Marta Gómez-Puig
email: marta.gomezpuig@ub.edu

UNION ON EU-15 SOVEREIGN DEBT YIELD SPREADS

Keywords: Monetary integration, Sovereign securities markets, International and domestic credit risk, Market liquidity JEL Classification Numbers: E44, F36, G15 Monetary integration, sovereign securities markets, international and domestic credit risk, and market liquidity

Yield spreads (corrected for exchange rate risk) over 10-year German securities of European Union countries that did not join EMU experienced an average decrease of 14.20 basis points during the first three years after the beginning of Currency Union. Conversely, Euro-area countries' adjusted spreads registered an average rise of 11.98 basis points in the same period. This paper examines the elements (a possible change in the relative importance of domestic or international risk factors) behind these results using both panel estimations in the two groups of countries and a country-by-country specification in each of them.

Introduction

Two of the main factors that determined yield differentials in EMU participating countries were eliminated with the introduction of a common currency in January 1999 and the elimination (or reduction to insignificant levels) of differences in tax treatment during the 1990s. This fact implied and increase in both the degree of substitution between issues and in the relevance of credit risk and market liquidity differences in their yield spreads 1 . Nevertheless, segmentation did not disappear completely. The persistence of yield differentials is a clear example of it. With this regard, from our sample, which is composed of daily data from January 1996 to December 2001, we can draw the following conclusions.

Certainly, in EMU-countries, table 1 shows an increase in the correlation coefficient between their yields and those of Germany with the beginning of Currency Union. This convergence in total yield differentials over 10-year German bond yields during the aforementioned period is displayed in table 2a. Conversely, the three European Union countries that did not participate in the EMU, outside the increased competition between Euro-area markets, seem to have benefited from both a lower assessment of their risk premium and a higher assessment of their particular "idiosyncrasies" by market participants. This has attracted to their markets investors who wished to reduce their portfolio risk through the diversification of their investments. Table 1 shows that the correlation coefficient between non-Euro and Germany yields registered a substantial decrease since the introduction of the euro and, on average, these countries experienced a spread reduction which is more than twice that registered by Euro-countries (see table 2a).

The main objective, in this paper, is to extend the analysis presented in [START_REF] Gómez-Puig | Monetary Integration and the Cost of Borrowing[END_REF] to the European Union countries that did not participate in the EMU. So, the sample will then include all EU-15 countries (with the exception of Luxembourg and Greece and) and in order to compare the results with those we obtained for the participant countries, we will analyze the same period: 1996-2001 as in our previous papers: Three years before and three years after the introduction of the euro. As in our earlier papers, the analysis in this paper will also be threefold: First, in order to have homogeneous series throughout all the sample for non-Euro and Euro participating countries, in which exchange rate risk was removed in 1999, we follow [START_REF] Favero | High Yields: The Spread on German Interest Rate[END_REF] and correct yield spreads from the exchange rate factor (during the period 1996-1999 in EMU-countries and in the whole period in non-EMU countries) by estimating the foreign exchange factor as the differential between the 10 year swap rate in the currency of denomination of the bond and the 10 year swap rate in Deutsche marks 2 . Then, we break down yield spreads into their two main domestic components not related to exchange risk. Second, we examine whether there was a change in the price assigned to them by markets after the introduction of the Euro which might explain the observed yield spread behavior. Third, we examine the effects of 1 The introduction of the euro also implied a strong sovereign bond market growth which, as de [START_REF] De Bondt | Sovereign Empirical estimates of the impact of the euro on the corporate bond market in the euro area[END_REF] point out, has also been translated to the corporate bond market and has benefited economic activity in the euro area. 2 This correction is broadly explained in [START_REF] Gómez-Puig | Monetary Integration and the Cost of Borrowing[END_REF]. 3 international risk factors on yield differentials. The main goal of the analysis is to identify the possible factors behind the immediate effect of EMU on EU-15 sovereign yield spreads. In particular, the average decrease of 14.20 basis points in non-Euro yield spreads during the first three years of Monetary Union (once they are corrected from the exchange rate factor), compared to the average increase of 11.98 basis points observed in EMU-countries.

We present the results of two different specifications which are the ones that presented the highest explanatory power in our previous studies. Therefore we implement (I) a static panel regression3 , and (II) a static regression for each individual country which includes the same explanatory variables as in the panel estimation. The empirical evidence shows that the relevance of international risk factors in explaining the observed change in adjusted spreads is larger in non-Euro participating countries than in Euro-area countries. The fact that these countries kept their Monetary Autonomy might explain this greater vulnerability to external risk factors4 . However, the results of all the specifications are highly consistent, providing evidence that in all European markets market size scale economies increased with Currency Union and that the rise was higher in smaller debt markets5 . Hence, they suggest that the removal of the exchange rate barrier might have penalized EMU small markets twice. First, within the Euro-area, the German market could have concentrated the majority of the trading activity, and in the current context of increased competition between these markets, their relative success might be dependent on their size. And, second, outside the Euro-area, the Currency Union has enhanced the "singularity" of the debt markets because their securities are still denominated in their own currency. In particular, the British market, which before EMU not only was one of the most important European debt markets, but also was the European market that held the highest share of foreign assets as a function of total financial wealth (see [START_REF] Tesar | Home bias and high turnover[END_REF], is surely the one that has capitalized most on this new advantage and has attracted a significant volume of funds. The rest of the paper is organized as follows: Section 2 outlines evidence concerning Monetary Integration in Europe and the evolution of the relative cost of borrowing in EU-15 countries. Section 3 focuses on the various domestic and international factors to which adjusted spreads might be sensitive, and describes the data. Section 4 explains the models and estimation methodology. Section 5 reports the results.

Lastly, section 6 draws conclusions.

Monetary integration and the relative cost of borrowing in EU-15: Some evidence.

If we analyze the spread behaviour of non-EMU participating countries in the first three years since the introduction of the Euro we observe huge differences with EMU-countries. Figure 1 shows that, for the former, the spread reduction is more than twice that registered by Euro-countries. In particular, the The different pattern that it already showed before the Euro (see figure 2) has been accentuated after Currency Union and the close convergence to zero of swap differentials among Euro-countries. Hence, the temporal evolution of the adjusted spread presents a completely different picture for non-Euro countries after January 1999 (see figure 3) and its average value has also decreased: 14.20 basis points on average between the two periods. Actually, it clearly decreases in Sweden and the United Kingdom (the two countries that really kept a floating exchange rate regime), while it experiences a slight increase in Denmark (0.31 basis points). It has to be noted that Denmark is not only the non-Euro country with the smallest debt-market (see table 3), but that its exchange rate also maintained a link with the Euro; consequently its adjusted spread behaviour is quite similar to that of the Euro-zone countries.

Therefore, in a context of higher integration between European markets, with the exception of Denmark, the countries that did not join Monetary Union seem to have benefited from that fact in terms of an important decrease in their risk premium over Germany (not related to exchange rate factors), which has resulted in lower borrowing costs. The main goal of this paper will be to find an explanation for the different behaviour that yield spreads experienced in the two groups of countries during the first three years of EMU. One possible explanation could be that, in the current context of increased competition between Euro-area government securities markets, their success might be limited by the extent of their liquidity and market size. Specifically, on the one hand, as the German sovereign debt market is the second largest in the Euro-area (only surpassed by the Italian), a concentration of trading activity in the German market might have occurred and, consequently, wider liquidity differences vis-à-vis German bonds might have been translated into higher adjusted spreads in EMU-participating countries 6 . Nevertheless, on the other hand, the British sovereign debt market not only is the fourth largest in the European Union-15 area (see table 3) but, since Monetary Integration, has also benefited from a new advantage over Euro-area debt markets because its debt is still denominated in a different currency which allows portfolio diversification and risk reduction. Therefore, since EMU the British market might have capitalized on its role as the main competitor to the German market, and might have attracted funds from those investors who wished to reduce their risk by investing in a market that still permits portfolio diversification. Consequently, with the Euro the small-size Euro-area debt markets might have been twice penalized. First, within the Euro-area, the German market could have concentrated the majority of the trading activity. And, second, outside the Euro-area, the enhanced British market might have attracted a significant volume of funds due to its "renewed" singularity. 6 The existence of a very liquid futures bond market in Germany also represents an additional advantage of holding German bonds. Remolona (2000) note that if substantial fixed costs are involved in the production of information about the future path of interest rates, the size of the whole debt market matters. They calculate that there may be a size threshold around $100-200 billions; below this level, they state that sustaining a liquid government market may not be easy. Table 3 shows that while in the Euro-area only five countries (Italy, Germany, France, Spain and Belgium) surpassed that threshold, in the non-Euro-area two countries did (Sweden and the United Kingdom) and the third (Denmark) came close 7 . Economides and Siow (1988) point out that there may be a trade-off between liquidity and market size: the smaller the market, the lower the outstanding volume traded in it and the more difficult it will be for investors to process and evaluate information about securities traded in that market, which would imply higher transaction costs and liquidity premium. Hence, if size matters for liquidity, "ex-ante" traders would prefer bigger and liquid markets and liquidity will be selffulfilling. On the other hand, another point that is important to assess is whether the too big to fail theory (TBTF), taken from the banking system (see [START_REF] Kaufman | Too big to fail in banking: What remains?[END_REF] might also hold in sovereign debt markets; if it does apply, the removal of the exchange rate barrier would have punished smaller countries by making them pay both a higher liquidity and higher default risk premium than large ones.

Domestic and international risk factors explaining adjusted yield spreads.

Now that we have defined the dependent variable (ASPREAD it ) which allows separation of risk components not related from expected exchange-rate depreciation, decomposition between domestic is attempted by modelling their behaviour to a number of factors that potentially affect only one of them. With regard to domestic risk factors, a crucial issue in this paper (and one that is vital for policymaking) is the identification of the two main domestic sources of risk that have made up yield spreads in EU-15 countries since the start of Monetary Integration: (1) differences in credit risk and (2) differences in market liquidity, in order to assess whether their impact over yield spreads has changed with the common currency. With this goal in mind, the relative debt-to-GDP ratio will be used as a proxy to measure differences in credit risk. This variable has been widely used in the literature by other authors and presents the advantage over other measures such as the rating differential that it cannot be considered an ex-post measure of fiscal sustainability. As in [START_REF] Gómez-Puig | Monetary Integration and the Cost of Borrowing[END_REF], two different proxy variables will be used to measure the market liquidity effect: (i) the bid/ask spread and (ii) the on-the run/off-the run spread. Lastly, a third point that will be assessed in this paper is the influence of international risk factors on yield spreads. Hence, the spread between 10-year fixed interest rates on US swaps and the yield on 10-year Moody's Seasoned AAA US corporate bonds is introduced in the model as a proxy of international risk factors. 7 Within the Euro-area: Austria, Finland, Greece, Ireland, and Portugal present an overall amount of public sector outstanding debt below the $100 billion level, while The Netherlands entire amount of outstanding public debt is between $100 and $200 billions.

Outside the euro-area: only Denmark presents an amount slightly below the $100 billion level. As defined, the dependent variable is ASPREAD it , i.e. the difference between the total yield differential of 10-year government bonds and the 10-year interest rate swap differential. The sample comprises daily data spanning the period January 1, 1996 to December 31, 2001. Yields and swap rates are obtained from Datastream and correspond to the benchmark 10-year issue for each market at every moment of time. As a benchmark changes, data are taken from a new stock on the first day of the month 8 . With regard to the bid/ask spreads and the on-the-run/off-the-run series, daily time-series have been created using data collected from Bloomberg. The overall outstanding amounts of public debt data have been drawn from the Bank for International Settlements (BIS; see table 3) and the GDP from Eurostat. And finally, the spread between 10-year fixed interest rates on US swaps and the yield on 10-year Moody's Seasoned AAA US corporate bonds (USSPREAD it ), has been calculated from daily data obtained from Datastream. All the variables included in the estimation that capture domestic risk factors are in relative terms to the German ones, as our dependent variable (ASPREAD it ) is the difference between the total yield differential and the swap differential of country i over Germany.

Modeling adjusted yield spread behavior.

We will present the results of two different specifications which are the ones that presented the highest explanatory power in our previous studies 9 . Therefore we will first implement (I) a static panel regression, and (II) a static regression for each individual country which will include the same explanatory variables as in the panel estimation. Therefore, model I will be a panel regression with both domestic and international risk variables:

y it = α i + βX it +γDPRE it +δMONTHLYDUMMIES t + λCOUNTRYDUMMIES i + ε it (1)
Where, with the international (IRV it ) and domestic risk variables (DRV it, ) previously defined, the vector of independent variables will be:

X it =(IRV it ,DRV it ,DRV it *IRV it ) (2)
In addition

β = β 1 + β 2 DPRE it (3)
Finally, in model II, using the same independent variables as in the panel regression, a static estimation will be implemented separately for each of the three non-Euro countries in the sample. The estimation methods used in all specifications, Feasible Generalized Least Squares (FGLS) in the panel estimation and a regression with Newey-West standard errors in the estimations for each non-Euro-country, are robust to the possible existence of autocorrelation and heteroscedasticity in the error terms.

8 Table 4 presents the starting benchmark dates used by Datastream as well as the characteristics of the different benchmarks that compose the yield and swap series for non-EMU participating countries, whilst the references used in the case of euro-participating countries are described in Gómez-Puig (2008). 9 These specifications are broadly explained in [START_REF] Gómez-Puig | Size Matters for Liquidity: Evidence from EMU sovereign yield spreads[END_REF][START_REF] Gómez-Puig | Monetary Integration and the Cost of Borrowing[END_REF]. Tables 5 and6 present respectively, the values and standard errors of the estimated coefficients corresponding to the first and second specifications. In particular, table 5 presents the results for the static panel regression and, in order to compare the results, also introduces the results obtained from the same panel regression when it was applied to the Euro-participating countries (see Gómez-Puig, 2008)10 . Because of their length, monthly and country dummy variables' coefficients are not presented, although monthly dummies are significant in the majority of the periods. As for the country dummies, all of them are significant. Specifically, the panel regression for non-Euro countries shows that not only does the default risk premium not increase with Currency Union but its marginal impact becomes negative with the Euro. Even so, the increase in the EMU period of the marginal impact of the interaction of the default risk proxy with the international risk factor qualifies to some extent the previous results. Actually, what seems to be relevant is the increase in the marginal effect of the international factor which, in addition, is higher than the one we obtained for Euro-countries. Finally, with regard to the variables that capture liquidity risk, we should note that not only its marginal impact increases with the Euro, but also shows a non-linear behaviour that supports the self-fulfilling behaviour of liquidity. Table 6 presents the results of the country-specific estimations for the non-Euro countries. In the case of the British market we should point out that all the explanatory variables used in the regression lose their significance in the EMU period. Therefore, variables other than those used as proxies of domestic risk or international risk must explain the decrease of the 10-year adjusted spread over Germany in the EMU period. In our opinion, one possible explanation could be a flight of funds from small Euro-area debt markets to the enhanced British debt market which not only is big enough to be liquid by itself, but, since the introduction of the common currency, presents an additional advantage in terms of allowing portfolio diversification, since its securities are not denominated in Euros. In the Swedish market we should also mention the decrease in the marginal impact of the default risk variable in the EMU period, in spite of its very high debt-to-GDP ratio. Hence, it seems that the default risk might be compensated by its increased liquidity, both because it has a "relevant" size (which could reduce the importance of default risk as long as agents believe that it is "too big to fail") and because its singularity has increased since Monetary Union. The increase in the significance of the non-linear term of the bid-ask spread since EMU supports the self-fulfilling nature of liquidity and is in concordance with the rest of the results. Finally, Denmark, the only non-Euro participating country that has experienced a slight increase of its adjusted spread over Germany with the Euro, is precisely the one whose exchange rate does not float and with the smallest debt-market. This seems to support the theory that big markets are the ones that have experienced the most benefits from Monetary Integration. Actually, the marginal impact of the non-linear term of both liquidity proxies 8 registers an increase in the EMU period when it is interacted with the international risk proxy. This result supports the increasingly nature of illiquidity in the case of a small-debt market such as the Danish market.

Conclusions

The immediate effect of Currency Union on EU-15 sovereign yield spreads can be summarized as follows.

Non-Euro participating countries' adjusted spreads experienced an average decrease of 14.20 basis points with Currency Union. Conversely, Euro-area countries' adjusted spreads over 10-year German securities registered an average rise of 11.98 basis points in the first three years of EMU. Therefore, in a context of higher integration between European markets, the countries that did not join Monetary Union, and thus did not experience an increase in their degree of substitutability and competition with German securities, seem to have benefited from that fact, in the shape of an important decrease in their risk premium that has resulted in lower borrowing costs. However, while in Euro-area markets a change in the market assessment of domestic rather than international risk factors might be behind the increase observed in adjusted spreads with Monetary Integration; as mentioned, in non-Euro participating countries, the importance of international risk factors in explaining adjusted spread changes is higher. The fact that these countries do not share the European Central Bank monetary policy, which main goal is achieving price stability, might explain this greater vulnerability to external risk factors 11 . The results of all specifications are very consistent. They provide evidence that market size scale economies seem to have increased with Currency Union and that the smaller the debt market, the higher the rise. Actually, since January 1999 the adjusted spread over 10-year German bonds has increased in all Euro-area countries and in the non-Euro participating country (Denmark) that presents the smallest debt market and whose exchange rate is still linked to the Euro, and table 3 shows that the German market is the second biggest in the Euro-area.

Hence, on the one side, an improvement of relative German market liquidity might be behind the adjusted spread changes. In fact, within the Euro-area, the countries with a larger debt market relative to Germany (Italy, France and Spain) are the ones that have experienced the lowest rise in their adjusted spreads with the introduction of the Euro (see table 2b). On the other hand, outside the Euro-area, the enhanced British market might also have attracted a significant volume of funds due to its "renewed" singularity which still allowed investors to reduce their risk investing in a market where debt is denominated in a different currency. Hence, the British market might have capitalized on its role as the German market's main competitor. To conclude, with the introduction of a common currency and in the current context of higher competition between Euro-area government securities markets, the success of these sovereign 11 Altavilla and Landolfo (2005) analyze whether the ECB and the Bank of England have a different behaviour during recession and expansion. They results confirm that whilst the primary goal of the ECB consists of achieving price stability, the Bank of England contemporaneously targets output and inflation. securities debt markets may be highly dependent on their market size (the removal of the exchange rate barrier seems to have punished Euro-area smaller markets twice, by making them pay both higher liquidity and a higher default risk premium than larger ones). In the case of non-Euro participating countries: on the one hand, since they did not suffer the increase in their degree of substitutability and competition mentioned above, they seem to have benefited from the fact that market participants consider their risk premium to be low and the investment advantages to be high and; on the other, the maintenance of their monetary autonomy might be related with their higher vulnerability to external risk factors.

F

5

  Some literature supports the importance of market size in the success of a debt market. McCauley and

  average spread over German yields decreased by 73.06 basis points in the EMU period (see table 2) in the three non-Euro countries as a whole. On the other hand, the swap differential behaviour clearly differs.

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TABLE 2a TABLE 2b

 2a2b

			PRE-EMU (1996-1998)		EMU (1999-2001)		Differences between EMU and PRE-EMU
		(I i -I DM ) (1)	( I R S i -IRS DM ) (2)	A S P R E A D i (3)=(1)-(2)	(I i -I DM ) (4)	( I R S i -IRS DM ) (5)	ASPREAD i (6)=(4)-(5)		(I i -I DM ) (4)-(1)	ASPREAD i (6)-(3)
	EURO							EURO
	AT BE FI FR	9.07 33.06 43.56 2.97	-0.33 4.29 41.31 -3.10	9.40 28.77 2.25 6.07	24.42 46.30 21.95 14.05	-0.01 -0.01 -0.01 0.00	24.43 46.31 21.96 14.05	AT BE FI FR IE	15.34 13.24 -21.61 11.08 -35.74	15.03 17.53 19.71 7.98 8.10
	IE	50.52	43.84	6.68	14.78	0.00	14.78	IT	-125.40	7.58
	IT	157.73	133.04	24.69	32.32	0.05	32.27	NL	16.92	13.40
	NL	-2.70	-3.52	0.83	14.22	-0.01	14.23	PT	-79.88	11.31
	PT	111.73	91.42	20.31	31.85	0.22	31.63	SP	-90.82	7.13
	SP	118.06	97.99	20.07	27.24	0.04	27.20	Average	-32.99	11.98
	Average	58.22	44.99	13.23	25.24	0.03	25.21	St.dev.	53.77	4.69
	St.dev.	57.48	51.37	10.33	10.66	0.08	10.64
	NON-EURO							NON-EURO
	DK	64.01	61.09	2.92	35.83	32.61	3.23	DK	-28.18	0.31
	SW	108.48	117.15	-8.67	28.14	49.01	-20.87	SW	-80.33	-12.20
	UK	129.95	142.05	-12.10	19.27	62.07	-42.80	UK	-110.68	-30.70
	Average	100.81	106.77	-5.95	27.75	47.90	-20.15	Average	-73.06	-14.20
	St.dev.	33.63	41.46	7.87	8.29	14.76	23.02	St.dev.	41.73	15.60
	NOTE: AT: Austria, BE: Belgium, FI: Finland, FR: France, IE: Ireland, IT: Italy, NL: The Netherlands, PT: Portugal, SP: Spain, DK:
	Denmark, SW: Sweden and UK: United Kingdom. Source: Datastream. (I i -I DM ) = 10-year yield difference over Germany. (IRS i -
	IRS DM ) = 10-year interest rate swap difference over Germany. ASPREAD i = (I i -I DM ) -(IRS i -IRS DM )

TABLE 3 DOMESTIC DEBT SECURITIES PUBLIC SECTOR AMOUNTS OUTSTANDING (Billions of euros) 1995-12 1996-12 1997-12 1998-12 1999-12 2000-12 2001-12 average % over EMU % over EU-15

 3

	Ireland	19.93	23.20	23.12	21.93	24.73	24.07	19.95	23.15	0.69	0.59
	Portugal	35.19	36.47	32.84	34.04	37.49	42.35	45.61	37.67	1.13	0.95
	Finland	33.20	38.15	41.56	44.28	45.60	47.70	46.28	43.39	1.30	1.10
	Austria	57.04	58.95	63.87	69.28	86.05	99.74	100.52	76.80	2.30	1.94
	Greece	64.10	79.58	84.47	84.80	88.43	96.73	102.20	87.23	2.62	2.21
	Netherlands	155.64	159.89	159.68	170.12	178.14	180.98	177.50	171.44	5.14	4.34
	Belgium	228.86	230.59	228.41	229.67	231.85	246.18	248.66	236.75	7.10	5.99
	Spain	211.07	241.63	259.63	272.41	287.34	311.04	299.43	269.56	8.09	6.82
	France	497.35	536.05	565.50	623.91	639.85	708.45	709.23	614.79	18.45	15.56
	Germany	676.53	682.74	699.45	738.75	767.35	816.77	790.81	734.97	22.05	18.60
	Italy	896.49	1022.19 1011.08 1037.09 1042.62 1088.36 1056.96	1036.69	31.11	26.23
	EMU	2875.40	3109.45 3169.63 3326.27 3429.43 3662.37 3597.15	3332.43	100.00	84.33
	Denmark	89.78	90.22	87.89	87.70	86.74	86.93	82.03	88.63	-	2.24
	Sweden	111.09	114.30	110.02	111.34	123.04	117.24	91.22	111.83	-	2.83
	U.Kingdom	316.49	373.76	418.68	396.12	456.97	475.31	460.79	418.69	-	10.60

TABLE 4

 4

	Non-EMU countries
	Starting date as a benchmark	Name	Coupon	Maturity date
	DENMARK
	Jan-96	DANSKE STAT	1994 8%	15/03/06
	Jul-97	DANSKE STAT	1996 7%	15/11/07
	Feb-99	DANSKE STAT	1998 6%	15/11/09
	Mar-01	DANSKE STAT	2000 6%	15/11/11
	SWEDEN
	Nov-96	SVENSKA	1996 6.5%
	Feb-97	SVENSKA	1996 8%	15/08/07
	Feb-98	SVENSKA	1997 6.5%	05/05/08
	Jul-98	SVENSKA	1993 9%	20/04/09
	Feb-01	SVENSKA	2000 5 1/4%	15/03/11
	UNITED KINGDOM
	Mar-96	TREASURY	7.50%	07/12/06
	May-97	TREASURY	7.25%	07/12/07
	Oct-98	TREASURY	9%	13/10/08
	Apr-99	TREASURY	5.75%	07/12/09
	Apr-01	TREASURY	6.25%	25/11/10
	Aug-01	TREASURY	5%	07/03/12
	Source: Datastream.

TABLE 5

 5

	Cross-Sectional Time-Serie FGLS Regression.
	Sample: Pre-EMU: 1996:01-1998:12
	EMU: 1999:01-2001:12
	dependent variable: ASPREAD	SPECIFICATION I (non-euro countries)	SPECIFICATION I (euro countries)
				(Gómez-Puig, 2006b)
	X it	ß 1 (X it )	ß 2 (DPRE it *X it )	ß 1 (X it )	ß 2 (DPRE it *X it )
	LNDEBTGDP it	-0.316**	0.563**	0.181**	-0.017**
		(0.060)	(0.080)	(0.008)	(0.002)
	ONOFFDIF it	1.162**	-3.193**	1.782**	-1.082**
		(0.087)	(0.202)	(0.104)	(0.118)
	ONOFFDIF2 it	3.968**	-2.888**	-10.686**	5.133**
		(0.516)	(0.681)	(0.608)	(0.616)
	BIDASKDIF it	-	1.307**	0.557**	-0.386**
			(0.475)	(0.050)	(0.075)
	BIDASKDIF2 it	-	-	-	-2.670**
					(0.742)
	USSPREAD it	0.109**	-0.198**	0.034**	-0.018**
		(0.021)	(0.041)	(0.007)	(0.009)
	LNDEBTGDP*USSPREAD it	0.254**	-0.845**	0.050**	-0.082**
		(0.051)	(0.113)	(0.003)	(0.003)
	ONOFFDIF*USSPREAD it	-0.802**	4.287**	-1.860**	0.899**
		(0.109)	(0.371)	(0.106)	(0.145)
	ONOFFDIF2*USSPREAD it	-5.700**	-	15.425**	-6.340**
		(0.815)		(0.720)	(0.726)
	BIDASKDIF*USSPREAD it	-0.822*	-	-0.401**	-
		(0.430)		(0.059)
	BIDASKDIF2*USSPREAD it	-	16.744**	-	4.301**
			(8.372)		(0.731)
		γ		γ
	DPRE it	0.129**		0.038**
		(0.032)		(0.009)
		α		α
	CONSTANT	-		0.160**
				(0.005)
	Number of observations =	3402		12139
	Number of groups =	3		9
	Avg obs per group =	1195.5		1406
	Log likelihood =	6734.189		23893.12
	Wald chi2 =	17824		53337.41
	Prob > chi2 =	0.00		0.00
	**Significant at 5 percent confidence level.
	*Significant at 10 percent confidence level.
	Standard Errors within parentheses

**Significant at 5 percent confidence level. *Significant at 10 percent confidence level. Standard Errors within parentheses Page 13 of 13 Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript

In[START_REF] Gómez-Puig | Monetary Integration and the Cost of Borrowing[END_REF], we estimated a dynamic model but the introduction of a lag of the dependent variable did not improve the results.

Nevertheless, it is important to note that, although EMU countries do not have monetary policy autonomy, they do not present the same response pattern to ECB decisions (see[START_REF] Clausen | Asymmetric monetary policy effects in EMU[END_REF].

In[START_REF] Gómez-Puig | Size Matters for Liquidity: Evidence from EMU sovereign yield spreads[END_REF] we deeply analysed the effect of market size on liquidity.

Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript

In the case of EMU-countries, we only show the results for the first specification, which have been drawn from[START_REF] Gómez-Puig | Monetary Integration and the Cost of Borrowing[END_REF].

Acknowledgments

I thank the participants in all the seminars where the paper has been presented for their useful comments.

I would also like to thank Analistas Financieros Internacionales, S.A. who have kindly provided part of the data used in the empirical analysis. Special thanks to Jordi Galí and Jaume Ventura, for their insightful comments on previous versions of the paper. I alone am responsible for any errors remaining in the final version.

01/01/1996 01/03/1996 01/05/1996 01/07/1996 01/09/1996 01/11/1996 01/01/1997 01/03/1997 01/05/1997 01/07/1997 01/09/1997 01/11/1997 01/01/1998 01/03/1998 01/05/1998 01/07/1998 01/09/1998 01/11/1998 01/01/1999 01/03/1999 01/05/1999 01/07/1999 01/09/1999 01/11/1999 01/01/2000 01/03/2000 01/05/2000 01/07/2000 01/09/2000 01/11/2000 01/01/2001 01/03/2001 01/05/2001 01/07/2001 01/09/2001 01/11/2001


Francisco ; Ledesma-Rodríguez

Manuel Navarro-Ibáñez

Jorge Pérez-Rodríguez

DOLLAR EXCHANGE RATE

Keywords: Exchange rate regimes, Implicit fluctuation bands, Exchange rates JEL classification: F31; F33 Exchange rate regimes, implicit fluctuation bands, exchange rates

This paper attempts to identify implicit exchange rate regimes for the Yen/Dollar exchange rate. To that end, we apply a sequential procedure that considers both the dynamics of exchange rates and central bank interventions to data covering the period from 1971 to 2003. Our results suggest that implicit bands existed in two subperiods: April-December 1980 and March-October 1987, the latter coinciding with the Louvre Accord. Furthermore, the study of the credibility of such implicit bands indicates the high degree of confidence attributed by economic agents to the evolution of the Yen/Dollar exchange rate within the detected implicit band rate, thus lending further support to the relevance of such implicit bands.

Introduction

The de facto exchange rate policy adopted by monetary authorities has tended to differ from the announced de jure exchange rate regime, which is why IMF classifications are not always a good guide to the true exchange rate intentions of said authorities.

The literature in this area seeks to achieve two linked objectives, namely, to detect divergences between de jure and de facto regimes and to assess the consequences of these differences on the relevance of exchange rates for macroeconomic performance1 . Recognition of the divergences opens up a number of key questions regarding the analysis and recommendations of international economic organizations as well as for academic work: which is the correct classification and which variables and methods should be considered for this purpose?

Recently, [START_REF] Reinhart | The Modern History of Exchange Rate Arrangements: A Reinterpretation[END_REF] have presented a comprehensive classification of the exchange rate regimes of 153 countries over the last half-century. Their research suggests the importance of de facto bands in the international economy. Other approaches focus on the variation of central bank reserves and acknowledge the relevance of intervention in detecting implicit pegs and bands (see, for instance, [START_REF] Poirson | Monetary Policy of the Bank of Japan-Inflation Target Versus Exchange Rate Target[END_REF].

The main objective of this paper is to use a sequential procedure that considers both the dynamics of exchange rates and central bank interventions to detect implicit bands for the Yen/Dollar exchange rate.

We analyse the Yen/Dollar exchange rate as a interesting case study since it has traditionally been considered a paradigmatic example of a flexible exchange rate (see e.g. [START_REF] Cooper | Exchange Rate Choices[END_REF]. Notwithstanding the customary consideration of the Yen/Dollar exchange rate as free-floating, a number of studies2 have examined the behaviour of the US Federal Reserve and the Japanese monetary authorities in exchange rate markets and the effectiveness of such intervention in driving the Yen/Dollar exchange rate. This paper is organized as follows. To place the study in its proper context, Section 2 presents a brief history of exchange rate regimes. In Section 3 we propose a test to detect implicit band and to assess the statistical significance of the [START_REF] Reinhart | The Modern History of Exchange Rate Arrangements: A Reinterpretation[END_REF] approach. In addition, we apply two tests to interventions and to exchange rate data to assess both the intention and the efficacy of foreign exchange market interventions. Section 4 examines the credibility of the implicit bands found in Section 3. Finally, Section 5 provides some concluding remarks. The relationship between a country's exchange rate regime and its macroeconomic performance has been discussed extensively ever since the collapse of the Bretton Woods system. After the prolonged period of fixed exchange rates which characterized the system, many anticipated a generalisation of more flexible regimes in the belief that these were better equipped to protect the economy from real and monetary shocks. Instead, however, in several countries the monetary authorities pegged the external value of their currencies to the Dollar, the Yen, the Pound Sterling, or to a basket of currencies, believing that greater exchange rate flexibility led to excessive fluctuations. Such volatility was considered to give rise to economic instability, having a negative impact on productive investment, international trade and growth.

During the 1980s, monetary authorities adopted their exchange rate regimes with the clear intention of seeking a sound stabilisation instrument to protect against real and monetary shocks. In particular, they expected that fixing the exchange rate would prevent excessive monetary growth, thus conferring greater discipline on public spending [START_REF] Levy-Yeyati | Exchange Rate Regimes and Economic Performance[END_REF]. The widespread monetary instability experienced during the period called for disinflation and budget consolidation policies and it was no surprise that monetary considerations attracted more attention.

The series of crises in the 1990s led to many to once again question the appropriateness of pegged exchange rates. More flexible systems were now considered more adequate than their fixed counterparts as a means of protection against speculative pressures. This change in perspective stemmed from the growing importance of movements of private capital between countries, a circumstance which had a profound impact on the international financial system. The crises experienced during these years centred on the evolution of the capital account, in contrast to the previous decades, when more traditional causes -high fiscal deficits and the ensuing monetisation, distortions in goods and services markets, as well as production market factors, among others-were paramount [START_REF] Summers | International Financial Crises: Causes, Prevention, and Cures[END_REF].

In this context, this paper aims to study the exchange rate regimes followed by the Yen/Dollar exchange rate. The monetary and trade relationships between Japan and US have been difficult in different periods of their recent history. The monetary policy pursued by the Federal Reserve seems to have been quite independent while the Japanese monetary policy appears instead to have been conditioned by the appreciating trend of the Yen with respect to the Dollar (Glick and Hutchinson, 1994). This trend may explain the differences, at least since 1971, between Japan and the US in trade policy and the financial pressures due to the accumulation of external surpluses. The observed appreciation of the Yen and the expectations of further appreciations might be reasons for the deflationary monetary policy of Japan at the end of the seventies.

Before the fall of Bretton-Woods, the sharp appreciation of the Yen implied better competitiveness for US industrial goods. As a response, the Bank of Japan reduced the short-term interest rates in order to switch this trend. The Japanese economy entered in an unstable period due to the depreciation, and expectations of further depreciation, of the Yen and the increasing risk derived from the accumulation of assets denominated in dollars by the Japanese financial institutions. In the 1990s the Japanese economy seemed to be in a liquidity trap externally imposed. Economists and practitioners alike were unable to identify the true origins of the crisis in which consumption and investment were weakened; in fact, this lack of knowledge is one of the most important failures of modern macroeconomics (McKinnon, 2000). In this period, Japan suffered high rates of unemployment and deflation, as well as low growth. In fact, the 1990s has been considered "a lost decade" by Hiyashi and Prescott (2002).

The choice of the exchange rate regime which every country has to make has also centred empirical discussion on the appropriate estimation of the economic costs and benefits of different systems. A difficulty that often arises concerns the wide range of possibilities since there are more than two or three regimes (in contrast to the approach taken in the numerous studies which naturally employed the official IMF classification). Rather, countries use a range of exchange rate systems, such as currency boards, narrow bands, moving or crawling bands, and managed floats.

To all these should be added another difficulty which has come to light more recently: many countries do not declare the true system used. The exchange rate policy followed de facto by numerous countries has been found to be vastly different to what was officially notified to the IMF by the economic authorities. Many countries experience what [START_REF] Calvo | Fear of Floating[END_REF] have called the "fear of floating", namely, they do not really allow their exchange rates to move freely, regardless of the de jure exchange rate system reported by the authorities to the IMF.

One of the consequences of this divergence between "deeds" and "words" (Levy-Yeyati and Sturzeneger, 2000;2001) has been to call into question the results of many empirical studies based on the IMF classification. For this reason, before proceeding any further with an evaluation of the different exchange rate regimes, a classification of the de facto systems is needed to replace the de jure systems used until recently by researchers in the field of International Economics.

One of the aims of this paper is to identify implicit band or peg regimes. Specifically, we examine the possible existence of fluctuation bands, "agreed" by the monetary authorities in order to intervene in the Yen/Dollar market during the period [START_REF] Wan | Effects of Japanese Intervention on Yen/Dollar Exchange Rate Volatility: A Conditional Jump Dynamics Approach[END_REF][START_REF] Dominguez | When Do Central Bank Interventions Influence Intra-Daily and Longer-Term Exchange Rate Movements?[END_REF]. In this regard, Fischer (2001), for example, has pointed to the possibility that a commitment to maintain a desired exchange rate target zone between the US Dollar, the Euro (the Deutsche Mark previously) and the Yen may have existed, albeit informally and loosely.

According to the literature on optimum currency area, the most appropriate regime may vary in each circumstance, attending to the nature of disequilibria suffered by an economy, the capacity to transmit or isolate from internal or external shocks, and the ability of economic authorities to use different instruments of economic policy (see, for instance, Horvath, 2003). The observed exchange rate system might be related to concrete episodes and the economic policy used as a response. This literature may provide a good guide to interpret the de facto deviations from the de jure exchange rate regime. In this sense, flexible exchange rates could be preferable when real shocks, both domestic and external, occur while fixed regimes seems to perform better when shocks are merely nominal (Buiter, 1995). A smaller degree of trade openness reduces the possible damage done to internal price stability and to the external balance of a country due to exchange rate variability (McKinnon, 1963). Also a small product diversification increases the likelihood of asymmetric shocks and so the need for exchange rate flexibility (Kenen, 1969), and it is more difficult to fix the exchange rate if the inflation rates of the two countries are quite dissimilar and prices and wages are sticky (Fleming, 1971). Lastly, pegging the exchange rate can provide a reasonably credible commitment to a non-inflationary policy but, as indicated by Stockman (1999), there are alternative institutional arrangements that have shown a better performance.

Implicit bands

3.1. Detection of implicit bands [START_REF] Reinhart | The Modern History of Exchange Rate Arrangements: A Reinterpretation[END_REF] proposed a "natural" classification of exchange rate regimes, as opposed to the "artificial" one followed by the IMF. In their extensive research they collected monthly data on the exchange rates of 153 countries from 1946 to 2001, highlighting the existence of dual, multiple, or even parallel (legally or otherwise) rates. In the event of the absence of a dual market to adequately classify the de facto regimes, their approach based the search for peg or band regimes on the proportional variation of the absolute value of the exchange rate, as well as on the probability that it would remain within a given fluctuation band (±1%, ±2% or ±5%) over a rolling 2 or 5-year period. Reinhart and Rogoff, somewhat surprisingly, focus on the evolution of exchange rates, without taking into account variations in official foreign currency reserves.

One of the weaknesses of the approach taken by [START_REF] Reinhart | The Modern History of Exchange Rate Arrangements: A Reinterpretation[END_REF] is that the results are not filtered by their statistical significance. For this reason we perform a variant approach to detect implicit pegs or bands that involves direct testing to see whether the average of the proportional absolute monthly variations for each rolling 24-month period is significantly less than ±1% or ±2%. To test if the population mean (of the monthly variations during 24-month periods) is less than or equal to a given mean 0 µ (±1% or ±2%) the following expression may be used:

0 1 0 0 : : µ µ µ µ > ≤ H H
, where 0 µ is the given mean.

The acceptance region of the null hypothesis is

ε ≤ x
, where x is the sample mean of the Yen/Dollar exchange rate and

n t n σ µ ε α 1 , 1 - - + =
, where

1 , 1 - -n t α
is the critical value of the t-Student distribution at a confidence level of α -1 , σ is the serial population deviation and n is the sample size. At a 5% confidence level we choose a critical value of 1.71.

The results of the application of this statistical procedure are given in Figures 1 and2.

[Figure 1, here] Figure 1 show the results when ±1% fluctuation bands are considered. The average value (24 months rolling) of absolute proportional variations of the exchange rate of each month with respect to the previous month is given in blue, while the critical 6 region appears in red. Thus, when the red series is above the blue one the null hypothesis cannot be rejected, which would suggest the presence of fluctuation bands. This occurs around the Bretton Woods period but extends until the end of 1977. With respect to the first years of the 1970s, any observer could argue that the Japanese economy was suffering a real shock due to the increase of the crude oil prices, and therefore the convenience of a flexible exchange rate. However the oil shock only had a temporary impact due to the rapid response of the Bank of Japan (Meltzer, 1986), quite different from the more permanent character of the monetary shock produced at the end of the Bretton Woods system (Hetzel, 2004); in this sense its temporary character would have made more appropriate a de facto regime. Furthermore, the small size of the Japanese economy compared to the US, its lesser diversification of production, and its continuous external surplus could explain why the Japanese monetary authorities optimally chose less flexibility for their exchange rate, as suggested by Aghion et al. (1999) andBachetta (2000). Likewise, between 1983Likewise, between and 1985Likewise, between , between 1995Likewise, between and 1997, and , and at the end of the sample period the results indicate that the regime was in the neighbourhood of the ±1% fluctuation band. In particular, during 2003 the Japanese economy was in a deep deflationary process, aggravated by a zero interest rate policy (Ito and Mishkin, 2004);and, in this context, Svensson (2003) pointed out that the Bank of Japan made a commitment of maintaining a level of the exchange rate compatible with the objective of affecting agent expectations. This non-conventional monetary policy and the fact that the deflation had its origin in a domestic monetary shock (Metzler, 2002) could explain the smaller de facto flexibility of the exchange rate in 2003.

[Figure 2, here]

As can be seen in Figure 2, the average of the monthly variations generally lies below the critical region when a ±2% fluctuation band is used, suggesting (given the rolling quality of the 24-month test) that in practical terms there were monthly limits of ±2% during the entire period. Combining this result with that observed with the ±1% band, we can be confident that fluctuation bands between ±1% and ±2% existed throughout the sample period, except during the three subperiods detected with the ±1% test, when the bands were narrower.

Sensitivity analysis 3

Results from the previous analysis seem reasonable, but monetary authorities could have used an alternative benchmark to define the implicit bands as the deviation from Purchasing Power Parity (PPP).

In its absolute version, PPP theory establishes a relationship between the exchange rate (S t , expressed as the home currency price of a unit of foreign exchange) and the ratio of domestic and foreign prices (P t and P t * respectively), so that * / As can be seen, the higher the domestic price level relative to the foreign price level, the higher must be the exchange rate in order to retain purchasing power parity between domestic and foreign currencies.

The absolute PPP is a too restrictive hypothesis for at least two reasons. First, factors such as costs of gathering and processing information, transport costs and other obstacles to trade (in particular tariffs and quotas), and market imperfections can limit spatial arbitrage and therefore account for deviations from absolute PPP. Second, the weights used in the computation of a price level could differ across countries and as a consequence the absolute PPP may be hardly held.

For these reasons, a less restrictive relationship between prices and exchange rate is considered. This is the relative PPP, which asserts that the percentage rate of change of the exchange rate will equal the differential between the percentage rates for change of price levels at home and abroad. That is

* t t t s p p ∆ = ∆ -∆
where ∆ denotes first difference and lower-case letters denotes logs. Therefore, if the domestic inflation rate exceeds the foreign inflation rate, a domestic currency depreciation (i.e, an increase in ∆ s t ) is required to sustain purchasing power parity between domestic and foreign currencies. Similarly, if the foreign inflation rate exceeds the domestic inflation rate, this will be associated with a domestic currency appreciation (i.e., a reduction in ∆ s t ).

Relative PPP is less strict than absolute PPP in allowing domestic and foreign prices (expressed in domestic currency) to differ from each other but still sustains the assumption that these deviations will not grow or diminish persistently over time. The relative purchasing power of domestic money vis-à-vis foreign money will therefore be fixed over time, with exchange rate changes ∆ s t assuring such parity. The relative version of PPP has a further advantage over absolute PPP in that as long as the weights used to define the domestic and foreign price indices remain constant over time, then the two weighting schemes do not need to be the same.

We compute an alternative indicator to detect implicit pegs or bands using deviations of observed changes in exchange rates from inflation differential between Japan and USA. Again we test whether the average of the proportional absolute monthly variations of the real exchange rate for each rolling 24-month period is significantly less than ±1% or ±2% 4 . Note that this time the sample covers until December 2007, in an attempt to detect any other episode of implicit band in the post- 4 We also explore the possibility of much wider implicit bands, but they were not consistent with the data. As a matter of fact, although the maximum deviation of the observed exchange rate variation from the theoretical exchange rate variation derived from relative PPP (i. e., the inflation differential between Japan and USA) was 10.27% during the January 1971-December 2007 period, the average deviation was 2.12% and the median 1.68%, giving further support to the hypothesis of implicit fluctuation bands of ±2%. [Figures 3 and4, here]

As can be seen, we obtain similar results than in Figures 1 and2, therefore providing further support to the fluctuation bands we have previously detected.

Incorporating interventions

In this section we incorporate foreign exchange intervention by monetary authorities into the search for bands in the Yen/Dollar exchange rate. In the previous section, de facto bands or pegs were identified for most of the sample period using an approach based on exchange rate data. This suggests that the results obtained are not informative. Most of the literature that classifies exchange rate regimes also uses exchange rate data or a combination of foreign reserve and exchange rate data. Such analysis either has either not taken central bank interventions into account or has used an imperfect proxy for them so as to detect periods with exchange rate regimes other than a free floating one 6 . An ideal method should, however, consider foreign exchange market interventions to screen both for the intentions of central banks and their efficacy with regard to peg or band regimes 7 .

In spite of its relevance, the availability of intervention data limits its consideration. Here we use Federal Reserve intervention data from 1 January 1980 until 31 December 2003 as well as data from the Japanese Ministry of Finance from 13 May 1991 until 31 March 2001. We consider the intervention to have a positive sign when the monetary authority buys US dollars and a negative one for other actions.

The [START_REF] Pesaran | A Simple Nonparametric Test of Predictive Performance[END_REF] test is used as a directional prediction test. In this test, the sign of central bank intervention and the exchange rate trend are related, particularly when lagged interventions (to measure efficacy) and leads (to detect the monetary authorities' intention to maintain bands or pegs) are considered relative to the exchange rate trend. In the first case, one would expect the ex ante intervention consisting of the sale of US Dollars to be followed by an appreciation of the Yen. In the second case, the ex post intervention is considered once the trend has been observed, 5 Jeon and Lee (2002) show that within-country market efficiency appears to have become stronger in the post-Plaza agreement period than before and have not been affected by the major foreign exchange policy co-ordinations. 6 Neely (2000) has shown that central bank interventions and reserve changes may be loosely related. Therefore, the use of reserves instead of interventions may lead to inadequate classifications. 7 We study the incidence of interventions at the exchange rate level. See Domínguez (1993Domínguez ( , 2003) ) for a survey of the literature analyzing the effect of intervention on the volatility of exchange rates. [START_REF] Wan | Effects of Japanese Intervention on Yen/Dollar Exchange Rate Volatility: A Conditional Jump Dynamics Approach[END_REF] find that foreign exchange interventions by the Japanese authorities were effective not only in altering the exchange rate level, but also in volatility reduction. On the other hand, results in [START_REF] Chen | The Effectiveness of Joint Intervention on the Yen/US Dollar Exchange Rate[END_REF] suggest no significant difference between the effectiveness of joint intervention and independent intervention on the yen/US dollar exchange rate during the 15 August 1996-6 January 1999 period. Finally, [START_REF] Ramchander | The Impact of Federal Reserve Intervention on Exchange Rate Volatility: Evidence from the Futures Markets[END_REF] show that Fed intervention is associated with negative changes in the US$/ volatility during the 1985 to 1993 period as a whole, and specifically during the 1 January, 1985 to 21 February, 1987 Plaza period and the 21 February, 1987 to 31 December, 1989 Louvre period. assuming that the intervention can be characterized as leaning against the wind: a depreciation of the Yen should normally be followed by the sale of Dollars 8 .

The test is applied to daily exchange rate and intervention data and calculated for monthly periods (i. e., the frequencies needed to construct the statistic are obtained for each month of the sample period) 9 . The sign of the exchange rate trend is measured by the difference between the current value s t and the previous value s t-k , where k=1,5,10,20,30,40,60.

The Pesaran and Timmermann (DA, 1992) test is a directional prediction test of changes under the null hypothesis that the actual and predicted values are independent.

The distribution of the DA statistic is N(0,1), which has the following structure: ( )( )

1 1 1 1 1 1 ˆp p p p SRI - - + =
, SRI being the success ratio in the case of independence between actual and predicted values under the null hypothesis. The other elements are:

[ ] ∑ = - > = H h h h y I H p 1 1 1 0 , [ ] ∑ = - > = H h h h y I H p 1 1 1 0 ˆ, ( ) ( ) [ ] SRI SRI H SR - = - 1 var 1 and ( ) ( ) ( ) ( ) ( ) ( )( ) [ ] 1 1 1 1 1 1 2 1 1 1 2 1 2 1 1 4 1 1 2 1 1 2 var p p p p p p p p p p H H SRI - - + - - + - - = - .
In the case of ex post interventions, the actual values are the exchange rate trends and the predicted values are the signs of the interventions. The contrary is true when ex ante interventions are considered. The description of this application is presented in Table 1.

[Table 1, here] For the analysis of the intention of the monetary authorities (ex-ante interventions) the description of each variable and function of the test is presented in the second and third columns. The analysis of the efficacy is explained in the forth and the fifth columns.

[Table 2, here]

The results for exchange-rate interventions by the Federal Reserve (FED) are reported in Table 2. Panel A suggests that the FED showed willingness to maintain the exchange rate only in specific subperiods. In particular, the Pesaran-Timmermann test indicates the years 1980 (coinciding with explicit commitments by the US and Japanese economic authorities) and 1987 (when the Louvre Accord was signed to stabilize 8 We adopt this approach because standard time-series techniques may not be appropriate when dealing with the study of foreign market intervention and the associated behaviour of exchange rates. Exchange rates are highly volatile and interventions are usually sporadic (Fatum andHutchison, 2003, 2005). In contrast, [START_REF] Frenkel | On the Determinants of Small and Large Foreign Exchange Market Interventions: The Case of the Japanese Interventions in the 1990s[END_REF] estimate a reaction function for sterilised interventions by the Japanese monetary authorities and find major interventions after 1995 in reaction to the previous exchange rate trend. 9 To calculate these frequencies we only consider the number of days in a given month in which the monetary authority intervened. Therefore, our results suggest signs of the presence of a target zone in 1980 and 1987. The later year coincides with the time of the Louvre Accord among the leading industrial nations. There are several papers analysing the Louvre Accord as a targetzone experiment due to its commitment towards the coordination of macroeconomic policies in order to stabilize the exchange rates [see, e. g., Ito (1999) and [START_REF] Nakamura | The Postwar Japanese Economy: Its Development and Structure, 1937-1994[END_REF]]. However, the presence of bands for the Yen/Dollar exchange rate in 1980 is an episode which has not previously been identified as a period where an implicit band regime was operating. Therefore a background account of such episode is necessary. In this sense, it should be remembered that, in 1979, as inflationary pressures at the wholesale level built up drastically and the current account was pushed deep into deficit, the Yen caved heavily on offer and depreciated sharply in the exchange market. In 1980, the year just after the tripling of oil prices, inflation as measured by the GDP deflator remained at only 5 percent. This suggest that homemade inflation was avoided, confirming that the Bank of Japan (BOJ) had both the ability and the intention to maintain price stability. In this sense, there were a series of coordinated changes in interest rates in the U. S. and Japan that did not leave the Yen/Dollar exchange rate unaltered [START_REF] Bomhoff | The Dollar-yen Exchange Rate[END_REF]. Trust in the BOJ was preserved, keeping expected inflation at a very low level and the actual inflation not deviating from expectations by any significant amount [START_REF] Suzuki | The Japanese Financial System[END_REF]1989) 12 . In addition, as documented in [START_REF] Cargill | The Political Economy of Japanese Monetary Policy[END_REF], the BOJ reacted very quickly selling Dollars in support of the Yen, sharply dropping its international reserves. This appreciation helped the Bank of Japan to moderate inflation. Following the adoption of more restrictive fiscal and monetary policies to stabilize the Yen in March, the main central banks announced a closed cooperation to prevent the Yen from declining excessively. By mid-April, with interest rates falling in the United States, the Yen began to recover along with other major currencies [see, e. g., OECD (1980OECD ( , 1981) ) and [START_REF] Pardee | Treasury and Federal Reserve Foreign Exchange Operations[END_REF][START_REF] Pardee | Treasury and Federal Reserve Foreign Exchange Operations, August 1980-January 1981 Semiannual Report[END_REF]]. In May, the BOJ intervened to counter disorderly conditions. The support of a firm inflationary effort from the new government after parliamentary elections in June reinforced the bank's credibility. Market participants become aware that Japan was achieving a rapid F o r P e e r R e v i e w adjustment to higher world oil prices, the Yen being remarkably resilient in the face of the prospective fall in oil production resulting of hostilities between Iran and Iraq. The BOJ intervened once more in September to moderate the rise of the Yen. After a series of financial measures, and given the strength of exports and investment demand, exchange rate sentiment became more favourable for the yen.

Regarding the directions of interventions during 1980, Schwartz (2000) suggests that the Fed acquired yens in the market from February to March 1980, and from late March it sold yen. By the end of July, the US monetary authorities were ageing accumulating yens. From September 1980 to February 1981, the aim of the Fed was to cushion the rise of dollar, acquiring yens to pay off swap debts. This behaviour is consistent with the detailed account provided in [START_REF] Pardee | Treasury and Federal Reserve Foreign Exchange Operations[END_REF][START_REF] Pardee | Treasury and Federal Reserve Foreign Exchange Operations, August 1980-January 1981 Semiannual Report[END_REF]:

i) in February the BOJ intervened to moderate the decline of the yen, supplementing its intervention in Tokyo with operations in New York through the Federal Reserve Bank of New York.

ii) in March there was a joint initiative by the BOJ, the FED, the Bundesbank and the Swiss National Bank to support the yen in the exchanges, indicating the FED its willingness to purchase yen in the New York market for its own account and to provide resources to the BOJ if needed. The sales of dollars by the Bank of Japan were reflected in the US$2.2 billion decline of foreign reserves during February-March. Meanwhile, the Fed bought US$216.8 million equivalent of yen in the New York market in coordinated operations with the BOJ.

iii) in April the Bank of Japan continued to intervene forcefully to defend the yen, buying back about half of the amount of dollars it sold earlier.

iv) in July, reserves increased by US$2.0 billion. v) in late September-early October, the BOJ intervened in the foreign exchange market, due to a substantial improvement in Japan's current account position and to heavy demands for yen-denominated assets, producing the rise of the yen. This operation contributed to a US$2.2 billion increase in foreign reserves.

vi) from early November the Yen/Dollar rate started to fluctuate around 212, finally dropping to 216.75. The interventions by the Fed and by the Bank of Japan suggest the presence of a crawling band.

Finally, it should be noted that, although Japan is by far the largest participant government in the foreign exchange market (see [START_REF] Fatum | Effectiveness of Official Daily Foreign Exchange Rate Intervention Operations in Japan[END_REF], the analysis of Japanese interventions was restricted by the availability of data (from March 1991 only). Though quite weak in April and August 1992, which might signal a lack of independence, in general the results do not seem to reject the hypothesis of independence 13 . With respect to the results obtained for 1987 and in relation to the FED, from 1987 up to 1992, Japanese monetary policy appears to have been conditioned by the Louvre Accord. In this sense, it is interesting to recall that large-scale, coordinated interventions, as those implied by the Louvre Accord, seem to have been very successful, as documented in Fatum and Hutchinson (2005) and Huang and Neum (2006). Indeed, the BOJ recognized the relevance of the stabilisation of the exchange rate, as its monetary policy was based in the reduction of short-run interest rates as a response to the growing external surplus and the subsequent appreciation of the Yen. This policy accelerated the increase of the asset prices until the collapse of the bubble. In fact, Hetzel (2004) pointed out that the initial shock had a monetary character. In addition, Leigh (2004) detected several negative monetary shocks in that period, something that could have been justified by the desire of the Japanese monetary authorities for a de facto smaller flexibility of the exchange rate.

Credibility and speculative pressures

In this section we study the degree of credibility for the implicit band regimes suggested by the analysis developed in the previous section and we check the degree of exchange market pressure for the Yen/Dollar exchange rate.

Regarding the credibility for the period going from 30 April to 31 December 1980, the implicit central parity is estimated by a least squares regression in which only a trend and a constant are included. The estimated central parity is shown in Figure 3. It should be noted in passing that this central parity coincides with the equilibrium Yen/Dollar rate for the year 1980 as suggested in Ito (1992, Figure 10.2). A band of ±6% is considered to include all observations falling within it during the aforementioned period 14 . From the analysis carried out in the previous section and from OECD reports, we assume a constant appreciation of the Yen/Dollar exchange rate within the implicit fluctuation bands.

As for the period going from 23 February to 18 October 1987, following [START_REF] Funabashi | Managing the Dollar: From the Plaza to the Louvre[END_REF] and [START_REF] Esaka | The Louvre Accord and Central Bank Intervention: Was There a Target Zone?[END_REF] we assume a target zone with a central rate of 153.50 Yen/Dollar and a band of ±5%, being the central rate, which was rebased on 7 April 1987 up to 146 Yen/Dollar to reflect new market conditions. The latter central parity is consistent with the results reported in Bergsten and Chen (1987), suggesting an equilibrium Yen/Dollar rate of 140-145 during 1987. Figures 5 and6 illustrate the evolution of the Yen/Dollar exchange rate, adding the central parities and the band for the two periods studied.

[Figures 5 and6, here] Credibility is analysed using three indicators: the Svensson simple test, the drift adjustment method and an inverse measure of the probability of realignment. [START_REF] Svensson | The Simplest Test of Target Zone Credibility[END_REF] provided a simple test to study the credibility of a target zone exchange rate regime with fluctuation bands. We calculate a 100% confidence interval for the expected rate of realignment of the Yen/Dollar exchange rate using the three-month interbank rate. Taking into account the uncovered interest parity hypothesis, the expected rate of realignment is bounded according to:

[ ] (1) / ) ( / / ) ( * * τ τ τ τ t t t t t t t t t t x x i i c E x x i i - - - ≤ ∆ ≤ - - - +
where x t is the deviation of the log exchange rate s t from the log central parity c t , t x and t x are the lower and upper bounds of the exchange rate bands, τ is the maturity (valued 14 This band has been chosen as an exploratory proposal and hence the results must be interpreted in relative terms, i.e. as a comparison of the different subperiods during the period studied, in this case 1980. The results of this test for 1980 and 1987 are shown in Figures 7 and8 respectively. As can be seen in both cases, the hypothesis of a realignment expectation equals to zero cannot be rejected. Nonetheless, in 1980 the expected rate of revaluation grows during the early part of the period, reaching its highest values around June. This behaviour was probably related to trader caution due to the upcoming parliamentary elections on 22 June, particularly in view of the sudden death of Prime Minister Ohira which added further uncertainty to the election campaign. The lowest values of the expectation of revaluation occur in August, most likely due to the outbreak of hostilities between Iran and Iraq [see, e. g., [START_REF] Pardee | Treasury and Federal Reserve Foreign Exchange Operations[END_REF][START_REF] Pardee | Treasury and Federal Reserve Foreign Exchange Operations, August 1980-January 1981 Semiannual Report[END_REF] and (OECD, 1980(OECD, , 1981))]. Furthermore, in the case of 1987 this measure could reflect both the existence of revaluation expectations at the end of March, just before the supposed change in central parity from 153.5 to 146 Yen/Dollar, and of the expectations of devaluation of the Yen at the end of July.

[Figures 7 and8, here]

The second indicator to gauge the degree of credibility is the drift adjustment method. This method, originally proposed by [START_REF] Bertola | Stochastic Devaluation Risk and the Empirical Fit of Target Zone Models[END_REF], computes an econometric estimate of the expectations of economic agents regarding the realignment. These realignment expectations constitute an inverse measure of credibility. The procedure involves estimating the expected rate of variation of the exchange rate within the band in the absence of realignment, and then computing the expected rate of realignment g τ t . Once g τ t has been estimated, the corresponding 90% confidence intervals can be calculated.

In this paper we have estimated the expected rate of depreciation within the bands using a linear regression model where the exchange rate and the domestic and foreign interest rates are taken as explanatory variables:

(2)

3 * 2 1 τ τ ε β β β α τ + + + + + + = - ∑ t t t t j j j t t i i x d x x
where x t+τ and x t are the exchange rate (log) deviation from the central parity at times t+τ and t, respectively. In the case of the 1987 bands, the variables d j denote the dummies for the subperiods defined by the realignment on 7 April suggested by [START_REF] Esaka | The Louvre Accord and Central Bank Intervention: Was There a Target Zone?[END_REF].

Figures 9 and 10 show the expected rate of realignment and the 90% confidence intervals for the studied periods of 1980 and 1987, respectively. As for the year 1980, expectations of revaluation are confirmed as increasing in May and June, as well as in December, following the announcement early that month by the Ministry of Finance that it would increase the quotas available to Japanese and foreign banks for swapping Dollar borrowing into Yen. This announcement gave more scope for capital inflows and improved market sentiment for the Yen. The expected rates of realignment greater than zero are obtained in August. With respect to 1987, the method enables us to reject the hypothesis of null expectations of a realignment during the more critical stages of the period studied. Thus, it clearly reflects both the expectations of revaluation in March, May-June and August-September, and the expectations of devaluation in July and October. These results are very similar to those obtained by Esaka (2000, p. 123).

[Figures 9 and 10, here] Lastly, the probability of non-realignment is obtained using Logit estimation.

Here we have introduced the exchange rate, the distance to central parity and the interest rate differential as the explanatory variables. The selection of these variables stems from our interest in estimating credibility with high frequency data.

Assuming there is no credibility when y t =0 and that when y t =1 there is credibility, we use the drift-adjustment method to design the Logit model. As explained above, the method estimates the 90% confidence interval. If both limits of the interval were simultaneously greater than, or less than, zero, the agents would have expected realignments with 90% confidence and y t =0, otherwise y t =1.

The probabilities estimated from the exchange rate, distance to central parity and the interest rate differential (not shown here to save space, but available from the authors upon request) suggest that, when the exchange rate is used as the explanatory variable in estimating the probability of non-realignment, May 1980 could be classified as a low-credibility month. When distance to central parity is used, credibility is reduced in August and at the beginning of December 1980. Finally, there is evidence of an increase in credibility from August until December, with some marginal credibility losses in October and December.

Regarding the 1987 period, when the exchange rate is used, the probability of non-realignment would have been lower at the end of February and in March 1987, as well as at the end of July and the early days of August of that year. Alternatively, when using the distance of the exchange rate to the central parity, the results suggest that the probability of realignment is higher during May and in the latter part of July. Finally, the use of the interest rate differential confirms the lowest credibility in March, as well as suggesting marginal credibility losses in July.

In recent years a number of researchers have claimed success in predicting currency crises. To that end, a definition of crisis has been necessary. Therefore, as a complementary analysis of the credibility measures, we calculate two exchange market pressure indices in order to know how robust the bands were. Both indices are weighted average of monthly percentage depreciations and monthly percentage reductions in reserves 15 . Both indices increase just before the beginning of the subperiod of 1980 (Figures 11 to 14). In fact, they exceed the critical level in one case, and decrease all during 1980. This suggests that the implicit band could have mitigated the speculative behaviour in the exchange market. The implications for the 1987 subperiod are less clear.

[ Figures 11 and 14,here] 15 The weights used by Edison (2003) incorporate the standard deviations of the exchange rate and the reserves, while [START_REF] Kaminsky | Leading Indicators of Currency Crises[END_REF] introduce the standard deviations of the variations of the exchange rate and the reserves. Furthermore, in the first paper the critical level to consider a currency crisis is the mean plus 1.5 times the standard deviation of the index, while in the second one is the mean plus 3 times the standard deviation of the index.

Concluding remarks

In this paper we have attempted to identify implicit exchange rate regimes for the Yen/Dollar. This particular rate was chosen because it is generally viewed as being the most flexible of all the exchange rates in the world economy. Confirmation of the existence of such regimes has major empirical implications given the widespread comparative use made of the rate.

To that end, we have applied different statistical approaches to data covering the period 1971-2003. Our results indicate that implicit regimes, excluding flexible ones, would have seemed to exist. An approach based on the use of exchange rate data to find de facto bands suggests that such regimes are present, but the results obtained are not informative. A more realistic method considers central bank interventions in the foreign exchange markets in order to study the intention (and efficacy) in maintaining the exchange rate within certain limits.

A directional prediction test has been applied, as standard time-series techniques may not be well suited to the study of the relationship between exchange rates and foreign exchange interventions. This test considerably restricts the implicit band regimes for the Yen/Dollar exchange rate. In the case of the Fed, the intention and efficacy of interventions are suggested for two subperiods: April-December 1980 and March-October 1987, the latter coinciding with the Louvre Accord.

To the extent that the market learns about the intentions behind central bank stabilizing interventions, an announcing hypothesis can also be considered. A study of the credibility of implicit bands was therefore undertaken for both subperiods mentioned above. Several critical events for the Yen/Dollar exchange were detected. For the episode of implicit bands detected for the year 1980, all the indicators reflect a lack of credibility in June, August and December. For the period identified around the Louvre Accord in 1987, there is evidence of credibility losses in May and June. For the remaining subperiods, the credibility indicators suggest a high degree of confidence by agents regarding the exchange rate's evolution within the implicit bands. This, in turn, could be considered to be further evidence supporting the existence of implicit fluctuation bands that compromised the behaviour of the Fed and the Bank of Japan in the exchange rate markets.

This paper has demonstrated the potential usefulness of a sequential procedure to detect implicit bands, taking into account both the dynamics of the exchange rate and the interventions of central banks. In our opinion, the results obtained suggest that further consideration of this procedure for other exchange rates could prove to be a fruitful exercise.

From the empirical point of view, central banks should be more transparent when communicating their interventions in foreign exchange markets, even providing researchers with the actual data involved in these operations. Where this is not possible, extensive literature exists to suggest alternative, more realistic measures of interventions other than changes in foreign reserves [see, e. g., [START_REF] Quirk | Exchange Rate Policy in Japan: Leaning Against the Wind[END_REF], [START_REF] Dornbusch | Exchange Rate Economics: Where Do We Stand?[END_REF], [START_REF] Gärner | Intervention Policy Under Floating Exchange Rates: An Analysis of the Swiss Case[END_REF] and [START_REF] Hodgman | Central Bank Exchange Rate Policy[END_REF]]. M12 1972 M5 1974 M10 1975 M3 1977 M8 1978 M1 1980 M6 1981 M11 1982 M4 1984 M9 1985 M2 1987 M7 1988 M12 1989 M5 1991 M10 1992 M3 1994 M8 1995 M1 1997 M6 1998 M11 1999 M4 2001 M9 2002 M2 2004 M7 2005 M12 2006 Average variation Critical region M12 1972 M5 1974 M10 1975 M3 1977 M8 1978 M1 1980 M6 1981 M11 1982 M4 1984 M9 1985 M2 1987 M7 1988 M12 1989 M5 1991 M10 1992 M3 1994 M8 1995 M1 1997 M6 1998 M11 1999 M4 2001 M9 2002 M2 2004 M7 2005 M12 2006 Average

  period 5 . Figures5 and 6show the results for ±1% and ±2% fluctuation bands, respectively.

  for most of the values of k. In the rest of the sample period the null hypothesis of independence is not rejected. These conclusions can be confirmed in Panel B, where the efficacy of the interventions is analysed. For several months in 1980, as well as in August of 1987, interventions seemed to have been effective 10 11 .

  12 for a 3-month maturity), i-i* is the interest rate differential and E[•] is the expectation operator.

  Figure 1

  Figure 4

Table 1 .

 1 Description of variables incorporated to the Pesaran-Timmermann test for the analysis of intention and efficacy

	variation	Critical region

Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK

  : the results for periods with Student-t close to 0.00 are omitted.

				Table 2
				Pesaran-Timmermann Test
	Months				k-values (days)
		1	5	10	20	30	40	60
				Panel A: ex-post
	1980-Jan	1.35	0.89	-0.78	1.41	0.45
	1980-Mar					2.00	2.00	2.00
	1980-Apr	3.03	2.27	1.73	1.13	1.48	1.48	1.48
	1980-May	1.59
	1980-Jul	1.11	0.50	-0.13	1.01	1.75	2.52	2.52
	1980-Aug	0.88	0.76	0.76	1.78	4.01	4.01	4.01
	1980-Nov	2.44	1.89	3.62	-0.33	1.89	1.09	1.01
	1980-Dec	-0.80				0.60	2.11	2.11
	1981-Jan	1.20	2.25	-1.52	0.95
	1982-Oct	0.71	0.71	0.71	0.71	0.71	0.71	0.71
	1987-Mar	1.98	3.02	3.02	3.02	3.02	3.02	3.02
	1987-Aug	2.14	2.86	2.14	2.86	2.86	2.86	2.86
	1988-Sep	0.71	0.71		0.71	0.71	0.71	0.71
	1989-Apr	0.71	0.71		0.71	0.71	0.71	0.71
	1989-May	1.50
	1989-Jun					2.00	2.00	2.00
	1989-Jul	1.00						1.00
	1990-Mar		1.41	1.41	1.41	1.41	1.41	1.41
				Panel B: ex-ante
	1980-Jan	0.78	-1.81	0.45
	1980-Mar						2.00	2.00
	1980-Apr	-0.43 -1.54
	1980-May	-1.26 1.59				-0.60
	1980-Jul	-1.26 1.75	1.75	2.52	1.75	-0.19
	1980-Aug	1.14	-0.54	-0.29
	1980-Nov	-0.63 0.92	1.09	-0.33
	1980-Dec	0.60	-0.40					-0.40
	1981-Jan	-1.20 0.92	1.34	0.51
	1982-Oct		0.71	0.71		0.71	0.71	0.71
	1987-Mar	0.66						0.43
	1987-Aug	0.48	-0.65	2.09	2.86	2.86	2.09
	1988-Sep	0.71	0.71		0.71	0.71	0.71	0.71
	1989-May	0.85	0.47	0.37	0.47	0.75	0.66	0.47
	1989-Jun					2.00

Note

See Coudert and Dubert (2004) for a survey of studies on implicit exchange rate regimes.[START_REF] Reinhart | The Modern History of Exchange Rate Arrangements: A Reinterpretation[END_REF] examine the relevance of the exchange rate regime classifications for empirical macroeconomics.

For example,[START_REF] Ito | What Promotes Japan to Intervene in the Forex Market?[END_REF] and[START_REF] Frenkel | On the Determinants of Small and Large Foreign Exchange Market Interventions: The Case of the Japanese Interventions in the 1990s[END_REF] estimate the Japanese monetary authorities' reaction function.

Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript

We are grateful to an anonymous referee for suggesting this sensitivity analysis using deviations from purchasing power parity.

In order to assess the robustness of results, we additionally apply the Fisher's Exact Test. This test of independence (for 2x2 tables) is used when the members of two independent groups can fall into one of two mutually-exclusive categories. In our case, each day in a given month can fall into one of two categorical variables: the sign of the exchange rate trend and the sign of the intervention. The former may give two levels (appreciation or depreciation of the Yen) while the latter indicates the purchase or sale of Dollars. The results confirm those obtained from the Pesaran-Timmermann test. Again, the results for Japanese interventions are less informative and the independence hypothesis could not be rejected for the whole sample period.

Based on an event study methodology,[START_REF] Fatum | Effectiveness of Official Daily Foreign Exchange Rate Intervention Operations in Japan[END_REF] analyse the Yen/Dollar exchange rate and find evidence that intervention affects the rate in the short term.[START_REF] Taylor | Is Official Exchange Rate Intervention Effective?[END_REF] also obtains evidence supporting the view that interventions increase the probability of stability (only when the exchange rate is misaligned) in a Markov-switching model.

It should be noted that, despite the aggressive actions taken by the BOJ to contain inflation and the importance of imported crude oil to Japan, the effect of the oil price on output appears to be moderate[START_REF] Hetzle | Japanese Monetary Policy: A Quantity Theory Perspective[END_REF], with Japan being the only major industrial country to avoid recession[START_REF] Cargill | The Political Economy of Japanese Monetary Policy[END_REF].

Schwartz (2000) argues that the strong Yen did not weaken as a result of interventions and sterilisation of Dollar purchasing. However, Pinto de Andrade and Divino (2005) attribute a major role to exchange rates in accounting for cyclical patterns of the interest rate. In this sense, the Bank of Japan appears to have attempted to stabilize the exchange rate via interest rates.

St. Louis) for kindly providing the data set on official interventions used in this paper. Financial support from the Spanish Ministry of Science and Technology (SEJ2005-09094/ECON) is also gratefully acknowledged.