This paper analyzes the 2002 Argentine crisis using the Jeanne and Masson (2000)
model with sunspots. Testing this model empirically through a Markov-switching model
suggests that self-sulfilling prophecies is a reasonable explanation for the devaluation of
the peso

Boinet, V

Napolitano, O

Spagnolo, N

English

Brunel University Research Archive

Are currency crises self-fulfilling?the case of ArgentinaVirginie Boinet, Oreste Napolitano and Nicola Spagnolo∗Department of Economics and Finance, Brunel University, LondonOctober 3, 2002AbstractThis paper analyzes the 2002 Argentine crisis using the Jeanne and Masson (2000)model with sunspots. Testing this model empirically through a Markov-switching modelsuggests that self-sulfilling prophecies is a reasonable explanation for the devaluation ofthe peso.Keywords: Currency crises, multiple equilibria, Markov-switching.JEL Classification: C22, D84, F311 IntroductionThroughout the eighties, the Argentine economy suﬀered from very high levels of inflation.To tackle hyperinflation, the convertibility system was introduced in 1991; it involved a currencyboard in which the peso was pegged one-to-one to the US dollar. Its success was undeniable inthis respect as it provided Argentina with its longest period of price stability within the last fiftyyears. Nevertheless, at the end of the nineties, domestic interest rates increased dramaticallyabove US levels, putting Argentina’s economy into severe recession. By the beginning of 2002,the peso had been devalued by approximately 50% and sovereign debts of over 150 billion dollarswere in default.According to Fronti, Miller and Zhang (2002), this final stage can be interpreted in twodiﬀerent ways. The Fenix plan (2001) pointed out the unsustainability of the peg because ofadverse economic fundamentals. The appreciation of the dollar against the euro, the devaluation∗We would like to thank Michael Arghyrou, John Bennet, Eric Girardin and Chris Martin for very usefulcomments and suggestions. Corresponding author: Virginie Boinet, Department of Economics and Finance,Brunel University, Uxbridge, Middlesex UB8 3PH, United Kingdom. Tel. +44 01895 203386, Fax: +44 01895203384. E-mail: virginie.boinet@brunel.ac.uk1of the Brazilian real, and the increased foreign debt made the peso over-valued and the debtburden unsustainable. In contrast, Mr. Cavallo (Economy Argentinian Minister) insisted thata credible peg oﬀered the prospect of low interest rates and continued economic growth. Thatmeans that advocating devaluation and default would wipe out the credibility gains achievedsince the beginning of the currency board.Without denying the important role of economic fundamentals, the aim of this paper is toinvestigate whether the crisis in Argentina was, to some extent, self-fulfilling. Our theoreticalbasis is the so-called “second-generation” models which explain a currency crisis as follows: thecost of maintaining the peg (an increase in unemployment or public debt for example) bringsthe sustainability of the fixed rate into question. Therefore, expectations of devaluation inducea policy change (typically an increase in the interest rate) that makes the crisis self-validating(Obstfeld, 1994; Jeanne, 1997). These models allow for multiple equilibria, and a crisis canoccur, even though economic fundamentals do not change, simply because private agents expectit. In the recent literature on self-fulfilling crisis, a very appealing approach was proposed byJeanne and Masson (2000). They provide a model with sunspots (multiple equilibria), whichtheoretically justifies the use of the Markov-switching regimes approach in empirical work oncurrency crisis. As a result, they show that the switch across regimes corresponds to jumpsbetween diﬀerent equilibria explained by abrupt shifts in devaluation expectations. We applytheir methodology to the Argentine peso to assert whether a model with multiple equilibria fitswell and therefore whether this crisis can be explained by self-fulfilling prophecies.The structure of the paper is as follows. Section 2 reviews and explains the estimationprocedure. Section 3 describes the results. Section 4 summarizes and concludes.2 The ModelWe use a two-state Markov-switching regimes of devaluation expectations. The dependantvariable (π) is the probability of devaluation. As Svensson (1993), and Jeanne and Masson(2000), we use as a proxy the diﬀerential between Argentine and US interest rates.1 The driftadjustment method of Svensson (1993) which refers to a target zone is not required in our casewhere the exchange rate remains totally fixed. Our sample includes quarterly data from 1992:1to 2001:4 taken from the IMF databank provided by Datastream. The economic fundamentalsthat we consider include the growth rate (gr), the deficit to GDP ratio (def), the real exchangerate (rer)2 and the trade balance as a ratio of GDP (trbal).3 These fundamentals are those1The proxy is expressed in percentage terms to ensure that the devaluation probability belongs to [0,1].2The real exchange rate is expressed by the ratio of domestic prices over US ones. The nominal exchange-ratedoes not appear because it is fixed and equal to one.3It is important to note that we have experimented with other fundamentals variables including foreigndirect investment flaws, money growth (narrow and wide definition) and unemployment rate. All of them werestatistically insignificant. It is also worthy to mention that we used deficit instead of the stock of public debt2underlined by the authors of the Fenix plan. The real exchange rate is essential to capturetensions related to the strength of the dollar. Furthermore, the trade balance allows us to alsoconsider problems of competitiveness due, to a large extent, to the devaluation of the real inBrazil (its largest trading partner) in 1999. The equation for the devaluation probability is thusspecified as4:πt = γst + βggrt + βddeft + βrrert + βbtrbalt + νt, t ∈ T (1)where the value of the constant term γ depends on the state {st}. The latter are random variablesin S = {1, 2} that indicate the unobserved state of the system at date t (credible versus non-credible). Throughout, the regime indicators {st} are assumed to form a homogeneous Markovchain on S with transition probability matrix P0 = [pij]2×2, wherepij = Pr(st = j|st−1 = i), i, j ∈ S,and pi1 = 1− pi2 (i ∈ S). It is also assumed that {st} and {vt} are independent with the errors,νt, normally distributed, with variance σ2v.Therefore, shifts across regimes aﬀect the devaluation probability by changing the constantterm of equation (1), but leave the coeﬃcients of the fundamentals unchanged (Jeanne andMasson, 2000). More particularly, a jump to a state of higher devaluation expectations makesthe devaluation more likely by increasing the constant term.3 Empirical ResultsWe first estimate the model without multiple equilibria using ordinary least squares, in orderto test a purely fundamentals-based model. The parameter estimates, together with associatedp-values, likelihood function values, and diagnostic statistics are presented in Table 1. Tests forserial correlation and heteroskedasticity in the standardized forecast residuals are also reported.The forecast values for the probability of devaluing are plotted against the data in Figure 1(first graph). The explanatory power of the fundamentals seems to be poor. The coeﬃcientshave the expected sign only for growth and deficit but not for the real exchange rate and thetrade balance. From Figure 1 (first graph), it can be seen that the fitted values follow the trendof πt, but do not capture movements associated with episodes of speculative attacks.The null hypothesis of linearity against the alternative of a Markov regime switching cannotbe tested directly using a standard likelihood ratio (LR) test.5 Therefore, we apply Hansen’sbecause all series available for the latter are discontinued.4This equation corresponds to the linearized reduced form of the Jeanne and Masson (2000) model withsunspots (see p. 340).5This is due to the fact that standard regularity conditions for likelihood-based inference are violated underthe null hypothesis of linearity, as some parameters are unidentified and scores are identically zero. However,appropriate test procedures that overcome the former or both of these diﬃculties do exist (Hansen, 1992, 1996;Garcia, 1998).3standardized likelihood ratio test. This procedure requires the evaluation of the likelihoodfunction across a grid of diﬀerent values for the transition probabilities and for each state-dependent parameter. The value of the standardized likelihood ratio statistics is 4.751 whichhas zero P -values under the null hypothesis6 (Table 2). We also test for the presence of a thirdstate (Table 2). The results provide strong evidence in favor of a two-state regime-switchingspecification.Insert Tables 1 and 2As shown in Table 1 (second column), the relation improves when the model is estimatedtaking into account an additional state. The fit of the model is considerably better, as evidencedby a lower σv, a higher log likelihood and very diﬀerent values of γ in the two states. Indeed,the value of the constant is substantially bigger in the “crisis” regime than in the other one.Therefore, for a same level of economic fundamentals, a jump in devaluation expectations leadsto a much higher probability of devaluation. Each coeﬃcient now has its expected sign and allare significant at the conventional level. Furthermore, the plot in Figure 1 (second graph) showsthat the model with multiple equilibria seems to capture well the episodes of sharp movementsin the devaluation probability.Insert Figure 1Based on the parameter estimates of γ, we can estimate the filter probabilities, which arethe probabilities that each observation is in the high or the low state. The filter probabilities ofa high γ are displayed in the bottom part of Figure 1 (third graph). The probability of stayingin the low mean regime is 0.997, while episodes of high mean last shorter. The diagnostic testsshow no sign of either serial correlation or heteroskedasticity. On the whole, the empirical resultssuggest that a Markov-switching model is able to capture the features of the data, allowing forperiods of unusually high mean through regime switches. The filter seems to match the evolutionof the probability of devaluation quite well. A first jump appears in the second quarter of 1992.This jump lasts until the beginning of 1993 and then the low regime prevails until 2001 (thirdquarter). In that quarter, a second jump to the high regime occurs, proving that higher privatedevaluation expectations have considerably increased the probability of devaluation before thecrisis7. This is illustrated in Figure 1 (second graph) where the probability of devaluationsubstantially increases due to a shift in the constant from 2.759 to 22.53. It seems very diﬃculthere to find the political events or news which could explain these jumps as it would require ahigher data frequency than quarterly. However, our results show that the explanatory power ofeconomic fundamentals improves considerably when abrupt shifts in devaluation expectationsare allowed. This would suggest that, despite adverse economic fundamentals, the peg mighthave been maintained with lower devaluation expectations and, therefore, that the crisis inArgentina was, at least to some extent, self-fulfilling.6The P -value is calculated according to the method described in Hansen (1996), using 1,000 random drawsfrom the relevant limiting Gaussian processes and bandwidth parameter M = 0, 1, . . . , 4, see Hansen (1992) fordetails.7Note that by the third quarter of 2001, the country risk premium was about 1500 basis points in Argentina.44 ConclusionBy using a Markov-switching model, this paper found compelling evidence that self-fulfillingprophecies have played an important role in the Argentina currency crisis of 2002. Indeed, themodel performs remarkably well when two states are considered, thus allowing for abrupt shiftsin devaluation expectations.References[1] Fronti, J., Miller M. and L. Zhang, 2002, Sovereign default by Argentina: “slow motion traincash” or self-fulfilling crisis?, CEPR Discussion Paper 3399.[2] Garcia, R., 1998, Asymptotic null distribution of the likelihood ratio test in Markov switchingmodels, International Economic Review, 39, 763—788.[3] Hansen, B.E., 1992, The likelihood ratio test under nonstandard conditions: testing theMarkov switching model of GNP, Journal of Applied Econometrics, 7, 61—82.[4] Hansen, B.E., 1996, Erratum: The likelihood ratio test under nonstandard conditions: test-ing the Markov switching model of GNP, Journal of Applied Econometrics, 11, 195—198.[5] Jeanne, O., 1997, Are currency crises self-fulfilling ? A Test, Journal of International Eco-nomics, 43, 3/4, 263-86.[6] Jeanne, O. and P. Masson, 2000, Currency crises, sunspots and Markov-switching regimes,Journal of International Economics, 50, 327-350.[7] Obstfeld, M., 1994, The logic of currency crises, Cahiers Economiques et Mone´taires, 43,189-213.[8] Svensson, L., 1993, Assessing target zone credibility: mean reversion and devaluation ex-pectations in the ERM, 1979-92, European Economic Review, 37, 763-802.5TABLE 1Parameters Linear Markovγ1 55.17(0.009)2.759(0.000)γ2 22.53(0.000)βg −37.41(0.116)−9.704(0.001)βd 0.301(0.101)0.080(0.021)βr −75.68(0.024)2.345(0.001)βb 0.186(0.679)−0.065(0.046)p11 0.997(0.001)p22 0.522(0.001)σν 5.132 2.867LogLik −119.51 −114.58Q(5) 0.521 0.167Q2(5) 0.854 0.244Note:Q(5) and Q2(5) are respectively the Ljung-Boxtest statistics for 5 lags in the standardized andstandardized squared residuals. P-values arereported in parentheses.TABLE 2Standardized LR testLinearity versus two-states Two states versus three-statesMarkov switching model Markov switching modelLR 4.751 0.8734M = 0 (0.0001) (0.4352)M = 1 (0.0001) (0.4351)M = 2 (0.0001) (0.4352)M = 3 (0.0001) (0.4355)M = 4 (0.0001) (0.4367)Note: See Hansen (1996) for details of the test statistic, such as the definition of M.P -values are in parentheses.6-10010203092 93 94 95 96 97 98 99 00 01ACTUAL FITTEDOne-state model05101520253092 93 94 95 96 97 98 99 00 01ACTUAL MARKOVTwo-state model0.00.20.40.60.81.0010203092 93 94 95 96 97 98 99 00 01FILTER1 ACTUALFigure 17

Are currency crises self-fulﬁlling ? A Test,

Assessing target zone credibility: mean reversion and devaluation expectations in the ERM, 1979-92,

Asymptotic null distribution of the likelihood ratio test in Markov switching models,

Currency crises, sunspots and Markov-switching regimes,

Erratum: The likelihood ratio test under nonstandard conditions: testing the Markov switching model of GNP,

Sovereign default by Argentina: “slow motion train cash” or self-fulﬁlling crisis?,

The likelihood ratio test under nonstandard conditions: testing the Markov switching model of GNP,

The logic of currency crises,

Are currency crises self-fulfilling? The case of Argentina

Are currency crises self-fulfilling? The case of Argentina

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