ExchRateReg&EconPerfmce

8/10/2019 ExchRateReg&EconPerfmce

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EXCHANGE RATE REGIMES AND

ECONOMIC PERFORMANCE1

Eduardo Levy-YeyatiUniversidad Torcuato Di Tella

Federico SturzeneggerUniversidad Torcuato Di Tella

October 2000

Preliminary draft. Comments welcome.


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1. INTRODUCTION

The proper assessment of costs and benefits of alternative exchange rate regimes has beena hotly debated issue and remains perhaps one of the most important questions ininternational finance. The theoretical literature has concentrated in understanding thetradeoff between monetary independence and credibility implied by different exchange

rate regimes, as well as in the insulation properties of each arrangement in the face ofmonetary and real shocks.2Recent episodes of financial distress have refocused the

discussion, by introducing the question of which exchange rate regime is better suited todeal with increasingly global and unstable world capital markets.3In particular, given the

increasing importance of international capital flows and the predominance of externalover domestic monetary shocks, the traditional tradeoff has narrowed down to a pricestability-growth dilemma. More precisely, while fixes are expected to increase the

credibility of non-inflationary monetary policies, reduce exchange rate variability and,through these two effects, reduce interest rates, thus fostering trade and growth, floats areseen as allowing the necessary price adjustments in the face of external (real and

financial) shocks at the expense of higher uncertainty on macro policies and potentiallyhigher interest rates. Surprisingly, in light of the relevance of this questions, empirical

corroboration of these facts is considerably behind the theoretical discussion, withopinions about the real impact, if any, of exchange rate regimes, diverging substantiallyand mostly following the subjective views of each author on the matter.

This lack of consensus on the subject has been paralleled by recent developments in the

real world. The latest years have witnessed an unprecedented number of changes ofexchange rate regimes, in a way that seems to provide partial support to almost any view

about the long run trends in the choice of regimes. Thus, while the inherent vulnerabilityof intermediate exchange rate arrangements to sudden aggregate shocks revealed by thenotorious collapses of pegs or managed floats in South East Asia and Latin America have

suggested to some observers the convenience of more flexible regimes, a number of


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the Bretton Woods period in which fixes were dominant due, to a large extent, to political

reasons, to concentrate in the recent period of increasing financial integration, in which,

we believe, the linkage between exchange rate regimes and the real economy was of adifferent nature.

Secondly, our analysis uses a new classification, described in detail in Levy-Yeyati and

Sturzenegger (2000), that groups exchange rate regimes according to the actual behaviorof the main relevant variables, as opposed to the traditional classification compiled by the

IMF based on the de jure(i.e., legal) regime that the countrys monetary authoritiesdeclare to be running.5By doing this, we refine the analysis substantially. On the one

hand, we avoid the misclassification of pegs that pursue independent monetary policies(and eventually collapse) or floats that subordinate their monetary policy to smooth outexchange rate fluctuations, which may bias the statistics of the tests towards lack of

significance, or may result in incorrect interpretations. In addition, the new classification(henceforth denoted LYS) distinguishes high from low volatility economies, providing anatural way to discriminate the impact of the regime in tranquil and turbulent times.6

Third, the paper, in addition to looking into the issue of how exchange rate regimes affect

inflation and growth, also discusses the impact of exchange rates on the cost of capital, asmeasured by the real interest rate, something which, to our knowledge, has not been doneyet in the literature. The issue has important policy implications inasmuch as lower

interest rates (as a result of lower inflation expectations) are typically invoked as a keyargument in favor of fixed exchange rates (and more recently, of the full adoption of a

foreign currency as legal tender).

Finally, contrasting results using the LYS and the IMF-based classification sheds light onthe announcement value of de jurearrangements, above and beyond the actual behaviorof the regime (the deeds vs. words comparison). More precisely, by crossing the de

factointermediate regimes with the de jureregime assigned by the IMF, we are able to


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Our main results are the following:

1.

Fixed exchange rate regimes seem to have no significant impact on the inflation levelwhen compared with pure floats, while intermediate regimes are the clearunderperformers. Moreover, among the countries that we classify as having anintermediate regime, those that claim to be fixes appear to be no different from the

rest. In short, words do not seem to provide additional benefits in terms of lowerinflation.

2. Pegs are significantly and negatively related with per capita output growth in non-industrial countries. On the other hand, de jure pegs that devalue exhibit faster growth

than its counterparts that defend the regime. Thus, in this case, deeds seem to matter:those countries that fixed and actually defended their regime were negativelyrewarded, growing less than those which eventually allowed their exchange rates to

float.3. Output volatility declines monotonically with the degree of regime flexibility.4. Real rates appear to be lower under fixed exchange rate regimes than under floats.

Indeed, de facto intermediate regimes that claim to be running a peg benefit fromlower rates, that is, in this case words (rather than deeds) matter.

The following section describes briefly the LYS and IMF classification used in the tests.Section 3 presents the data and the main empirical findings. Section 4 discusses the

implications and caveats of our approach, and outlines some areas for future research.

2. EXCHANGE RATE REGIME CLASSIFICATION

LYS classification


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The data provides a yearly figure for each classification variable for all countries reported

in the IFS, for the period 1974-1999.9The idea of the LYS classification is that,

according to the behavior of these three variables, we should be able to identify theexchange rate regime that a country is actually following. A textbook flexible exchangerate regime is characterized by little intervention in the exchange rate market togetherwith high volatility of exchange rates. Conversely, a fixed exchange rate regime should

display little volatility in the nominal exchange rate while reserves fluctuate substantially.Finally, an intermediate regime corresponds to the case in which volatility is relatively

high across all variables, with exchange rates moving in spite of active intervention.10

Table 1 summarizes the patterns that, a priori, should be expected for the different

regimes in terms of the three classification variables:

TABLE 1

ME DE MR

Inconclusive Low Low LowFlexible High High LowDirty Float Medium Medium Medium

Crawling Peg Medium Low Medium/HighFixed Low Low High

Note that countries that do not display significant variability in either variable are labeledas inconclusive. Underlying this label is the hypothesis that those countries, which arenot subject to sizeable shocks, should tell us little about the real impact of the regime, andthat their inclusion in our econometric tests should bias the regime coefficients


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K-means procedure is applied to re-normalized values, again allowing for five groups.

The two-stage procedure allows to differentiate 1 stand 2ndround regimes. Thus, a country

assigned to the fix group in the first round is denoted a 1st

round fix.14

IMF classification

As we mention above, we also conduct our tests using an IMF-based classification for the

purpose of comparison with previous work, as well as to address issues related with theannouncement value of an exchange rate regime, particularly in the case of pegs.15The

IMF has changed the way it classifies exchange rate regimes over the years. Prior to1998, the IMF allowed three basic categories: pegs, limited flexibility and moreflexibility. These, in turn, allowed for several subgroupings. After 1998, the classification

was changed to an eight-way grouping: no separate legal tender, currency boards,conventional fixed, horizontal bands, crawling pegs, crawling bands, dirty float and freefloats. In general, however, both categories allow a straightforward grouping of countries

into different forms of pegs (to a single currency, or to a disclosed or undisclosed basket),intermediate regimes (crawling pegs, bands, managed floats, cooperative arrangements)

and pure floats. As of late, the IMF started to acknowledge the difference between deedsand words by reporting, in some cases, countries with a formal regime and a different defacto one.16In what follows, we deliberately ignore this distinction and assign countries

according to their legal arrangement.

That both classifications are substantially different should be clear from Levy Yeyati andSturzenegger (2000), where we show that a mismatch index constructed as thepercentage of mismatches for any given year hovers around 50% of all cases. As we

show in that paper, the index is higher if we only consider 1 stround countries. There wealso discuss at length the differences between both data sets. According to the de jure

classification used by the fund, the number of countries running a fixed exchange rate


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The data

Our starting sample covers annual observations for 159 countries over the period 1974-1999. Our primary regime index is based on the LYS classification, which applies to asample of 2640 observations, of which 613 are labeled inconclusive in the second roundand therefore excluded. Table 2 shows the LYS classification of the remaining 2027

observations, along with the alternative IMF-based classification for the same group ofobservations.

TABLE 2

Regime 1st round 2ndround Total IMF

Float 431 219 650 430Intermediate 270 298 568 699

Fix 355 454 809 898

Total 1,056 971 2,027 2,027

All our data, including those used in the construction of the classification as well as the

controls in the regressions, comes from the International Financial Statistics of the IMF,

with two exceptions. Real GDP numbers are taken from the IMFs World EconomicOutlook and terms of trade are from the World Banks World Development Indicators.

Data availability varies across countries and periods, so that the tests in each subsectionwere run on a consistent subsample of observations (which is reported in each case along


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Table 3 provides a first glance at the data. The table shows the means and medians of

inflation and inflation volatility for each of our control groups, namely, the floating,intermediate and fixed exchange rate regimes according to the IMF and the LYSclassification (the latter being further disaggregated into 1 stand 2 ndround).1819Thesample of 994 observations comprises observations for which all variables used in the

econometric tests were available, after excluding the 1% upper tail of inflationdistribution (roughly, observations for which annual inflation exceeds 200%).

The first thing to be noted from the table is the fact that, for both classifications, the

intermediate regimes are the ones who fare the worse in terms of inflation. However,there are two important differences in this respect between classifications. Whereas theIMF index seems to indicate, surprisingly, that fixes are associated with slightly higher

inflation levels, the LYS index finds no difference between fixes and floats. This is alogical consequence of the fact that the IMF classification does not distinguish betweensuccessful and collapsing pegs, thus including in the fix group countries that displayed

high inflation levels as a result of a currency crisis.

More importantly, the difference between the three types of regime virtually disappearsonce we focus on the second round (low volatility) observations, confirming the intuition,mentioned above, that the influence of exchange rate regimes are sizeable only when they

are put to test. The same picture is given by the comparison of inflation volatility. Whilea de jure index suggests that intermediate regimes are associated with more predictable

inflation, the de facto classification regards as intermediate regimes both failed pegs andlegal floats under stress, leading to lower predictability. Again, it can be seen from thetable that this is largely reflecting the pattern of first round observations.

Of the two channels mentioned above through which a regime (and particularly, a peg)

may influence inflation, perhaps the most important is the discipline that it may impose


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These first impressions are confirmed by our econometric tests. We start from a standard

money demand equation to obtain:

= m- GDP+ i+ v, (1)

where all variables are in logs. Here, represents the inflation rate, mis broad money,

GDPis real output, iis the nominal interest rate, vis money velocity, andand arepositive constants. As mentioned, the exchange rate regime may affect inflation indirectly

through its disciplinary effect on m, as well as directly through lower inflationexpectations. While it is not completely clear how this last channel may be modeled, a

first assessment of this credibility effect may be obtained by including regime dummiesin the money demand equation (1). In addition, we include a measure of the openness ofthe economy (OPEN) to control for the potential disciplinary effect elicited by

international arbitrage.21Finally, we add the lagged dependent variable as a regressor tocapture for the effect of past policies on current expectations, as well as to control for the

possibility of backward-looking indexation.

The results, presented in Table 4, are largely consistent with those sketched in the

previous discussion.22The coefficients for real GDP, money, openness and interest rategrowth (resp. GDP, M2, OPENand INTRATE), as well as lagged inflation

(INFLATION1), are all highly significant and of the expected sign, with the onlyexception of real GDP growth for the first round regressions. Indeed, both classifications

yield essentially the same results when applied to the whole sample.23While fixes andfloats do not differ significantly from each other, intermediate regimes display higher

inflation rates on average, although the significance level improves substantially whenthe LYS is used. Again, this is related to the fact that, under the de facto classification,collapsing pegs are excluded from the fixes.24However, as before, the link between

intermediates and inflation reflects the behavior of high volatility observations, as


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The mismatch between the IMF and the LYS classification captures, among other things,

the presence of numerous cases of legal pegs that run independent monetary policies that

eventually makes them unsustainable. This opens the question of whether theannouncement of a fixed exchange rate has a benefit in terms of inflation, for a givenmonetary policy, thus justifying this seemingly inconsistent behavior. To address thispoint, we run the regressions of inflation and money growth for a sample that excludes de

facto pegs, controlling for IMF (de jure) fixes. In either case, the announcement of a pegdoes not seem to provide any significant benefit in terms of lower inflation to those

countries that do not effectively sustain it.

On the other hand, as expected, true fixes (i.e. both legally and de facto) display lowerinflation and money growth when compared with legal fixes that are not classified assuch by the LYS index. However, the results are not statistically significant.

A final potentially interesting distinction is made when we split the sample into industrialand non-industrial countries, following the IMF denomination.25The results show that

regimes appear to be important only for the latter.26

In sum, we find no evidence of a systematic link between either floating or fixedexchange rate regimes and inflation, nor any evidence that the announcement of a peg hasan impact in itself, beyond and above what the country actually does. On the other hand,

we find that intermediate regimes are typically accompanied by higher inflation andmoney growth rates.

Growth27

The literature on the relationship between exchange rate regimes and growth performanceis relatively scarce.28Aizenman (1991) and Ghosh and Pesenti (1994) find that the

adoption of a peg raises output volatility while fostering investment and growth Ghosh et


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peg in the event of negative external shock entails a significant cost in terms of real

interest rates, as well as increasing uncertainty as to the sustainability of the regime.29

To have a first pass at the data on this subject, Table 6 shows the means and medians ofthe rate of growth of real per capita GDP (GDPPC) and its volatility ( VOLGDPPC), for

a sample of 1079 observations, and split samples according to whether the country wasclassified in the 1 stand 2ndround by the LYS methodology.30

Simple inspection of the numbers signals a striking result:Fixed exchange ratessubstantially underperform floating exchange rate regimes, under both classifications.

According to the IMF classification, the average real per capita growth is 0.7% underfloats, while it is only to 0.3% under pegs. The difference is more remarkable when basedon the LYS index: average growth drops in this case from 1.9% to 0.3%. One of the

differences between both classifications comes from the fact that peg regimes thateventually devalue are regarded by the IMF as fix while LYS groups them as either

intermediate or float. This points at a somewhat surprising result: pegs that devaluedisplay higher growth rates than those that hold the line.31

On the other hand, the aggregate sample masks important differences between 1 stand 2 nd

round observations. While in the former intermediate cases show lower growth rates than

either fixes or floats, in the latter growth declines monotonically as we reduce exchangerate flexibility, with the difference between float and fixes widening to 2.5%.

Growth volatility behaves as described in previous work, decreasing monotonically withthe degree of flexibility of the exchange rate regime, except in the case of 2ndround

observations in which it is highest for intermediate regimes.

The table also reports the statistics of selected variables suggested by the growth

literature as the most systematically significant determinants of growth. While the


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We additionally included as controls the growth of government consumption ( GOV1),

lagged to avoid endogeneity problems, and per capita GDP at the beginning of the period

(GDPPC74) computed as the average over 1970-1973. The literature suggests a negativesign for the first variable, as it represents a less productive use of resources. Regardingthe second control, a negative sign would suggest the presence of conditionalconvergence, as poorer countries grow more rapidly than richer ones.33Finally, we

control for changes in the terms of trade (TI), which is another source of variation in

GDP.

Regression results are presented in Table 7. The table first shows the results when

regimes are grouped according to the IMF criteria, both including inconclusives (fullsample) and then excluding them. The control variables behave largely as expected: realgrowth is positively correlated with both investment and trade variations, and negativelycorrelated with government consumption. The link is less clear in the case of openness,

whereas the literature has found a positive effect.34Changes in the terms of trade displaythe correct sign in all but one case, but are only significantly positively correlated with

growth for the sample of industrial countries. Finally, the sign for the initial per capitaGDP is positive, indicating the lack of conditional convergence.

The coefficients of the regime dummies are consistent with the findings from theprevious table. Intermediates grow significantly more than the rest when the IMF index is

used. In contrast, the de facto classification reveals thatgrowth rate declinemonotonically as we go from float to fix. Interestingly, while intermediates are again theworse performers in the 1 stround group, growth under pegs is still significantly below

that under floats. On the other hand, in the 2 ndround group pegs clearly underperformintermediates and floats, which do not differ significantly from each other. A more

careful analysis of this result reveals that the negative impact of pegs is entirelyaccounted for by the group of non-industrial economies.35

It i i t t t t t thi i t th t f d f t l ifi ti h ld di l


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most cases, significant. The evidence on openness is mixed, while initial per capita GDP

display a positive and, in all but one case, significant sign.

The table shows that, with the exception of the 1 stround regression, in which the pegdoes not appear to have an impact and the intermediate regime is significant barely at11%, fixed exchange rate regimes are associated with higher real per capita output

growth volatility, a finding that is also obtained from the IMF index. The last regressionin the table shows, in addition, that the impact of the regime on output volatility is higher

for non-industrial countries.

Interest rates

While much has been said of the impact of exchange rate regimes on real wages and

employment, there is surprisingly little work on their effect on the cost of capital, whichaccounts for a larger share of production costs in most countries. Quite possibly, the

scarcity of research on the issue is due in part to the difficulty in obtaining reliableinterest rate data for a reasonably large number of countries, as in many cases interest

rates were largely administered and thus unrepresentative of actual market rates. On theother hand, episodes of very high inflation are typically characterized by negative realrates, as the banking sector sometimes is not allowed to fully accommodate extremely

high inflation expectations. Moreover, in a context of rapidly changing expectations, asmall mismatch between the time at which inflation and the nominal interest rate aremeasured may derive in sizeable distortions.

Measurement errors aside, the channels through which the exchange rate regime may

influence the real rate are by no means obvious. The case of a legal peg is a case in point.Whereas they are prone to exhibit peso problems that increase real interest rates, pegs onthe other side may reduce inflation expectations and thus nominal (and real) rates. This

last argument is consistent with the lower predicted inflation levels exhibited by pegs vis


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With all these caveats in mind, we attempted to explore the issue using a relatively broad

specification that captures some of the factors mentioned above. Thus, we include lagged

GDP growth rate to control for incentives to lower the real rate through monetarypolicies, the ratio of net interest payments over GDP (INETGDP) as a proxy for the levelof debt, the degree of openness ( OPEN) to control for international arbitrage constraints,and the ratio of fiscal surplus over GDP as an (inverse) measure of government crowding

out. We also included current inflation to control for potential measurement error due todifferences in the sampling time or to financial repression.36

We found that, using the IMF classification, real rates are significantly lower under pegs,

while both intermediate and floating regimes do not differ from each other. This result,again, can be a consequence of the inclusion of failed pegs among the fixers. Moreprecisely, unexpected devaluations may induce negative real interest rate in the aftermath

of the realignment of the nominal exchange rate. In contrast, no significant link wasdetected using the LYS index for the whole and the 1 stround samples, whereas the linkreappears in the 2 ndround regression. Indeed, this result holds true even after excluding

the intermediate dummy, as in the regressions reported in table 9. Moreover, a directcomparison between floats and fixes (i.e. running the regression excluding LYS

intermediate observations) shows that the latter are accompanied by significantly lowerreal rates.

We then focus on whether announcement of pegs has any impact on the real rate forintermediate and floating regimes. The finding indicates that countries that claim to

follow a peg but ultimately behave differently benefit from lower real rates than thosewho do not. Thus, words seem to matter in this case. The opposite is not true: we find thatde jure pegs are no better off by actually behaving like pegs, as the last regression in the

table illustrates.


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Even at this exploratory level, we believe that we have evidence that regimes indeed

seem to matter in terms of real economic performance. However, the liaison points in adifferent direction than what has been stressed in previous literature. While a fix-floatcomparison does not reveal a significant difference with respect to inflation levels,intermediate regimes, particularly those in high volatility periods, appear to be the clear

losers. The low effect on inflation indicates that there are minor credibility returns fromgoing to a fixed exchange rate regime. This is particularly striking given the possible

presence of endogeneity or reverse causation. If inflation is low (for reasons other thanthe choice of regime) it is more likely for a country to maintain (and, in turn, implement)

a peg. Although this would imply, in principle, a positive correlation between lowinflation and pegs, no evidence is found in this direction. For intermediates, however, theresults may suggest the presence of endogeneity. Higher inflation, and real shocks in

general, may push countries to either abandon their pegs or intervene extensively inexchange markets, landing the intermediate group. Untangling the direction of causalityfor intermediate regimes should be the subject of future research.

Regarding growth, our results are quite striking, indicating a weaker growth performance

for exchange rate pegs. To make things worse, this weak growth performance comestogether with higher growth volatility. These results should not present problems ofendogeneity, as there are no clear reason why GDP growth should be an important

determinant of exchange rate regimes. However, the findings may be reflecting thepresence of other variables that may be at the root of the choice of a fixed exchange rate

regime (lack of credibility, vulnerable financial sectors, etc) and that may also lead toslower growth. However, we find the results to be quite robust and we believe that theyshould survive even after conditioning by other omitted variables.37

The de facto index presents an additional benefit: It allows to test the relative value of

announcements (words) as opposed to actual behavior (deeds). For example, we find that


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results for each subsample. Finally, the distinction between industrial and non-industrial

countries is also highly relevant, with exchange rate regimes having much more

importance on the performance of non-industrial countries. Future discussion on thetopic, then, should concentrate primarily on these countries.

The present work leaves many open questions for future work. First, in light of the

results, one should wonder why do we see so many intermediate regimes in practice?This points at the crucial (and so far underplayed) issue of the endogeneity of exchange

rate regimes,40a problem that, as we mention above, may be biasing some of our results.Only when these two aspects of the problem are fully understood and put together will we

be able to fully assess the extent to which the choice of exchange rate regimes matters.


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REFERENCES

Aizenman, J. (1991), Foreign Direct Investment, Productive Capacity andExchange Rate Regimes, NBER Working Paper No. 3767.

Anderberg, M.R. (1973) Cluster Analysis for Applications, New York: AcademicPress.

Barro, R. and X. Sala-I-Martin (1995) Economic Growth, McGraw Hill.Eichengreen, B. (1994)International Monetary Arrangements for the 21st

Century, Brookings Institution, Washington, DC.Ghosh, A., A. M. Gulde, J. Ostry and H. Wolf (1997) Does the Nominal

Exchange Rate Regime Matter?, NBER Working Paper No. 5874, January.Ghosh, A. and P. Pesenti (1994), Real Effects on Nominal Exchange Rate

Regimes, IGIER Working Paper.

Larran, F. and A. Velasco (1999) Exchange Rate Policy for Emerging Markets:One Size Does not Fit all, forthcomingEssays in International Finance, PrincetonUniversity Press.

Levine, D and Renelt (1992).Levy-Yeyati, E. and F. Sturzenegger (2000a), Deeds vs Words: Classifying

Exchange Rate Regimes, Mimeo Universidad Torcuato Di Tella.Levy-Yeyati, E. and F. Sturzenegger (2000b), Exchange Rate Regime and

Growth, Mimeo Universidad Torcuato Di Tella.

Levy-Yeyati, E. and F. Sturzenegger (2000c), The Endogeneity of ExchangeRate Regimes, Mimeo Universidad Torcuato Di Tella.

Obstfeld, M. and K. Rogoff (1996), Foundations of InternationalMacroeconomics,MIT Press.

Norusis, M. (1993), SPSS Professional Statistics 6.1.

Romer, D. (1993), Opennes and Inflation: Theory and Evidence, QuarterlyJournal of Economics, Vol. CVIII(4), pp. 869-904.

Rose, A. (1999), One Money, One Market? The Effect of a Common Currency on


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18

TABLE 3. INFLATION

IMF LYS 1st

round 2nd

round

FLOAT INT FIX FLOAT INT FIX FLOAT INT FIX FLOAT INT FIX

256 397 321 389 278 307 254 107 169 135 171 138

INFLATION Means 11.5 17.9 13.2 11.1 24.4 10.4 12.5 48.7 11.5 8.4 9.3 9.1

Medians 6.0 9.0 8.0 7.0 10.5 7.0 7.0 34.0 7.0 7.0 7.0 7.0

VOLINF Means 8.1 6.5 7.6 5.5 11.2 6.0 6.1 19.4 5.3 4.2 6.3 6.9

Medians 2.0 3.0 3.0 3.0 4.0 3.0 3.0 12.0 2.0 2.0 2.0 3.0

DM2 Means 15.3 23.8 17.4 16.1 29.1 15.1 17.2 49.6 16.4 14.0 16.2 13.5

Medians 10.5 15.0 15.0 13.0 17.0 12.0 12.0 34.0 11.0 14.0 14.0 12.5

DGDP Means 2.4 3.5 3.3 3.4 2.4 3.4 3.2 0.4 3.4 3.8 3.6 3.4

Medians 3.0 3.5 3.4 3.5 2.8 3.6 3.3 1.7 3.6 3.9 3.6 3.5

DINTRATE Means -5.6 -0.5 1.2 -2.2 -2.7 -3.2 -2.8 -2.0 -5.9 -1.0 -3.1 0.0

Medians -2.0 0.0 0.0 0.0 0.0 0.0 0.0 9.0 -1.0 0.0 0.0 0.0

SUPGDP Means -3.3 -3.8 -3.5 -3.7 -3.6 -3.4 -3.4 -5.5 -3.6 -4.3 -2.5 -3.2Medians -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -3.0 -4.0 -3.0 -4.0 -2.0 -3.0

OPEN Means 26.2 28.5 41.9 26.5 30.1 41.8 24.3 26.5 40.1 30.6 32.4 43.2

Medians 27.0 26.0 39.0 25.0 28.0 35.0 23.0 24.0 33.0 28.0 29.0 40.5

INFLATIONFIT Means 8.6 11.9 7.8 7.9 15.5 6.6 9.3 30.0 8.2 5.3 6.5 4.6

Medians 3.5 5.6 3.7 4.7 5.6 3.1 4.7 14.8 3.0 4.4 4.2 3.1


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19

TABLE 4. INFLATION

IMF

(Full

Sample)

IMF

(w/o LYS

inc.)

LYS LYS

(1st

round)

LYS

(2nd

round)

LYS

(Industrial)

LYS

(Non-

industrial)

Do words matter?

(LYSfix)

Do deeds matter?

(IMF=fix)

Do deeds matter?

(IMFfix)

GDP -0.397*** -0.470*** -0.409*** -0.125 -0.323*** -0.096 -0.415*** -0.442*** -0.175* -0.677***

0.067 0.094 0.094 0.151 0.102 0.080 0.109 0.116 0.101 0.119

M2 0.396*** 0.401*** 0.396*** 0.363*** 0.332*** 0.015 0.391*** 0.570*** 0.217** 0.488***

0.070 0.080 0.079 0.084 0.073 0.035 0.085 0.075 0.095 0.081

INTRATE 7.163*** 7.062*** 7.057*** 6.345*** 8.068*** 2.897*** 7.157** 5.896*** 7.440*** 9.537***

2.093 2.372 2.335 2.094 1.712 0.489 2.795 2.101 2.681 1.971

INFLATION(-1) 0.359*** 0.346*** 0.342*** 0.329*** 0.277*** 0.855*** 0.332*** 0.288*** 0.490*** 0.291***

0.062 0.065 0.064 0.061 0.083 0.043 0.064 0.060 0.161 0.059

OPEN -5.754*** -7.453*** -6.794*** -5.762* -8.357*** 0.280 -8.941*** -5.592** -7.783* -5.977**

1.500 2.352 2.261 3.282 2.230 0.973 3.056 2.504 4.574 2.487

INT 1.440** 2.086** 3.544*** 13.16*** -0.534 -0.317 4.364***

1.020 0.825 1.044 2.716 0.566 0.292 1.373

FIX 0.873 2.298** 0.918 0.436 1.455 0.185 0.556

0.759 1.129 0.848 1.302 0.903 0.311 1.141

IMFFIX 0.753

1.096

LYSFIX -0.499 -0.770

1.137 1.199

N of observations 1463 974 974 530 444 335 639 667 321 653

R2 0.7735 0.7829 0.7851 0.8201 0.5442 0.8168 0.7758 0.8460 0.6173 0.8506

***, **, and * represent 99, 95 and 90% significance

Standard errors in italics.


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20

TABLE 5. M2IMF

(w/o LYS

inc.)

LYS LYS

(1st

round)

LYS

(2nd

round)

LYS

(Industrial)

LYS

(Non-industrial)

Do words

matter?

(LYSfix)

Do deeds matter?

(IMF=fix)

Do deeds matter?

(IMFfix)

SUPGDP -23.293* -25.093** -29.662 1.229 -16.937 -32.779** -30.500** -15.724 -31.689

12.068 11.599 20.846 8.675 10.451 14.175 14.439 12.601 20.065

GDP(-1) -0.102 -0.037 -0.165 0.247 0.319 -0.168 -0.097 -0.017 0.026

0.152 0.148 0.260 0.157 0.198 0.175 0.200 0.194 0.228

M2(-1) 0.381*** 0.369*** 0.313*** 0.401*** 0.348*** 0.310*** 0.503*** 0.094 0.480***

0.092 0.091 0.096 0.125 0.094 0.094 0.108 0.218 0.099

OPEN -16.12*** -15.23*** -22.232*** -4.120 2.968 -24.405*** -13.464** -19.293*** -10.138

3.910 4.031 6.754 3.481 4.281 4.940 5.664 5.404 6.736

INT 6.879*** 9.055*** 23.159*** 1.164 0.164 9.969***

1.773 1.862 4.341 1.086 1.230 2.385

FIX 4.592** 1.419 2.555 0.063 -0.346 -0.2492.088 1.853 3.222 1.190 1.102 2.537

IMFINT

IMFFIX 1.222

1.735

LYSFIX -5.548 -2.595

3.866 2.184

N of observations 974 974 530 444 335 639 667 321 653

R2 0.2684 0.2783 0.3135 0.2514 0.1651 0.2705 0.3884 0.0898 0.3672

***, **, and * represent 99, 95 and 90% significanceStandard errors in italics.


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21

TABLE 6. GROWTH

IMF LYS 1st

round 2nd

round

FLOAT INT FIX FLOAT INT FIX FLOAT INT FIX FLOAT INT FIX

213 423 434 390 328 352 266 148 168 124 180 184

DGDPPC Means 0.7 1.8 0.4 1.9 0.6 0.3 1.9 -1.6 1.0 2.0 2.4 -0.4

Medians 1.2 2.1 0.6 2.2 1.1 0.7 2.1 -0.9 1.0 2.5 2.1 0.1

VOLGDP Means 2.6 2.6 4.5 2.7 3.5 4.0 2.8 4.0 3.5 2.5 3.0 4.5

Medians 2.1 2.2 3.8 2.3 3.1 3.2 2.4 3.7 2.7 2.0 2.2 4.0

VOLGDPPC Means 2.8 2.9 4.6 2.9 3.7 4.3 3.0 4.4 4.0 2.6 3.1 4.7

Medians 2.3 2.5 4.0 2.4 3.3 3.6 2.5 4.2 3.0 2.1 2.3 4.1

DTI Means -0.2 0.3 2.0 -0.4 1.7 1.5 -0.3 1.4 1.2 -0.5 1.9 1.8

Medians 0.0 0.0 -1.0 -1.0 0.0 -1.0 0.0 -1.0 -1.0 -1.0 0.0 -0.5

GOV1 Means 22.4 26.4 22.0 19.0 37.4 16.5 20.9 62.1 19.0 14.8 17.1 14.1

Medians 9.0 17.0 16.0 14.0 18.0 14.0 14.0 37.0 13.5 14.0 14.0 14.0

INVGDP Means 20.7 21.7 21.0 21.3 21.3 21.1 21.3 18.5 21.0 21.2 23.6 21.1Medians 20.0 21.0 20.0 21.0 21.0 20.0 21.0 19.0 20.0 21.0 22.0 21.0

DTRADE Means 7.6 8.4 8.3 10.0 6.3 8.1 8.8 0.3 9.7 12.5 11.2 6.7

Medians 7.0 8.0 7.0 9.0 7.0 7.0 7.5 -0.5 7.0 10.5 11.0 7.0

OPEN Means 26.3 28.5 37.0 25.3 30.8 39.1 24.4 26.7 40.3 27.2 34.1 38.0

Medians 26.0 25.0 33.0 23.0 28.0 35.0 23.0 25.0 35.0 25.0 31.0 35.0

GDPPC74 Means 2573 1669 1037 1983 1313 1421 1995 870 2024 1957 1677 870

Medians 2700 1124 325 1124 454 510 1263 454 1106 665 512 325


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22

TABLE 7. GROWTH REGRESSIONS

IMF

(Full

Sample)

IMF

(w/o LYS

inc.)

LYS LYS

(1st round)

LYS

(2nd round)

LYS

(Industrial)

LYS

(Non-

industrial)

Does it pay to

comply? (de jure

fix)

Does it pay to

comply? (de jure

no fix)

TI -0.807 0.317 0.313 0.024 0.565 5.219** 0.386 0.384 0.780

0.795 0.760 0.759 1.172 1.139 2.550 0.727 0.917 1.204

GOV1 -1.153 -1.412*** -1.329*** -0.817* -2.346* -1.300 -1.166*** -1.397** -1.141**

0.718 0.404 0.417 0.479 1.392 1.883 0.430 0.552 0.579

INVGDP 11.90*** 11.72*** 11.58*** 6.734* 14.374*** 5.619* 12.183*** 7.250* 14.238***

3.240 2.788 2.770 3.567 3.981 3.324 3.286 4.372 2.935

TRADE 12.98*** 9.335*** 9.179*** 7.183*** 10.992*** 7.936*** 9.296*** 10.192*** 8.083***

2.480 1.238 1.233 1.541 1.527 1.357 1.334 1.442 1.921

OPEN -2.581* -1.265 -0.738 0.231 -1.950 1.787 -0.685 0.740 -0.652

1.492 0.858 0.873 1.238 1.339 1.223 1.135 1.412 1.151

GDP74 0.000 0.000 0.000 0.000 0.000* 0.000 0.000 0.000 0.000

0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

INT 0.947** 0.951*** -0.764** -2.395*** 0.310 -0.341 -0.987**

0.368 0.298 0.298 0.508 0.372 0.302 0.383

FIX -0.279 -0.392 -1.425*** -0.971** -1.820*** -0.036 -1.843***

0.704 0.429 0.348 0.405 0.572 0.365 0.408

LYSFIX -1.272**

0.498

LYSFLOAT 0.509*

0.284

N of observations 1080 1070 1070 582 488 306 764 434 636

R2 0.2028 0.2086 0.2063 0.2163 0.2585 0.2169 0.2148 0.2052 0.2172




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23

TABLE 8. OUTPUT VOLATILITY

IMF

(w/o LYS inc.)

LYS LYS

(1st round)

LYS

(2nd round)

LYS

(Non-industrial)

VOLGOV 1.092** 1.216*** 1.035** 0.904 0.657

0.454 0.460 0.456 1.407 0.472

VOLINVGDP 29.491*** 30.82*** 36.071** 18.744** 26.365**

11.185 11.438 17.416 8.703 10.230

VOLTI 0.015** 0.019*** 0.034** 0.010 0.009

0.007 0.007 0.013 0.007 0.006

OPEN -0.989 -0.783 -1.949 1.276 -1.449

0.997 1.005 1.234 0.985 1.115

GDP74 0.000** 0.000** 0.001 0.000** 0.001***

0.000 0.000 0.000 0.000 0.000

INT -0.216 0.257 0.416 0.190 0.385*

0.299 0.213 0.287 0.323 0.222

FIX 1.033*** 0.736*** 0.033 1.331*** 1.029***

0.309 0.224 0.297 0.327 0.239

N of observations 790 790 409 468 695

R2 0.1710 0.1456 0.1651 0.1843 0.2146




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24

TABLE 9. REAL INTEREST RATES

IMF

(w/o LYS

inc.)

LYS LYS

(1st

round)

LYS

(2nd

round)

LYS

(w/o

intermediate)

Announcement

effect

(LYS no fix)

Does it pay to

comply?

(de jure fix)

INETODGDP 10.583** 8.755** 13.633* -4.992 -2.240 18.669** 3.217

4.161 4.113 6.994 4.262 3.218 8.198 1.983

GDP1 0.089** 0.096** 0.095* 0.083 0.040 0.195*** 0.034

0.038 0.039 0.049 0.061 0.035 0.073 0.028

INFLATION -0.095*** -0.094*** -0.072*** -0.440*** -0.245*** -0.072*** -0.539***

0.025 0.025 0.023 0.055 0.030 0.022 0.046

OPEN 2.831** -0.248 -0.655 -3.334*** -1.006 1.768 -1.384

1.286 1.180 1.767 1.269 0.992 1.784 1.168

SUPGDP -4.930 -4.773 1.107 -2.772 -4.729 -6.714 2.229

3.619 3.585 7.084 3.256 4.915 4.722 1.936

FIX -3.259*** -0.413 0.949 -1.817*** -0.966**0.526 0.446 0.683 0.4869 0.420

IMFFIX -3.798***

0.757

LYSFIX -0.331

0.562

N of observations 851 851 447 404 608 638 244

R2 0.1600 0.1165 0.1102 0.3369 0.2912 0.1565 0.6636



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