Choice of Exchange Rate Regime in Middle East and North Africa Countries: An Empirical Analysis Darine GHANEM* Claude BISMUT* LAMETA University Montpellier I June 2009 (Preliminary Version) Abstract This paper investigates empirically the reasons behind the popularity of fixed adjustable pegs in Middle East North Africa region (MENA). We have used an ordered multinomial random effects probit model for explaining the exchange rate according to the official (de jure) and to the actual (de facto) Exchange rate classifications. Many indicators have been used as proxies for the different relevant factors. We find that, the fear of floating factors appear to play a direct important role in the choice of regime. Keywords: Exchange Rate Regime, Multinomial Random-Effects Probit Model, MENA * : LAMETA : Laboratoire Montpelliérain d’Economie Théorique et Appliquée, Université Montpellier I, UFR Sciences Economiques. Avenue de la Mer - Site de Richter C.S 79606, 34960 MONTPELLIER Cedex 2. Correspondent to: d.ghanem Tel: 33 (0)467158334; Fax: 33 (0)467158467;E-mail : darine. ghanem.lameta.univ-montp1.fr ; [email protected]• Please do not cite without authors permission.
Transcript
Choice of Exchange Rate Regime
in Middle East and North Africa Countries: An Empirical Analysis
Darine GHANEM* Claude BISMUT*
LAMETA University Montpellier I
June 2009 (Preliminary Version)
Abstract This paper investigates empirically the reasons behind the popularity of fixed adjustable pegs
in Middle East North Africa region (MENA). We have used an ordered multinomial random
effects probit model for explaining the exchange rate according to the official (de jure) and to
the actual (de facto) Exchange rate classifications. Many indicators have been used as proxies
for the different relevant factors. We find that, the fear of floating factors appear to play a
direct important role in the choice of regime.
Keywords: Exchange Rate Regime, Multinomial Random-Effects Probit Model, MENA
* : LAMETA : Laboratoire Montpelliérain d’Economie Théorique et Appliquée, Université Montpellier I, UFR Sciences Economiques. Avenue de la Mer - Site de Richter C.S 79606, 34960 MONTPELLIER Cedex 2. Correspondent to: d.ghanem Tel: 33 (0)467158334; Fax: 33 (0)467158467;E-mail : darine. ghanem.lameta.univ-montp1.fr ; [email protected] • Please do not cite without authors permission.
1 Introduction
The proper choice of the exchange rate regime has been a central and a highly
controversial debate, with successive shifts that can be traced to changing events, since the
seventies After the breakdown of the fixed adjustable peg system of Breton Woods, the
general advice of IMF had moved toward either irrevocably fixed rates (currency board or
dollarization) or truly flexible rates corner regimes. Intermediate regimes had been strongly
discouraged especially after the Asian crisis which has often been interpreted as evidence
against the soft pegging regimes. More recently a growing body of opinion has questioned the
relevance of the two corners; an appropriate exchange rate regime has to be analyzed from the
point of view of the economics and historical characteristics of a country. Actually the
evidence indicates that, many countries are moving away from these extremes regimes, in
particular, in the MENA region.
Most MENA countries opted for a fixed adjustable exchange rate regime in the early
1970s. The adoption of fixed rate was originally justified by the desire to dampen inflationary
pressures and to achieve macro-economic stability. However, once the immediate threats of
high inflation had been avoided, most MENA countries moved to intermediate regimes, only
a small number of countries actually turned to a fully flexible exchange rates. Moreover the
longevity of those soft peg exchange rate regimes makes MENA countries somewhat peculiar
and raise questions.
The Middle East and North Africa (MENA) countries, although economically heterogeneous,
share a common heritage, and a common set of challenges. Oil, and other natural resources,
remain a substantial source of foreign exchange earnings in this region.
Large external and real shocks have made the region sensitive to speculative attacks.
Conventional theory tell us that, a greater degree of exchange rate flexibility is advisable in
this case, which cast doubts on the viability of intermediate regimes given that, the other
conditions necessaries to amplify the ampler of shocks like as, flexibility of wages and prices,
are not available. Indeed, the majority of MENA countries covered in this analysis have
maintained some degree of price controls, contributing to price stickiness, a feature which is
confirmed by labour market indicators for most of them. 1
1 This rigidity was more pronounced in the cases of Egypt, Morocco, Algeria, and Tunisia, while Jordan, Lebanon, Kuwait, Saudi Arabia and UAE seem to have some labour market flexibility. Source: (www.pogar.org) Programme on Governance in Arab Region.
So far, the MENA countries have avoided severe crisis which plagued other regions over the
past two decades although for different reasons. Most of these countries with no oil resources,
were relatively closed and centrally planned, and have reduced exposure to external shocks
using strict controls on capital movement. In the case of oil producers, such as Gulf’s
countries which were more open and thus more vulnerable the large amount of reserves in
US$ resulting from exports of oil and profit returns of overseas investments helped to dampen
the magnitude of the shock and thus sustain the peg.
However, if certain MENA countries have implemented sustainable exchange rate regimes
under current economic and financial conditions, others are undergoing pressure to reforms
in response to new domestic and global challenges. Globalizations, international and regional
trade liberalization in general or within the framework of regional agreements, such as the
Association Agreement with the European Union (AAEUs) or the Grand Arab Area of Free
Trade (GAAFT) represent a major change of the economic environment on Mena countries.
These development s raise the question whether, the current exchange rate regimes remains
appropriate Actually , the 20th century was a decade of economic reforms and certain
countries have accomplished a considerable progress toward market economy and financial
integration. Prices and trade regimes were liberalized and foreign direct investment was
encouraged while exchange rates became more flexible. However, while some countries
moved to more flexible regimes, they have continued to heavily manage their currencies,
although they sometimes officially declared to be floaters.
In this paper, we aim to investigate the main determinants of exchange rate regimes in MENA
countries using a large set of economic and political variables. In this effort, we use a pooled
ordered probit model as the reference for our empirical test. Then, we employ statics and
dynamic ordered random effects probit model in order to exploit the panel structure of our
data. Our analysis relay first on IMF (de jure) classification and then we check our results
against LYS (de facto) classification in order to explore any discrepancies of results under the
two classification.
In the following section, we describe the evolution of exchange rate arrangement and the
discrepancies of de facto and de jure classifications in MENA countries. Section 3 reviews the
theoretical hypotheses of different approaches to the exchange rate regime choice. In Section
4, we discuss the construction of our independents variables and then test their relevance
empirically using different estimation strategies and employing both de jure and de facto
classification. The results of our estimations are presented in Section 5. Finally Section 6
provides some conclusions.
2 2 2 2 Regimes in Middle East and North Africa Countries
2.1 2.1 2.1 2.1 Classification of Exchange Rate Regime in MENA Countries
Employing the proper classification of exchange rate arrangements is not a straight-
forward work. The result s might be highly depending on the employed methods of
classification. Judging the result from official classification and could be misleading.
Many important research papers on exchange rate regimes2 stress the gap between what
countries say they do and what they really do. Calvo and Reinhart (2000) find that countries
who claim they allow their exchange rate to float often do not actually do so. Either, Gosh et
al (1997), report that many countries that have a fixed exchange rate, realign their exchange
rates frequently, thus in a sense moving in the direction of floating exchange rate regime.
In this study we first review the results obtained using the official classification, of the IMF’s
Annual Report on Exchange Arrangements and Exchange Restrictions. Then we aggregate
the eight different categories of the IMF to only three broad categories: fix, intermediate and
float. The de jure classification captures essentially the type of commitment of the central
bank on which the expectation is built. However, it fails to account observed policies, which
turn to be inconsistent with this commitment, as shown by Guillermo Javier Vuletin (2004).
For this reason; we supplement our analysis by the de facto classification, based on the
indexes calculated by Bubula Ökter-Robe (2002), henceforth BOR and Levy-Yeyati et al (
2005) henceforth LYS which are also classified into three groups, Table (1) in Annex (I).
In fact, Bubula Ökter-Robe (2002) use the classification adopted by the IMF since 1999 and
then returns back in time to perform their data. Their approach includes some refinement to
the IMF classification by distinguishing between "backward-looking crawls" and "forward-
looking" and between strictly managed float and other managed float regimes. Their
characterization of the de facto behavior of these countries relies heavily on official
information from members countries and IMF country disk beside to other source of
information like press report.
Contrary to BOR, Levy-Yeyati et al (2005) ignore the IMF classification. They build their
own classification based on two criteria which are the volatility of exchange rates and
reserves. This makes data availability for a longer time period. However, this classification
2 New methodologies in classification have been proposed by Reinhart and Rogoff (2002 and 2004), Bubula Otker Robe (2002),Levy-Yeyati and Sturzenegger ( 2005), Dudas, Lee, Mark (2005) Ghosh, Gulde, Ostry, Wolf, (1997), Poirson (2001), Courdet, Dubert (2004), Shambaugh J. (2003).
suffers from serious drawbacks. In particular a few countries or some years could not be
classify unambiguously and a special the category “inconclusive”3 was introduced to
overcome this problem we took the classification of Reinhart and Roggof (2002) whenever
available, and if not, we took the IMF classification after comparing it with the BOR
classification. We obtain thereby a completed series for the period 1990-2004.4
2.22.22.22.2 Evolution of Exchange Rate Regimes in MENA
We show the general trend of regime evolution in this region according first to the IMF
classification and then the de facto classification of BOR and LYS in order to explore any
discrepancies between the three methods of classification. The graph below shows the
evolution of exchange regimes through 1990 -2006.
Figure (1): Evolution of Exchange Rate Regime: IMF (de Jure) Classification
0
20
40
60
80
1990
1992
1994
1996
1998
2000
2002
2004
2006
year
Co
un
t S
amp
le(%
)
fixe intermediaite float
We can arguably distinguish two sub-periods. During the first period, between 1990 and
1999 51% of MENA countries have adopted a fixed exchange rate regime, more precisely an
adjustable peg. This proportion decreased slightly during the beginning of 1995 in favor of
more flexible regimes but it underwent a significant increase during the second period (67.5)
%. The adoption of more rigid regimes by the six countries of Gulf which are currently in a
convergence process for a monetary union in 2010 , may explain the rising share of fixed in
3 In the latest version of their study, LYS considered that the observations inconclusive are peges although the volatility of their exchange rate is zero or if they are declared as being fixed exchange rate regime by the IMF and the Volatility of their nominal exchange rate is less than 0.1%. This drastically reduces the number of observations inconclusive to 2.4%. 4 Countries for which LYS dataset are missing data (including inconclusive) are Algeria (4 observations), Egypt (9 observations), Kuwait (5 observations), Libya (3 observations), Morocco (14 observations), and Yemen (4 observations).
detriment of intermediate regimes which fell by 14 percent between 1998 and 2006 . The
following table gives further information on the changes of regimes during this period.
Table 2: countries included in the sample with information on the direction and the number of exchange rate regimes switch for the sample period
Total deviation from announcement 47.54% 42.64% 9.80%
Note: numbers in bold show observations where announced regime correspond to real one. Celles below
indicate fear of float and those above indicate fear of peg
5 More specifically, we have less number of floating regime lesser comparing to the number obtained by official typology (9 against 25% in average). 6 (Alesina and Wagner, 2006)
Table 4 : indicates divergence between deed (de facto) LYS versus word (de jure) IMF Sample period: 1990-2004
Total deviation from announcement 69.68% 9.05% 21.25%
Note: numbers in bold show observations where announced regime correspond to real one. Celles below
indicates fear of float and those above indicate fear of peg
We remark that a large number of observations indicate a deviation from the policy
announced with greater divergence for floating regimes. While we have 79 observation (83%
of countries) manifest a fear of floating7, we have only 21 observation (58%) manifest a fear
of peg.8
3 3 3 3 Theoretical Determinants of Exchange Rate Regimes The modern literature about the choice of an exchange rate regime goes back to the
sixties with Mundell’s theory of optimum currency area (OCA). This approach, relates the
choice of an exchange rate regime to a set of criteria. Mundell (1961) claimed that, fixed
exchange rate is advisable in presence of mobility of production’s factors (works and capital)
and/or flexibility of prices and wages. In these two cases the adjustment can be achieved
without exchange rate flexibility. Mac kinnon (1963) argued that, the more open the economy
the more it has to benefit from exchange rate stability because it reduces the fluctuations of
relative prices between tradable and non-tradable goods and its repercussions to domestic
prices. Furthermore, he dismissed the effectiveness of parity changes and said in particular
that the expected effects of devaluation (the increase of exportation or the decrease of
importation) will be limited. 9 Kenen (1969) found that, a diversified economy can
7 Tunisia 1990-1992 and 1996/1998/2001 Egypt: 1990-1998 Syria 1993-1998 and 2002 2004 Yemen: 1999-2004 Iran: 1994-1998/2003/ 2004. 8 Tunisia 99/2000/2003/2004, Libya 92-93-94-98-99-2002, Egypt: 99/2000/2001/2002, Jordan and Lebanon 1990-1993. 9 In an open economy, the cost of production will be influenced by the prices of gross primary materials and the imported intermediate goods. Furthermore, in the case of devaluation, the effects of inflation caused by the rise of the necessary importation’s prices raise immediately the prices of other goods and wages limiting hence the expected effects of devaluation and the exchange rate lost its ability like an adjustment instrument.
successfully offset shocks and hence can easily adopt a fixed exchange rate and rejoins an
optimal currency area.
Mundell and -Fleming (1970) made a step further when they acknowledged that the choice of
an optimal regime has to take into account not only the structural characteristics of the
economy, but also the nature of shocks. In particular is that, monetary and real shocks have
different implications on the economy if the source of perturbation comes s from the good’s
market, a flexible exchange rate should be preferred. On the contrary, a fixed exchange rate
would be more appropriate if the source of shocks is in the money market.10 This is consistent
with the Keynesian view on regime’s selection, which stresses the importance of achieving
simultaneously external and internal equilibria while using the exchange rate.11
During the nineties a significant increase in capital’s mobility, has stressed the importance of
sound a stable domestic financial sectors as a condition for the choice of an exchange rate
regime, Chang and Velasco (1998). This new economic environment creates the potential for
large and sudden reversals in net flows and thus, the capacity of countries to avoid an
exchange rate crisis depends on its capacity to appropriately manage huge amount of inflow
and outflows. An excessive capital outflow accompanied with overspending form an
immediate source for currency crisis. Krugman (1996) explains that if a small open economy
has created an excess of domestic credit over the demand of money, economic agents will
observe this misalignment between fixed exchange rate and growth rate of money and, a
speculative attack may be occur. Even so, a simple rumour on possible devaluation is
capable, according to self-fulfilling hypothesis, to create a bank crisis. This problem is more
pronounced in countries with an open capital account which can prompt theses countries to
move toward either hard pegs or pure float. Nevertheless, capital account controls might make
it easier to sustain a fixed exchange rate and thus some developing and emerging market may
be still reasonably well off with intermediate regime.
10 Real shocks represents par example the fluctuations in the foreign demand on the export of goods and services (tourism), weather condition, changes in productivity, term of trade shock. As for Monterey’s shocks, they reflect the instability of money demand manifested the undesirability of economics’ agents to acquit the domestic money either the fluctuation of confidence level. 11 Devereaux (1999), in his dynamic general equilibrium model find that the adoption of fixed exchange rate interrupts an effective response to shocks. The results indicate that, exchange rate role, as a macroeconomic instrument of adjustment does not help the economy to adjust face to specific productivity or demand shock. Since prices are pre-set, productivity’s shock has no effect on the output, which is determined by the demand, and therefore, the exchange rate does not response to productivity shock specific to the country even under floating exchange rate. Fixed exchange rate does not eliminate hence the ability of the economy to adjust face of different shocks.
A new approach, the so called “fear of floating”, introduced by Calvo and Reinhart (2000),
has been put forward, most recently and forcefully after the advanced researches on method of
classification. Calvo and Reinhart notice that many countries that say they float did not in
reality whereas; countries with fixed exchange rate have a de facto intermediate regime. Such
a practice is common between emergent and developing countries due to various reasons like
exchange rate pass-through, credibility issues, original sin12, and currency mismatch. Theses
raisons make exchange rate volatility intolerable for emerging market countries, Hausman
Ugo and Stein (2001).
On empirical plan, Reinhart Rogoff and Savastano (2003) studied various dollarized
economies through the period 1996-2001. They find that, the pass through is very important
in highly dollarized economies which explains why central banks in emerging countries show
less of tolerance toward important variation of exchange rate. Indeed, economic dollarization
combined with the lack of credibility draw on liability dollarization, which incite theses
economies to take into account the adverse effects of exchange rate variation on sectorial
sheet, and in consequence on aggregated revenue.
Hausmann, Ugo and Stein (2001) have tested currency mismatch hypothesis and exchange rate
pass through in a sample of 30 countries having de facto floating exchange rate. Their results
confirm that central banks have been more concerned with limiting exchange rate volatility if
currency mismatch and pass through level are very high. Moreover, Countries with unhedged
foreign currency debt have a tendency to keep an important level of foreign reserves and to
intervene in exchange markets in order to mitigate exchange rate volatility, Hausmann and Ugo
(2003).
Berg, Borensztein (2000) find that a high level of currency substitution implies fixed
exchange rate. Their conclusion is not clear-cut because; the source of shocks is still matter.
However, it is highly plausible that in the case of an extensive currency substitution, monetary
shocks will be relatively higher in magnitude, than real shocks and thus a fixed exchange rate
regime will be more appropriate.
Honig (2005) use different measures of dollarization on a large cross-country sample through
the period 1988-2001. He finds that, an increase in dollarization is associated with less
flexible exchange rate regime but he adds that, the effect of dollarization’s variables on
12 Calvo and Reinhart (2000) show that if a country has a large share of exports and imports libelled U.S. $, a depreciation tends to induce debt and fiscal crisis because, it increases the debt denominated in foreign currency.
exchange rate regime choice should depend on the degree of openness of the economy13 and
in particular, the extent to which firms earn revenue in dollars.14
Additional reasons why there is still a strong support for fixed exchange rate in some
countries mainly are related to the political economies consideration and the pressures of
interest groups. The decision about the exchange rate regime choice is mostly implemented
taking into account pressures as well as the need to build support for policies.15 More clearly, a
high volatility of nominal exchange rate combined with rigid price translates into volatility in
relative prices of tradable and non-tradable goods. This could cause political upheaval in a
country where both sectors are large and or the lobbies are powerful. It is still true for producers
and exporters of light manufacturing goods for which the volatility of exchange rate will be a real
constraint for the development of this sector and thus there is a need to be protected.
An additional raison that explains why there is still support for fixed exchange rate in some
countries. Moreover, beside to the fear of floating, some countries may experience a "fear of
pegging". The peg may invite speculation when a misalignment is expected, Levy-Yeyati and
Sturzenegger (2002). Therefore, there are always good reasons to avoid both the system of fixed
exchange and floating regime and opt for an intermediate regime.
Numerous authors emphasize the role of credibility of monetary authorities and other political
and institutional factors in the process of selecting an optimal exchange rate regime.
Lack of institution strength or political instability make fixed exchange rate more difficult to
be sustained which may increase the attractiveness of tying one’s hand through a currency
board that impose fiscal and monetary discipline and thus reinforces the credibility and the
public confidence. However, Tornel and Velasco (1994) show that this is not entirely true and
that all depend on discount rate of government and the advantage induced by each regime.
The government can finance budgetary deficits by issuing debt for a temporary period
(inflation tax). The costs of such fiscal policy appear differently, according to the exchange
rate regime in place. Under a fixed exchange rate regime, the costs will not be observable
until the inflation manifest at some point in the future. Conversely, under flexible exchange
13 He explains that the negative effect of increased dollarization on exchange rate flexibility should be smaller (in absolute value) in more open economies as dollar liabilities are more likely to be matched with dollar assets. 14 For example, if firms borrow in dollar and earn in dollar, they face no currency mismatch, but if they earn in local currency, depreciation may cause a net loose. 15 Bernhard and Leblang (1999)
rate regime, inflation rate is observed in the present, due to anticipation of a higher future
inflation. 16
Furthermore, the type of relation that induces the governance and political factors is
not always clear. For example, while Edward (1996) and Collin (1996) consider that a weak
government and unstable political environment reduce the probability of choosing fixed
regime17. Alesina and Wargner (2006) and Honig (2007) argue that weak governments may
be willing to use a peg as an instrument to enhance the credibility and to increase the
confidence in the domestic currency and thus tame inflationary expectation.
4444 Identifying Exchange Rate Regimes Choice in MENA Countries In this section we present the econometric model which is applied to test the
hypotheses presented in the previous section, in a unified framework.
4444....1 1 1 1 The Data
The sample includes 17 transition and developing MENA countries. Data were not
available for a uniform period for all country. We conduct then our analysis on an unbalanced
panel data for the period 1990-2006.
Our dependant variable represents the choice of exchange rate regime that takes three values
ordered by level of flexibility. See table 1, Appendix I.
The control variables are chosen to proxy the factors discussed in section 3.1 and are
extracted from various sources. Our data includes; the degree of openness approximated by
the ratio of exports plus imports of goods and services to GDP using data from International
Financial Statistics (IFS); the level of economic development measured as the log of a five
year moving average of real per capita GDP, source (CEPII); the geographical concentration
of trade measured by Gini-Hirchman coefficient; the degree of specialisation in primary
goods exports calculated as a ratio of primary commodity exports to total exports. 18 To
construct these two proxies, we use essentially data from UN cometrade database and when
16 Then, a fixed exchange rate induces more fiscal discipline when the fiscal authorities are sufficiently patient so that, costs in the future will have a deterrent power. If the fiscal authorities are impatient, flexible rate will provides more fiscal discipline. 17 According to Edward (1996) discount rate factor of the government is negatively correlated with political instability. high political instability contribute to shorten the horizon in politicians’ decision making who favourite intermediate benefits to long term benefits to ensure their re-election. 18 This data base is mapped into SITC classification. We use 9-digit SIC classification. The primary goods exports comprise the commodities in SITC section 0 to 5.
trade data was not available for a certain country in a certain years, we consult Arabe
Monetary Fund data base (AMF).
Financial development level is approximated by the ratio of domestic credit provided by
banking sector to GDP, source (IFS). To proxy balance sheet effects, we use two indicators.
The first one is the ratio of external dollar mismatch in the bank system defined as the ratio of
foreign liabilities to foreign assets and the second is the ratio of foreign-currency liabilities to
money supply. Data for both measures are obtained from IFS statistics.
To test for other variables linked to institutional and politics factors we consider first inflation
differential rate, calculated as the difference between domestic price levels (measured by the
consumer price index) and the foreign price level, the latter being the trade-weighted average
of its first five trading partners' consumer price indices, both in natural logarithms; second,
capital control index defined as the sum of four dummies variables that represent the
existence of the following restrictions: i. separate exchange rates for some or all capital
transactions; ii. restrictions on payments for current transactions; iii. restrictions on payments for
capital transactions19 and iii. surrender on repatriation requirement for export proceeds. All are
taken from Annual Report on Exchange Arrangements and Exchange Restrictions and finally,
control for corruption index that measures the extent to which public power is exercised for
private gain, including petty and grand forms of corruption, as well as “capture” of the state
by elites and private interests. The latter indicator is available only for the period 1996-2006
and is obtained from Kaufmann et al (World Bank).
We add also a dummy variable (time) that takes the value of 1 for all year from 1999 onwards
and zero otherwise. This variable examines the change in distribution of exchange rate regime
that has been shown since 1999 (see graphic 1).
We should note that, taking in account that many countries in our sample are producers and
exporters of oil and other primary goods; some previous variables namely specialisation level
could be given a politic economy interpretation although they reflect the structural
characteristic of the country. This is du probably to the high weight given to this variable in
19 Since 1997, EAER reports 11 separate categories for controls on capital transactions which are: (1) capital market securities, (2) money market instruments, (3) collective investment securities, (4) derivatives and other instruments, (5) commercial credits, (6) financial credits, (7) guarantees, sureties, and financial backup facilities, (8) direct investment, (9) liquidation of direct investment, (10) real estate transactions, and (11) personal capital movements. we follow thus since this date Glik and Hutchison’s definition (2005) and consider that the restrictions on payments for capital transactions dummy takes the value of 1 if controls were in place 5 or more of the EAER 11 sub-categories of capital account restriction and “financial credit” was one of the categories restricted and 0 otherwise.
designing the exchange rate policy. Indeed, openness could be also considered as a proxy for
the pass through of the exchange rate into imports price hence reflecting the fear of floating
view, Bénassy-Quèré and Coeuré (2002).
Appendix (I) provide more information on the construction and the sources of all variables
used in our empirical analysis (table 5), including the summary statistics (table 6) and the
correlation matrix table (7).
4444....2 2 2 2 The Methodology The starting point for our econometric specification is an unobserved latent
dependant variable y*it which describe the choice of exchange rate regime, given that the
possible choices are yit= {0, 1, 2} for fixed, intermediate, and floating regimes respectively.
We can estimate then the following model:
y* i,t = βX 'i,t + νi,t for i = 1,2……N; t= 1,2,…..T(i) Where the subscripts i and t stand for the country and time indices, respectively, x'it
is a vector of exogenous determinants of the exchange rate regime choice in the sense that
E(X i,t, ε j,s)=0 and β is the coefficient vectors to be estimated.
We start our estimation by employing a pooled ordered probit model assuming the error term
νi,t to be independent and identically distributed with a means zero and a variance σ² for all
countries i and over time t ignoring thus the additional information contained in our panel.
Then we exploit the panel structure of our data taking into account the unobserved
heterogeneity factors that could affect country’s decision about exchange rate regime. We
control for this effects by estimation a random-effects ordered probit model 20since the fixed
effects probit model is actually always inconsistent in the case of non linear models and is
subject to incidental parameters problem, Green (2002).
In the random effects specification the error term νi,t is the sum of two components:
νi,t = ηi + εi,t the term ηi is assumed to be a time independent individual specific random
effect with means zero and variance ση reflecting the unobserved country heterogeneity that
could affect the choice of particular exchange rate regime while εi,t is assumed to be a
20 We use Butler and Moffitt (1982) randome effects probit model written and is implemented in STATA by Frechette (2001).
normally distributed random error term with mean zero and variance σε21 that is independent
both among individuals and over time.
The random effects model impose also the restriction that the correlation between successive
error terms for the same country is a constant: corr (νi,t, νj s)= ρ= ση/(1+ ση) if t≠s.
Since y*i,t is unobservable, what we observe is the choice of exchange rate regime yit for
country i, at meeting t. We therefore have that conditional on being in each regime; yit is
related to this latent variable and a cut-off parameter µ22 as;
0 if y*i,t ≤ 0 , y i,t = 1 if 0 < y*i,t ≤ µ , 2 if µ ≤ y*i,t Under the unrestrictive assumption of normality of εi,t the associated probabilities of being in each state j (j = 0, 1, 2) are : (Maddala 1983) Pyit=0 = Ф(-Xit'β – ηi) Pyit=1 = Ф(µ-Xit'β – ηi) - Ф(-Xit'β – ηi) Pyit=2= 1- Ф(µ-Xit'β – ηi) The parameters of the model, the βs (the coefficients on the X variables) and the unknown
cut-off values (the µs) can be estimated then by Maximum likelihood function using the
standard normal distribution function Ф(.).
As well, we are also particularly interested in state dependence effect, which may potentially
be an important factor in our study, as the present exchange rate regime choice may be highly
correlated with the past choice. To control for state dependence, we include the lagged choice
of exchange rate regime as an explanatory variable into the model, then:
y* i,t = γ y* i,t-1 + βX 'i,t + νi,t for i = 1,2……N; t= 1,2,…..T(i) Where y* i,t-1 is a vector for dummy variables and represent the country’s choice of exchange
rate regimes in the previous period . We assume that the initial observations are exogenous
variables.
Before discussing the results of our empirical test it is important to note that previous studies
on exchange rate regime choice have raised doubt on the direction of the causal relation
21 In ordered probit specification, the variance of the error term is normalised to 1 : σε=1. 22It is not possible to identify both the constant term and all of the cut-off points. So, in order to estimate the model, some of the threshold values (µ’s) have to be fixed. the first seuil (µ1) is set equal to zero or the constant term is excluded from the regression model
between certain determinants and exchange rate regime as for inflation and foreign liability.
We choose hence to instrumentalise some of our explanatory variables by including their first
lags in the regression in order to mitigate potential endogeneity bias.
5555 The Econometric Results
In the next sub-section, we examine the empirical relevance of the previous variables
in explaining the de jure and de facto choice of exchange rate regime in MENA. We use two
estimation strategies. First of all, we run a full sample pooled ordered probit. Second, we re-
estimate the model using random effects ordered probit controlling hence for country
heterogeneity. In the first sub-section we discuss the results obtained under IMF classification
and in the second those obtained under LYS.
We should note that random effects specification implies the elimination from the sample all
countries that stay on the same regime through all the whole period of analysis. This leaves
us, unfortunately, with a smaller sample size (12 countries for IMF classification and only 9
for LYS classification). This change in sample size makes the comparison between the (de
jure) and the (de facto) results more difficult and have to be analysed with caution.
The estimation results are presented in a sequential way. we start the regression with a set of
factors relating to OCA, financial development and fear of floating approaches (column1), we
introduce then progressively more factors representing institutional and politics variables
(column 2 to 4).
The log-likelihood (LL) chi-square and pseudo-R² de Mac-Fadden, presented below the
tables, are the two measures of goodness of fit we use to compare across models.23 Rho (ρ) is
the coefficient of cross-correlation that measures the significance of random effects. It is
strongly significant in all cases for de jure classification and in two cases (column 1 and 3) for
de facto classification, suggesting significant heterogeneity effect.
A negative sign of a coefficient means that an increase of the associated variable raises the
probability of choosing fixed regime relative to intermediate and floating ones.
The time dummy, we have included, reveals also a strong significant sign across models and
specifications. But, while it reflects the general move toward less flexible regimes (adjustable 23 A high value of these two statistical tests suggests that the model explains the choice of currency regimes best. The log likelihood chi-square is an omnibus test to see if the model as a whole is statistically significant. It is 2 times the difference between the log likelihood of the current model and the log likelihood of the intercept-only model. A pseudo R-square capture more or less the same thing in that it is the proportion of change in terms of likelihood. Mc Fadden R² = 1- (last iteration / itteration0).
peg) in the de jure classification, it reflects a shift toward more flexible regimes in the de
facto classification.
We should note that some of previous variables can be a proxy for different theories and the
sign of the coefficients could bear different interpretations. The theoretical researches on
exchange rate regime choice are ambiguous. Even at the empirical levels, the evidences are
controversial and not able to provide conclusive evidence on any set of determinants.
The results are highly dependant on the sample of countries, period of analysis, variables
included, strategy of estimation, and the method of classification employed.
We think that, when a country do not choose the exchange rate regime which is presumed to
be more appropriate according to one approach. This is because, it might have another
characteristics that makes it likely chooses another regime. Expanding exchange rate
determinants progressively should help us to provide a more comprehensive picture on
countries’ economic and institutional restriction. The estimated coefficient sign help us to
judging the most pertinent theory in explaining exchange rate regime choice.
5.1.5.1.5.1.5.1.1111 De Jure Exchange Rate Regime Table (8-a, 8-b) reports the estimation results for static pooled and random effects ordered
probit model respectively.
The results highlight the high level of statistic significance of the included variables. The two
goodness of fit, we use, increase monotony with the inclusion of more variables. Comparing
across model, pseudo-R² is higher in the random effects specification, suggesting that this
model explains better the choice of exchange rate regime in our sample.
Most variables show a robust and significant unchanged sign across all models under both
specifications strategy with a few exceptions.
The variables that stay robust under all models in both specifications include: openness,
specification level, financial development, liability dollarization and capital control factors.
Foreign liability variable has more larger and significant effects in random effects
specification. The GDP per capita, although play a significant role in favour of more fixed
regime in the full sample pooled, it has a very small and insignificant effects in the random
effects one. Either, currency mismatch has no significant effects in pooled model; it seems to
be positively associated with floating exchange rate regime under two models (column 3-4) in
random effects specification.
Control for corruption variable has no significant effect in the pooled model while it has a
very significant effect in the random effect model.
In contrast, while almost all previous variables raise the likelihoods of preferring a fixed
exchange rate, the effect of inflation differential on the probability of choosing a specific
regime appears puzzling. This variable, notwithstanding shows a strong positive association
with floating regime in the pooled specification it turns to be significantly associated with
fixed one in the random effects specification. Geographical concentration of trade was not
associated with any particular regime in both specifications.
The previous results, in generally, suggest that MENA countries fit well with their pegged
adjustable rate. In fact, the expected effect of some variables on the choice of exchange rate
regime is not so evident a priori and has to be analysed attentively. This concerns mainly
factors related to openness, level of specialisation, and the financial development.
The conventional view on the choice of exchange rate regime stress that more open economy
are more exposure to external and reel shocks such as terms-of-trade fluctuation. This is
probably true for our sample countries, where most countries are small in size and are mainly
producer and exporter of primary goods like as oil and agriculture product for which prices
are very volatile. A more flexibility of exchange rate in this case allows for rapid adjustment
of relative prices by exchange rate instrument without incurring a high output cost especially
if domestic price are rigid and administrable controlled, as is the case, so that the adjustment
of domestic prices will be slow. Moreover, one would expect that face to large external
negative shocks, the central bank would need to intervene heavily in order to maintain a stable
exchange rate. If such negative shock still for long time, the risk of speculation pressure will
rise and the peg may be no more sustainable. More generally, the choice of floating regime
should likely be better for more open and financially developed economies with higher
vulnerability to reel external shocks.
However, the choice of fixed exchange rate may lie beyond other reasons. It is argued that if
the balance sheet effects exist, the conventional wisdom may be do not hold.
More over, a high sensitivity of domestic prices to exchange rate fluctuation makes the case
for fixed exchange rate to be preferred. Note, that a high value for openness variable means
also a high pass-through.24 A high exchange rate fluctuation under floating exchange regime
worse the bank’s balance sheet and could trigger a financial crisis given the intrinsic currency
24 for middle East countries, the he coefficient of pass-through is 0.49 and 0.96 for the periods 1990-1999 and 2000-2007 respectively ( Allégret, Ayadi, Khouni (2008)
mismatch and liability dollarization in banks’ balance sheet. An explanation of this logic is
that, if the exchange to depreciate in response to negative shock the dollar denominated debt
burden will increase and increase hence liability dollarization, while revenues from depressed
domestic economy decrease, thus triggering bankruptcy and further output contraction despite
the expansionary effects of devaluation, (Honig 2005). The balance sheet effects are reflected
by the high significant coefficient for liability dollarization variable in our estimation.
Yet more, the case for more flexible exchange rate regimes will be more relevant in more
financial developing economies. However, financial and foreign exchange markets in MENA
countries are thin. Indeed, this countries lack the institutional requirement for a domestically
oriented policy as inflation target making it difficult to conduct an effective monetary policy
under floating exchange rate.
Currency mismatches variable measure the extent of exposure to currency risk. A currency
mismatch ratio highly superior to 1 state that the country is incapable to match its foreign
liabilities by its foreign assets meaning higher exposure to currency crises. If it is the case, we
can expect that more flexible regime would be preferred because fixed exchange rate will not
be sustainable. These results are in line with the fear of floating approach of Calvo and
Reinhart (2002) and Haussman, Ugo and Stein (2000/2001))
Turning to inflation differential variable, we expect that countries with persistence higher
inflation rate relative to their trading partners would rather opt for floating exchange rate,
because persistence higher inflation rate makes the peg more difficult to be sustained.
Nevertheless, inflation rate is subject to endogeneity and reverse causality problem. It is not
always obvious if the inflation rate affects the choice of a particular exchange rate regime or if
it is the result of the exchange rate regime in place. However, we expect that a country with
weak institution would likely peg in order to import the monetary credibility and anchor
inflationary expectation.
Capital account control variable is associated with fixed exchange rate as expected indicating
more ability to maintain the fixed rate. Control for corruption is also associated with fixed rate
suggesting that countries with better institutional quality are more able to keep their
commitment to peg and to maintain the required macro economic stability for holding the peg.
to sum up our finding, a country in our sample would likely choose to fix its exchange rate de
jure if it has the following characteristics: high openness or/and pass through level, more
economically and financially developed, high level of specialization in primary goods exports,
various capital control and good institutional quality. A more flexible rate would be retained if
inflation bias or currency risk exposure is very high.
5.1.25.1.25.1.25.1.2 De Facto Exchange Rate Regime
Although the de jure classification reflects the commitment to a particular exchange rate
regime, nevertheless, it fails to capture macroeconomic policy that is inconsistent with the
announced regime. For example, if the institutional setting prevents the country from
maintaining exchange rate stability while the country still claims to have its exchange rate
fixed, the failure to sustain the fixed rate will not be reflected in the regression results, Vuletin
(2004).
For this reason we test in this sub-section the robustness of our previous finding for de facto
classification using the two estimation strategies mentioned before. Goodness of fit increase
progressively with the inclusion of more variables as before, but it is now larger in the full
pooled model than in the restricted one. Table (9-a and 9-b) reports the results for LYS
classification.
First of all, the results yield a very significant and robust coefficient estimate for currency
mismatch, foreign liability and capital control factors. These results in line with those
obtained for de jure classification, but they show now larger and stronger significant effects.
Inflation differential is also robust and positively related to floating exchange rate. This sign
for inflation under de facto classification provide an explanation for our previous finding, the
negative sign for inflation in the restricted de jure specification, suggesting that countries use
fixed exchange rate as a credibility singling device. Control for corruption is associated with
fixed exchange rate as before but it is now more significant under random effects
specification. Trade concentration variable has always no effect on regime choice.
GDP per capita’s coefficient is small and has no significant effect across all models except in
one model in the random effect specification.
Specialization level has no more significant role in explaining exchange rate regime choice in
the pooled model. Or, it appears to be interestingly positively but not robustly related to
more flexible regime in the random effect specification (model3) 25 Moreover, financial
development variable works now in favour of more flexible exchange rate regime as predicted
by OCA theory.
Other robust but ambiguous result concerns the coefficient estimate of openness. This variable
inters the regression with a significant negative sign (column 1) but it changes the sign when
introducing inflation differential variable in the regression. To explore any potential
25 It is significant at 11% and 12% in model (1) and (2) respectively. In fact, the restricted model does not include the 6 oil exporting Gulf countries making the value of specialization in primary goods very low
connection between the two variables, we rerun the regression for models 2-3-4 after
eliminating inflation variable. Interestingly, openness variable find again the previous
negative sign. We then rerun the same regression eliminating this time openness variable. The
sign of inflation coefficient did not change. Many researches try to explore the relationship
between openness and inflation rate. One explanation is provided by Romer (1992) who
studies the relation between openness and inflation on a large sample of countries using Barro
Gordon type model. Romer finds that openness is associated with lower inflation and that, the
disinflation effects of openness appear to be stronger in countries with floating exchange rate
regime. He explains that unanticipated monetary expansion cause real exchange rate to
depreciate, and since the harm of real depreciation is greater in more open economies, the
benefit of surprise inflation is decreasing function of the degree of openness. This implies
that, in the absence of pre-commitment, monetary authorities in more open economy will on
average expand less and the results will be lower average inflation. This is especially an
important issue for dollarized and highly indebted economies. Taking this in mind, the
positive correlation between openness and fixed exchange rate is still hold.
In general conclusion, a country would likely choose de facto fixed exchange rate regime if it
has a high pass through, foreign liability dollarization, capital account controls and goods
institutional quality. A more flexible regime is preferred with a higher inflation differential
rate and a higher currency risk exposure.
6 ConclusionConclusionConclusionConclusion
This paper has discussed and analyzed empirically the determinants of exchange rate
regime choice in MENA countries since 1990. Many indicators have been used to proxy for
different relevant factors that may have influenced the decision about the exchange rate
regime. During most of the period from 1999 to 2000, usually a period of structural reforms,
several countries have reconsidered their choices and have followed more flexible exchange
rate policy as they become more open and integrated in international economy.
Nonetheless, even countries with more flexible exchange rate regime have manifested some
fear of floating. They continue to intervene heavily in exchange rate market, often sustain
capital account control, and still stockpiling reserves as complementary strategies to attenuate
exchange rate fluctuations when necessary. Our finding points that, although the higher
vulnerability of this region to external and real shocks, which calls for a more flexible
exchange rate as suggested by the conventional wisdom view, the fear of floating factors such
as a high pass through and a foreign liability dollarization were behind the rationality of the
adjustable peg exchange rate regime choice; since fixed rate provides more financial stability
in the face of external shocks when balance sheet effects prevails. However, for country with
a high inflation differential rate and a higher exposure to currency risk, a more flexible regime
seems better.
References Alesina, A.F., wagner, A.F., (2006) Choosing and reneging on exchange rate regimes, Journal of the European Economic Association, Vol. 4 No. 4, June 2006 , pp: 770-799. Allégret J.P., Ayadi M., Khouni L.H, (2008), Le choix d’un régime de change dans les pays émergents et en développement peut-il etre optimal dehors des solutions bi-polaires ?, Université Lumiere 2 Lyon, GATE working paper No. 19, July 2008. Bénassy-Quèré, A., Coeuré,B., (2002), The survival of intermediate exchange rate regimes” CEPII working paper No.7, July 2002. Bernhard, W., Leblang, D., (1999), Democratic institutions and exchange-rate commitments, International Organization Journal, Vol. 53, 1999, pp: 71-97. Berg A., Borensztein E., (2000), The choice of exchange rate regime and monetary target in highly dollarized economies”, IMF Working Paper No. 29, February 2000. Bubula, A., Okter-Robe, I., (2002), The evolution of exchange rate regimes since 1990: evidence from de facto policies”, IMF working paper No: 155, 2002. Buttler. J., Moffit. R., (1982), A computationally efficient quadrature procedure for the one factor multinomial probit model, Econometrica, vol 50, No: 3, May 1982, pp: 761-764. Calvo, G. A., Reinhart, C. M., (2000), Fixing for your life, NBER Working Paper No. 8006, November 2000. Calvo, G. A., Reinhart, C. M., (2002), Fear of floating”, The Quarterly Journal of Economics, Vol.117, Issue 2, Mayy 2002, pp: 379-408. Chang, R., Velasco, A., (1998), Financial fragility and the exchange rate regime, Economic Research Reports, New York University, Faculty of Arts and Science, Department of Economics, February 1998. Collin, S. M., (1996), On becoming more flexible: Exchange rate regimes in Latin America and Caribbean.” Journal of Development Economics, Vol. 51, September 1996, pp: 117-138. Coudert V., Dubert M., (2004), Does exchange rate regime explain differences in economic results for Asian countries? CEPII Working paper, May No. 2004-05. Devereux B. M., (1999), A simple dynamic general equilibrium analysis of the trade-off between fixed and floating exchange rate, Discussion Paper No. 99-22, University of British Columbia and Centre for Economic Policy Research, September 1999. Dubas, J. M., Lee, B-J., and Mark, N. C., (2005), Effective exchange rate classifications and growth”, NBER Working Paper No. 11272, April 2005. Edwards, S., (1996), The determinants of choice between fixed and flexible exchange rate regimes.” NBER Working Paper No. 5756, September 1996. Eichengreen, B., Hausmann, R., and Ugo P., (2003), The Pain of Original Sin, 2003. Frechette, G., (2001), Random-effects ordered probit. STATA Technical Bulletin, Vol: 10, No: 59, 2001. Glick R., Hutchison M., (2005), Capital controls and exchange rate instability in developing economies, Journal of International Money and Finance, No. 24, pp: 387-412, 2005. Gosh, A.R., Gulde, A-M., Ostry J. D., and Wolf, H. C., (1997), Does nominal exchange rate matter?”, NBER Working Paper No. 5874, January 1997. Greene, W., (2002), convenient estimation for the panel probit model: further results, Department of Economics, Stern School of Business, New York University, March 2002. Greene, W., (2002), Econometric analysis of cross-section and panel data, th edition, Princeton-Hall International, Inc, July 2002. Hausmann, R., Ugo, P., and Stein, E., (2000), Why do countries float the way they float? Inter-American Development Bank, Research department, Working Paper No. 418, May 2000.
Hausmann, R., Ugo, P., and Stein, E., (2001), Original sin, pass-through, and fear of floating, January 2001. Hausmann, R., Ugo, P., (2003), The determinants of "Original Sin": An empirical investigation”, Journal of International Money and Finance, Vol. 22, Issue7, December 2003, pp: 957-990. Honig, A., (2005), Fear of floating and domestic liability dollarization, Emerging Market Review, Vol 6, Issue 3, June (2005), pp: 289-307. Honig, A., (2007), Dollarization, Exchange Rate Regimes and Government Quality, Department of Economics, Amherst College, May 2007. Krugman, P., (1996), Are currency crises self-fulfilling? NBER Macroeconomics Annual Cambridge, pp: 345–78, 1996. Levy-Yeyati, E., Sturzenegger, F., and Reggio, (2006), I., On the endogeneity of exchange rate regimes, Paper provided by Harvard University, John F. Kennedy School of Government in its series Working Paper Series, No. rwp047, November 2006. Levy-Yeyati, E., Sturzenegger, F., (2005), Classifying exchange rate regimes: Deeds vs. Words, European Economic Review, Vol. 49, Issue 6, August 2005, pp: 1603-1635. McKinnon, R., (1963), Optimum currency areas, American Economic Review 53, (1963), pp: 717-725. Mundell, R., (1916 a), A theory of optimum currency areas, American Economic Review 51 (1916), pp: 509-517. Obstfeld, M., Rogoff, K., (1995), The mirage of fixed exchange rates, Journal of Economic Perspectives, Vol. 9, July1995, pp: 73-96. Poirson, H., (2001), How do countries choose their exchange rate regime? IMF working paper No. 46, April 2001. Reinhart, C., Rogoff, K. S., and Savastano, M. A., (2003), Addicted to Dollars, NBER Working Paper No.10015, October 2003. Reinhart, C., Rogoff, K. S., and Savastano, M. A., (2003), Addicted to Dollars, NBER Working Paper No.10015, October 2003. Romer H. David, (1992), Openess and inflation: Theory and evidence, University of Califirnia, Berkeley, Department of Economics, National Bureau of Economic Research, NBER Working paper No. w3936, December 1992. Shambaugh, J. C., (2004), The effect of fixed exchange rates on monetary policy, Quarterly Journal of Economics Vol.119, 2004, pp: 301-52. Swoboda, A. V., (2004), Exchange rate regimes: Does what countries say matter, graduate institute of international studies, Geneva, Switzerland, May 2004. Tonell, A., Velasco, A., (1994), Fiscal policy and the choice of exchange rate regime, Inter-American Development Bank, Office of the Chief Economist, working paper N: 303, November 1994. Von Hagen, J., Zhou, J., (2004), choice of exchange rate regimes in developing countries: a multinomial panel analysis, ZEI Working Paper No.32, 2004. Vuletin, G. J., (2004), Exchange rate regimes and fiscal performance. Do fixed exchange rate regimes generate more discipline than flexible ones?, North American Winter Meeting of the Econometric Society Working Paper No. 474, 2004.
Annex I
Table 1: Exchange Rate Classification
Regime IMF BOR LYS
0 Fix Pegged to: single
currency,composite of currencies
conventional fixed peg to single currency, conventional
fixed peg to basket Fix
1 Intermediate Flexibility limited, peg with
horizontal bands, crawling peg crawling bands
pege in horizontals bands, forward-looking crawling peg,
No. Of obs. 197 194 194 155 Log likelihood -170.64092 -161.51139 -161.25433 -111.85114 Pseudo R² 0.1376 0.1733 0.1746 0.2657 Note: z-statistics are presented below the coressponding coefficient standard errors are corrected for potential heterososcedasticity using Huber/White/sandwich estimator Full sample: 17 countries 1990-2006 *** Significant at 1% level. ** Significant at 5% level. * Significant at 10%
Table 8-b : Choice of Exchange Rate Regime: IMF (de Jure) Classification
No. Of obs. 174 171 171 139 Log likelihood -110.11496 -82.971904 -83.695372 -58.551184 Pseudo R² 0.2401 0.4142 0.4091 0.4927 Note: z-statistics are presented below the coressponding coefficient standard errors are corrected for potential heterososcedasticity using Huber/White/sandwich estimator Full sample: 17 countries 1990-2004 *** Significant at 1% level. ** Significant at 5% level. * Significant at 10%
Table 9-b : Choice of Exchange Rate Regime: LYS (de Facto) Classification Random Effects Ordered Probit Model Estimation
