Agent-Based Computational Economics: a Constructive
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Computational Economics and Econometrics
Computational Economics and Econometrics A. Ronald Gallant Penn State University c 2015 A. Ronald Gallant Course Website http://www.aronaldg.org/courses/compecon Go to website and discuss • Preassignment • Course plan (briefly now, in more detail a few slides later) • Source code • libscl • Lectures • Homework • Projects Course Objective – Intro Introduce modern methods of computation and numerical anal- ysis to enable students to solve computationally intensive prob- lems in economics, econometrics, and finance. The key concepts to be mastered are the following: • The object oriented programming style. • The use of standard data structures. • Implementation and use of a matrix class. • Implementation and use of numerical algorithms. • Practical applications. • Parallel processing. Details follow Object Oriented Programming Object oriented programming is a style of programming devel- oped to support modern computing projects. Much of the devel- opment was in the commercial sector. The features of interest to us are the following: • The computer code closely resembles the way we think about a problem. • The computer code is compartmentalized into objects that perform clearly specified tasks. Importantly, this allows one to work on one part of the code without having to remember how the other parts work: se- lective ignorance • One can use inheritance and virtual functions both to describe the project design as interfaces to its objects and to permit polymorphism. Inter- faces cause the compiler to enforce our design, relieving us of the chore. Polymorphism allows us to easily swap in and out objects so we can try different models, different algorithms, etc. • The structures used to implement objects are much more flexible than the minimalist types of non-object oriented language structures such as subroutines, functions, and static common storage. -
Computational Topics in Economics and Econometrics Spring Semester 2003 Tuesday 12-2 Room 315 Christopher Flinn Room 302 Christopher.fl[email protected]
Computational Topics in Economics and Econometrics Spring Semester 2003 Tuesday 12-2 Room 315 Christopher Flinn Room 302 christopher.fl[email protected] Introduction: The objective of this course is to develop computational modeling skills that will increase the stu- dent’s capacity for performing quantiative research in economics. The basic premise of the course is the following. To adequately explain social phenomena of interest to economists requires the use of relatively sophisticated, albeit stylized, models. These models, whether involving only the solution of individual decision rules in a dynamic context or the determination of equilibria in a general equilibrium model, can only be solved numerically. We will review techniques that allow the solution of a large class of fixed point problems, which virtually all economic problems can be cast as, and will illustrate and compare techniques in the context of diverse examples. As an integral part of the course, students will be expected to contribute problems of their own, hopefully taken from current research questions they are investigating. We will also study the use of computational-intensive techniques in econometrics. Over the past several decades there have been a lot of exciting developments in this area due to enormous increases in processor speed and affordability. Topics in this area that we will treat include general computational issues in the estimation of nonlinear models, simulation estimation methods (maximum likelihood and method of moments), bootstrap methods, and the E-M algorithm. Examples from my own and other applied economists’ research will be used to illustrate the methods where appropriate. Because applied numerical analysis is at least one-half art form, it will be extremely useful for all of us to hear from individuals who have successfully completed large research projects that required them to solve daunting computational problems in the process. -
Complexity Economics Theory and Computational Methods
Complexity Economics Theory and Computational Methods Dr. Claudius Gräbner Dr. Torsten Heinrich Institute for the Comprehensive Analysis of the Economy (ICAE) Institute for New Economic Thinking (INET) & Oxford Martin School Johannes Kepler University Linz University of Oxford & & Institute for Socio-economics University of Bremen University of Duisburg-Essen & www.torsten-heinrich.com ZOE. Institute for Future-Fit Economies @TorstenHeinriX www.claudius-graebner.com @ClaudiusGraebner Summer Academy for Pluralism in Economics Exploring Economics 10.08.2018 Plan for first lecture • Getting to know ourselves • Clarify organizational issues and resolve open issues • Introduce and explain background of course outline • Start with meta-theoretical framework 2 Claudius Gräbner & Torsten Heinrich: Complexity Economics. Theory and Comp Methods @ Exploring Economics Summer Academy, Aug 9-16 2019 Intro Claudius Torsten • Studied economics in Dresden and Madrid • Studied „Staatswissenschaften“, i.e. economics, law, and social sciences in Erfurt • PhD and Habilitation in economics in Bremen, Germany • PhD in economics in Bremen, Germany • Now: Post Doc at Oxford University • Several stays in Santa Fe, USA • Institute for New Economic Thinking (INET), • Now: Post Doc at the Johannes Kepler University in Oxford Martin School (OMS) & Wolfson College Linz, Austria & University of Duisburg-Essen, Germany • Main interests: • Main interests: • Complex systems science and agent-based • Economic development, technological change computational economics and -
Simulating Inflation 1
Running head: SIMULATING INFLATION 1 Simulating Inflation: Is the Economy a Big Balloon? Ryan Heathcote A Senior Thesis submitted in partial fulfillment of the requirements for graduation in the Honors Program Liberty University Spring 2013 SIMULATING INFLATION 2 Acceptance of Senior Honors Thesis This Senior Honors Thesis is accepted in partial fulfillment of the requirements for graduation from the Honors Program of Liberty University. ______________________________ Mark Shaneck, Ph.D. Thesis Chair ______________________________ Terry Metzgar, Ph.D. Committee Member ______________________________ Monty Kester, Ph.D. Committee Member ______________________________ James H. Nutter, D.A. Honors Director ______________________________ Date SIMULATING INFLATION 3 Abstract Inflation is a common problem in modern economics, and it seems to persist, requiring government financial policy intervention on a regular basis in order to properly manage. The mechanics of inflation are difficult to understand, since the best metric modern society has for inflation involves taking samples of prices across the country. A simulation can give deeper insight into more than the mere fact that prices rise over time: a simulation can help to answer the “why” question. The problem with this statement is that developing a simulation is not as simple as writing some code. A simulation is developed according to a paradigm, and paradigms are not created equal. Research reveals that traditional paradigms that impose order from the outside do not mimic reality and thus do not give a good degree of accuracy. By contrast, Agent Based Modelling models reality very closely and is consequently able to simulate economic systems much more accurately. SIMULATING INFLATION 4 Simulating Inflation: Is the Economy a Big Balloon? It is often said that life’s two inevitabilities are death and taxes. -
Tipping Points in Macroeconomic Agent-Based Models
Tipping points in macroeconomic Agent-Based models Stanislao Gualdi,1 Marco Tarzia,2 Francesco Zamponi,3 and Jean-Philippe Bouchaud4 1 Universit´ePierre et Marie Curie - Paris 6, Laboratoire de Physique Th´eoriquede la Mati`ere Condens´ee, 4, Place Jussieu, Tour 12, 75252 Paris Cedex 05, France and IRAMIS, CEA-Saclay, 91191 Gif sur Yvette Cedex, France ∗ 2 Universit´ePierre et Marie Curie - Paris 6, Laboratoire de Physique Th´eoriquede la Mati`ere Condens´ee, 4, Place Jussieu, Tour 12, 75252 Paris Cedex 05, France 3Laboratoire de Physique Th´eorique, Ecole´ Normale Sup´erieure, UMR 8549 CNRS, 24 Rue Lhomond, 75231 Paris Cedex 05, France 4CFM, 23 rue de l'Universit´e,75007 Paris, France, and Ecole Polytechnique, 91120 Palaiseau, France. The aim of this work is to explore the possible types of phenomena that simple macroeconomic Agent-Based models (ABM) can reproduce. Our motivation is to understand the large macro- economic fluctuations observed in the \Mark I" ABM devised by D. Delli Gatti and collaborators. Our major finding is the existence of a first order (discontinuous) phase transition between a \good economy" where unemployment is low, and a \bad economy" where unemployment is high. We show that this transition is robust against many modifications of the model, and is induced by an asymmetry between the rate of hiring and the rate of firing of the firms. This asymmetry is induced, in Mark I, by the interest rate. As the interest rate increases, the firms become more and more reluctant to take further loans. The unemployment level remains small until a tipping point beyond which the economy suddenly collapses. -
Enhanced Step-By-Step Approach for the Use of Big Data in Modelling for Official Statistics
Enhanced step-by-step approach for the use of big data in modelling for official statistics Dario Buono1, George Kapetanios2, Massimiliano Marcellino3, Gian Luigi Mazzi4, Fotis Papailias5 Paper prepared for the 16th Conference of IAOS OECD Headquarters, Paris, France, 19-21 September 2018 Session 1.A., Day 1, 19/09, 11:00: Use of Big Data for compiling statistics 1 Eurostat, European Commission. Email: [email protected] 2 King’s College London. Email: [email protected] 3 Bocconi University. Email: [email protected] 4 GOPA. Email: [email protected] 5 King’s College London. Email: [email protected] Dario Buono [email protected], European Commission George Kapetanios [email protected] King’s College London Massimiliano Marcellino [email protected] Bocconi University Gian Luigi Mazzi [email protected] GOPA Fotis Papailias [email protected] King’s College London Enhanced step-by-step approach for the use of big data in modelling for official statistics DRAFT VERSION DD/MM/2018 PLEASE DO NOT CITE (optional) Prepared for the 16th Conference of the International Association of Official Statisticians (IAOS) OECD Headquarters, Paris, France, 19-21 September 2018 Note (optional): This Working Paper should not be reported as representing the views of the Author organisation/s. The views expressed are those of the author(s). ABSTRACT In this paper we describe a step-by-step approach for the use of big data in nowcasting exercises and, possibly, in the construction of high frequency and new indicators. We also provide a set of recommendations associated to each step which are based on the outcome of the other tasks of the project as well as on the outcome of the previous project on big data and macroeconomic nowcasting. -
Dr Martin Kliem
Martin Kliem Deutsche Bundesbank Office Phone: +49-(0)69-9566-4759 Research Centre Mail: [email protected] Wilhelm-Epstein-Straße 14 60431 Frankfurt am Main Germany EDUCATION 05/2005 - 07/2009 Doctorate in Economics at the Humboldt-Universität zu Berlin (Ph.D. equivalent) Advisor: Prof. Harald Uhlig, Ph.D. Thesis: "Essays on Asset Pricing and the Macroeconomy" 10/1998 - 08/2004 Diploma in Business Administration at Humboldt-Universität zu Berlin (M.A. equivalent) 10/1998 - 04/2004 Diploma in Economics at Humboldt-Universität zu Berlin (M.A. equivalent) WORK EXPERIENCE 04/2009 - present Economist, Deutsche Bundesbank, Research Centre 09/2014 - 11/2014 European University Institute, Florence Pierre Werner Fellow at the Robert Schuman Centre of Advanced Studies 05/2005 - 03/2009 Humboldt-Universität zu Berlin Research associate at the Collaborative Research Center 649 "Eco- nomic Risk" 09/2004 - 04/2005 Consultant, J.O.R. FinConsult GmbH, Berlin RESEARCH INTERESTS Macroeconomics, Applied Macroeconometrics, Asset Pricing, Fiscal and Monetary Policy 1 PUBLICATIONS Monetary-fiscal policy interaction and fiscal inflation: a tale of three countries, with Alexan- der Kriwoluzky and Samad Sarferaz, European Economic Review, Vol. 88, 158-184, 2016. On the low-frequency relationship between public deficits and inflation, with Alexander Kri- woluzky and Samad Sarferaz, Journal of Applied Econometrics, Vol. 31(3), 566-583, 2016. Bayesian estimation of a dynamic stochastic general equlibrium model with asset prices, with Harald Uhlig, Quantitative Economcis, Vol. 7(1), 257-287, 2016. Toward a Taylor rule for fiscal policy, with A. Kriwoluzky, Review of Economic Dynamics, Vol. 17(2), 294-302, 2014. Assessing macro-financial linkages: A model comparison exercise, with R. -
Agent-Based Computational Economics Documentation Release 0.9.3B0
Agent-Based Computational Economics Documentation Release 0.9.3b0 Davoud Taghawi-Nejad Jul 24, 2021 Contents 1 Introduction 3 1.1 Design..................................................3 1.2 Download and Installation........................................7 1.3 Interactive jupyter notebook Tutorial..................................9 1.4 Walk through...............................................9 1.5 Tutorial for Plant Modeling....................................... 16 1.6 Examples................................................. 20 1.7 unit testing................................................ 24 2 Simulation Programming 25 2.1 The simulation in start.py........................................ 25 2.2 Agents.................................................. 28 2.3 Groups.................................................. 29 2.4 Physical goods and services....................................... 31 2.5 Trade................................................... 32 2.6 Messaging................................................ 32 2.7 Firm and production........................................... 32 2.8 Household and consumption....................................... 35 2.9 Observing agents and logging...................................... 36 2.10 Retrieval of the simulation results.................................... 37 2.11 NotEnoughGoods Exception....................................... 38 3 Advanced 39 3.1 Quote................................................... 39 3.2 Spatial and Netlogo like Models..................................... 39 -
The Role of Values of Economists and Economic Agents in Economics: a Necessary Distinction Nestor Nieto
The Role of Values of Economists and Economic Agents in Economics: A Necessary Distinction Nestor Nieto To cite this version: Nestor Nieto. The Role of Values of Economists and Economic Agents in Economics: A Necessary Distinction. 2021. hal-02735869v2 HAL Id: hal-02735869 https://hal.archives-ouvertes.fr/hal-02735869v2 Preprint submitted on 28 May 2021 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Copyright The Role of Values of Economists and Economic Agents in Economics: A Necessary Distinction Nestor Lovera Nieto1 Abstract The distinction between the value judgments of economists and those of economic agents is not clear in the literature of welfare economics. In this article, I show that this distinction is important because economists have to step back and consider not only their own value judgments but also those of economic agents when they study economic phenomena. I use the subject of Interpersonal Comparisons of Utility to discuss this distinction, more specifically the analysis of Harsanyi’s impartial observer theorem, which provides a framework to justify that value judgments of economists and those of economic agents have to be properly identified. I suggest that it is essential to have a theoretical framework to make this distinction. -
Agent-Based Macroeconomics
Faculty of Business Administration and Economics Working Papers in Economics and Management No. 02-2018 January 2018 Agent-Based Macroeconomics H. Dawid D. Delli Gatti Bielefeld University P.O. Box 10 01 31 33501 Bielefeld − Germany ISSN 2196−2723 www.wiwi.uni−bielefeld.de Agent-Based Macroeconomics Herbert Dawid∗ Domenico Delli Gatti yz January 2018 This paper has been prepared as a chapter in the Handbook of Computational Economics, Volume IV, edited by Cars Hommes and Blake LeBaron. Abstract This chapter surveys work dedicated to macroeconomic analysis using an agent- based modeling approach. After a short review of the origins and general characteristics of this approach a systemic comparison of the structure and modeling assumptions of a set of important (families of) agent-based macroeconomic models is provided. The comparison highlights substantial similarities between the different models, thereby identifying what could be considered an emerging common core of macroeconomic agent-based modeling. In the second part of the chapter agent-based macroeconomic research in different domains of economic policy is reviewed. Keywords: Agent-based Macroeconomics, Aggregation, Heterogeneity, Behavioral Rules, Business Fluctuations, Economic Policy JEL Classification: C63, E17, E32, E70, 1 Introduction Starting from the early years of the availability of digital computers, the analysis of macroe- conomic phenomena through the simulation of appropriate micro-founded models of the economy has been seen as a promising approach for Economic research. In an article in the American Economic Review in 1959 Herbert Simon argued that "The very complexity that has made a theory of the decision-making process essential has made its construction exceedingly difficult. -
Economy-Wide Modeling: Evaluating the Economic Impacts of Air Regulations
Economy-Wide Modeling: Evaluating the Economic Impacts of Air Regulations DRAFT: June 14, 2016 Prepared for the U.S. EPA Science Advisory Board Panel (SAB) on Economy-Wide Modeling of the Benefits and Costs of Environmental Regulation This paper has been developed to inform the deliberations of the SAB Panel on the technical merits and challenges of economy-wide modeling for an air regulation. It is not an official U.S. Environmental Protection Agency (EPA) report nor does it necessarily represent official policies or views of the U.S. EPA. 1 Table of Contents 1. Introduction .......................................................................................................................................... 4 2. Measuring Economic Impacts and the Role of CGE Modeling at EPA .................................................. 5 3. Quantitative evaluation of economic impacts by EPA ........................................................................ 10 3.1 Regional or State-Implemented Emission Targets ............................................................................ 11 3.2 Other Types of Air Regulations ......................................................................................................... 13 3.2.1 Single Sector Emission Rate Limits ............................................................................................. 14 3.2.2 Multi-Sector Boiler or Engine-Level Emission Limits ................................................................. 15 3.3.3 Federal Product Standards ........................................................................................................ -
Lawrence J. Christiano
1 August, 2016 LAWRENCE J. CHRISTIANO VITA Personal Data Home Address Office Address 2517 Thornwood Department of Economics Wilmette, Illinois 60091 Northwestern University (847) 251-5710 Evanston, Illinois 60208 Citizenship: U.S.A. (847) 491-8231 Education Degree Field Institution Year Ph.D. Economics Columbia University 1982 M.Sc. Econometrics/Mathematical London School of Economics 1977 Economics M.A. Economics University of Minnesota 1975 B.A. History/Economics University of Minnesota 1973 Experience September 1 2002 – present: Alfred W. Chase Chair in Business Institutions, Northwestern University. Summers 1999, 2000, 2001: Visiting Scholar, International Monetary Fund. Summers, 2001 and 2002: Visiting Scholar, European Central Bank. Fall 1999 – present: Short courses on ‘Monetary Economics’ at Stockholm School of Economics, International Monetary Fund, Banca D’Italia, Central Bank of Portugal, Central Bank of Chile, European Central Bank, University of Bonn, New University of Lisbon, Humboldt University, Bocconi University, Massachusetts Institute of Technology, Study Center Gerzensee, Central Bank of Israel, Central Bank of Turkey, European Business Cycle Network, Brazilian Central Bank, Reserve Bank of New Zealand, Swiss National Bank, University of Amsterdam, University of Toronto, American Economic Association, Central Bank of Peru, Central Bank of Colombia, Central 2 Bank of Hungary, Central Bank of Czech Republic, Kiel Institute, Central Bank of Korea, Hanqing Advanced Institution of Economics and Finance, Renmin University of China, Shanghai Advanced Institute of Finance. Summer 1996 – 2007, consultant, Federal Reserve Bank of Cleveland. Fall 2008 - present, consultant, Federal Reserve Bank of Atlanta. July, 1995: consultant, Board of Governors, Federal Reserve System. August 1993, May-June 1998, Summers 1999, 2000, 2001: Visiting Scholar, International Monetary Fund.