Public Choice 111: 209–236, 2002. © 2002 Kluwer Academic Publishers. Printed in the Netherlands.
209
Containing contagious financial crises: The political economy of joint intervention into the Asian crisis ∗ KJELL HAUSKEN1 & THOMAS PLÜMPER2 1 School of Economics, Culture and Social Sciences, University of Stavanger, N-4091 Stavanger, Norway; e-mail:
[email protected]; 2 Faculty of Public Administration,
University of Konstanz, D-78434 Konstanz, Germany; e-mail:
[email protected] Accepted 23rd October 2000 Abstract. The notion of contagion has changed the way scientists perceive financial crises, causing heated debate on the political economy of crisis intervention. Based on a formal model that shows how a financial crisis can escalate and spread contagiously, this article analyzes game-theoretically how a financial market crisis can be contained through intervention. The central focus is the role that international organizations play in overcoming the collective action problem of joint intervention. It is argued that the IMF support programs were helpful, and probably necessary in a class of cases we analyze more carefully, in surpassing the threshold level of collective action.
1. Introduction Before the onset of the Asian crisis, financial crises were mainly considered a result of poor national regulatory systems and unsound economic policies. Most observers contend that political failures make economies prone to exogenous economic shocks, and then a crisis occurs (Krugman, 1979; Kaminsky, 1998). This view of economic crises is similar to the way in which physicians characterize the onset of a heart attack. A crisis occurs as a sudden and isolated event. The Asian crisis dramatically changed the way financial turmoil was perceived. Financial turbulence in Asia suddenly emerged in Thailand in the spring of 1997, and ended in Indonesia in 1999. That a crisis could emerge in relatively well-governed and fast-growing economies astounded most observers (Eichengreen, 1998: 186). The Asian crisis unexpectedly illustrated that countries with seemingly favorable economic and financial ∗ Earlier versions of this paper were presented at the Universities of Constance and Mannheim, at the Arbeitskreis für Handlungs- und Entscheidungstheorie annual conference in Stuttgart, 26th–27th February 1999, and at the DVPW section International Politics conference in Arnoldshain, 8th–10th July 1999. We would like to thank the conference and workshop participants, as well as Marcel Fratzscher, Bernhard Boockmann, and Gerald Schneider, for their helpful comments. Brooke A. Luetgert provided excellent language assistance.
210 conditions may encounter severe economic problems if similar and neighboring countries do. Thus, crises are no longer considered isolated events. On the contrary, the notion of contagion has received widespread attention, dominating both academic journals and the popular press (Radelet and Sachs, 1998; Eichengreen et al., 1996; Choueiri, 1999; Fratzscher, 1998; Kaminsky and Reinhart, 1998; Stiglitz, 1998). This view of economic crises is similar to the way physicians think about, for example, a flu epidemic or the plague. A contagious financial crisis begins in a given location and may escalate and spread, threatening the infection of other countries. The strongest or more financially stable countries may be more resistant to financial crisis, but may experience diminishing growth rates, caused by a decline in trade. As a consequence, the stronger countries may find it in their own best interests to implement counter-measures. The notion of contagion has also changed the way government intervention into financial market crises is heeded. After the Asian crisis, almost all economists were sceptical about the provision of financial support to countries affected by a crisis. In their view, an expected ‘bail-out’ increases the creditors’ incentive to invest in risky assets, and thereby also increases the likelihood of future crises. While this line of argumentation certainly holds some truth, it nevertheless became apparent that ‘doing nothing’ in a serious crisis would most likely be even more damaging than expected, because a crisis spreads and may ultimately endanger the entire global financial system. Governments in industrialized and neighboring countries, which face the threat of a regional crisis, may often have an incentive to ‘intervene’, thereby transforming the short-term liabilities of countries in crisis into long-term liabilities. Hence, the notion of contagion has changed the view governments and central banks have of intervention in a crisis, because the opportunity costs of ‘doing nothing’ dramatically increase. Instead of calculating the costs of a crisis in a single and apparently isolated country, politicians must now consider the potential costs of a widespread financial epidemic. A country’s incentive to ‘do something’ does not only result from its economic ties with an already infected country, but also from its relations with countries threatened by contagion. However, that a country has an incentive to intervene in a contagious financial crisis does not mean that it will actually intervene. The problem with containing a financial crisis is that the costs of intervention most likely exceed each single country’s incentive to intervene. Containing a financial crisis typically constitutes a collective action problem where each country prefers joint action, while each country is better off when it can free-ride on
211 the other countries that incur the costs of intervening monetarily in tumbling markets. In the remainder of this article, we analyze the dynamics of intervention in contagious currency crises from a game-theoretical perspective. Although contagion is not our principal concern, in Section 2 we nevertheless begin by developing a dynamic model of how a financial crisis emerges, and may escalate and spread. We then model how the crisis can be remedied or at least contained either ‘artificially’ through intervention, or ‘naturally’ due to the lapsing of time. In Section 3, we chronicle the Asian crisis from the perspective of intervention. In Section 4, we use a simple principal component analysis to quantify the severity of the crisis in the three aforementioned countries, and simulate the dynamics of the crisis in a study based on the model developed in Section 2. Section 5 evaluates the incentives to intervene in a number of selected countries, and interprets the results in game-theoretical terms. The evaluation of countries’ utilities uses the crisis severity indicator and the results of the simulation study. Section 6 relates the results obtained to the broader discussion of the future of the IMF and the quest for an international-lender-of-last-resort.
2. The model 2.1. Modelling a contagious financial crisis Conventional models of contagious spread in the sense of epidemiology are digital in nature: an agent is either infected or not infected.1 A financial crisis in country i is continuous in nature, which we model as a degree si (t) to denote the severity of the crisis (the severity of the ‘infection’) at time t, 0 ≤ si (t) ≤ 1.2 si (t) equals zero before the crisis starts, i.e., si (t) = 0 when t < 0. si (t) can also be interpreted as the probability that a crisis of severity 1 occurs at time t. An incipient crisis in country i may grow in severity just as a virus spreads, making the infected agent gradually more unwell. One of the most common ways of modelling such ‘growth’, which generally means modelling the kinetics of an evolving system, is to use the analogy from population ecology. Lotka (1924: 64–66) assumed that the growth of a single population X growing under constant conditions is a function F(X) of the population X. Developing F(X) as a Taylor series gives ∂X/∂t = F(X) = A + BX + CX2 + DX3 + . . .
(2.1)
F(X) has one root at X = 0,3 hence A = 0. To allow for a stationary population, a second root is necessary. Lotka chose the simplest two-root version of (2.1), viz.
212 ∂X/∂t = BX + CX2 ⇒ X(t) =
B
−C + e−Bt
B X(0)
+C
,
(2.2)
which is known as the logistic function.4 X(t) increases in an S-shaped manner from X(0) to −B/C, assuming 0 < X(0) < −B/C. For our purposes, modelling the severity si (t) of a crisis to increase logistically in degree from 0 to 1, we rewrite (2.2) as 1 ∂si (t) , = ai si (t)(1 − si (t)) ⇒ si (t) = 1 ∂t 1 + e−ai t si (0) −1
(2.3)
where ai denotes the speed by which country i becomes increasingly affected by the crisis. The growth of ai si (t) starts out as virtually exponential when t is small. As t increases, ai si (t)2 grows large, limiting the growth of si (t), which would stop if it reached ai si (t)(1 − si (t)) = 0 or si (t) = 1. This point is approached but never reached. (2.3) assumes that ai is constant. The nature of a financial crisis is such that it may either cease to exist by itself in a ‘natural’ way (e.g., as a person naturally recovers from having flu without medical treatment), or it may be brought ‘artificially’ to an end through monetary intervention designed to remedy/contain the crisis (e.g., as a person ‘artificially’ recovers from having flu with the help of medication).5 Hence, we substitute ai with a term that varies over time and can be both positive (as the severity of the crisis increases) and negative (as the crisis is cured/contained or ceases to exist). We therefore substitute (2.3) with ∂si (t) = [ai − bi Ii (t) − vi (t)]si (t)(1 − si (t)), (2.4) ∂t where Ii (t) is the impact of the intervention in country i at time t, bi is a constant, and vi (t) is a suitable stopping function for how the crisis may cease to exist on its own. We propose 0 when t < ts (2.5) vi (t) = eαi (t−ts ) − 1 when t ≥ ts , where αi is a constant and ts is the time at which the crisis starts to remedy itself in a natural way. 1 − si (t) can be interpreted as the probability that the crisis is contained at time t. Assuming there is no crisis prior to t = 0, i.e., sj (t) = 0 for all j when t < 0, a crisis originates at time t = 0 in one or several countries j by letting sj (0) > 0 for at least one j, j = 1, . . . , n, where n is the number of countries. To model how a crisis spreads contagiously from
213 country j to country i, we introduce a linkage parameter rji , determined by the economic channel between j and i, where rii = 1. rji is large if i is strongly affected by a crisis in j, small if affected to a lesser degree, and zero if not affected at all.6 We measure the monetary contagion effect directly by estimating the severity in affected countries, while setting the linkage parameter rji consistent with the empirical analysis by Taimur Baig and Ilan Goldfajn (1998). A crisis spreads more quickly when the rji -values are large. Multiplying rji with the severity sj (t) of the crisis in country j, adding this product up over all infected countries, and dividing by the GDP in country i, gives an expression of how much country i is actually affected. With this conception, contagion can be seen as originating in one or several countries j, where sj (0) > 0, and then spreading back and forth between all infected countries until some kind of equilibrium is reached. Consequently, we substitute (2.4), which describes the process of crisis escalation (infection) for one country in isolation, with ∂si (t) ∂t
=
ai GDPi
n
sj (t − Lji)rji − bi si (t)
j=1
n j=0
Iji (t) − vi (t)si (t)
(2.6)
×(1 − si (t)), i = 1, . . . , n, where Lji is the time lag by which contagion in a crisis spreads from country j to country i, and GDPi is the gross domestic product of country i. (2.6) only applies to countries that are prone to contagion.7 According to recent research, the likelihood of contagion depends on a variety of factors, such as the fragility of country i’s financial system, financial market regulation, its current account, the ratio of its reserves to its short-term debt, the economic ties between its financial market and an already affected financial market, the similarity of its export structure to the export structure of already affected countries, investors characterized by a short-term horizon and the possibility of panicking behavior, differential benchmark behavior, etc. (Kaminsky, 1998; Fratzscher, 1998; Kaminsky and Schmuckler, 1999). The first term within the square bracket in (2.6) adds up over all infected countries j how country i is affected by the crisis of magnitude sj (t), multiplied with the linkage parameter rji , in country j. For Iji (t)=0=si (t), note that the root si (t)=0 is only obtained when sj (t)=0 for all j, j = 1, . . . , n, which means that the crisis in i will only cease when it ceases in all countries j where rji > 0. The second term within the square bracket generalizes the intervention process, where Iji (t) is the impact of the intervention by country j in country i and I0i (t) is the impact of the intervention by an institutional actor in country i, given by
214
Ijt (t) =
mji
Ijik (t), Ijik (t) =
k=1
0 when t < tk (2.7) 2 t Ijim (tk )e−βi (t−(tk+di )) e−γ i when t ≥ tk .
We regard the institutional actor to consist of the International Monetary Fund (IMF), the World Bank (IBRD), and the Asian Development Bank (ADB). (2.7) assumes that country j intervenes mji times in country i. Let us consider the intervention of monetary size Ijim (tk ) at time tk , which has impact Ijik (t). Prior to tk , there is no impact. The impact at time tk will not be instantaneous, due to inertia in the economy, and other factors. We expect the impact to increase in a somewhat logistic manner, reach a high point, and then decrease toward zero as the benefits of the intervention are fully absorbed. More specifically, assuming that the impact can be modeled as a Gaussian distribution with a mean tk +di , the high point is suitably reached a time di later than the intervention at tk , where di denotes the inertia in the economy. βi is inversely proportional to the standard deviation of the ‘distribution’, and denotes the sustained impact of the intervention over time. γi accounts for the reduced impact of subsequent interventions, occurring considerably later than the crisis initiation time t = 0. 2.2. Modelling third parties’ incentive to intervene We set st (t) = 0 for all t≥0 for countries that are not prone to contagion. Although such countries cannot be infected by a crisis, they may nevertheless suffer costs resulting from the crisis, particularly if they are strongly connected with infected countries through trade. We model such trade networks with a trade parameter gji (t) determined by the economic channel between j and i. A crisis affects third countries to a greater extent if the gjt (t)-values are large. gji (t) is large if i is strongly affected by a crisis (of some magnitude) in j, small if affected to a lesser degree, and zero if not affected at all. We measure gji (t) empirically by the export level from a non-infected country i to an infected country j (appendix). We therefore model country i’s utility as
ui (t) = unc − λi
n j=1
sj (t − Dji )gji (t) − ci
n
Iij (t), i, j = 1, . . . , n,
(2.8)
j=1
where unc is the ‘reference utility’ with no crisis, gji (t) expresses a ‘cost transfer’ from j to i scaled in size by the constant λi , Dji denotes the time lag of the cost transfer, and ci is a constant that scales the size of the monetary intervention by country i in terms of utility. Dji = 0 unless the infected
215 country has reserves or unless intervention can contain the cost transfer. The cost to uninfected countries as expressed in (2.8) appears as abrupt ‘financial flows reversals’, due to a balance-of-payments crisis. Capital importers prone to infection may suddenly and unexpectedly become capital exporters, due to the flight of investor capital. Unless short-term capital outflows are matched by long-term capital inflows, e.g., through intervention, this implies that infected countries have to reduce their imports. The primary concern of an uninfected country equipped with si (t)=0 is not to avoid infection, but to avoid the negative stimuli in the ‘real economy’. We model the institutional actor (the IMF, IBRD, and ADB) as a collective actor with the utility function u0 (t) =
n
ui (t) − c0
i=1
n
I0j (t), i, j = 1, . . . , n.
(2.9)
j=1
Although it might, in principle, be possible to differentiate between the three international organizations involved, we decided to sacrifice some empirical accuracy here for the sake of increased simplicity. Countries and the institutional actor assess not only instantaneous utilities, but also accumulated utilities from time t = 0 to t = T, expressed by uacc i (T)
t=T = ui (t)δi (t)dt, i = 0, . . . , n,
(2.10)
t=0
where δi (t) is the discount factor in country i, 0 ≤ δi (t) ≤ 1. The objective of each country and the institutional actors is to choose Iij (t) so as to maximize uacc i (T), i.e.,
max uacc i (T) , i = 0, . . . , n, lij (t)
j = 1, . . . , n.
(2.11)
(2.11) is appropriately solved numerically and game-theoretically by considering various simulation scenarios, applying conventional optimization techniques, and determining the mutually best response functions. Observe the strength of the model in that it allows a practitioner to run his own simulation scenarios, including ‘relevant’ countries and third parties, varying parameters, varying sizes of interventions and timing of interventions, and testing hypotheses in a manner that is too space-consuming for this article.
216 3. Financial crisis and the coordination of intervention in Thailand, Korea, and Indonesia The Asian crisis originated in Thailand in the summer of 1997 and only then spread to other Asian countries, most notably to Indonesia and Korea.8 Governments and central bankers in the industrialized world did not consider the crisis to be severe, even though Thailand’s reserves fell from 37 billion to below 10 billion dollars following a desperate effort to maintain the fixedexchange rate regime (Sharma, 1998: 34). Central bankers and politicians obviously underestimated the virulence with which the crisis was spreading to neighboring countries (Eichengreen, 1998: 191). Considering the crisis as a singular event, governments refused to support the Thai economy. To the Thai government’s consternation, even Japan refused its appeals for assistance (Sharma, 1998: 35). Instead, Japan’s finance minister, Hiroshi Mitsuzuka, announced that Japan would stabilize Thailand’s currency, the Baht. However, he explicitly rejected a concrete support package to help relieve the country’s financial problems (FT July 19th, 1997). At the same time, IMF’s deputy managing director, Stanley Fischer, said that the continuing financial problems in Asia were much less severe than those that had struck Mexico in 1994 (FT July 22nd, 1997). Three eventful weeks later, the governments learned that financial assistance to Thailand would be necessary in order to restabilize the country’s economy. On August 11th, 1997, Thailand and the IMF agreed on a support package and economic policy reforms. In addition, Japan took the lead ahead of a group of eight Asian countries9 , unveiling a credit package of 16 billion dollars. At that time, Thailand’s liquidity crisis was considered to be a purely Asian problem, with the USA and the European countries standing aside while Japan hosted a conference with the sole aim of organizing a joint Asian support package. There are at least two reasons for the Japanese intervention efforts during what was considered Thailand’s balance of payments crisis. First, Japan had the largest economic stake in Thailand. Its direct investment position in Thailand had reached approximately 8.5 billion dollars, nearly twice that of the US direct investment position and about 20 times that of German foreign investment in Thailand (OECD, various issues). Secondly, Japan had become aware that the Thai crisis offered an unexpected opportunity to demonstrate its regional leadership potential. However, the Japanese authorities remained ambivalent and appeared to be torn between the country’s ‘regional responsibilities’ and its reluctance to act unilaterally. As one official put it: “It is important that it is not just Japan taking action – we do not want to become responsible for Thailand’s problems alone.” (FT August 8th, 1997). The financing came in the form of medium-term loans, close to market rates, with a maturity of three to five years. After the support
217 program had been negotiated and the Thai government had started a number of reforms on their way, most observers considered the crisis to be resolved. Unfortunately, those who believed that the Thai crisis would come to a rapid end following the announcement of a policy reform package and the approval of support from neighboring countries and the IMF, were soon proven wrong. In the last days of August 1997, the crisis swept over from Thailand to Indonesia and even affected some of the countries who had assembled in support of Thailand. Most importantly, Indonesia failed to defend the Rupiah’s exchange rate to the Dollar. The sharp devaluation of the Indonesian currency made it obvious that the Asian crisis was indeed severe and that it was also threatening the world economy. On August 30th, 1997, the Financial Times published an alarming article arguing that the ‘little local difficulty’ that had emerged in Thailand in July would soon turn out to become a problem of global proportions. By this time, the Asian crisis had already begun to show consequences in Malaysia, Indonesia, Korea, and the Philippines. On October 8th, 1997, the Indonesian government – very unwillingly – approached the IMF for help in stopping the slide of its currency. Since August, the Rupiah had fallen in value by more than 25 percent and the Jakarta Stock Exchange index had dropped by 30 percent. While Indonesia’s reserves had been estimated by IMF officials to be just over 20 billion dollars, the government debt peaked at 50 billion dollars and the private debt was estimated at between 56 and 100 billion dollars. However, partly because the Indonesian government was reluctant to accept IMF conditionality, and partly because industrialized countries could not agree on coordinated intervention, an agreement to support Indonesia did emerge until November 5th, 1997. IMF support was particularly disliked among Indonesian politicians because the IMF demanded a stiff budget cut, the lifting of subsidies on fuel prices, the liquidation of some of Indonesia’s undercapitalized and mismanaged banks, the giving up of plans to establish a national car manufacturer to be managed by President Suharto’s son, Tommy, and the ending of trading monopolies – many owned by the president’s relatives and political friends. Therefore, IMF conditionality threatened not only the politicians’ popularity among the voters, but would also result in deep cuts in the dense system of patronage which had long stabilized Indonesia’s government. While Indonesian officials were about to conclude talks on policy reforms with the IMF, IBRD, and ADB, neighboring countries led by Malaysia and Singapore pledged more than 11 billion dollars. This offer was immediately instrumentalized by the Indonesian government to push the IMF for softer conditionality (FT October 30th, 1997). However, the neighboring countries never stated precisely whether their offer was unconditionally valid or dependent on an agreement between Indonesia and the IMF. Only Singapore
218 claimed it considered the credit line supplementary to the expected IMF support program. After the Suharto government had attempted to urge the IMF into less strict lending conditions, Australia and Japan immediately made it clear that the proposed credit was conditional on an agreement between Indonesia and the IMF. Thus, it was hardly surprising that Indonesia had to back down almost immediately and, only two days later, accepted the conditions insisted upon by the IMF. On October 31st, 1997, just one day after the agreement with the IMF, Indonesian officials announced that they would cut import tariffs, curtail trading monopolies, and close down 16 private banks. After announcement of the agreement, Australia, China, Hong Kong, Japan, Malaysia, Singapore and the USA indicated that, in the event of “unanticipated adverse external circumstances” creating the need for additional resources, they “would be prepared to consider making available supplemental financing.” (IMF: Survey 26:20). This ‘second line of defense’ added up to 17 billion dollars, while the IMF, IBRD, and ADB together made more than 18 billion dollars available to Indonesia. This money was only to be drawn on if the IMF package failed to restore stability. The aggregate size of the support package – about 35 billion dollars – exceeded the amount of money Indonesia’s officials had requested. Initially, the scale of support was placed at four billion dollars. Moreover, the decision by the USA to become directly involved in the political attempts to contain the crisis were considered fierce indicators of how serious the financial turmoil had already become. Additionally, between the onset of the Thai crisis and the outbreak of the financial crisis in Indonesia, politicians had become fully aware of the risk of ‘contagion’. However, the restoration of calm in the region observed after the announcement of the support package to Indonesia only lasted for a week (Kaminsky and Schmuckler, 1999: 541). On November 7th, 1997, the crisis reached Korea and even threatened to affect Japan. Korea initially appeared relatively unaffected by the Asian crisis, but finally became ‘infected’, when the Won began to tumble. On November 19th, 1997 the Korean minister of finance, Kang Kyong-shik, retired because he was accused of having worsened the crisis by neglecting support measures for the financially troubled KIA group. One day after his retirement, Korean officials claimed to have launched an economic reform package that was set up to avert an IMF bail-out. On that day, the Won fell by ten percent as investors showed their disapproval of the reform plans. The following day, November 21st, 1997, the government ‘unconditionally surrendered’ to the markets, and asked the IMF for a support program of approximately 20 billion dollars. The size of the support request was well below the expected 60–80 billion dollars because the government was worried that, with increasing demands, the IMF would ask for tougher
219 conditions. The Korean government correctly anticipated that the IMF would not be reluctant to dismantle ‘Korea Inc.’, which would be the practice of interventionist policies. Upon the announcement of negotiations, the IMF’s deputy managing director, Stanley Fisher, flew to Korea. Japan then indicated that it would not offer financial support to South Korea until Seoul had reached an agreement with the IMF (FT November 21st, 1997). Furthermore, a group of European countries, Britain, France, Italy and Germany, amplified the Japanese position by offering their assistance in the Asian crisis to the IMF. The efforts to contain the Asian crisis had finally become truly global. On December 4th, 1997, the IMF approved a stand-by agreement of over 21 billion dollars. The IMF, IBRD, and ADB contributed another 12 billion dollars, while other countries pledged a second line of defense totalling 23.35 billion dollars (IMF: Survey 26: 23). Ultimately, the IMF committed even more credit to Korea than the government had requested (IMF, 1998; Radelet and Sachs, 1998). Table 1 displays the emerging pattern of intervention. During the early days of the Asian crisis, only Asian countries supported Thailand. The USA stepped in to support Indonesia, while European countries waited until Korea was affected. Although Korea is the 11th largest, Indonesia the 22nd largest, and Thailand the 24th largest economy in the world, Korea’s GDP is still only about five percent of the US GDP. Allan Meltzer thus argues that, although a serious currency crisis in Asia is costly for the industrialized world, it is not a ‘world-shaking event’ (Meltzer, 1998: 271). Nevertheless, there were obvious incentives to intervene. This becomes apparent in Figure 1, which depicts the decline in Japanese, US, and German exports to the most severely affected Asian countries, i.e., Thailand, Indonesia, and Korea. On average, exports to Thailand, Indonesia, and Korea in the second half of 1997 declined by about 50 percent compared to average exports in the first half of 1997. After a sudden collapse in December 1997, imports by Asian countries immediately reached a surprisingly stable level.
4. Simulating the crisis dynamics We begin the empirical analysis of the crisis dynamics with an evaluation of the relative crisis severity in Thailand, Indonesia, and Korea, see Table 2.10 The crisis erupted in Thailand (country i = 1) and we set initial conditions s1 (1) = 0.05 for t = 1 January 1st, 1997. At that time, Indonesia (country i = 2) and Korea (country i = 3) were not infected, and thus, we set s2 (1) = 0 = s3 (1). Based on the empirical analysis by Taimur Baig and Ilan Goldfajn (1998), we assume linkage parameters r12 = 0.25 = r21 ,
220
Table 1. Commitments of international organizations and ‘interested countries’ during the Asian crisis.
Date
Thailand
Indonesia
Korea
August 11, ’97
November 5, ’97
December 4, ’97
Total
IMF IBRD ADB
3.90 1.50 1.20
10.14a 4.50 3.50
21.00b 10.00b 4.00b
35.04c 16.00c 8.70c
Japan Singapore Australia China Hong Kong Malaysia Brunei Korea USA Canada New Zealand France Germany Italy United Kingdom Belgium Netherlands Sweden Switzerland
4.00 1.00 1.00 1.00 1.00 1.00 0.50 0.50
5.00 5.00 1.00 1.00 1.00 1.00
10.00
19.00 6.00 3.00 2.00 2.00 2.00 0.50 0.50 8.00 1. 00 0.10 1.25 1.25 1.25 1.25 0.31d 0.31d 0.31d 0.31d
Total
3.00
16.60
35.14
1.00
5.00 1.00 0.10 1.25 1.25 1.25 1.25 0.31d 0.31d 0.31d 0.31d 58.35
110.09c
a The IMF added 1.3 bn$ on July 15th, 1998 and 1 bn$ August 25th, 1998. b The IMF added 2.0 bn$, the IBRD 3.0 bn$, and the ADB 2.0 bn$ on December 24th, 1997. c Total intervention during the Asian crisis: IMF: 39.34 bn$, IBRD: 19.00 bn$, ADB: 10.70
bn$. This gives a total Asian crisis intervention of 119.39 bn$. d Rounded off (exact amount 0.3125).
221
Figure 1. The decline in Japanese, US, and German exports to the most severely affected countries in Asia (Thailand, Indonesia, and Korea) (Q1 1997 = 1.0).
r13 = 0.26 = r31 , r23 = 0.32 = r32 . Specifically, the linkage parameter is constructed according to rji = θ Mji = rij , where Mji is the sum of the stock index correlation, the exchange rate correlation, and the sovereign spread correlation, between countries j and i (all standardized to be between 0 and 1), as estimated by Baig and Goldfajn, and for convenience, θ is set at 0.35. In the interests of simplicity, we assumed a time lag Lji = 0 days, and used the 1997 GDPs which are 154 bn$ for Thailand, 215 bn$ for Indonesia, and 443 bn$ for Korea. Curve fitting gives the parameters a1 = 1.9, a2 = 2.8, a3 = 2.7, b1 = 0.0023, b2 = 0.00075, b3 = 0.00085, d1 = 450, d2 = 350, d3 = 400, βi = 0.000015. Figures 2–4 show the empirical estimates and simulated values of si (t), as determined by (2.6) in Thailand, Korea, and Indonesia, where t along the horizontal axis counts the days starting with January 1st, 1997. The principal component estimate of the crisis severity si (t) suggests that Korea was the least affected, that Thailand was intermediately infected, and that Indonesia was the most affected. The results imply a shorter duration of the crisis in Korea, which may be due to successful intervention or to the fact that Korea’s departure from its economic long-term equilibrium was well below Thailand’s or Indonesia’s. These results, and the differing severity estimates, are debatable. Nevertheless, the results seem to be reasonable if one considers the political turmoil in Indonesia and the comparably early and generous support program devoted to Korea. A better estimate would need to include additional variables in the principal component, especially
222
Table 2. Empirical estimates of the severity si (t) of the crisis, standardized values.
The gray shaded area indicates crisis levels above si (t) > 0.20 and approximates the duration of the crisis.
223
Figure 2. Empirics and simulation of si (t) in Thailand; t counts the days starting with January 1st, 1997.
Figure 3. Empirics and simulation of si (t) in Indonesia; t counts the days starting with January 1st, 1997.
224
Figure 4. Empirics and simulation of si (t) in Korea; t counts the days starting with January 1st, 1997.
capital flows. (Please see Kaminsky et al., 1998 for suggestions for additional variables.) Given that these are comparably precise evaluations of the crisis dynamics, it is interesting to note that it took almost five months from the onset of the Thai crisis until the support program for Thailand was negotiated (March–August 11th, 1997), four months to do the same for Indonesia (July–November 5th, 1997), and slightly more than one month for Korea (November–December 4th, 1997). On the one hand, this illustrates the greater importance of Korea as a substantial player in global economic affairs. On the other, the promptness of support for Korea shows that the international organizations and the interested countries did not consider the three crises as separate issues. The more dramatically the Asian countries became affected, the more seriously the crisis was taken by industrialized countries, and the level of monetary interventions grew accordingly.
5. A game-theoretic analysis of the incentives to intervene While the estimates of the dynamics of crisis severity si (t) give an impression of how costly the Asian crisis potentially was, the actual costs to indirectly affected countries can only be calculated by multiplying the potential costs by a parameter which estimates the economic ties between affected and unaffected
225 countries, lij . Since it is extremely difficult to estimate such a parameter precisely, we use a logarithm of bilateral trade as a simple first proxy. Of course, the costs of a severe financial crisis in one country or group of countries to not affected countries is influenced by additional factors such as foreign direct investment and financial flows. However, since these financial relations tend to be correlated with trade, we would not gain much by using more complex estimates. We assume that Japan, the USA, and all countries in Europe cannot be infected by a crisis. In other words, we assume that the financial market regulations of the OECD-24 countries are sufficient to render contagion unlikely. For Russia and countries in Latin America, we assume that ‘partial infection’ may be possible. Again, this procedure is open to discussion. The model operates such that when no intervention occurs, the crisis in the infected countries gets worse, as expressed by the si (t) curves in Figures 2–4 being higher. Each country measures the cost of intervention against the benefit arising from containing the crisis, as formulated by (2.9)–(2.11). This allows us to carry out a game-theoretic analysis of the intervention game. Each country i’s utility at a given point in time t is given by ui (t) in (2.9), and the institutional actor’s utility at time t is given by u0 (t) in (2.10). Integrating the discounted utilities ui (t) over the time duration of the crisis, from t = 0 to t = T, gives actor i’s accumulated utility uacc i (T) from (2.11), which is the utility we present in the subsequent payoff matrices. We first consider Japan (country 4) and the USA (country 5) who intervened in the aggregate with 19 billion US dollars and 8 billion dollars, respectively, to help contain the crisis in Thailand, Korea, and Indonesia. There are four possible outcomes of uacc i (T) for each of the two countries, depending on whether they do (int) or do not (Nint) intervene in the given amounts. uacc i (T) is calculated from (2.11) applying the same parameters and initial values as in Section 3, unc = 0, T = 852, Dji = 0 days, δi (t) = 1, c4 = 5, c5 = 2.5, c6 = 5, λ4 = 1/(122∗ 10ˆ3), λ5 = 1/10ˆ3, λ6 = 1/(0.89∗ 10ˆ6), where we apply the average exchange rates US$1 = 122 Yen = 0.89 ECU for 1997 to account for gji (t) in the Appendix being expressed in different currencies. It is convenient to illustrate the utilities acc uacc 4 (852) and u5 (852) of Japan and the USA, for the four combinations that (Japan, USA) either (intervene 19 bn$, intervene 8 bn$), (intervene 19 bn$, intervene 0 bn$), (intervene 0 bn$, intervene 8 bn$), or (intervene 0 bn$, intervene 0 bn$), as a function of the total amount provided by countries other than Japan and the USA. In the crisis, these other countries intervened with 92.39 bn$, which is found by subtracting 19 bn$ + 8 bn$ from the total amount provided, which is 119.39 bn$ (see Table 1). We thus introduce a factor that we allow to vary from zero and upwards and which we multiply by
226
Figure 5. Payoffs to Japan when other actors intervene with 92.39 bn$∗ factor.
Figure 6. Payoffs to the USA when other actors intervene with 92.39 bn$∗ factor.
92.39 bn$. When factor=0, other countries do not intervene. When factor = 1, other countries intervene with 92.39 bn$. When factor = 2, other countries intervene with 2 × 92.39 bn$ = 184.78 bn$, etc. Figures 5 and 6 show the acc utilities uacc 4 (852) and u5 (852) to Japan and the USA, respectively, as a function of a factor multiplied by the total interventions of all the other actors except Japan and the USA.
227 Table 3. The intervention game between Japan and the USA when no other actors intervene. USA Intervene
Not intervene
Intervene
–1703, –1209
–1753, –1245
Not intervene
–1688, –1295
–1702, –1290
Japan
Note how the accumulated payoffs increase logistically, making Japan and the USA the beneficiaries of other actors taking on the burden of intervention. The interpretation of this is straightforward: the countries’ marginal incentives to intervene are given by the first derivative of the estimated logistic function, while the utilities of intervention are given by the logistic function itself. The marginal incentive describes when the incentive of a country, here the USA and Japan, is highest. Trivially enough, this is the case when the crisis is not yet contained by intervention from other countries, while the intervention of other countries is large enough that the marginal intervention of one additional country has a noticeable impact on the severity of the crisis. Therefore, each country intervenes until its marginal utility equals the cost of its intervention. From a game-theoretic perspective, this is not the whole story. In addition to what can be observed by neoclassical marginal utility analysis, each country is better off when other countries bear the burden of intervention. Therefore, in what follows we analyze the ‘game’ between potential intervening countries. Figures 5 and 6 show how Japan and the USA prefer not to intervene with 19 billion dollars and 8 billion dollars when factor is above a certain value, since other actors then incur the main cost of intervention. That there is a lower bound of factor to ensure the participation of Japan and the USA in the intervention can be demonstrated with a more conventional game analysis. Setting factor = 0 gives the utilities in Table 3, which correspond to those in Figures 5 and 6. Table 3 specifies the situation faced by Japan and the USA, given that no other actors intervene in the crisis. Neither the IMF, IBRD, nor ABD, nor any other country, intervenes. The unique Nash equilibrium is (Not intervene, Not intervene) with utilities (–1702,–1290) to (Japan, USA), i.e., a defection game. This suggests that, without intervention by the international organizations, neither Japan nor the USA has the incentive to intervene in the Asian crisis.
228 Table 4. The intervention game between Japan and the USA. USA Intervene
Not intervene
Intervene
–1059, –634
–1091, –637
Not intervene
–1127, –739
–1154, –742
Japan
Increasing factor to factor = 1 gives the utilities in Table 4, which also correspond to those in Figures 5 and 6. Table 4 specifies the situation faced by Japan and the USA, given that the other actors intervened as they actually did in the Asian crisis, i.e., with 92.39 bn$. The structure of Table 4 is no longer a defection game, but a pure cooperation game with a unique Nash equilibrium (Intervene, Intervene) and utilities (–1059, –634) to (Japan, USA). This suggests that intervention by the international organizations as a first-mover was a necessary and crucial condition of collective action in containing the Asian crisis. Table 4 suggests that Japan has an incentive to intervene unilaterally even when the USA does not intervene. This is consistent with Japan initially organizing the collective intervention in the Thai crisis without officially seeking the support of the USA. However, the USA marginally prefers not to intervene when Japan does not intervene. When both Japan and the USA intervene, as they do in equilibrium, the USA’s incentive to intervene is smaller than Japan’s. European countries intervened only negligibly in the Asian crisis. All European countries together committed themselves to support Korea with 6.25 billion dollars. This sum exceeded the contribution of Singapore only slightly, and remained well below the USA’s and Japan’s commitments. To analyze the strategic considerations by European countries, we consider Germany (country 6) which participated with a modest 1.25 bn$ in the second line of defense contribution to Korea. The left part of Table 5 repeats Table 4 for Japan and the USA, and is supplemented by Germany’s utilities, given Germany’s modest intervention. The right part of Table 5 considers the hypothetical case of Germany intervening beyond its modest 1.25 bn$, in the same manner as the USA intervened (5 bn$ to Korea December 4th, 1997 and 3 bn$ to Indonesia November 5th, 1997). Note in Table 5 how both Japan and the USA prefer Germany to intervene with 9.25 bn$, thereby taking part in bearing the cost, through intervention, of
Table 5. The intervention game between Japan, the USA, and Germany. USA
Intervene
USA
Intervene
Not intervene
–1059, –634, –233
–1091, –637, –240
Intervene
Intervene
Not intervene
–1027, –611, –266
–1059, –614, –273
Japan Not intervene –1127, –739, –264 –1154, –742, –269 Germany intervenes with 1.25 bn$
Not intervene
–1098, –716, –298 –1127, –719, –304 Germany intervenes with 9.25 bn$
229
230 containing the crisis. However, Germany prefers not to intervene with merely 1.25 bn$, regardless of the strategies chosen by Japan and the USA. The situation resembles a game where Germany uses its strategically advantageous position to participate only marginally.11
6. Conclusion The Asian crisis has spurred considerable interest in the political economic conditions that increase the likelihood of the emergence and spread of balance-of-payments and financial market crises. Far less effort, in fact none that we are aware of, has been devoted to the analysis of those political economic conditions that aim at containing a financial crisis once it has occurred. This imbalance is surprising for two primary reasons: firstly, many economists blamed the IMF for causing a moral hazard problem of international lending, and thereby increasing the likelihood that investors invest monetarily in ill-regulated markets. By giving investors the illusion of limited risks, the Peso-crisis bail-out contributed to the over-investment in Asia (Krugman, 1998; Corsetti, Pesenti; Roubini, 1998: 15; Meltzer, 1998: 268; Sarno and Taylor, 1999). In the view of its critics, the IMF’s massive financial rescue efforts in the Peso crisis crucially intensified the moral hazard problem of financial markets. Thus, Calomiris (1998: 275) suggests that the responses of the IMF and interested countries to the most recent crises seem to be of ‘dangerous short-sightedness’. However, those who want to eliminate the IMF (i.e., Milton Friedman in FT September 19th, 1997) seem to look selectively at its potential costs, without considering its benefits. In fact, ignoring the IMF’s role in organizing support programs to heavily affected countries is justified if either financial crises were exclusively caused by moral hazard problems or the interventions of international organizations and interested countries were of no help. Both assumptions are not very plausible. Firstly, studies analyzing the history of financial market crises demonstrate that there are numerous origins (Kindleberger, 1978; Palma, 1998). Secondly, it has been convincingly argued that central banks in developing countries have, at best, a very limited ability to extricate their countries from a crisis (Mishkin, 1999: 715). Hence, the recovery from a contagious financial market crisis requires foreign assistance, one of the main objectives of which is to prevent the snowballing of collapsing currencies. Thus, once financial turmoil has emerged, political efforts to contain financial crises are rational and in the interest of all economically-open countries. However, this does not mean that IMF intervention was necessary to contain the crisis. Instead of support programs negotiated by the international
231 organization, the countries themselves could unilaterally or cooperatively organize collective intervention. However, the analysis in this article supports the view that the IMF at least increased the likelihood of multilateral action in containing the crisis. The results of our simulation study and the gametheoretic analysis suggest that the intervention by the IMF, IBRD, and ABD ensured that Japan and the USA did in fact have an incentive to intervene. Furthermore, we show that if the IMF, IBRD, and ABD had not intervened, then not even Japan and the USA would have had the incentive to intervene. Note that since this is a small-N analysis, we should be careful in arguing that the IMF actually was a necessary condition for crisis intervention. However, our results suggest that the IMF very likely was a decisive figure in the organization of collective action in the Asian crisis. An emerging normative question is whether IMF member countries should amend the IMF treaty. IMF officials have started to plea for institutional change, which would oblige the IMF to be ready with backstop finance in case private capital proves to be hard to come by (Obstfeld, 1998: 27; IMF, 1999). Although the IMF with its current organization cannot effectively play the role of an international lender-of-last-resort (Radelet and Sachs, 1999: 189), our analysis suggests that it is not necessary to provide the IMF with additional resources. On the contrary, the emerging pattern of international institutional lending supported by multilateral ‘second lines of defense’ allows for better control of the IMF and should moderate ensuing moral hazard problems. The more decentralized a substitute to a lender-of-last-resort is, the less certain investors are about the potential of a bail-out in future crises. Hence, the trade-off between the efficiency of crisis intervention and the likelihood that intervention causes or amplifies the moral hazard problem of international lending can partly be resolved by retaining a certain slack in the institutional arrangement.
Notes 1. The classic version presented by Kermack and McKendrick (1927) assumes that I agents are infected, S agents can be infected, and R agents are removed (either because they die or because they are cured and become immune) from the sample of N = I + S + R agents. The model is such that ∂S/∂t = −rSI, ∂I/∂t = rSI − γ I, ∂R/∂t = γ I, where r and γ are constants. 2. We do not distinguish between different kinds of contagion, which complicates the model. See Fratzscher (1998) for a discussion of four kinds of contagion: fundamental contagion, real integration contagion, herding contagion, institutional contagion. 3. Biologically this is because at least one female is necessary to initiate growth. 4. For a discussion of the history of the logistic hypothesis, first presented by Verhulst (1845), in population ecology, see Kingsland (1985: 64–97). Logistic increase has found its application in many fields, e.g., the impact of advertising in marketing.
232 5. The Asian crisis that originated in Thailand lasted for approximately two years, 1997– 1998. We may speculate that it could have lasted 3++ years if no-one had intervened to remedy/contain it. 6. Empirically, we can distinguish between three channels of contagion. ‘Fundamental contagion’ implies that the crisis spreads from one country to another if both countries have similar unsound economic fundamentals or face a common economic shock. ‘Institutional contagion’ implies that a financial crisis in one country leads to a decline in stock market returns and thereby may induce investors to change their portfolios. Finally, ‘herding contagion’ refers to panicking investors following or mimicking other investors in withdrawing their assets in favor of their home or other seemingly safe markets (Fratzscher, 1998). Due to data restrictions, we limit our analysis to trade data. 7. Just as Spencer’s (1851) analogy between biological and social systems has strengths and weaknesses, the same is the case for the analogy between financial and health crises. In particular, the likelihood of contagion in a financial crisis depends on psychological factors such as investors’ assessments of their own and other investors’ current and future behavior, the possible expectation that institutions may intervene (without actually intervening), etc. The model, and its comparative statics, can perhaps be said to reduce such ‘psychological features’ to ‘mechanistic features’. 8. Although the crisis affected almost all countries in the region, we concentrate on those countries that asked for IMF support. 9. Australia, Hong Kong, Singapore, Indonesia, Korea, Malaysia, and China. 10. Estimates are based on a Principal Component Analysis (Orthotran-Varimax) of exchange rates, exchange rate volatility and interest rates. Variables have been standardized to ensure international comparability. The procedure is similar to the use of first derivatives. The estimated formula is CSSTD = STD[log(δ0.899EXRSTD + 0.906FLUCSTD + 0.603CLMSTD )], where CSSTD is the standardized value of crisis severity, STD means standardization, so that the estimated values fall between 0 and 1. A Box-Cox transformation was used to estimate the degree of the logarithm and δ is a discount factor that controls for the hysteresis effects of the exchange rate. The estimate yields satisfying results [Bartlett’s χ 2 = 83, 447, R2 = .728]. Although many more indicators have been used to determine the existence of financial market crises (Kaminsky et al., 1998), the Principal Component Analysis sufficiently evaluates the dynamics of crises for our purposes. If we account for the changing exchange rates in Thailand, Indonesia, and Korea before, during, and after the crisis, the crisis severity s1 (t), s2 (t), s3 (t) will lie 15 to 25 percent lower. Different views may exist on which severities are the most descriptive, but choosing one set in preference to another does not alter the nature of the argument in this article. 11. Future research should address the question of whether the results differ in the Peso-crisis (the Latin American Crisis of 1994–1995), where the USA appeared to have a very strong incentive to provide unilateral assistance. European countries and Japan seemingly did not have the same obvious incentive, and yet they still unsuccessfully tried to block the US initiative for an IMF stand-by arrangement. This behavior by the various actors needs to be analyzed. Note that the USA and EU countries have a veto position in the IMF, which is crucially relevant for the IMF’s evaluation of how to increase its capital base.
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Appendix 1. Empirical estimates of the trade parameter gji (t) determined by export from country i (Japan, the US, Germany) to country j (Thailand, Indonesia, Korea). Japan numbers are in million Yen from ‘Japan Exports & Imports’ published by Japan Tariff Association ISSN 0910-3007. US numbers are in US million $ from http://www.census.gov/foreign-trade/. German numbers are in 1000 ECU from the Eurostat database on ‘Internal and External trade of the EU’. Jap-IDN
Jap-KO
US-TH
US-IDN
US-KO
Ger-TH
Ger-ID
Ger-KO
173,540 177,326 162,398 163,555 155,934 160,742 169,583 143,308 172,116 193,780 167,441 165,027 151,458 151,360 133,137 133,854 126,346 107,279 119,345
83,215 81,534 75,653 88,069 91,597 88,380 95,453 66,411 106,985 115,359 110,133 102,889 104,033 114,451 111,631 112,697 111,756 89,071 84,820
271,082 287,681 265,624 268,292 275,760 264,864 279,964 242,529 261,407 293,705 300,144 272,650 258,783 256,825 245,806 254,760 289,081 245,782 232,278
683.9 501.1 522.2 481.4 671.0 451.7 878.7 584.7 596.5 640.9 679.0 559.0 561.8 534.0 591.1 749.1 670.8 652.3 538.0
334.9 279.9 281.4 238.9 308.9 333.8 534.1 315.0 357.0 365.0 328.8 487.5 407.8 364.2 309.8 322.5 372.4 423.6 478.0
2270.1 2066.7 2417.2 2028.1 2213.2 2265.3 2471.8 1969.7 1983.9 2474.4 2504.4 2388.0 2235.9 2325.8 1910.7 1684.1 2080.7 1829.4 1679.6
219,812 260,302 235,813 211,770 292,265 205,708 249,917 183,446 191,576 186,436 260,957 175,881 195,759 247,348 158,592 199,308 178,133 158,632 172,534
172,474 222,943 141,219 182,447 300,841 157,982 203,496 182,518 160,249 147,253 200,976 200,786 207,551 226,055 268,677 269,649 281,861 223,383 281,715
409,735 467,352 397,406 390,088 448,057 401,135 449,536 388,259 336,157 402,875 447,734 369,912 386,651 435,408 341,038 420,406 390,768 366,160 416,078
235
Jun 96 Jul 96 Aug 96 Sep 96 Oct 96 Nov 96 Dec 96 Jan 97 Feb 97 Mar 97 Apr 97 May 97 Jun 97 Jul 97 Aug 97 Sep 97 Oct 97 Nov 97 Dec 97
Jap-TH
236
Appendix 1. Continued.
Jan 98 Feb 98 Mar 98 Apr 98 May 98 Jun 98 Jul 98 Aug 98 Sep 98 Oct 98 Nov 98 Dec 98 Jan 99 Feb 99 Mar 99 Apr 99 May 99 Jun 99
Jap-TH
Jap-IDN
Jap-KO
US-TH
US-IDN
US-KO
Ger-TH
Ger-ID
Ger-KO
93,909 100,954 112,000 96,057 112,092 107,977 113,010 98,782 107,250 98,200 84,652 97,253 83,611 95,987 114,198 100,914 94,039 114,181
54,133 47,118 53,230 51,783 35,175 39,589 43,484 47,428 50,451 49,398 41,766 46,505 33,483 39,485 42,383 39,312 35,194 42,431
141,043 160,061 189,467 177,829 165,574 165,792 166,227 152,555 168,202 170,552 156,953 190,287 154,788 168,708 226,067 219,296 192,954 216,970
556.95 417.17 463.67 417.30 386.58 360.04 350.27 334.51 343.42 383.42 367.63 852.39 331.97 330.41 379.08 345.66 511.47 377.96
275.04 171.17 167.77 159.98 132.49 166.44 182.42 155.33 147.27 155.82 173.72 403.45 134.58 120.30 164.01 145.43 153.81 181.77
1095.52 1128.11 1276.57 1398.83 1275.37 1196.05 1207.43 1213.22 1311.35 1492.46 1551.56 2391.79 1526.48 1418.99 1898.78 2106.79 1807.62 1978.65
155,789 113.663 136,784 124,330 125,544 124,333 132,048 130,888 115,298 136,712 99,663 143,072 104,120 147,442 132,590 101,174 92,832 113,746
146,700 132,233 118,080 180,820 210,825 89,908 125,755 107,623 197,774 93,955 184,918 106,653 68,177 71,482 115,864 66,384 58,590 81,485
237,250 190,083 260,085 212,493 193,231 181,342 201,624 231,150 192,402 190,880 219,748 243,385 190,779 204,261 262,595 231,804 255,917 262,523
