[go: up one dir, main page]

IDEAS home Printed from https://ideas.repec.org/p/zbw/cauewp/202101.html
   My bibliography  Save this paper

Estimation of Heuristic Switching in Behavioral Macroeconomic Models

Author

Listed:
  • Kukacka, Jiri
  • Sacht, Stephen
Abstract
This paper offers a simulation-based method for the estimation of heuristic switching in nonlinear macroeconomic models. Heuristic switching is an important feature of modeling strategy since it uses simple decision rules of boundedly rational heterogeneous agents. The simulation study shows that the proposed simulated maximum likelihood method identifies the behavioral effects that stay hidden for standard econometric approaches. In the empirical application, we estimate the structural and behavioral parameters of the US economy. We are especially able to reliably identify the intensity of choice that governs the models' nonlinear dynamics.

Suggested Citation

  • Kukacka, Jiri & Sacht, Stephen, 2021. "Estimation of Heuristic Switching in Behavioral Macroeconomic Models," Economics Working Papers 2021-01, Christian-Albrechts-University of Kiel, Department of Economics.
  • Handle: RePEc:zbw:cauewp:202101
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/231265/1/1748724886.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. repec:hal:spmain:info:hdl:2441/4pa18fd9lf9h59m4vfavfcf61e is not listed on IDEAS
    2. Lamperti, Francesco & Roventini, Andrea & Sani, Amir, 2018. "Agent-based model calibration using machine learning surrogates," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 366-389.
    3. George-Marios Angeletos & Chen Lian, 2018. "Forward Guidance without Common Knowledge," American Economic Review, American Economic Association, vol. 108(9), pages 2477-2512, September.
    4. Mariano Kulish & Adrian Pagan, 2017. "Estimation and Solution of Models with Expectations and Structural Changes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 255-274, March.
    5. Franke, Reiner & Jang, Tae-Seok & Sacht, Stephen, 2015. "Moment matching versus Bayesian estimation: Backward-looking behaviour in a New-Keynesian baseline model," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 126-154.
    6. Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez, 2007. "Estimating Macroeconomic Models: A Likelihood Approach," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 74(4), pages 1059-1087.
    7. Hommes, Cars & Massaro, Domenico & Weber, Matthias, 2019. "Monetary policy under behavioral expectations: Theory and experiment," European Economic Review, Elsevier, vol. 118(C), pages 193-212.
    8. Evans, George W. & Honkapohja, Seppo, 1996. "Least squares learning with heterogeneous expectations," Economics Letters, Elsevier, vol. 53(2), pages 197-201, November.
    9. Michael Woodford, 2019. "Monetary Policy Analysis When Planning Horizons Are Finite," NBER Macroeconomics Annual, University of Chicago Press, vol. 33(1), pages 1-50.
    10. Bertrand Munier & Reinhard Selten & D. Bouyssou & P. P. Bourgine & R. Day & N. Harvey & D. Hilton & M. Machina & Ph. Parker & J. Sterman & E. Weber & B. Wernerfelt & R. Wensley, 1999. "Bounded rationality modeling," Post-Print hal-02361947, HAL.
    11. Roberto Dieci & Xue-Zhong He, 2018. "Heterogeneous Agent Models in Finance," Research Paper Series 389, Quantitative Finance Research Centre, University of Technology, Sydney.
    12. Kristensen, Dennis & Shin, Yongseok, 2012. "Estimation of dynamic models with nonparametric simulated maximum likelihood," Journal of Econometrics, Elsevier, vol. 167(1), pages 76-94.
    13. Blix, Mårten, 1999. "Forecasting Swedish Inflation With a Markov Switching VAR," Working Paper Series 76, Sveriges Riksbank (Central Bank of Sweden).
    14. Paul De Grauwe, 2014. "Booms and Busts in Economic Activity: A Behavioral Explanation," World Scientific Book Chapters, in: Exchange Rates and Global Financial Policies, chapter 19, pages 521-556, World Scientific Publishing Co. Pte. Ltd..
    15. Olivier Coibion & Yuriy Gorodnichenko, 2012. "What Can Survey Forecasts Tell Us about Information Rigidities?," Journal of Political Economy, University of Chicago Press, vol. 120(1), pages 116-159.
    16. Sylvain Barde & Sander van Der Hoog, 2017. "An empirical validation protocol for large-scale agent-based models," Working Papers hal-03458672, HAL.
    17. Richard Clarida & Jordi Galí & Mark Gertler, 2000. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 115(1), pages 147-180.
    18. Gaunersdorfer, Andrea & Hommes, Cars H. & Wagener, Florian O.O., 2008. "Bifurcation routes to volatility clustering under evolutionary learning," Journal of Economic Behavior & Organization, Elsevier, vol. 67(1), pages 27-47, July.
    19. Assenza, T. & Heemeijer, P. & Hommes, C.H. & Massaro, D., 2021. "Managing self-organization of expectations through monetary policy: A macro experiment," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 170-186.
    20. Kristensen, Dennis, 2009. "Uniform Convergence Rates Of Kernel Estimators With Heterogeneous Dependent Data," Econometric Theory, Cambridge University Press, vol. 25(5), pages 1433-1445, October.
    21. Michael Creel, 2008. "Estimation of Dynamic Latent Variable Models Using Simulated Nonparametric Moments," UFAE and IAE Working Papers 725.08, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC), revised 02 Jun 2008.
    22. Thomas A. Lubik & Frank Schorfheide, 2004. "Testing for Indeterminacy: An Application to U.S. Monetary Policy," American Economic Review, American Economic Association, vol. 94(1), pages 190-217, March.
    23. Torben G. Andersen & Luca Benzoni & Jesper Lund, 2002. "An Empirical Investigation of Continuous‐Time Equity Return Models," Journal of Finance, American Finance Association, vol. 57(3), pages 1239-1284, June.
    24. V. V Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2002. "Can Sticky Price Models Generate Volatile and Persistent Real Exchange Rates?," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 69(3), pages 533-563.
    25. Jang, Tae-Seok & Sacht, Stephen, 2021. "Forecast heuristics, consumer expectations, and New-Keynesian macroeconomics: A Horse race," Journal of Economic Behavior & Organization, Elsevier, vol. 182(C), pages 493-511.
    26. Giorgio Fagiolo & Mattia Guerini & Francesco Lamperti & Alessio Moneta & Andrea Roventini, 2017. "Validation of Agent-Based Models in Economics and Finance," LEM Papers Series 2017/23, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    27. Andrea Gaunersdorfer & Cars Hommes, 2007. "A Nonlinear Structural Model for Volatility Clustering," Springer Books, in: Gilles Teyssière & Alan P. Kirman (ed.), Long Memory in Economics, pages 265-288, Springer.
    28. De Grauwe, Paul & Ji, Yuemei, 2020. "Structural reforms, animal spirits, and monetary policies," European Economic Review, Elsevier, vol. 124(C).
    29. Tiziana Assenza & Te Bao & Cars Hommes & Domenico Massaro, 2014. "Experiments on Expectations in Macroeconomics and Finance," Research in Experimental Economics, in: Experiments in Macroeconomics, volume 17, pages 11-70, Emerald Group Publishing Limited.
    30. John C. Cox & Jonathan E. Ingersoll Jr. & Stephen A. Ross, 2005. "A Theory Of The Term Structure Of Interest Rates," World Scientific Book Chapters, in: Sudipto Bhattacharya & George M Constantinides (ed.), Theory Of Valuation, chapter 5, pages 129-164, World Scientific Publishing Co. Pte. Ltd..
    31. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
    32. Grazzini, Jakob & Richiardi, Matteo G. & Tsionas, Mike, 2017. "Bayesian estimation of agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 77(C), pages 26-47.
    33. Boswijk, H. Peter & Hommes, Cars H. & Manzan, Sebastiano, 2007. "Behavioral heterogeneity in stock prices," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 1938-1970, June.
    34. Anufriev, Mikhail & Chernulich, Aleksei & Tuinstra, Jan, 2018. "A laboratory experiment on the heuristic switching model," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 21-42.
    35. Frank Schorfheide, 2008. "DSGE model-based estimation of the New Keynesian Phillips curve," Economic Quarterly, Federal Reserve Bank of Richmond, vol. 94(Fall), pages 397-433.
    36. Andrew G. Haldane & Vasileios Madouros, 2012. "The dog and the frisbee," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 109-159.
    37. Assenza, T. & Heemeijer, P. & Hommes, C.H. & Massaro, D., 2011. "Individual Expectations and Aggregate Macro Behavior," CeNDEF Working Papers 11-01, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    38. Jesús Fernández-Villaverde & Pablo A. Guerrón-Quintana, 2021. "Estimating DSGE Models: Recent Advances and Future Challenges," Annual Review of Economics, Annual Reviews, vol. 13(1), pages 229-252, August.
    39. Hommes,Cars, 2015. "Behavioral Rationality and Heterogeneous Expectations in Complex Economic Systems," Cambridge Books, Cambridge University Press, number 9781107564978, September.
    40. Sylvain Barde, 2017. "A Practical, Accurate, Information Criterion for Nth Order Markov Processes," Computational Economics, Springer;Society for Computational Economics, vol. 50(2), pages 281-324, August.
    41. Kukacka, Jiri & Barunik, Jozef, 2017. "Estimation of financial agent-based models with simulated maximum likelihood," Journal of Economic Dynamics and Control, Elsevier, vol. 85(C), pages 21-45.
    42. Steffen Ahrens & Stephen Sacht, 2014. "Estimating a high-frequency New-Keynesian Phillips curve," Empirical Economics, Springer, vol. 46(2), pages 607-628, March.
    43. Mikhail Anufriev & Cars Hommes & Tomasz Makarewicz, 2019. "Simple Forecasting Heuristics that Make us Smart: Evidence from Different Market Experiments," Journal of the European Economic Association, European Economic Association, vol. 17(5), pages 1538-1584.
    44. Adriana Cornea-Madeira & Cars Hommes & Domenico Massaro, 2019. "Behavioral Heterogeneity in U.S. Inflation Dynamics," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(2), pages 288-300, April.
    45. Michael Creel & Dennis Kristensen, 2012. "Estimation of dynamic latent variable models using simulated non‐parametric moments," Econometrics Journal, Royal Economic Society, vol. 15(3), pages 490-515, October.
    46. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    47. Barde, Sylvain, 2020. "Macroeconomic simulation comparison with a multivariate extension of the Markov information criterion," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    48. Adam Check & Jeremy Piger, 2021. "Structural Breaks in U.S. Macroeconomic Time Series: A Bayesian Model Averaging Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 53(8), pages 1999-2036, December.
    49. Paul Grauwe, 2011. "Animal spirits and monetary policy," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 47(2), pages 423-457, June.
    50. George William Evans, 2001. "Expectations in Macroeconomics Adaptive versus Eductive Learning," Revue économique, Presses de Sciences-Po, vol. 52(3), pages 573-582.
    51. Del Negro, Marco & Schorfheide, Frank & Smets, Frank & Wouters, Rafael, 2007. "On the Fit of New Keynesian Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 123-143, April.
    52. repec:hal:spmain:info:hdl:2441/13thfd12aa8rmplfudlgvgahff is not listed on IDEAS
    53. Cars Hommes & Tomasz Makarewicz & Domenico Massaro & Tom Smits, 2017. "Genetic algorithm learning in a New Keynesian macroeconomic setup," Journal of Evolutionary Economics, Springer, vol. 27(5), pages 1133-1155, November.
    54. Lux, Thomas, 2018. "Estimation of agent-based models using sequential Monte Carlo methods," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 391-408.
    55. Kohlscheen, Emanuel & Moessner, Richhild, 2022. "Globalisation and the slope of the Phillips curve," Economics Letters, Elsevier, vol. 216(C).
    56. Olivier Coibion & Yuriy Gorodnichenko, 2015. "Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts," American Economic Review, American Economic Association, vol. 105(8), pages 2644-2678, August.
    57. Özge Dilaver & Robert Calvert Jump & Paul Levine, 2018. "Agent‐Based Macroeconomics And Dynamic Stochastic General Equilibrium Models: Where Do We Go From Here?," Journal of Economic Surveys, Wiley Blackwell, vol. 32(4), pages 1134-1159, September.
    58. repec:hal:spmain:info:hdl:2441/5fafm6me7k8omq5jbo61urqq27 is not listed on IDEAS
    59. Liu, Chunping & Minford, Patrick, 2014. "Comparing behavioural and rational expectations for the US post-war economy," Economic Modelling, Elsevier, vol. 43(C), pages 407-415.
    60. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
    61. Cars Hommes & Joep Sonnemans & Jan Tuinstra & Henk van de Velden, 2005. "Coordination of Expectations in Asset Pricing Experiments," The Review of Financial Studies, Society for Financial Studies, vol. 18(3), pages 955-980.
    62. Cars Hommes, 2021. "Behavioral and Experimental Macroeconomics and Policy Analysis: A Complex Systems Approach," Journal of Economic Literature, American Economic Association, vol. 59(1), pages 149-219, March.
    63. Vandin, Andrea & Giachini, Daniele & Lamperti, Francesco & Chiaromonte, Francesca, 2022. "Automated and distributed statistical analysis of economic agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    64. Sylvain Barde, 2022. "Bayesian Estimation of Large-Scale Simulation Models with Gaussian Process Regression Surrogates," Studies in Economics 2203, School of Economics, University of Kent.
    65. Anufriev, Mikhail & Bao, Te & Tuinstra, Jan, 2016. "Microfoundations for switching behavior in heterogeneous agent models: An experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 129(C), pages 74-99.
    66. Moons, Cindy & Garretsen, Harry & van Aarle, Bas & Fornero, Jorge, 2007. "Monetary policy in the New-Keynesian model: An application to the Euro Area," Journal of Policy Modeling, Elsevier, vol. 29(6), pages 879-902.
    67. Guerini, Mattia & Moneta, Alessio, 2017. "A method for agent-based models validation," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 125-141.
    68. Hommes, Cars H., 2006. "Heterogeneous Agent Models in Economics and Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 23, pages 1109-1186, Elsevier.
    69. Jang, Tae-Seok, 2012. "Structural estimation of the New-Keynesian Model: a formal test of backward- and forward-looking expectations," MPRA Paper 39669, University Library of Munich, Germany.
    70. Farmer, J. Doyne & Dyer, Joel & Cannon, Patrick & Schmon, Sebastian, 2022. "Black-box Bayesian inference for economic agent-based models," INET Oxford Working Papers 2022-05, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    71. Fabio Milani, 2011. "Expectation Shocks and Learning as Drivers of the Business Cycle," Economic Journal, Royal Economic Society, vol. 121(552), pages 379-401, May.
    72. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
    73. Mikhail Anufriev & Cars Hommes, 2012. "Evolutionary Selection of Individual Expectations and Aggregate Outcomes in Asset Pricing Experiments," American Economic Journal: Microeconomics, American Economic Association, vol. 4(4), pages 35-64, November.
    74. Frank Kleibergen & Sophocles Mavroeidis, 2014. "Identification Issues In Limited‐Information Bayesian Analysis Of Structural Macroeconomic Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(7), pages 1183-1209, November.
    75. Jang, Tae-Seok, 2012. "Structural estimation of the New-Keynesian Model: a formal test of backward- and forward-looking expectations," MPRA Paper 40278, University Library of Munich, Germany.
    76. Paul De Grauwe, 2010. "Top-Down versus Bottom-Up Macroeconomics," CESifo Economic Studies, CESifo Group, vol. 56(4), pages 465-497, December.
    77. Fernández-Villaverde, J. & Rubio-Ramírez, J.F. & Schorfheide, F., 2016. "Solution and Estimation Methods for DSGE Models," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 527-724, Elsevier.
    78. Szabolcs Deák & Paul Levine & Joseph Pearlman & Bo Yang, 2017. "Internal Rationality, Learning and Imperfect Information," School of Economics Discussion Papers 0817, School of Economics, University of Surrey.
    79. William A. Brock & Cars H. Hommes, 2001. "A Rational Route to Randomness," Chapters, in: W. D. Dechert (ed.), Growth Theory, Nonlinear Dynamics and Economic Modelling, chapter 16, pages 402-438, Edward Elgar Publishing.
    80. Mario Martinoli & Alessio Moneta & Gianluca Pallante, 2022. "Calibration and Validation of Macroeconomic Simulation Models by Statistical Causal Search," LEM Papers Series 2022/33, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    81. Gavin Goy & Cars Homme & Kostas Mavromatis, 2018. "Forward Guidance and the Role of Central Bank Credibility," DNB Working Papers 614, Netherlands Central Bank, Research Department.
    82. Lee, Donghoon & Song, Kyungchul, 2015. "Simulated maximum likelihood estimation for discrete choices using transformed simulated frequencies," Journal of Econometrics, Elsevier, vol. 187(1), pages 131-153.
    83. Hommes, Cars & Sonnemans, Joep & Tuinstra, Jan & van de Velden, Henk, 2008. "Expectations and bubbles in asset pricing experiments," Journal of Economic Behavior & Organization, Elsevier, vol. 67(1), pages 116-133, July.
    84. Anindya S. Chakrabarti & Lukáš Pichl & Taisei Kaizoji (ed.), 2019. "Network Theory and Agent-Based Modeling in Economics and Finance," Springer Books, Springer, number 978-981-13-8319-9, January.
    85. Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 2, number 2.
    86. Grazzini, Jakob & Richiardi, Matteo, 2015. "Estimation of ergodic agent-based models by simulated minimum distance," Journal of Economic Dynamics and Control, Elsevier, vol. 51(C), pages 148-165.
    87. Francesco Lamperti, 2018. "Empirical validation of simulated models through the GSL-div: an illustrative application," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(1), pages 143-171, April.
    88. Tae-Seok Jang & Stephen Sacht, 2016. "Animal Spirits and the Business Cycle: Empirical Evidence from Moment Matching," Metroeconomica, Wiley Blackwell, vol. 67(1), pages 76-113, February.
    89. Eo Yunjong, 2016. "Structural changes in inflation dynamics: multiple breaks at different dates for different parameters," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(3), pages 211-231, June.
    90. Franke, Reiner & Westerhoff, Frank, 2012. "Structural stochastic volatility in asset pricing dynamics: Estimation and model contest," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1193-1211.
    91. Linde, Jesper, 2005. "Estimating New-Keynesian Phillips curves: A full information maximum likelihood approach," Journal of Monetary Economics, Elsevier, vol. 52(6), pages 1135-1149, September.
    92. Tae-Seok Jang, 2012. "Structural Estimation of the New-Keynesian Model: A Formal Test of Backward- and Forward-Looking Behavior," Advances in Econometrics, in: DSGE Models in Macroeconomics: Estimation, Evaluation, and New Developments, pages 421-467, Emerald Group Publishing Limited.
    93. Filippo Altissimo & Antonio Mele, 2009. "Simulated Non-Parametric Estimation of Dynamic Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(2), pages 413-450.
    94. Roberto Veneziani & Luca Zamparelli & Reiner Franke & Frank Westerhoff, 2017. "Taking Stock: A Rigorous Modelling Of Animal Spirits In Macroeconomics," Journal of Economic Surveys, Wiley Blackwell, vol. 31(5), pages 1152-1182, December.
    95. James M. Nason & Gregor W. Smith, 2008. "The New Keynesian Phillips curve : lessons from single-equation econometric estimation," Economic Quarterly, Federal Reserve Bank of Richmond, vol. 94(Fall), pages 361-395.
    96. David Hendry & Grayham E. Mizon, 2010. "On the Mathematical Basis of Inter-temporal Optimization," Economics Series Working Papers 497, University of Oxford, Department of Economics.
    97. Edward Herbst & Frank Schorfheide, 2014. "Sequential Monte Carlo Sampling For Dsge Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(7), pages 1073-1098, November.
    98. Jang, Tae-Seok, 2012. "Structural estimation of the New-Keynesian model: A formal test of backward- and forward-looking behavior," Economics Working Papers 2012-07, Christian-Albrechts-University of Kiel, Department of Economics.
    99. Lamperti, Francesco, 2018. "An information theoretic criterion for empirical validation of simulation models," Econometrics and Statistics, Elsevier, vol. 5(C), pages 83-106.
    100. Tolga Özden, 2021. "Heterogeneous Expectations and the Business Cycle at the Effective Lower Bound," Working Papers 714, DNB.
    101. A. Doucet & M. K. Pitt & G. Deligiannidis & R. Kohn, 2015. "Efficient implementation of Markov chain Monte Carlo when using an unbiased likelihood estimator," Biometrika, Biometrika Trust, vol. 102(2), pages 295-313.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhang, Jinyu & Zhang, Qiaosen & Li, Yong & Wang, Qianchao, 2023. "Sequential Bayesian inference for agent-based models with application to the Chinese business cycle," Economic Modelling, Elsevier, vol. 126(C).
    2. Lux, Thomas, 2024. "Lack of identification of parameters in a simple behavioral macroeconomic model," Economics Working Papers 2024-02, Christian-Albrechts-University of Kiel, Department of Economics.
    3. Proaño, Christian R. & Kukacka, Jiri & Makarewicz, Tomasz, 2024. "Belief-driven dynamics in a behavioral SEIRD macroeconomic model with sceptics," Journal of Economic Behavior & Organization, Elsevier, vol. 217(C), pages 312-333.

    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. Kukacka, Jiri & Jang, Tae-Seok & Sacht, Stephen, 2018. "On the estimation of behavioral macroeconomic models via simulated maximum likelihood," Economics Working Papers 2018-11, Christian-Albrechts-University of Kiel, Department of Economics.
    2. Giorgio Fagiolo & Mattia Guerini & Francesco Lamperti & Alessio Moneta & Andrea Roventini, 2017. "Validation of Agent-Based Models in Economics and Finance," LEM Papers Series 2017/23, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    3. Kukacka, Jiri & Barunik, Jozef, 2017. "Estimation of financial agent-based models with simulated maximum likelihood," Journal of Economic Dynamics and Control, Elsevier, vol. 85(C), pages 21-45.
    4. Kukacka, Jiri & Kristoufek, Ladislav, 2021. "Does parameterization affect the complexity of agent-based models?," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 324-356.
    5. Hommes, Cars, 2018. "Behavioral & experimental macroeconomics and policy analysis: a complex systems approach," Working Paper Series 2201, European Central Bank.
    6. Bao, Te & Hommes, Cars & Pei, Jiaoying, 2021. "Expectation formation in finance and macroeconomics: A review of new experimental evidence," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).
    7. Galanis, Giorgos & Kollias, Iraklis & Leventidis, Ioanis & Lustenhouwer, Joep, 2022. "Generalizing Heuristic Switching Models," Working Papers 0715, University of Heidelberg, Department of Economics.
    8. Giovanni Dosi & Andrea Roventini, 2019. "More is different ... and complex! the case for agent-based macroeconomics," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 1-37, March.
    9. Lamperti, Francesco & Roventini, Andrea & Sani, Amir, 2018. "Agent-based model calibration using machine learning surrogates," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 366-389.
    10. 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.
    11. Galanis, Giorgos & Kollias, Iraklis & Leventidis, Ioanis & Lustenhouwer, Joep, 2022. "Generalizing Heterogeneous Dynamic Heuristic Selection," CRETA Online Discussion Paper Series 73, Centre for Research in Economic Theory and its Applications CRETA.
    12. Donovan Platt, 2022. "Bayesian Estimation of Economic Simulation Models Using Neural Networks," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 599-650, February.
    13. Platt, Donovan, 2020. "A comparison of economic agent-based model calibration methods," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    14. Zila, Eric & Kukacka, Jiri, 2023. "Moment set selection for the SMM using simple machine learning," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 366-391.
    15. Mauersberger, Felix, 2021. "Monetary policy rules in a non-rational world: A macroeconomic experiment," Journal of Economic Theory, Elsevier, vol. 197(C).
    16. Lamperti, Francesco & Roventini, Andrea & Sani, Amir, 2018. "Agent-based model calibration using machine learning surrogates," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 366-389.
    17. Tae-Seok Jang & Stephen Sacht, 2016. "Animal Spirits and the Business Cycle: Empirical Evidence from Moment Matching," Metroeconomica, Wiley Blackwell, vol. 67(1), pages 76-113, February.
    18. repec:hal:spmain:info:hdl:2441/13thfd12aa8rmplfudlgvgahff is not listed on IDEAS
    19. Barde, Sylvain, 2020. "Macroeconomic simulation comparison with a multivariate extension of the Markov information criterion," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    20. Hommes, Cars, 2011. "The heterogeneous expectations hypothesis: Some evidence from the lab," Journal of Economic Dynamics and Control, Elsevier, vol. 35(1), pages 1-24, January.
    21. Anufriev, Mikhail & Bao, Te & Tuinstra, Jan, 2016. "Microfoundations for switching behavior in heterogeneous agent models: An experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 129(C), pages 74-99.

    More about this item

    Keywords

    Behavioral Heuristics; Heuristic Switching Model; Intensity of Choice; Simulated Maximum Likelihood;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • E12 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Keynes; Keynesian; Post-Keynesian; Modern Monetary Theory
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

    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:zbw:cauewp:202101. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/vakiede.html .

    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.