Blair (2009), appendix

 

Class #2 (August 09, 2022)

Topic: “Economic Base Models I”

Key learning outcome:

  • Broad perspective of regional policies, with an overview of the theoretical background and rationale which are essential to the definition of priorities and strategies
  • Review the simple Keynesian model and the elementary economic-base models
  • Methods of estimating the values of EB multipliers

Manual chapters and readings:

Article: “O PIB e a Renda” (Paulo R. Haddad) – O Tempo, 17/10/2019

Activity 1: Angola Brazil

Solution: Angola Brazil

 

Class #3 (August 16, 2022)

Topic: “Economic Base Models II”

Key learning outcome:

  • Review key elements of regional accounts
  • Introduce students to EB structural models

Manual chapters and readings:

Activity 2: Questions Angola Brazil

Solution: Brazil

 

Class #4 (August 16, 2022)

Topic: “Theoretical Structure of Input-Output Models”

Key learning outcome:

  • Investigate the fundamental structure of the input-output model, the assumptions behind it, and some of the simplest kinds of problems to which it is applied

Manual chapters and readings:

Example IO: Excel (ver https://guilhotojjmgen.wordpress.com/)

Activity 3: Data Brazil_1a Data_Angola

Solution: Brazil Angola

 

Class #5 (August 30, 2022)

Topic: “Impact Analysis and Multipliers”

Key learning outcome:

  • Assess the effects on an economy of changes in elements that are exogenous to the model of that economy
  • Develop summary measures derived from the elements of the Leontief inverse matrix

Manual chapters and readings:

Activity 4: Data_Brazil_2a Data_Angola

Solution: Brazil Angola

Solution: Activity 5: Challenge (Man-year equivalent)

 

Class #6 (August 30, 2022)

Topic: “Regional and Inter-regional Input-Output Models”

Key learning outcome:

  • Incorporate features of a regional economy into an input-output framework

Manual chapters and readings:

Solution: Activity 6 (Key sectors)

 

Class #7 (September 13, 2022)

Topic: “Applications of Input-Output Models I”

Key learning outcome:

  • Linkage measures
  • Key sector analysis
  • Output decomposition

Manual chapters and readings:

Solution: Activity 7 (Decomposition of regional output)

 

Class #8 (September 13, 2022)

Topic: “Applications of Input-Output Models II”

Key learning outcome:

  • Extraction method

Manual chapters and readings:

Example (SAMIR – Marrocos): Excel file

Activity 8: Data_Brasil Data_Angola

Solution: Activity 8

 

Class #9 (September 20, 2022)

Topic: “Applications of Input-Output Models III”

Key learning outcome:

  • Structural decomposition analysis

Manual chapters and readings:

Example (SDA): Excel file

Activity 9 (SDA – Employment): Data

Solution: Activity 9

 

Class #10 (September 20, 2022)

Topic: “Global Input-Output Models” (Prof. Inácio Araújo)

Key learning outcome:

  • Review the global input-output databases
  • Present potential applications

Manual chapters and readings:

 

Class #11 (September 27, 2022)

Topic: “Methods of Regionalization / Miyazawa”

Key learning outcome:

  • Estimate an inter-regional input-output system using the IIOAS method
  • Miyazawa extended input-output framework
  • Explore the nature and strength of economic interdependence in metropolitan areas
  • Analyze interactions between different groups and sectors

Manual chapters and readings:

Example (IIOAS Method): Excel file

 

Class #12 (Date to be defined)

Topic: “Applications of Input-Output Models with R” (Prof. Vinicius Vale)

Key learning outcome:

  • Use R to solve input-output models

Manual chapters and readings:

Database and RScript: see here

 

Class #13 (October 04, 2022)

Topic: “Social Accounting Matrix”

Key learning outcome:

  • Inspect the different dimensions of income flows embedded in a SAM
  • Explore the relationships between output, factor demand and income, and the decomposition of these relationships into separate effects

Manual chapters and readings:

Example (SAM for Brazil): Data

Exercise: SAM of a Closed Economy

Activity 10: Questions Data

 

Class #14 (October 04, 2022)

Topic: “The Johansen Approach”

Key learning outcome:

  • How microeconomic theory – cost-minimizing, utility-maximizing – underlies the equations of a CGE model
  • The use of nested production and utility functions
  • How input-output data are used in equations
  • How model equations are represented in percent change form
  • How the choice of exogenous variables makes a model more flexible

Manual chapters and readings:

 

Class #15 (October 11, 2022)

Topic: “Introduction to GEMPACK” (Prof. Inácio Araújo)

Key learning outcome:

  • Use GEMPACK to solve a CGE model

Manual chapters and readings:

  • Dixon et al. (1992): chapter 3

 

Class #16 (October 11, 2022)

Topic: “Course Projects”

Key learning outcome:

  • Develop presentation skills

Manual chapters and readings:

 

Part II: EAE6061 – Applied General Equilibrium Models II

 

Class #1 (October 18, 2022)

Topic: “The ORANI Model I”

Key learning outcome:

  • Understand the structure of database

Manual chapters and readings:

ORANI-G (Brazil): Files

Example (ORANI for Brazil): Data

Activity 1: Data

 

Class #2 (October 18, 2022)

Topic: “The ORANI Model II”

Key learning outcome:

  • Understand the equation system of a national CGE model

Manual chapters and readings:

Activity 2: Questions

 

Class #3 (October 25, 2022)

Topic: “The ORANI Model III”

Key learning outcome:

  • Understand the equation system of a national CGE model
  • Calibrate a CGE model
  • Use of a national CGE model for policy analysis

Manual chapters and readings:

Activity 3: Questions

 

Class #4 (October 25, 2022)

Topic: “The ORANI Model IV”

Key learning outcome:

  • Use of a national CGE model for policy analysis

Manual chapters and readings:

Exercises: (i) Homogeneity test (ii) Reduction in real wages

 

Class #5 (November 01, 2022)

Topic: “The Miniature MONASH Model I”

Key learning outcome:

  • Introduce recursive-dynamics in CGE models

Manual chapters and readings:

 

Class #6 (November 01, 2022)

Topic: “The Miniature MONASH Model II”

Key learning outcome:

  • Build baseline and policy scenarios using dynamic CGE models

Manual chapters and readings:

Exercise (database): Questions

MM Model: Files

Wage Cut Simulation: Guide

Activity 4: Questions

 

Class #7 (November 08, 2022)

Topic: “The EFES Model”

Key learning outcome:

  • Introduce students to forecasting exercises with a CGE model for Brazil
  • Top-down regional disaggregation of national results
  • Review non-academic, government and business-related applications of CGE models

Manual chapters and readings:

 

Class #8 (November 08, 2022)

Topic: “Spatial CGE Models I”

Key learning outcome:

  • Introduce students to applied general interregional equilibrium models

Manual chapters and readings:

 

Class #9 (November 22, 2022)

Topic: “Spatial CGE Models II”

Key learning outcome:

  • Develop an operational spatial CGE model under conditions of limited data availability

Manual chapters and readings:

 

Class #10 (November 22, 2022)*

Topic: “The B-MARIA Model I”

Key learning outcome:

  • Develop bottom-up interregional CGE model
  • Introduce a transportation sector and non-constant returns to scale into CGE models
  • Understand the role of transportation costs in spatial CGE models
  • Integrate CGE models to transportation networks
  • Apply CGE models for assessing the impacts of transportation infrastructure
  • Integrate spatial/metropolitan CGE models to travel demand models

Manual chapters and readings:

 

Class #11 (November 29, 2022)

Topic: “The B-MARIA Model II”

Key learning outcome:

  • Calibrate a bottom-up interregional CGE model
  • Use of an ICGE model for policy analysis

Manual chapters and readings:

Examples BMMX

BMMX ICGE Model: files

 

Class #12 (November 29, 2022)

Topic: “The B-MARIA Model III”

Key learning outcome:

  • Calibrate a bottom-up interregional CGE model

Manual chapters and readings:

Data for calibration exercise: Files

 

Class #13 (December 06, 2022)

Topic: “The B-MARIA Model IV”

Key learning outcome:

  • Integrate CGE models to transportation networks
  • Apply CGE models for assessing the impacts of transportation infrastructure
  • Integrate spatial/metropolitan CGE models to travel demand models

Manual chapters and readings:

 

Class #14 (December 06, 2022)

Topic: “Course Projects”

Key learning outcome:

  • Develop presentation skills

 

Class #15 (December 06, 2022)

Topic: “The GTAP Model I” (TBC)

Key learning outcome:

  • Introduce students to the structure of the standard GTAP model, a multi-country, multi-sector, CGE model, with perfect competition and constant returns to scale

Manual chapters and readings:

 

Class #16 (December 06, 2022)

Topic: “The GTAP Model II” (TBC)

Key learning outcome:

  • Overview of the GTAP database
  • Introduce students to GTAP applications

Manual chapters and readings:

BMAPSP ICGE Model: files

 

 

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