Interactions between monetary and macroprudential policies

References

• Adão, L.F.S., Silveira, D., Ely, R.A. and Cajueiro, D.O., The impacts of interest rates on banks' loan portfolio risk-taking. J. Econ. Dyn. Control, 2022, 144, 104521.
   Web of Science ®Google Scholar
• Adrian, T. and Shin, H.S., Financial Intermediaries, Financial Stability, and Monetary Policy. FRB of New York staff report, (346) 2008.
   Google Scholar
• Agénor, P.-R. and Jackson, T.P., Monetary and macroprudential policy coordination with biased preferences. J. Econ. Dyn. Control, 2022, 144, 104519.
   Web of Science ®Google Scholar
• Alexandre, M. and Lima, G.T., Combining monetary policy and prudential regulation: An agent-based modeling approach. J. Econ. Interact. Coord., 2020, 15(2), 385–411.
   Web of Science ®Google Scholar
• Allen, F., Carletti, E. and Gu, X., The roles of banks in financial systems. In The Oxford Handbook of Banking, Second Edition, 2014 (Oxford University Press: Oxford, UK).
   Google Scholar
• Allen, F. and Gale, D., Optimal financial crises. J. Finance, 1998, 53, 1245–1284.
   Web of Science ®Google Scholar
• Allen, F. and Gale, D., Bubbles and crises. Econ. J., 2000a, 110(460), 236–255.
   Web of Science ®Google Scholar
• Allen, F. and Gale, D., Financial contagion. J. Polit. Econ., 2000b, 108, 1–33.
   Web of Science ®Google Scholar
• Angeloni, I., Faia, E. and Duca, M.L., Monetary policy and risk taking. J. Econ. Dyn. Control, 2015, 52, 285–307.
   Web of Science ®Google Scholar
• Bakker, B.B., Dell'Ariccia, G., Laeven, L., Vandenbussche, J., Igan, D. and Tong, H., Policies for Macrofinancial Stability: How to Deal with Credit Booms, 2012 (International Monetary Fund: Washington, DC).
   Google Scholar
• Bardoscia, M., Barucca, P., Battiston, S., Caccioli, F., Cimini, G., Garlaschelli, D., Saracco, F., Squartini, T. and Caldarelli, G., The physics of financial networks. Nat. Rev. Phys., 2021, 3, 490–507.
   Google Scholar
• Barroso, R.V., Lima, J.I.A.V., Lucchetti, A.H. and Cajueiro, D.O., Interbank network and regulation policies: An analysis through agent-based simulations with adaptive learning. J. Netw. Theory Finance, 2016, 2, 53–86.
   Google Scholar
• Battiston, S., Glattfelder, J.B., Garlaschelli, D., Lillo, F. and Caldarelli, G., The structure of financial networks. In Network Science, pp. 131–163, 2010 (Springer: London, UK).
   Google Scholar
• Berardi, S. and Tedeschi, G., From banks' strategies to financial (in)stability. Int. Rev. Econ. Finance, 2017, 47, 255–272.
   Web of Science ®Google Scholar
• Bernanke, B.S. and Gertler, M., Inside the black box: The credit channel of monetary policy transmission. J. Econ. Perspect., 1995, 9(4), 27–48.
   Web of Science ®Google Scholar
• BIS, Basel III: A Global Regulatory Framework for More Resilient Banks and Banking Systems. Technical Report, Basel Committee's, 2011.
   Google Scholar
• BIS, The basel framework. In Bank for International Settlements, Basel Committee on Banking Supervision, 2019 (Bank for International Settlements: Basel, Switzerland).
   Google Scholar
• Boss, M., Elsinger, H., Summer, M. and Thurner, S., Network topology of the interbank market. Quant. Finance, 2004, 4(6), 677–684.
   Web of Science ®Google Scholar
• Boss, M., Summer, M. and Thurner, S., Contagion flow through banking networks. In Computational Science - ICCS 2004, edited by M. Bubak, G.D. van Albada, P.M.A. Sloot, and J. Dongarra, pp. 1070–1077, 2004 (Springer Berlin Heidelberg: Berlin, Heidelberg).
   Google Scholar
• Brini, A., Tedeschi, G. and Tantari, D., Reinforcement learning policy recommendation for interbank network stability. J. Financ. Stab., 2023, 67, 101139.
   Web of Science ®Google Scholar
• Brockmeijer, J., The interaction of monetary and macroprudential policies—background paper, 2012.
   Google Scholar
• Bruno, V., Shim, I. and Song Shin, H., Comparative assessment of macroprudential policies. J. Financ. Stab., 2017, 28, 183–202.
   Web of Science ®Google Scholar
• Cajueiro, D.O., Bastos, S.B., Pereira, C.C. and Andrade, R.F.S., A model of indirect contagion based on a news similarity network. J. Complex Netw., 2021, 9(5), cnab035.
   Web of Science ®Google Scholar
• Cajueiro, D.O. and Tabak, B.M., The role of banks in the Brazilian interbank market: Does bank type matter?. Physica A, 2008, 387, 6825–6836.
   Web of Science ®Google Scholar
• Camerer, C. and Ho, T., Experience weighted attraction learning in normal form games. Econometrica, 1999, 67, 827–874.
   Web of Science ®Google Scholar
• Cerutti, E., Claessens, S. and Laeven, L., The use and effectiveness of macroprudential policies: New evidence. J. Financ. Stab., 2017, 28, 203–224.
   Web of Science ®Google Scholar
• Chemmanur, T.J., Qin, J., Sun, Y., Yu, Q. and Zheng, X., How does greater bank competition affect borrower screening? Evidence from China's WTO entry. J. Corp. Finance, 2020, 65, 101776.
   Web of Science ®Google Scholar
• Claessens, S., An overview of macroprudential policy tools, 2014.
   Google Scholar
• Craig, B. and von Peter, G., Interbank tiering and money center banks. J. Financ. Intermed., 2014, 23(3), 322–347.
   Web of Science ®Google Scholar
• Davis, E.P., Liadze, I. and Piggott, R., Assessing the macroeconomic impact of alternative macroprudential policies. Econ. Model., 2019, 80, 407–428.
   Web of Science ®Google Scholar
• de Moraes, C.O., Montes, G.C. and Antunes, J.A.P., How does capital regulation react to monetary policy? New evidence on the risk-taking channel. Econ. Model., 2016, 56, 177–186.
   Web of Science ®Google Scholar
• Delis, M.D. and Kouretas, G.P., Interest rates and bank risk-taking. J. Bank. Finance, 2011, 35(4), 840–855. Crete Conference 2010: The Future of Universal Banking.
   Web of Science ®Google Scholar
• Dell'Ariccia, G., Laeven, L. and Suarez, G.A., Bank leverage and monetary policy's risk-taking channel: Evidence from the United States. J. Finance, 2017, 72(2), 613–654. doi: 10.1111/jofi.12467
   Web of Science ®Google Scholar
• Ely, R.A., Tabak, B.M. and Teixeira, A.M., The transmission mechanisms of macroprudential policies on bank risk. Econ. Model., 2021, 94, 598–630.
   Web of Science ®Google Scholar
• Fudenberg, D. and Levine, D.K., Theory of Learning in Games, 2018 (MIT Press: MA).
   Google Scholar
• Gabbi, G., Iori, G., Jafarey, S. and Porter, J., Financial regulations and bank credit to the real economy. J. Econ. Dyn. Control, 2015, 50, 117–143. Crises and Complexity.
   Web of Science ®Google Scholar
• Gambacorta, L., Monetary policy and the risk-taking channel. BIS Q. Rev., December 2009.
   Google Scholar
• Gambacorta, L. and Murcia, A., The impact of macroprudential policies in Latin America: An empirical analysis using credit registry data. J. Financ. Intermed., 2020, 42(C), 100828.
   Google Scholar
• Garcia Revelo, J.D. and Levieuge, G., When could macroprudential and monetary policies be in conflict?. J. Bank. Finance, 2022, 139, 106484.
   Web of Science ®Google Scholar
• Garcia Revelo, J.D., Lucotte, Y. and Pradines-Jobet, F., Macroprudential and monetary policies: The need to dance the Tango in harmony. J. Int. Money. Finance, 2020, 108(C), 102156.
   Google Scholar
• Giri, F., Riccetti, L., Russo, A. and Gallegati, M., Monetary policy and large crises in a financial accelerator agent-based model. J. Econ. Behav. Organ., 2019, 157, 42–58.
   Web of Science ®Google Scholar
• Grimm, V., Berger, U., Bastiansen, F., Eliassen, S., Ginot, V., Giske, J., Goss-Custard, J., Grand, T., Heinz, S.K., Huse, G. and Huth, A., A standard protocol for describing individual-based and agent-based models. Ecol. Modell., 2006, 198(1–2), 115–126.
   Web of Science ®Google Scholar
• Grimm, V., Berger, U., DeAngelis, D.L., Polhill, J.G., Giske, J. and Railsback, S.F., The ODD protocol: A review and first update. Ecol. Modell., 2010, 221(23), 2760–2768.
   Web of Science ®Google Scholar
• Grimm, V., Railsback, S.F., Vincenot, C.E., Berger, U., Gallagher, C., DeAngelis, D.L., Edmonds, B., Ge, J., Giske, J., Groeneveld, J. and Johnston, A.S., The ODD protocol for describing agent-based and other simulation models: A second update to improve clarity, replication, and structural realism. J. Artif. Soc. Soc. Simul., 2020, 23(2), 7.
   PubMed Web of Science ®Google Scholar
• Gurgone, A., Iori, G. and Jafarey, S., The effects of interbank networks on efficiency and stability in a macroeconomic agent-based model. J. Econ. Dyn. Control, 2018, 91, 257–288. Special Issue in Honour of Prof. Carl Chiarella.
   Web of Science ®Google Scholar
• Gómez, F., Failed bank takeovers and financial stability. J. Financ. Stab., 2015, 16, 45–58.
   Web of Science ®Google Scholar
• Iori, G., Jafarey, S. and Padilla, F.G., Systemic risk on the interbank market. J. Econ. Behav. Organ., 2006, 61(4), 525–542.
   Web of Science ®Google Scholar
• Iori, G., Mantegna, R.N., Marotta, L., Micciche, S., Porter, J. and Tumminello, M., Networked relationships in the e-MID Interbank market: A trading model with memory. J. Econ. Dyn. Control, 2015, 50, 98–116.
   Web of Science ®Google Scholar
• Iori, G., Renò, R., De Masi, G. and Caldarelli, G., Trading strategies in the Italian interbank market. Physica A, 2007, 376, 467–479.
   Web of Science ®Google Scholar
• Jiménez, G., Ongena, S., Peydró, J.-L. and Saurina, J., Hazardous times for monetary policy: What do twenty-three million bank loans say about the effects of monetary policy on credit risk-taking? Econometrica, 2014, 82(2), 463–505.
   Web of Science ®Google Scholar
• Kashyap, A.K., Stein, J.C., The role of banks in monetary policy: A survey with implications for the European monetary union. Econ. Perspect. Federal Reserve Bank Chic., 1997, 21, 2–18.
   Google Scholar
• Kazil, J., Masad, D. and Crooks, A., Utilizing python for agent-based modeling: The mesa framework. In Social, Cultural, and Behavioral Modeling, edited by R. Thomson, H. Bisgin, C. Dancy, A. Hyder, and M. Hussain, pp. 308–317, 2020 (Springer International Publishing: Cham).
   Google Scholar
• Kim, S. and Mehrotra, A., Effects of monetary and macroprudential policies—Evidence from four inflation targeting economies. J. Money Credit Bank., 2018, 50(5), 967–992.
   Web of Science ®Google Scholar
• Kim, S. and Mehrotra, A., Examining macroprudential policy and its macroeconomic effects—Some new evidence. J. Int. Money Finance, 2022, 128, 102697.
   Web of Science ®Google Scholar
• Krug, S., Lengnick, M. and Wohltmann, H.-W., The impact of Basel III on financial (in)stability: An agent-based credit network approach. Quant. Finance, 2015, 15(12), 1917–1932.
   Web of Science ®Google Scholar
• Lorenčič, E. and Festić, M., The impact of macroprudential policy on financial stability in selected EU countries. Public Sector Econ., 2022, 46(1), 141–170.
   Google Scholar
• Lubis, A., Alexiou, C. and Nellis, J.G., What can we learn from the implementation of monetary and macroprudential policies: A systematic literature review. J. Econ. Surv., 2019, 33(4), 1123–1150.
   Web of Science ®Google Scholar
• Mantegna, R.N., Hierarchical structure in financial markets. Eur. Phys. J. B, 1999, 11, 193–197.
   Web of Science ®Google Scholar
• Moreno, R., Monetary policy transmission and the long-term interest rate in emerging markets. BIS Pap., 2008, 35, 61–80.
   Google Scholar
• Müller, B., Bohn, F., Dreßler, G., Groeneveld, J., Klassert, C., Martin, R., Schlüter, M., Schulze, J., Weise, H. and Schwarz, N., Describing human decisions in agent-based models : ODD + D, an extension of the ODD protoc. Environ. Model. Softw., 2013, 48, 37–48.
   Web of Science ®Google Scholar
• Neuenkirch, M. and Nöckel, M., The risk-taking channel of monetary policy transmission in the euro area. J. Bank. Finance, 2018, 93, 71–91.
   Web of Science ®Google Scholar
• Nier, E., Yang, J., Yorulmazer, T. and Alentorn, A., Network models and financial stability. J. Econ. Dyn. Control, 2007, 31(6), 2033–2060. Tenth Workshop on Economic Heterogeneous Interacting Agents.
   Web of Science ®Google Scholar
• Poledna, S. and Thurner, S., Elimination of systemic risk in financial networks by means of a systemic risk transaction tax. Quant. Finance, 2016, 16, 1599–1613.
   Web of Science ®Google Scholar
• Pouget, S., Adaptive traders and the design of financial markets. J. Finance, 2007, 62, 2835–2863.
   Web of Science ®Google Scholar
• Roth, A.E. and Erev, I., Learning in extensive-form games: Experimental data and simple dynamic models in the intermediate term. Games Econ. Behav., 1995, 8(1), 164–212.
   Web of Science ®Google Scholar
• Rubio, M. and Yao, F., Bank capital, financial stability and Basel regulation in a low interest-rate environment. Int. Rev. Econ. Finance, 2020, 67, 378–392.
   Web of Science ®Google Scholar
• Steinbacher, M., Raddant, M., Karimi, F., Camacho Cuena, E., Alfarano, S., Iori, G. and Lux, T., Advances in the agent-based modeling of economic and social behavior. SN Bus. Econ., 2021, 1(99), 1–24.
   Google Scholar
• Viegas, E., Goto, H., Takayasu, M., Takayasu, H. and Jensen, H.J., Assembling real networks from synthetic and unstructured subsets: The corporate reporting case. Sci. Rep., 2019, 9, 11075.
   PubMed Web of Science ®Google Scholar
• Warusawitharana, M., Research and development, profits, and firm value: A structural estimation. Quant. Econom., 2015, 6(2), 531–565.
   Web of Science ®Google Scholar
• Wolski, M. and van de Leur, M., Interbank loans, collateral and modern monetary policy. J. Econ. Dyn. Control, 2016, 73, 388–416.
   Web of Science ®Google Scholar
• Zanganeh, T., Rastegar, M.A., Chavoshi, K. and Shams, M.F., Systemic risk assessment of the banking system by modeling of the topology of the interbank market network. J. Invest. Knowl., 2020, 9(35), 21–48.
   Google Scholar