Ricardian Business Cycles

Lorenzo Bretscher, Jesus Fernandez-Villaverde and Simon Scheidegger
Additional contact information
Lorenzo Bretscher: University of Lausanne; Swiss Finance Institute, and CEPR

No 23-43, Swiss Finance Institute Research Paper Series from Swiss Finance Institute

Abstract: This paper presents a dynamic stochastic general equilibrium model of Ricardian business cycles. Our model is Ricardian because countries (or, equivalently, regions) trade to take advantage of their comparative advantages. Their relative efficiencies, however, change over time stochastically. Similarly, country-specific shocks to demand, supply, and investment efficiency induce countries to engage in intra- and intertemporal substitutions in non-durable consumption, investment, services, and trade, generating business cycles. Finally, all agents have rational expectations about the stochastic components of the model. We solve the model globally using deep neural networks and calibrate it to the U.S., Europe, and China. Our quantitative results highlight the role of trading costs in shaping the responses of the economy to different shocks.

Keywords: International Trade; Business Cycles; General Equilibrium; Comparative Advantage; Deep Learning (search for similar items in EconPapers)
JEL-codes: C45 C63 F10 F40 (search for similar items in EconPapers)
Pages: 62 pages
Date: 2023-01
New Economics Papers: this item is included in nep-big, nep-cmp, nep-dge and nep-int
References: Add references at CitEc
Citations:

Downloads: (external link)
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4278274 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:chf:rpseri:rp2343

Access Statistics for this paper

More papers in Swiss Finance Institute Research Paper Series from Swiss Finance Institute Contact information at EDIRC.
Bibliographic data for series maintained by Ridima Mittal ().