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Exchange-Rate Dark Matter

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Abstract

Dark matter is believed to account for 83 percent of the matter in the universe and plays a central role in cosmology modeling. This paper argues that an analogous form of dark matter plays a similarly important role in international macroeconomics. Like its cosmological counterpart, exchange-rate dark matter cannot be directly observed, but its existence can be inferred from observations on the real exchange rates and interest rates. In the first part of this paper I show that dark matter is the dominant driver of short- and medium-term changes in real exchange rates for the G-7 countries; accounting for more than 90 percent of the variance at the five-year horizon. Although standard models stress the role of real interest differentials as the proximate drivers of real exchange-rate variations, my findings indicate that they are empirically unimportant. To understand the nature of exchange-rate dark matter, the second part of the paper develops an open-economy DSGE model in which the risk shocks driving households' habits interact with collateral constraints and incomplete markets. The model not only shows that risk shocks can account for the role of dark matter as a driver of real exchange-rate dynamics, but also that these same shocks have significant macroeconomic implications. My analysis suggests that exchange rates appear disconnected from traditional macroeconomic fundamentals because they are particularly susceptible to risk shocks that play an important role in international macroeconomics

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  • Martin D. D. Evans, 2012. "Exchange-Rate Dark Matter," Working Papers gueconwpa~12-12-01, Georgetown University, Department of Economics.
  • Handle: RePEc:geo:guwopa:gueconwpa~12-12-01
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    2. Carlo Altavilla, 2003. "Assessing monetary rules performance across EMU countries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 8(2), pages 131-151.
    3. Martin D. D. Evans & Dagfinn Rime, 2017. "Order Flow Information and Spot Rate Dynamics," World Scientific Book Chapters, in: Studies in Foreign Exchange Economics, chapter 17, pages 725-776, World Scientific Publishing Co. Pte. Ltd..
    4. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    5. Hossein Bastanzad & Pedram Davoudi & Hossein Tavakolian, 2018. "Foreign Exchange Rate Pricing at the Future Contract (Case of I.R. of Iran)," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 22(1), pages 253-293, Winter.
    6. Brissimis, Sophocles N. & Magginas, Nicholas S., 2006. "Forward-looking information in VAR models and the price puzzle," Journal of Monetary Economics, Elsevier, vol. 53(6), pages 1225-1234, September.
    7. Martin Evans, 2012. "International Capital Flows and Debt Dynamics," Working Papers gueconwpa~12-12-04, Georgetown University, Department of Economics.
    8. Jaehun Chung & Yongmiao Hong, 2007. "Model-free evaluation of directional predictability in foreign exchange markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(5), pages 855-889.
    9. Stephane Dees & M. Hashem Pesaran & L. Vanessa Smith & Ron P. Smith, 2010. "Supply, Demand and Monetary Policy Shocks in a Multi-Country New Keynesian Model," CESifo Working Paper Series 3081, CESifo.
    10. Gavin, William T. & Kemme, David M., 2009. "Using extraneous information to analyze monetary policy in transition economies," Journal of International Money and Finance, Elsevier, vol. 28(5), pages 868-879, September.
    11. Brodbeck, Karl-Heinz, 2019. "Die Illusion der Identität und die Krise der Wissenschaften," Working Paper Serie des Instituts für Ökonomie Ök-47, Hochschule für Gesellschaftsgestaltung (HfGG), Institut für Ökonomie.
    12. Charles Engel, 2016. "Exchange Rates, Interest Rates, and the Risk Premium," American Economic Review, American Economic Association, vol. 106(2), pages 436-474, February.
    13. Shiu-Sheng Chen, 2004. "Real exchange rate fluctuations and monetary shocks: a revisit," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 9(1), pages 25-32.
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    15. Darmoul Mokhtar, 2006. "The impact of monetary policy signals on the intradaily Euro-dollar volatility," Cahiers de la Maison des Sciences Economiques bla06049, Université Panthéon-Sorbonne (Paris 1).
    16. Mackowiak, Bartosz, 2006. "What does the Bank of Japan do to East Asia?," Journal of International Economics, Elsevier, vol. 70(1), pages 253-270, September.
    17. K. Arin & Sam Jolly, 2005. "Trans-Tasman Transmission of Monetary Shocks: Evidence From a VAR Approach," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 33(3), pages 267-283, September.
    18. Jae Kim, 2005. "Investigating the advertising-sales relationship in the Lydia Pinkham data: a bootstrap approach," Applied Economics, Taylor & Francis Journals, vol. 37(3), pages 347-354.
    19. Jiang, Zhengyang, 2021. "US Fiscal cycle and the dollar," Journal of Monetary Economics, Elsevier, vol. 124(C), pages 91-106.
    20. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    21. Berg, Kimberly A. & Mark, Nelson C., 2015. "Third-country effects on the exchange rate," Journal of International Economics, Elsevier, vol. 96(2), pages 227-243.

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    More about this item

    Keywords

    Exchange Rate Dynamics; Open-Economy Macro Models; Habits; Incomplete Markets; Collateral Constraints.;
    All these keywords.

    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange

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