IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2402.09563.html
   My bibliography  Save this paper

ABIDES-Economist: Agent-Based Simulation of Economic Systems with Learning Agents

Author

Listed:
  • Kshama Dwarakanath
  • Svitlana Vyetrenko
  • Peyman Tavallali
  • Tucker Balch

Abstract

We introduce a multi-agent simulator for economic systems comprised of heterogeneous Households, heterogeneous Firms, Central Bank and Government agents, that could be subjected to exogenous, stochastic shocks. The interaction between agents defines the production and consumption of goods in the economy alongside the flow of money. Each agent can be designed to act according to fixed, rule-based strategies or learn their strategies using interactions with others in the simulator. We ground our simulator by choosing agent heterogeneity parameters based on economic literature, while designing their action spaces in accordance with real data in the United States. Our simulator facilitates the use of reinforcement learning strategies for the agents via an OpenAI Gym style environment definition for the economic system. We demonstrate the utility of our simulator by simulating and analyzing two hypothetical (yet interesting) economic scenarios. The first scenario investigates the impact of heterogeneous household skills on their learned preferences to work at different firms. The second scenario examines the impact of a positive production shock to one of two firms on its pricing strategy in comparison to the second firm. We aspire that our platform sets a stage for subsequent research at the intersection of artificial intelligence and economics.

Suggested Citation

  • Kshama Dwarakanath & Svitlana Vyetrenko & Peyman Tavallali & Tucker Balch, 2024. "ABIDES-Economist: Agent-Based Simulation of Economic Systems with Learning Agents," Papers 2402.09563, arXiv.org.
    • Handle: RePEc:arx:papers:2402.09563
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2402.09563
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. George W. Evans & Seppo Honkapohja, 2005. "Policy Interaction, Expectations and the Liquidity Trap," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 303-323, April.
    2. Greg Kaplan & Benjamin Moll & Giovanni L. Violante, 2018. "Monetary Policy According to HANK," American Economic Review, American Economic Association, vol. 108(3), pages 697-743, March.
    3. Frank Smets & Rafael Wouters, 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach," American Economic Review, American Economic Association, vol. 97(3), pages 586-606, June.
    4. Marco Del Negro & Marc P. Giannoni & Frank Schorfheide, 2015. "Inflation in the Great Recession and New Keynesian Models," American Economic Journal: Macroeconomics, American Economic Association, vol. 7(1), pages 168-196, January.
    5. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2005. "Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 1-45, February.
    6. Adler, Jeffrey L. & Satapathy, Goutam & Manikonda, Vikram & Bowles, Betty & Blue, Victor J., 2005. "A multi-agent approach to cooperative traffic management and route guidance," Transportation Research Part B: Methodological, Elsevier, vol. 39(4), pages 297-318, May.
    7. Andrew G. Haldane & Arthur E. Turrell, 2019. "Drawing on different disciplines: macroeconomic agent-based models," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 39-66, March.
    8. Per Krusell & Anthony A. Smith & Jr., 1998. "Income and Wealth Heterogeneity in the Macroeconomy," Journal of Political Economy, University of Chicago Press, vol. 106(5), pages 867-896, October.
    9. Joseph E Stiglitz, 2018. "Where modern macroeconomics went wrong," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 34(1-2), pages 70-106.
    10. Hinterlang, Natascha & Tänzer, Alina, 2021. "Optimal monetary policy using reinforcement learning," Discussion Papers 51/2021, Deutsche Bundesbank.
    11. Michael Curry & Alexander Trott & Soham Phade & Yu Bai & Stephan Zheng, 2022. "Analyzing Micro-Founded General Equilibrium Models with Many Agents using Deep Reinforcement Learning," Papers 2201.01163, arXiv.org, revised Feb 2022.
    12. Nikolsko-Rzhevskyy, Alex & Papell, David H. & Prodan, Ruxandra, 2021. "Policy Rules and Economic Performance," Journal of Macroeconomics, Elsevier, vol. 68(C).
    13. J. Doyne Farmer & Duncan Foley, 2009. "The economy needs agent-based modelling," Nature, Nature, vol. 460(7256), pages 685-686, August.
    14. Marlon Azinovic & Luca Gaegauf & Simon Scheidegger, 2022. "Deep Equilibrium Nets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(4), pages 1471-1525, November.
    15. Michael Woodford, 2009. "Convergence in Macroeconomics: Elements of the New Synthesis," American Economic Journal: Macroeconomics, American Economic Association, vol. 1(1), pages 267-279, January.
    16. Hildenbrand, Werner, 1983. "On the "Law of Demand."," Econometrica, Econometric Society, vol. 51(4), pages 997-1019, July.
    17. Edward Hill & Marco Bardoscia & Arthur Turrell, 2021. "Solving Heterogeneous General Equilibrium Economic Models with Deep Reinforcement Learning," Papers 2103.16977, arXiv.org.
    18. Maliar, Lilia & Maliar, Serguei & Winant, Pablo, 2021. "Deep learning for solving dynamic economic models," Journal of Monetary Economics, Elsevier, vol. 122(C), pages 76-101.
    19. Callum Rhys Tilbury, 2022. "Reinforcement Learning for Economic Policy: A New Frontier?," Papers 2206.08781, arXiv.org, revised Feb 2023.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jialin Dong & Kshama Dwarakanath & Svitlana Vyetrenko, 2023. "Analyzing the Impact of Tax Credits on Households in Simulated Economic Systems with Learning Agents," Papers 2311.17252, arXiv.org.
    2. Adem Feto & M. K. Jayamohan & Arnis Vilks, 2023. "Applicability and Accomplishments of DSGE Modeling: A Critical Review," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(2), pages 213-239, September.
    3. Fernández-Villaverde, Jesús & Marbet, Joël & Nuño, Galo & Rachedi, Omar, 2023. "Inequality and the Zero Lower Bound," CEPR Discussion Papers 18168, C.E.P.R. Discussion Papers.
    4. repec:zbw:bofrdp:2018_022 is not listed on IDEAS
    5. Ciccarelli, Matteo & Darracq Pariès, Matthieu & Priftis, Romanos & Angelini, Elena & Bańbura, Marta & Bokan, Nikola & Fagan, Gabriel & Gumiel, José Emilio & Kornprobst, Antoine & Lalik, Magdalena & Mo, 2024. "ECB macroeconometric models for forecasting and policy analysis," Occasional Paper Series 344, European Central Bank.
    6. Gulan, Adam, 2018. "Paradise lost? A brief history of DSGE macroeconomics," Research Discussion Papers 22/2018, Bank of Finland.
    7. Thomas J. Sargent & John Stachurski, 2024. "Dynamic Programming: Finite States," Papers 2401.10473, arXiv.org.
    8. Poledna, Sebastian & Miess, Michael Gregor & Hommes, Cars & Rabitsch, Katrin, 2023. "Economic forecasting with an agent-based model," European Economic Review, Elsevier, vol. 151(C).
    9. Gregor Boehl & Gavin Goy & Felix Strobel, 2020. "A Structural Investigation of Quantitative Easing," CRC TR 224 Discussion Paper Series crctr224_2020_193, University of Bonn and University of Mannheim, Germany.
    10. Nils M. Gornemann & Keith Kuester & Makoto Nakajima, 2021. "Doves for the Rich, Hawks for the Poor? Distributional Consequences of Systematic Monetary Policy," Opportunity and Inclusive Growth Institute Working Papers 50, Federal Reserve Bank of Minneapolis.
    11. Giovanni Dosi & Mauro Napoletano & Andrea Roventini & Joseph E. Stiglitz & Tania Treibich, 2020. "Rational Heuristics? Expectations And Behaviors In Evolving Economies With Heterogeneous Interacting Agents," Economic Inquiry, Western Economic Association International, vol. 58(3), pages 1487-1516, July.
    12. Lawrence J. Christiano & Martin S. Eichenbaum & Mathias Trabandt, 2018. "On DSGE Models," Journal of Economic Perspectives, American Economic Association, vol. 32(3), pages 113-140, Summer.
    13. Senbeta, Sisay, 2011. "How applicable are the new keynesian DSGE models to a typical low-income economy?," MPRA Paper 30931, University Library of Munich, Germany.
    14. Emmet Hall-Hoffarth, 2023. "Non-linear approximations of DSGE models with neural-networks and hard-constraints," Papers 2310.13436, arXiv.org.
    15. Böhl, Gregor & Strobel, Felix, 2020. "US business cycle dynamics at the zero lower bound," IMFS Working Paper Series 143, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    16. Lemoine, Matthieu & Lindé, Jesper, 2023. "Fiscal stimulus in liquidity traps: Conventional or unconventional policies?," European Economic Review, Elsevier, vol. 151(C).
    17. Min Fang, 2021. "Lumpy Investment, Fluctuations in Volatility and Monetary Policy," Working Papers 002001, University of Florida, Department of Economics.
    18. Hikaru Saijo, 2018. "Redistribution and Fiscal Uncertainty Shocks," IMES Discussion Paper Series 18-E-15, Institute for Monetary and Economic Studies, Bank of Japan.
    19. Michał Brzoza-Brzezina & Jacek Suda, 2021. "Are DSGE models irreparably flawed?," Bank i Kredyt, Narodowy Bank Polski, vol. 52(3), pages 227-252.
    20. repec:hal:spmain:info:hdl:2441/31dhti786q9k0q2i04klh6no54 is not listed on IDEAS
    21. Gulan, Adam, 2018. "Paradise lost? A brief history of DSGE macroeconomics," Bank of Finland Research Discussion Papers 22/2018, Bank of Finland.
    22. Jesper Lindé, 2018. "DSGE models: still useful in policy analysis?," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 34(1-2), pages 269-286.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2402.09563. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.