Exchange rate determination andstructural changes in response

to monetary policiesYutaka Kurihara

Department of Economics, Aichi University, Aichi, Japan

Abstract

Purpose – The purpose of this article is to analyse methods for determination of exchange rates inresponse to fundamental economic variables and changes in monetary policies.

Design/methodology/approach – The paper undertakes empirical examination of exchange ratemovements and their structural changes in response to changes in macroeconomic variables andmonetary policies in the USA, the Euro area, and Japan.

Findings – Exchange rates have been influenced by macroeconomic fundamentals and have beenimpacted by the conduct of monetary policies in some cases. Some structural changes in exchangerates have coincided with implementation of drastic monetary policies but not in others. The Japanesequantitative easing policy has had an effect on exchange rates.

Originality/value – Monetary policy has been often examined; however, few studies have examinedthe response of exchange rate movements to monetary policies. Moreover, structural changes inexchange rates are examined in comparison with domestic monetary policies in the USA, the EuroArea, and Japan.

Keywords Exchange rates, Macroeconomic fundamentals, Monetary policy, Structural change, Japan,United States of America, Euro

Paper type Conceptual paper

1. IntroductionExchange rates are still one of the most controversial areas in both theoretical andempirical economics and international finance. Although recent empirical models mostlyneglect the potential existence of a long-run relationship between exchange rates andeconomic fundamentals, structural models have been employed in the study of exchangerates[1]. Surprisingly, little attention has been directed to analysis of the relationshipbetween exchange rates and economic fundamentals with respect to structural changes(Beckmann et al., 2011). The relationship between exchange rates and macroeconomicfundamentals remains an important problem and should be analyzed more.

Chueng and Chinn (2005) and Gehrig and Menkhoff (2006) suggested that variousfundamentals are important for exchange rate determination at different times.Kurihara (2007, 2011), which is based on behavioral financial economics, showed thateconomic agents rely on a fundamental approach when “stock prices” differ from thesimulations; on the other hand, agents use a chartist approach when the departure issmall. Bacchetta and van Wincoop (2009) showed that market participants emphasizesome economic fundamentals when structural parameters in the economy are unknownand subject to change. Similarly, Goldberg and Frydman (1996, 2007) suggested that

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JEL classification – E44, E52, F31The author would like to thank Akihiro Amano for his helpful comments and suggestions.

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Studies in Economics and FinanceVol. 29 No. 3, 2012

pp. 187-196q Emerald Group Publishing Limited

1086-7376DOI 10.1108/10867371211246858

parameter instabilities can be obtained from the imperfect knowledge approach. Also,the authors showed that economic fundamentals matter in a way that is not entirelyconsistent with the monetary approach model during some periods of floating. However,Chueng and Chinn (2005) showed that the results depend on time periods[2].

Mehrotra (2010) found no evidence of a structural break in the estimated reactionfunction in Chinese monetary policy. Giannellis and Koukouritakis (2011) appliedrecent unit root and system cointegration techniques in the presence of structural shiftsand indicated the existence of an equilibrium relationship between exchange rates andthe economic fundamentals in the monetary approach model. Hanabusa (2012)indicated that the exchange rate in Japan did not reflect certain information on futureeconomic performance from 2001 to 2006 (i.e. during the quantitative easing policyperiod). Hoshikawa (2012) employed cointegration with break to show that exchangerate and Japanese international reserves had a long-run relationship. The results varydepending on the hypotheses and aims and are inconclusive.

The present study focuses on the monetary approach model with a hypothesis thata relationship between exchange rates and economic fundamentals holds continuouslyin most cases. The research examines whether or not economic fundamentals haveinfluenced exchange rates. Structural changes in exchange rates also are analyzedwhile considering domestic monetary policies. Three currency markets, the US dollar,the Japanese yen, and the euro area, are examined relative to monetary policies.

This paper is structured as follows. Section 2 provides theoretical views for empiricalanalyses. Section 3 shows the results of empirical analyses. Section 4 analyses theresults. Finally, a brief summary is presented.

2. Theoretical analysis2.1 A model of exchange rates: monetary approach modelSince the 1970s, exchange rates have started to move with asset prices. Great capitalflows over GDP started to occur all over the world. Until then, exchange rates had beenmoving with international trade, but the situation has changed greatly. Some famouspapers, for example, Dornbusch (1976), Frenkel (1976) and Kouri (1976), have consideredthis issue. All models of this kind rely on a stable money demand function in thefollowing form:

M=P ¼ LðY ; i Þ ð1Þ

where M denotes the money supply, P the price level, L the money demand, Y realincome, and i interest rate. A basic assumption of this “monetary approach model” is thatthe purchasing power parity holds:

S ¼ P=P* ð2Þ

where S means nominal exchange rate and P * means foreign price.In the log linearized form, the exchange rate can be expressed as the difference

between domestic and foreign money supply, real incomes, and interest rates. If themoney supply and income elasticities are equal in each currency market, exchange ratesare determined as follows:

S ¼ aþ bðm2m* Þ2 gð y2 y* Þ þ hði2 i* Þ ð3Þ

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a is a constant term. b, g, and h are (semi-) elasticities. The interest rates are expressedby as percentage. So, exchange rates are expressed as follows:

s ¼ sðm2m* ; y2 y* ; i2 i* Þ ð4Þ

Some other “strict” assumptions underpin this model:. real income and money market rate are at equilibrium;. domestic and foreign goods are perfect substitutes; and. uncovered interest rate parity holds, and so on.

Results from empirical literature reviews appear mixed. However, this paper employsthis model for empirical analysis[3].

2.2 Chow’s breakpoint testsThe idea of the breakpoint Chow test is to fit the equation separately for eachsubsample and to examine whether there are significant differences in the estimatedequations for different data sets based on F-test. This test does not help pinpoint whichvariable(s) is (are) causing structural change; however, it is often employed. The test ismost commonly used in time series analysis to test for the presence of a structuralbreak and helps to determine whether the independent variables have different impactson different subgroups of the linear equation. A significant difference indicates astructural change in the relationship. This study uses this method and analyses theresults later.

2.3 Unit root testsIt is necessary to check unit root tests for estimation. This paper uses three methods,augmented Dickey-Fuller (ADF), Phillips-Perron (PP), and Kwiatkowski-Phillips-Schmidt-Shin (KPSS) tests.

ADF is most used for empirical estimation; however, if the series is correlated at higherorder lags, the assumption of white noise disturbances is violated. The PP test proposes amethod by which to control for higher order serial correlation in a series than is accepted inthe equation. The test makes a nonparametric correction to the t-test statistic. The test isrobust with respect to unspecified autocorrelation and heteroscedasticity in thedisturbance process of the test equation. Finally, KPSS time series is stationary around adeterministic trend. This test differs from those in common use in that they have a nullhypothesis of stationarity. The test may be conducted under the null of either trendstationarity or nontrend stationarity. Inference from this test is complementary to thatderived from those based on the ADF. This test is often employed with ADF to examinethe possibility that a series is fractionally integrated.

2.4 VAR analysisFinally, this paper examines the effect of Japanese quantitative easing on exchangerates. The method employed is vector autoregression (VAR), which is commonly usedto forecast systems of interrelated time series and to analyse the dynamic impact ofrandom disturbances on the employed variables. Empirical estimation and interfaceare complicated by the fact that endogenous variables may appear on both the leftand right sides of equations. The use of VAR means simultaneously can avoid thisissue.

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The variables employed are monetary base, domestic interest rate, and exchangerate. For the USA, the sample period is too short for adoption of a quantitative easingpolicy, “new monetary policy instrument”. For this reason, only the Japanese case isexamined. Also, impulse responses are examined to trace the effect of a one-timeshock to one of the innovations on current and future values of the endogenousvariables.

3. Empirical analyses3.1 DataThe sample is quarterly from 1975:Q1 to 2010:Q2 for the case of the USA and Japan.For the euro area, the sample period is from 1999:Q1 to 2010:Q4. The euro was firstintroduced in 1999[4]. For Japanese quantitative easing, the sample period is from2000:Q1 to 2010:4.

M1 is used for money supply. Also, monetary base is used in the case of the VARmodel to analyse the effect of the Japanese quantitative easing policy. Real income isproxied by the real production index. For short-term interest rates, money market rateswith a maturity of three months are used. All series are seasonally adjusted and arefrom International Financial Statistics of the International Monetary Fund.

3.2 Unit root testsThe first step tests stationarity in levels and differences are taken and tested again.The necessary first step is to test the data for unit roots. The results of three methodsexplained in the previous section are shown in Table I.

In a few cases, the results are mixed and are not perfectly conclusive. However, theuse of first differences is not problematic for empirical estimations. Most of the resultscan be considered as integrated at order one.

Levels First differencesADF PP KPSS ADF PP KPSS

USAs 20.9938 21.0650 1.2517 * * * 24.2197 * * * 211.3032 * * * 0.0500m 2 m * 21.6098 20.5611 0.8687 * * * 21.6152 * 210.7147 * * * 0.2188y 2 y * 0.2615 0.1910 1.2564 * * * 23.0565 * * 210.1348 * * * 0.1499i 2 i * 23.0937 * * 23.0768 * * 0.2576 22.8788 * 29.0008 * * * 0.1427Japans 20.9938 21.0655 1.2517 * * * 24.2197 * * * 211.3032 * * * 0.0502m 2 m * 20.1424 20.5611 0.8887 * * * 21.9554 * 210.7147 * * * 0.2188y 2 y * 0.2615 0.1910 1.2564 * * * 23.0565 * * 210.1348 * * * 0.1499i 2 i * 23.0937 * * 23.0768 * * 0.2576 22.8788 * 29.0008 * * * 0.1427Euro areas 20.7185 20.7185 0.7162 * 22.7640 * 24.7079 * * * 0.1916m 2 m * 0.0952 0.2479 0.8426 * * * 21.8620 * 28.6107 * * * 0.2552y 2 y * 0.2953 20.6679 0.8238 * * * 22.8338 * 23.5153 * * 0.0697i 2 i * 21.8338 * 21.8479 0.1611 21.8526 * 23.5811 * * * 0.0801

Notes: Statistical significant at: *10, * *5 and * * *1 percent levels, respectively; for the ADF and PPtests, the series contain a unit root under the null, whereas the KPSS test assumes stationarity underthe null

Table I.Unit root tests

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3.3 Empirical results of the model’s regressionsThe regression method is ordinary least squares (OLS) in this section. The checkingpoints are whether exchange rates can be explained by macroeconomic variables or inequation (4). The results are shown in Table II.

The results are pretty good except for the case of euro area. Exchange rates can beexplained by macroeconomic fundamental variables. For the euro area, some variables arenot significant but the signs are as expected. One reason is that the sample period is tooshort.

3.4 Breakpoints of the sample periodTable III shows the breakpoints identified from application of Chow’s test. As thebreakpoints occur frequently according to the selected probability, cases with morethan 70 percent probability are listed in Table III. Null hypothesis means no breaks atspecified breakpoints.

The results contain interesting and important findings. Interpretations are found inthe next section.

3.5 VAR resultsTable IV shows the result of the VAR for Japan instead of the OLS. The time lag is oneand two. Time lag was selected by Akaike info criterion.

It should be noted that monetary base (lag ¼ 2) strongly influences exchange rates.On the other hand, the domestic interest rate does not.

Finally, the results of impulse responses are shown in Figure 1. JER meansexchange rate, JM1 means monetary base, and JIR means interest rate. The monetarybase continuously affects exchange rate.

The results are clear and are analyzed in the next section.

USA Japan Euro area

Constant 0.2174 * (1.5389) 20.0045 * * (22.1057) 20.0022 (20.6764)m 2 m * 0.2536 * * * (3.9925) 0.4804 * * * (3.0648) 0.0435 (0.6831)y 2 y * 1.4998 * * * (15.7005) 0.0047 * * * (3.0234) 0.4494 (1.0495)i 2 i * 20.0057 * * * (22.3625) 20.0011 (20.6756) 20.039 * (21.6013)Adj. R 2 0.7047 0.4830 0.3664F-value 117.9743 33.4701 0.5452D.W. 1.7207 1.9153 1.4381

Note: Statistical significant at: *10, * *5 and * * *1 percent levels, respectively

Table II.Exchange rate

determinations by macrofundamental variables

Break points F-value Probability

USA2004Q1 1.2788 0.0812Japan2003Q1 1.2788 0.2812Euro area2001Q1 2.3223 0.07372001Q2 2.7919 0.0394

Table III.Breakpoints in monetarymodels of exchange rates

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4. Interpretation of empirical analysesAgain, macroeconomic fundamental variables have affected exchange rates significantly,especially in the cases of the USA and Japan. As money supplies and interest rates that arerelated to monetary policies both have influenced exchange rates, there is some possibilitythat monetary policies affect the economies in the middle- or long-run.

Figure 1.Impulse responsesof three variables

–0.02

–0.01

0.00

0.01

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0.03Response of JER to JER Response of JER to JM1 Response of JER to JIR

Response of JM1 to JER Response of JM1 to JM1 Response of JM1 to JIR

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0.15Response of JIR to JER Response of JIR to JM1 Response of JIR to JIR

Response to Cholesky One S.D. Innovations ± 2 S.E.

1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10

1 2 3 4 5 6 7 8 9 10–0.02

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Explanation variable Exchange rate

Constant 0.2905 (1.2623)Monetary base (21) 20.5972 * * * (23.0175)Monetary base (22) 0.5173 * * (2.6454)Interest rate (21) 0.0196 (0.4035)Interest rate (22) 20.0511 (21.0675)Exchange rate (21) 0.7598 * * * (4.9935)Exchange rate (22) 0.2027 (1.3217)Adj. R 2 0.8408F-value 37.1004

Note: Statistical significant at: *10, * *5 and * * *1 percent levels, respectively

Table IV.VAR estimation ofmonetary base, interestrate, and exchange rate

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Table III shows interesting results. In 1985, a major agreement was achieved by theG5 countries. The plaza accord was an agreement among the G5 economies todepreciate the US dollar in relation to the Japanese yen and German deutsche mark bycooperatively intervening in foreign exchange markets. The exchange rate of the dollardeclined rapidly and greatly. It is interesting to note that this accord and the Louvreaccord in 1987 did not confer structure breaks in exchange rates in the USA and Japan.

It should be noted that the USA has not frequently changed its monetary policy’sstance. The only exception found is 2004:Q1. There is some possibility that this actionwas taken to boost the economy strongly while considering exchange rate movements.On the other hand, rising interest rates after that time (from 2004 to 2006) did notchange exchange rate movements structurally.

On September 11, 2001, the USA experienced its most devastating terrorist attack.However, the results of this study show no structural breaks in exchange rates. It isknown that foreign exchange markets react highly sensitively to events attributed topolitical factors, of which war and coup are the most significant. However, foreignexchange markets were not closed even in the middle of the 9/11 attack. There seems tohave been no damage to liquidity, volatility, trading volumes, bid-ask spreads, and so on.

The US Fed has taken unprecedented action in the form of an aggressive quantitativeeasing policy from 2008 to 2011 (QE1 and QE2). The US economy has become increasinglydependent upon exports to offset recent weakness in domestic spending. Its policy has hadthe effect of triggering a large decline in the dollar. Rosa (2011) showed that policydecisions and communication have large and significant effects on exchange rates. Theeffects did not appear as breaking points; however, only a short time has passed since then.It should take some time to judge whether or not structural change occurs[5].

Japan had no structural breaks during the 1990s, as shown in Table III[6]. The lowerboundary of interest rates reduced the degree of freedom of monetary policy. Japanstarted an unprecedented quantitative easing policy in 2001 and zero interest rate policyin 1999. The quantitative easing policy continued until 2006. At first, the market’sconsciousness about exchange rates was not so high, but this effect may have increasedgreatly around 2003. At that time, the Japanese economy was hit by the 2001 terrorismand huge bad loans by banks. The Bank of Japan has taken various and drastic measuresto boost the economy. The policies seem to have changed the movement of exchangerates as shown in Table III.

Japan’s recent intervention in the foreign exchange market is unlikely to work. Currencyinterventions require counterparty cooperation to be really successful. This effort seemsnot to have boosted exports but some time is needed before it is possible to judge this.

The quantitative easing policy in Japan has had a beneficial influence on exchangerates, as shown in Figure 1. However, whether the yen’s depreciation has conferred anincrease in exports and boosted GDP is difficult to judge.

The last part of Table III shows the results for the euro area. The euro areaintroduced the euro in 1999, and its general usage started in 2002, when it became theonly legal currency. The effect of this seems to have appeared around 2001.

In 2004, 12 CEE countries joined the EU. However, no structural breaks weredetected. The main reason is that the new countries satisfied the strict conditions forparticipation in the area. Around that time, economic conditions had been good, so ithad not been necessary to implement drastic monetary policies. Of course, the sampleperiod is too short, so some time is needed before the results can be judged.

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5. ConclusionThis paper’s results are clear and highlight important suggestions. It examinedwhether exchange rates can be empirically explained by macroeconomic variables andconsidered structural breaks in the underlying coefficients.

Exchange rates are affected by some macroeconomic fundamental variables.Also, some breakpoints are found especially in the cases of the USA and Japan. Thedates almost fit well with the dates when large monetary policies were implemented.Monetary authorities have influenced exchange rate movements and are expected totake exchange rate movements into account when they conduct monetary policies insome cases.

However, there are some problems with this study. First, the sample periods in theeuro area too short, which makes it difficult to draw conclusions or make judgments.It is necessary to wait until much more data have accumulated. Also, the sample periodis too long in the case of the USA and Japan. Division into short sub periods wouldbe necessary. Second, there are other methods by which to calculate estimations.For example, to model exchange rates in a linear fashion would be problematic.

I leave the interesting task of corroborating the results to further research.

Notes

1. The exceptions are Lorıa et al. (2010) and Uz and Ketenci (2010).

2. Sarno et al. (2004) employed a Markov regime-switching model. De Grauwe andVansteenkiste (2007) investigated the adjustment of exchange rates under different inflationregimes.

3. Beckmann et al. (2011) also introduced a monetary approach model that uses trading goodsprices and analyzed long-run analysis with time-varying coefficients.

4. There is a possibility of reliance on the Deutschmark and the fundamentals of Germanybefore the introduction of the euro. The empirical outcomes remain mixed. Although Fry(1991) found strong support for the monetary approach, Lyons (1992) did not.

5. Gertler and Karadi (2011) showed that a quantitative monetary policy in Japan may besubstantial during a crisis if the relative efficiency costs of central bank intermediation arewithin the reason.

6. Miyao (2000) used the VAR model and demonstrated that a persistent effect of monetarypolicy on real output is detected and such effect disappears with the subsample of the 1990sin Japan.

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About the authorYutaka Kurihara is a Professor of International Economics and formerly (2007-2011) Dean atAichi University, Japan. He has taught economics courses at both the graduate andundergraduate levels. His principle interests include international economics, finance, and digitaleconomy. He has published about 150 papers, including some in refereed international journals.His recent published books are Global Economics Declaration (2009), Economics Declaration(2006), Global Information Technology and Competitive Financial Alliances (2005), Business& Policy Design in the Globalization (2003), Intellectual Skills for Freshman (2003), andEU Currency Integration (2000). He is the Executive Director of the Japan Association ofMonetary Economics. Yutaka Kurihara can be contacted at: kurihara@vega.aichi-u.ac.jp

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