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A Model of Exchange-Rate Determination with Policy Reaction: Evidence From Monthly Data

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  • William H. Branson

Abstract

During the 1970s an extensive theoretical literature has developed analyzing market determination of freely floating exchange rates. At the same time, there has been extensive and continuous intervention in the market by central banks. Exchange rates have not been floating freely; they have been managed, or manipulated, by central banks. However, most of the description of exchange rate policy, as actually practiced, has been informal, or "literary," not integrated with the formal theoretical literature. Recent examples are the surveys in Branson (l98la) and Mussa (1981).In this paper I integrate exchange-rate policy into a model of exchange-rate behavior, and examine the monthly data from the 1970s econometrically,to infer hypotheses about policy behavior. I focus on four major currencies, the U.S. dollar, the Deutschemark, Sterling, and the Japanese yen,and analyze movements in their effective (weighted) exchange rates ascalculated by the IMF. In section II a model of market determination of a floating exchange-rate is laid out. It is a rational-expectations version of the model in Branson(1977), and it draws on the model of Kouri (1978). It is the same as the model in Branson (1983). The model shows how unanticipated movements in money, the current account, and relative price levels will cause first a jump in the exchange rate, and then a movement along a "saddle path" to the new long run equilibrium. Here the role of "news" in moving the exchange rate, as recently emphasized by Dornbusch (1980) and Frenkel (1981), is clear.The model emphasizes imperfect substitutability between domestic and foreign bonds, in order to prepare for the analysis of intervention policy in section III. Exchange-rate policy is introduced in section III. We analyze the options available to the central bank that wants to reduce the jump in the exchange rate following a real or monetary disturbance--"news" about the current account, relative prices, or money. This is the policy characterized as"leaning against the wind" in Branson (1976). The distinction is made between monetary policy and sterilized intervention. In section IV we turn to the monthly data. The quarterly data were analyzed in Branson (1983). Systems of vector autoregressions (VARs) are estimated for each of the countries, and the correlations among their residuals are studied. These represent the "innovations," or "news" in the time series. A clear pattern emerges in these correlations, in which policy in the U.S. and Japan drives exchange rates, and policy in Germany and the U.K. reacts by moving interest rates, and by sterilized intervention. This is essentially the same result that appeared on the quarterly data in Branson (1983). Thus the analyses tend to reinforce each other; both datasets tell basically the same story.

Suggested Citation

  • William H. Branson, 1983. "A Model of Exchange-Rate Determination with Policy Reaction: Evidence From Monthly Data," NBER Working Papers 1178, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:1178
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    4. Deng-Kui SI & Xiao-Lin LI & Tsangyao CHANG & Lu BAI, 2018. "Co-movement and Causality between Nominal Exchange Rates and Interest Rate Differentials in BRICS Countries: A Wavelet Analysis," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 5-19, December.
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    9. O. P. C. Muhammed Rafi & M. Ramachandran, 2018. "Capital flows and exchange rate volatility: experience of emerging economies," Indian Economic Review, Springer, vol. 53(1), pages 183-205, December.
    10. Hong-Ghi Min & Judith A. McDonald & Sang-Ook Shin, 2016. "What Makes a Safe Haven? Equity and Currency Returns for Six OECD Countries during the Financial Crisis," Annals of Economics and Finance, Society for AEF, vol. 17(2), pages 365-402, November.
    11. Deng-Kui Si & Xiao-Lin Li & Xinyu Ge, 2020. "On the link between the exchange rates and interest rate differentials in China: evidence from an asymmetric wavelet analysis," Empirical Economics, Springer, vol. 59(6), pages 2925-2946, December.
    12. Thobekile Qabhobho & Anokye M. Adam & Emmanuel Asafo-Adjei, 2023. "Do Local and International Shocks Matter in the Interconnectedness amid Exchange Rates and Energy Commodities? Insights into BRICS Economies," International Journal of Energy Economics and Policy, Econjournals, vol. 13(6), pages 666-678, November.
    13. Erick Lusekelo Mwambuli & Zhang Xianzhi & Zakayo S. Kisava, 2016. "Volatility Spillover Effects Between Stock Prices and Exchange Rates in Emerging Economies: Evidence from Turkey," Business and Economic Research, Macrothink Institute, vol. 6(2), pages 343-359, December.
    14. Tanveer Bagh & Tahir Azad & Sadaf Razzaq & Idrees Liaqat & Muhammad Asif Khan, 2017. "The Impact of Exchange Rate Volatility on Stock Index: Evidence from Pakistan Stock Exchange (PSX)," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 7(3), pages 70-86, July.
    15. Omer Ahmed Sayed Mohamed & Faiza Omer Mohammed Elmahgop, 2020. "Is the Effect of the Exchange Rate on Stock Prices Symmetric or Asymmetric? Evidence from Sudan," International Journal of Economics and Financial Issues, Econjournals, vol. 10(2), pages 209-215.

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