Monetary policy in the Asian crisis programs faced a difficult task of balancing two objectives. On the one side was the desire to avoid a depreciation-inflation spiral. During the crisis, exchange rates initially depreciated far beyond real levels consistent with the medium-term fundamentals; had monetary policy fully accommodated these depreciations, the new exchange rates would eventually have been validated by inflation. It could not be taken for granted that these countries' track records of relatively low inflation would be an adequate anchor for market expectations. On the other side were concerns that excessive monetary tightening could severely weaken economic activity.
The programs sought to balance these two concerns. Thus, in the face of the massive portfolio shifts taking place in financial markets, as reflected in substantial increases in country risk premia, policies did not target a preannounced level of the exchange rate, but sought to lean against the wind with a view to averting a depreciation-inflation spiral. While this approach risked following a moving target, a rigid approach was not a practical alternative in the midst of the crisis.
Monetary policy was being carried out in an environment in which high debt-equity ratios in the corporate sectors as well as systemic and structural problems made the financial sector more vulnerable to increases in interest rates. By the same token, these factors, together with the prevalence of unhedged foreign currency liabilities of these countries' financial and corporate sectors, meant that exchange rate depreciation could also have a substantial effect on the real economy.
In Korea and Thailand, policies were eventually tightened as envisaged in the monetary program, preventing the large initial currency depreciations from initiating depreciation-inflation spirals. By the summer of 1998, interest rates had returned to precrisis levels and over half of the sharp initial exchange rate depreciation had been reversed. In Indonesia, in contrast, monetary developments were already heading seriously off track by December 1997, reflecting political turbulence and extreme financial system weaknesses. Macroeconomic turmoil ensued, with spiraling inflation, rising risk premiums, continued capital flight, and a dramatic collapse of economic activity. The situation stabilized only in the latter months of 1998.
In Indonesia, monetary policy was emphatically not too tight: on the contrary, nominal interest rates and exchange rates were driven by market risk premiums, while underlying real interest rates remained negative. Money and credit growth accelerated strongly, falling in real terms only subsequently when there were bursts of inflation.
A more difficult question is whether the Thai and Korean programs' successful stabilization caused monetary conditions to become too tight, contributing excessively to the contraction in economic activity. This section examines evidence on various monetary indicators, including interest rates as well as monetary and credit aggregates. By these measures, monetary tightening in these countries was not extreme (in degree or duration) in relation to other crises elsewhere.
At the same time, persistent reports of disruption in access to credit are of concern. Recent and on-going research examining the possibility of an aggregate credit crunch has not yet generated convincing results—although disruptions in credit markets are a frequent feature of many crisis situations. Moreover, shifts in the distribution of credit, reflecting heightened perceptions of risk, may well have been destabilizing to the activities of specific sectors and enterprises and may at least in part account for perceptions of a credit crunch. To the extent that such microeconomic problems are involved (even if initially triggered by monetary tightening or by the crisis more generally), this would point to the need for progress with corporate and financial restructuring.
Monetary Program Design and Implementation
The behavior of exchange rates through the crisis period varied considerably across the three countries (Figure 6.1).1 In Thailand, after an initial 24 percent depreciation in July 1997, there were a series of smaller (although still substantial) monthly depreciations over a prolonged period, culminating in 16–17 percent depreciations at the end of 1997 and in early 1998, when the rate at last bottomed out. In Korea, substantial depreciation was avoided until late 1997, with the exchange rate then slipping more abruptly to its weakest point, also in early January 1998. Indonesia's exchange rate, in contrast, depreciated fairly steadily starting in July 1997, with depreciation only reaching above 20 percent a month in December 1997—followed by over 120 percent in January 1998. A limited recovery in the next several months was reversed by large further depreciation in May-June 1998, most of which had been recovered by late October 1998.
Program Design
In pursuing exchange rate stability, the programs made no attempt to stick to a preannounced level or range for the exchange rate. Instead, the announced goal was currency stability in the less ambitious sense of avoiding further bouts of rapid depreciation.2 Programs did assume that varying degrees of nominal appreciation would follow an initial tightening of policy, but these projections were strictly speaking not objectives, since there was no presumption that policy would be tightened by what-ever amount necessary to achieve these exchange rate levels.3
The strategy strongly emphasized the use of credit and interest rate policies, rather than direct foreign exchange intervention, to restore currency stability. (A notable exception was Indonesia's original program, discussed below.) Some limitation on exchange market intervention was implicit in (end-period) performance criteria on reserves; moreover, informal understandings sought to limit intervention to “smoothing” operations, rather than attempts to counter strong market pressures. The intent was not to preclude resistance to such pressures, but to encourage the use of interest rate policy as the instrument of such resistance as reserves for intervention were in short supply, particularly in Korea and Thailand.
The conduct of monetary policy in the programs was oriented mainly toward interest rates and exchange rates. This approach was appropriate under the circumstances: in particular, given rapidly shifting market conditions, day-to-day policymaking needed to be based on variables that were readily observable. Monetary and credit aggregates were disqualified for this operational role: lags in their measurement limited short-run policy control, and uncertainty about the behavior of money demand in the crisis militated against rigid adherence to preannounced monetary targets. But, at the same time, given market pressures affecting exchange rates and interest rates, and considerable uncertainties over the required real exchange rate adjustment, money and/or credit aggregates, as well as related quantitative variables such as net domestic assets (NDA), were potentially useful indicators that would provide clear-cut warning signals in the event that policy implementation veered substantially off track.
Accordingly, as regards program monitoring, both the Thai and Korean programs used ceilings on NDA of the central bank and floors on net international reserves (NIR) as formal performance criteria. It was presumed that the NDA ceiling would provide an adequate limit on money growth, even though it permitted money to grow faster than programmed in the event—viewed as unlikely—that NIR grew much faster than expected.4 In addition, as described below, monitoring put a special, less formal, focus on interest rates.
In Indonesia, in contrast, the initial program explicitly provided for “judicious and closely monitored” intervention. This was based on the perception that Indonesia was suffering more from adverse contagion effects and structural weaknesses rather than from traditional macroeconomic imbalances that might require further real depreciation. Accordingly, the performance criterion floor for NIR was set well below the NIR path built into the program's central scenario.5 In the initial program, this was associated with a ceiling on base money rather than NDA. In principle, adherence to this predetermined base money path should have provided the advantage of a nominal anchor—one consistent with a floating exchange rate regime. However, in a setting with severe market pressures, and in the absence of a policy of clean floating, it turned out to be a weakness: since the NIR floor allowed room for intervention in support of the currency, a base money ceiling would in principle allow most6 of the monetary impact of any such unprogrammed reserve losses to be sterilized by faster-than-programmed credit expansion, which was an unsustainable and probably ineffective policy response to the severe market pressures.
Since, in all three countries, monetary policy between program reviews was oriented by exchange rates and interest rates, these performance criteria needed to be supplemented by commitments and/or understandings on the behavior of interest rates. Such less formal interest rate understandings, which were set in simple nominal terms, clearly needed to be flexible, to adapt to rapidly changing market conditions. There were no specific commitments about how interest rates should be adjusted in response to shocks—only understandings defined in broad terms, relying largely on the authorities' good judgment and continuous contact with IMF staff.7
In summary, the essential task of monetary policy was to counter the slide of the exchange rate, but there were no specific exchange rate targets. The nominal interest rate—rather than credit or monetary aggregates—was adopted as the de facto gauge and instrument of monetary policy tightening, which together with the exchange rate guided day-to-day policy. This approach has some well-known weaknesses: in particular, an interest rate rule does not provide a nominal anchor. The uncertainties associated with the crisis, however, called for an approach to implementation that emphasized frequent reassessment and flexibility; discretion rather than rules. In this setting, the role of formal performance criteria was generally secondary—that is, they indicated consistency with the central scenario of the program.
Program Implementation
How well did the implementation of monetary policy accord with the programs? From a comparison of actual reserve and broad money developments and their initial program expectations (Figure 6.2),8 it is immediately obvious that Indonesia's program, approved in November 1997, was already heading seriously off track by the December 1997 test date. Korea and Thailand, however, generally stayed within programmed broad money growth rates, and always well inside expectations for reserve money.9 Why did Indonesia's program go off track and the others stay on?
Indonesia, Korea, and Thailand: Reserve and Broad Money Growth, Initial Program Expectations and Outcomes1,2
Sources: Data provided by the authorities; and IMF staff estimates.1 Cumulative growth, in percent, from end-March 1997. Differences between program and actual data prior to programs inceptions reflect data revisions.2 For Indonesia and Thailand, all projections are based on initial program. For Korea, initial program projections extended to December 1997 only; projections for March and June 1998 are those established in February 1998, at the first quarterly program review.Indonesia, Korea, and Thailand: Reserve and Broad Money Growth, Initial Program Expectations and Outcomes1,2
Sources: Data provided by the authorities; and IMF staff estimates.1 Cumulative growth, in percent, from end-March 1997. Differences between program and actual data prior to programs inceptions reflect data revisions.2 For Indonesia and Thailand, all projections are based on initial program. For Korea, initial program projections extended to December 1997 only; projections for March and June 1998 are those established in February 1998, at the first quarterly program review.Indonesia, Korea, and Thailand: Reserve and Broad Money Growth, Initial Program Expectations and Outcomes1,2
Sources: Data provided by the authorities; and IMF staff estimates.1 Cumulative growth, in percent, from end-March 1997. Differences between program and actual data prior to programs inceptions reflect data revisions.2 For Indonesia and Thailand, all projections are based on initial program. For Korea, initial program projections extended to December 1997 only; projections for March and June 1998 are those established in February 1998, at the first quarterly program review.The most fundamental problem facing implementation of Indonesia's monetary program was the near-collapse of the banking system during November 1997 through January 1998.10 Several banks were insolvent, or at least suffered from serious weaknesses, well before the crisis; the banks' difficulties were compounded by the losses incurred when the rupiah began to depreciate. The closure of some banks, together with the absence of a coherent strategy for dealing with the others (including the scope of guarantees for depositors), was followed by widespread bank runs that led to calls for massive liquidity support from Bank Indonesia. This support, intended to keep the payment system from breaking down, was provided quite indiscriminately, in part because of the difficulties of determining whether individual banks were facing liquidity or solvency problems, fears of contagion, and concern over the drying up of interbank lending reflecting uncertainty about which banks would survive.11 Such liquidity support, which the central bank made only limited efforts to sterilize, resulted in a massive increase in the NDA of the central bank—which during November 1997 to March 1998 amounted to more than twice the entire stock of base money at the beginning of that period.12 Although much of the central bank's NDA increase translated into a loss of reserves as Bank Indonesia attempted to arrest the decline of the rupiah, base money was far above its program ceilings, growing by 126 percent (in the six months to March 1998) compared with an original program ceiling of roughly 10 percent.13 No monetary program could have withstood this kind of stress. As already noted, the design of the original Indonesian program allowed room for unprogrammed intervention to support the currency, to be accompanied by a partially sterilizing increase in NDA; in the event such interventions did occur. Although this was a significant shortcoming in program monitoring, the performance criteria for base money were eventually exceeded (as the excess NDA expansion far outstripped the decline of reserves), signaling clearly that the program was off track. It was thus a flaw in program design, but was by no means the main reason the program went off track. At the time of Indonesia's first program review in April 1998, the monetary program was reformulated in terms of “firm control of NDA of Bank Indonesia,” which replaced base money as a performance criterion. The revised program was also intended to dig in heels sharply, by holding both base money and NDA broadly constant through end-1998. However, against the background of gathering political unrest, the programmed monetary tightening did not materialize and the program soon went off the new track, with base money and broad money again well above the paths envisaged.14
An alternative, more radical solution to monetary policy—a currency board—was also considered by both the IMF staff and the authorities, but ultimately rejected. The continuing banking crisis, the need for legal and institutional changes, and gathering political uncertainty—and serious concerns about continued political interference in monetary policy—argued against this proposal (see Box 6.1).
A new monetary program was established, under calmer conditions, in mid-1998, again envisaging nominal appreciation and calling for base money and NDA to be held broadly flat in the quarter just ahead. As of end-October 1998, monetary developments were essentially on track, and the currency had appreciated dramatically.
A Currency Board for Indonesia?
A possible alternative method of restoring confidence and stopping the depreciation of a currency is to establish a currency board. Such arrangements have been successfully adopted in a number of IMF-supported stabilization efforts and, soon after the crises broke, serious consideration was given to their possible use, especially in Indonesia.1 While there are some good arguments in favor, such a regime change was ultimately rejected for Indonesia because of concerns about its credibility and sustainability—especially at an exchange rate far above the prevailing market rate—in the light of ongoing capital outflows as well as practical considerations.
Arguments in favor of a currency board in Indonesia included the following:
A currency board would end the run on the rupiah. It was felt that the depreciation had entered a “vicious circle” and gone well beyond what was justified on grounds of the changed fundamentals. The strictures of a currency board, and the associated interest rate moves, would reinstill confidence in the domestic currency. While in principle this could also be achieved by a tight-money-based regime, “tying their hands” could allow the authorities to achieve the same credibility faster, with potentially beneficial effects on inflation and growth.2
A currency board would discipline the central bank. In Indonesia, the money supply was chronically difficult to control, given the availability of large central bank liquidity credits to banks and preferred private borrowers. A currency board would facilitate the politically difficult task of severing such credit links.
A currency board would force a solution to the financial sector problems, by making it clearer which institutions were solvent and circumscribing the central bank's ability to support those that were not. (But this was a two-edged sword, as discussed below.)
There were, however, serious arguments questioning the feasibility of a currency board. Among them:
If the currency board was less than fully credible—as seemed likely, given turbulent conditions, and market concerns that the authorities may be unable or unwilling to sustain the arrangement—the resulting capital outflow, by automatically contracting the money supply, would lead to punishingly high interest rates.
In light of the financial sector problems, a currency board—which prevents the central bank from acting as lender of last resort—could only be stable after progress in financial sector reform. In particular, the central bank would either have had to formally revoke deposit guarantees—which would probably have triggered another panic—or committed itself to honoring them—which would not have been feasible in view of available reserves.3
There are legal and institutional requirements for a currency board that are needed to make the system operational.4 While no specific analysis has been undertaken of what those requirements would be in the case of Indonesia, other countries (with simpler institutional setups) required several months of preparations.
An unsustainable currency board could have depleted the country's reserves through an exit of capital at a highly appreciated exchange rate, benefiting only those who could get access to the foreign currency before the currency board broke down.
Indonesia's experience through the first half of 1998 thus emphatically cannot be interpreted as reflecting adherence to an overly tight monetary program prescribed by the IMF. The actual out-turns bore virtually no relation to program targets. Instead, the main factor driving monetary developments was the hemorrhage of liquidity to a collapsing banking system, which, in the existing political and economic climate, the authorities did little to staunch. A vicious circle developed whereby any policy move toward laxity or accommodation was reflected quickly in currency depreciation, which then further weakened the corporate sector and (hence) banks, leading the central bank to provide even more liquidity support—fueling further depreciation and inflation. Early signals of lack of commitment to the program and later political and social upheavals also contributed to this cycle. It was this climate, and this loss of monetary control, that led Indonesia's nominal interest rates to become the highest in the region, reflecting a widening country risk premium and well-grounded fears of continuing depreciation and inflation.
In both Korea and Thailand, in contrast, basic monetary control was maintained. Both reserve and broad money growth rates were generally under, or very close to, original program expectations (see figure 6.2),15 and all quarterly NDA and NIR performance criteria through September 1998 were met (figure 6.3), usually with sizable margins16—implying that the programs' formal performance criteria were far from being a binding constraint on the conduct of monetary policy in pursuit of exchange rate stability.17
Korea and Thailand: Differences Between Net International Reserves (NIR) and Net Domestic Assets (NDA) Outturns and Performance Criteria,1,2
(In percent of reserve money)
Sources: Data provided by the authorities.1 Outturn minus final performance criterion for each test date (after any adjustments or modifications), as percent of actual reserve money stock. Data for September 1998 are preliminary.2 The first quarterly test date for Korea was December 1997 (September 1997 for Thailand).3The NIR margin in this instance was essentially zero.Korea and Thailand: Differences Between Net International Reserves (NIR) and Net Domestic Assets (NDA) Outturns and Performance Criteria,1,2
(In percent of reserve money)
Sources: Data provided by the authorities.1 Outturn minus final performance criterion for each test date (after any adjustments or modifications), as percent of actual reserve money stock. Data for September 1998 are preliminary.2 The first quarterly test date for Korea was December 1997 (September 1997 for Thailand).3The NIR margin in this instance was essentially zero.Korea and Thailand: Differences Between Net International Reserves (NIR) and Net Domestic Assets (NDA) Outturns and Performance Criteria,1,2
(In percent of reserve money)
Sources: Data provided by the authorities.1 Outturn minus final performance criterion for each test date (after any adjustments or modifications), as percent of actual reserve money stock. Data for September 1998 are preliminary.2 The first quarterly test date for Korea was December 1997 (September 1997 for Thailand).3The NIR margin in this instance was essentially zero.The path of nominal interest rates differed between Korea and Thailand. In Korea, the authorities were initially reluctant to raise interest rates, but did so abruptly in the face of the funding crisis in late December 1997, and thereafter seem to have followed the path one would expect of a successful currency stabilization effort, that is, a very gradual decline, reaching precrisis levels by mid-1998. Importantly, Korea avoided the syndrome—earlier found in Indonesia and to a lesser degree in Thailand, in 1997—in which interest rates are eased too soon in the currency stabilization effort, forcing a return to yet higher rates, presumably with a loss of credibility and, hence, effectiveness in the process.
Monetary Policy Stance
The next question is whether the monetary stance in these programs was appropriate—that is, whether the right balance was struck between the twin objectives of exchange rate and output stability. This section addresses this question based on available indicators of monetary policy, as well as with reference to the experience of other countries facing exchange rate crises.
In none of the countries did monetary policy go to the limit needed to ensure absolute exchange rate stability. This is implicit in the decision not to repeg exchange rates at any predetermined level and is also obvious from the fact that the currency depreciations in all three countries went well beyond any reasonable estimate of the real exchange rate adjustment required. However, from a slightly longer perspective, the fact that Korea's and Thailand's currencies recovered substantially by mid-1998 as interest rates declined to precrisis levels and inflation remained subdued suggests that with these policies stability is being restored. (Indonesia's progress on the stabilization came later in the year, following the eventual firming of monetary policy.)
Another indication of the impact of monetary policy in stabilizing the exchange rate is the dollar rates of return expected by investors (that is, domestic rates of return corrected for expected currency depreciation). To provide a disincentive for the exit of capital, expected dollar returns would need at the very least to be positive—and more generally, would be expected to exceed the safe rate on dollar deposits by a margin sufficient to compensate for higher risk. Expected monthly dollar returns (based on surveys of exchange rate fore-casts)18 are estimated to have been negative for some periods during 1997 in both Korea and Thailand, becoming strongly positive by February 1998 (figure 6.4).19 This suggests that interest rates were initially inadequate to offer sufficient incentive to hold those currencies, but became high enough in early 1998. This, together with the large depreciations of the currencies that occurred in late 1997, suggests that policies would have needed to have been tightened sooner to arrest the currency depreciations.20 There was also a stop-go element to monetary tightening (see figure 6.5)—with a tendency, especially in Thailand in 1997, to lower nominal interest rates at the first signs of exchange rate stability—which may have contributed to undermining policy credibility and heightening perceptions of exchange rate risk. (To the extent that there is contagion—as discussed in Box 6.2—negative returns in one country might also spark higher risk premiums in others.) In Indonesia, in contrast, dollar rates of return were negative in the early months of the program, then pushed up to high levels in the spring of 1998 with increasing political and social unrest.
Indonesia, Korea and Thailand: Expected Monthly Rates of Return in U.S. Dollar Terms1
(In percent a month)
Sources: Interest rates provided by the authorities; and currency forecasts from the Financial Times Currency Forecaster.1 Overnight interest rates, adjusted by the rate of expected depreciation implied by one-month-ahead exchange rate forecasts (forecasts are surveyed near the end of each month). For presentational clarity, returns are shown on a monthly rather than an annualized basis.Indonesia, Korea and Thailand: Expected Monthly Rates of Return in U.S. Dollar Terms1
(In percent a month)
Sources: Interest rates provided by the authorities; and currency forecasts from the Financial Times Currency Forecaster.1 Overnight interest rates, adjusted by the rate of expected depreciation implied by one-month-ahead exchange rate forecasts (forecasts are surveyed near the end of each month). For presentational clarity, returns are shown on a monthly rather than an annualized basis.Indonesia, Korea and Thailand: Expected Monthly Rates of Return in U.S. Dollar Terms1
(In percent a month)
Sources: Interest rates provided by the authorities; and currency forecasts from the Financial Times Currency Forecaster.1 Overnight interest rates, adjusted by the rate of expected depreciation implied by one-month-ahead exchange rate forecasts (forecasts are surveyed near the end of each month). For presentational clarity, returns are shown on a monthly rather than an annualized basis.
Indonesia, Korea, and Thailand: Nominal and Estimated Real Interest Rates1,2
Sources: Data provided by the authorities; International Monetary Fund, International Financial Statistics; and IMF staff estimates.1 Nominal interest rates are overnight interbank rates (average during month). Lending rate definitionas vary by country as follows: Indonesia, weighted average lending rate on loans to private sector for working capital; Korea, minimum rate charged to general enterprises by deposit money banks on loans of general funds for up to one year; Thailand, minimum rate charged by commercial blanks on loans to prime customers.2 Real interest rates based on estimates of contemporaneous inflation, a three-month moving average of monthly consumer price index changes (previous month, current month, and one-month ahead, as available).Indonesia, Korea, and Thailand: Nominal and Estimated Real Interest Rates1,2
Sources: Data provided by the authorities; International Monetary Fund, International Financial Statistics; and IMF staff estimates.1 Nominal interest rates are overnight interbank rates (average during month). Lending rate definitionas vary by country as follows: Indonesia, weighted average lending rate on loans to private sector for working capital; Korea, minimum rate charged to general enterprises by deposit money banks on loans of general funds for up to one year; Thailand, minimum rate charged by commercial blanks on loans to prime customers.2 Real interest rates based on estimates of contemporaneous inflation, a three-month moving average of monthly consumer price index changes (previous month, current month, and one-month ahead, as available).Indonesia, Korea, and Thailand: Nominal and Estimated Real Interest Rates1,2
Sources: Data provided by the authorities; International Monetary Fund, International Financial Statistics; and IMF staff estimates.1 Nominal interest rates are overnight interbank rates (average during month). Lending rate definitionas vary by country as follows: Indonesia, weighted average lending rate on loans to private sector for working capital; Korea, minimum rate charged to general enterprises by deposit money banks on loans of general funds for up to one year; Thailand, minimum rate charged by commercial blanks on loans to prime customers.2 Real interest rates based on estimates of contemporaneous inflation, a three-month moving average of monthly consumer price index changes (previous month, current month, and one-month ahead, as available).A further question is whether the authorities should have pushed interest rates to much higher levels in order to stabilize the exchange rate. In addition to concerns over the likely effects of such a policy on the real economy, it is not clear that this approach would have been successful in stabilizing exchange rates under the conditions prevailing in early 1998. For one thing, real interest rates far higher than those that actually prevailed might have had little favorable impact on international capital flows, or may even have had a perverse effect, owing to their impact on balance sheets that were already crippled by the currency depreciations. Some critics of the monetary programs in the Asian crisis have argued that such perverse effects actually materialized but as yet no convincing evidence has been presented showing that interest rates reached levels at which such perverse effects would be important (Box 6.3).
Another issue is the transmission mechanism: in at least some of these countries, the range of short-term domestic currency financial instruments is limited,21 narrowing the scope for higher interest rates to lure investors into domestic currency assets. Notwithstanding the latter observation, however, there were still important channels through which domestic interest rates could influence capital flows and the exchange rate: exporters faced a trade-off between holding foreign assets and repatriating revenues; banks could intermediate capital flows in the form of deposits or direct borrowing from the capital markets; and residents faced a trade-off between holding domestic and foreign deposits (although these mechanisms were no doubt impaired by the sorry—and worsening—state of domestic banking systems).
Another indicator that is particularly relevant with regard to the implications of monetary policy for real activity is the behavior of real interest rates, as shown in Figure 6.5. In Indonesia, real overnight and lending rates were consistently negative from late 1997 through August 1998. In contrast, in Korea and Thailand, real rates became very low or negative in the months immediately following the onset of the exchange rate crisis, but since then they have been consistently positive.22 In Thailand, real interest rates rose to an average 13 percent in the fourth quarter of 1997 and the first quarter of 1998, falling to 11 percent in the second quarter of 1998, and then declined further. In Korea, nominal rates were raised sharply in late 1997, and after a strong but brief surge of inflation, real rates became quite high by historical standards, averaging more than 20 percent in the second quarter of 1998; Korea's nominal interest rates have declined quite steadily since their January 1998 peak, and by August 1998 were back to near precrisis levels.23 In sum, it is far from clear that the path of real interest rates has implied a sustained or crushing burden on economic activity. Moreover, the initial increases in real interest rates were certainly less aggressive than those seen occasionally in other countries during exchange rate crises or in their immediate aftermath, as discussed in Box 6.4.
High-Frequency Contagion in the Exchange and Equity Markets
One of the factors complicating stabilization efforts during the East Asian crisis was the contagion across countries. Such contagion effects arise because of trade and financial linkages, or because events in one country change perceptions about prospects in others, or simply because of herd behavior on the part of investors.
While there are various measures of contagion, perhaps the simplest and most robust is the correlation of exchange rate (or stock market price) movements across countries. These correlations rose significantly in the latter half of 1997 and, while falling somewhat more recently, remain positive and significant. Using a sample consisting of Indonesia, Korea, Malaysia, the Philippines, and Thailand, the accompanying table reports a panel regression of daily exchange rate (or stock market price) movement in one country on the average exchange rate (stock market price) movement in the four other countries (denoted the “contagion” variable).1
According to the estimates, a 1 percent average depreciation in the four other countries is associated with a 0.38 percent depreciation in the country's own exchange rate.2 Indeed, there is Granger causality from the contagion variable to changes in the country's own exchange rate—that is, the contagion variable helps predict movements in that country's exchange rate even when past movements in the same country's exchange rate are taken into account. A 1 percent contagion depreciation is associated with a 0.31 depreciation on the following day, controlling for lagged changes in the country's own exchange rate.
More recently, the contagion effect has diminished in magnitude, while remaining positive and highly statistically significant. Finally, it is worth noting that contagion effects are discernible not only at very high frequencies but also with monthly data, and are robust to the inclusion of the country's interest rate (either in levels or in first differences).
The results for stock market prices are broadly similar. Estimating the regression over the period July 1997 to June 1998 shows that a 1 percent decline in the average stock prices of the four other countries is associated with a 0.64 percent decline in the country's own stock price. There is, however, some evidence of this “contagion” effect as far back as 1996 (albeit of smaller magnitude). As with exchange rate movements, the contagion variable Granger causes subsequent movements in stock market prices.
Contagion in Exchange and Equity Markets
Contagion in Exchange and Equity Markets
| Exchange Rate, Δlog(e) | Stock Market Price, Δlog(p) | ||||
|---|---|---|---|---|---|
| Daily | Monthly | Daily | Monthly | ||
| Contemporaneous contagion, Jan.–Dec. 1996 | |||||
| Coefficient | -0.016 | -0.308 | 0.443 | 0.473 | |
| t-statistic | -0.22 | -1.12 | 7.33 | 2.28 | |
| R2 | 0.02 | 0.20 | 0.11 | 0.17 | |
| Contemporaneous contagion, July 1997–June 1998 | |||||
| Coefficient | 0.380 | 0.604 | 0.643 | 0.831 | |
| t-statistic | 5.64 | 3.80 | 12.96 | 4.94 | |
| R2 | 0.10 | 0.23 | 0.23 | 0.45 | |
| Lagged contagion (Granger causality), July 1997–June 1998 | |||||
| Coefficient | 0.314 | -0.007 | 0.235 | 0.412 | |
| t-statistic | 3.53 | -0.02 | 3.97 | 1.49 | |
| R2 | 0.07 | 0.08 | 0.05 | 0.11 | |
| Contemporaneous contagion, Jan.–May 1998 | |||||
| Coefficient | 0.359 | 0.503 | 0.763 | 0.915 | |
| t-statistic | 4.34 | 2.61 | 12.12 | 2.78 | |
| R2 | 0.12 | 0.24 | 0.32 | 0.43 | |
| Lagged contagion (Granger causality), Jan.–May 1998 | |||||
| Coefficient | 0.349 | 0.067 | 0.288 | 1.434 | |
| t-statistic | 2.74 | 0.18 | 3.22 | 4.46 | |
| R2 | 0.08 | 0.16 | 0.05 | 0.58 | |
Contagion in Exchange and Equity Markets
| Exchange Rate, Δlog(e) | Stock Market Price, Δlog(p) | ||||
|---|---|---|---|---|---|
| Daily | Monthly | Daily | Monthly | ||
| Contemporaneous contagion, Jan.–Dec. 1996 | |||||
| Coefficient | -0.016 | -0.308 | 0.443 | 0.473 | |
| t-statistic | -0.22 | -1.12 | 7.33 | 2.28 | |
| R2 | 0.02 | 0.20 | 0.11 | 0.17 | |
| Contemporaneous contagion, July 1997–June 1998 | |||||
| Coefficient | 0.380 | 0.604 | 0.643 | 0.831 | |
| t-statistic | 5.64 | 3.80 | 12.96 | 4.94 | |
| R2 | 0.10 | 0.23 | 0.23 | 0.45 | |
| Lagged contagion (Granger causality), July 1997–June 1998 | |||||
| Coefficient | 0.314 | -0.007 | 0.235 | 0.412 | |
| t-statistic | 3.53 | -0.02 | 3.97 | 1.49 | |
| R2 | 0.07 | 0.08 | 0.05 | 0.11 | |
| Contemporaneous contagion, Jan.–May 1998 | |||||
| Coefficient | 0.359 | 0.503 | 0.763 | 0.915 | |
| t-statistic | 4.34 | 2.61 | 12.12 | 2.78 | |
| R2 | 0.12 | 0.24 | 0.32 | 0.43 | |
| Lagged contagion (Granger causality), Jan.–May 1998 | |||||
| Coefficient | 0.349 | 0.067 | 0.288 | 1.434 | |
| t-statistic | 2.74 | 0.18 | 3.22 | 4.46 | |
| R2 | 0.08 | 0.16 | 0.05 | 0.58 | |
Episodic Evidence on the Interest Rate-Exchange Rate Relationship
A number of recent studies have tried to assess empirically whether higher interest rates are useful in supporting the exchange rate (that is, the “traditional” effect) or whether they instead have an opposite, “perverse” effect. Rather than examining the long-run relationship between monetary policy and the exchange rate, these studies focus on patterns inside selected short episodes.
The results of these studies are inconclusive and indeed quite mixed. In general, they fail to find overwhelming evidence of the traditional effect—though this is not surprising, given the inherent policy endogeneity problem (that is, interest rates are likely to be raised precisely during episodes of currency depreciation, as both variables respond to shifts in market sentiment). On the other hand, neither is there a clear pattern of evidence across studies of a perverse effect of interest rate policy.
Furman and Stiglitz (1998) identify a set of 13 episodes, in nine emerging markets, of “temporarily high” interest rates (episodes in which interest rates rose by more than 10 percentage points for at least five days, then fell back). Using a simple regression analysis, they find that both the magnitude and duration of such interest rate hikes are associated with exchange rate depreciation. While Furman and Stiglitz note that this evidence is not definitive, and that its interpretation is fraught with difficulties concerning endogeneity, they conclude that it at least questions the usefulness of raising interest rates.
Kraay (1998) focuses instead on episodes of speculative attacks on currencies and uses a more sophisticated and complex methodology. He identifies a set of 121 attacks that were successful, in the sense that there was an uncharacteristically large monthly depreciation; he also identifies (with greater inherent difficulty) a set of 192 unsuccessful attacks. The essential finding is that increases in central bank discount rates are neither necessary nor sufficient for staving off a speculative attack. Indeed, no relationship is found between central bank discount policy and the success or failure of speculative attacks. When Kraay tries to control for the endogeneity of interest rate policy, the results are similar, although, as he notes, they are preliminary and could reflect the difficulty of specifying appropriate instrumental variables to control for policy endogeneity.
Goldfajn and Gupta (1998) ask a somewhat different question, one probably more relevant for the East Asian countries during their IMF-supported programs. They consider cases following an exchange rate crisis in which the real exchange rate has become clearly undervalued, so that considerable real appreciation is likely to follow. They then study whether tighter monetary policies—in terms of higher-than-average real interest rates—are associated with the corrective real appreciation occurring mainly through currency appreciation rather than through higher inflation.
In general, Goldfajn and Gupta find that tight monetary policy does raise the probability of “success”; that is, achieving the corrective real appreciation via currency appreciation. However, when the sample is restricted to cases where the banking sector is fragile, tight monetary policy seems to reduce the probability of success (though as the authors note, this latter result is based on very few cases and is not robust).
Goldfajn and Baig (1998), rather than defining and identifying crisis episodes from a broad sample of countries, focus on the very recent experience of five Asian countries, from mid-1997 through May 1998. Using daily data, they analyze the relationship between nominal interest rates and nominal exchange rates during the recent Asian crisis. A vector autoregression does not find a significant relationship—in either direction—for any of the five Asian countries. On the other hand, a panel regression using changes in interest rates and exchange rates yields a traditionally signed coefficient over all the sample spans examined, though this is statistically significant only in some subperiods. Countryby-country regressions find a significant traditionally signed coefficient in some periods for Indonesia, Korea, and the Philippines (the only significant coefficient with the opposite sign is found for Malaysia, and this in one subperiod only). Goldfajn and Baig thus conclude that their study finds no evidence that higher interest rates lead to weaker exchange rates; if anything, there are periods where higher rates lead to stronger exchange rates.
Real interest rates may not provide an adequate measure of the tightness of monetary conditions if the volumes of liquidity and/or lending are falling sharply in nominal or real terms. Real broad money, in Indonesia and Korea, however, far from severely contracting, continued growing in the second half of 1997 and the first half of 1998—albeit at slower rates than previously (Figure 6.6).24 In Thailand, real money did contract steadily, but not dramatically, by about 5 percent from mid-1997 through mid-1998.
High Interest Rates in International Perspective
Although interest rates in East Asia rose in early 1998, they typically fell shy of the very high nominal and real interest rates occasionally seen in some other countries during (or in the aftermath of) an exchange rate crisis.
In Sweden, the Riksbank raised its marginal lending rate to 75 percent a year on September 8, 1992 in defense of the krona's parity in the exchange rate mechanism. Interest rates were lowered the following week, but on September 16, renewed turmoil in the currency markets forced an increase in the marginal lending rate, first to 75 percent a year, and later that afternoon, to an unprecedented 500 percent a year. Effective September 21, the marginal lending rate was lowered to 50 percent a year, and, in early October, to 20 percent. Through October and early November, the marginal rate was decreased by degrees to 11.5 percent.
During the crisis, interbank interest rates averaged 82 percent in September 1992 (74 percent in real terms), falling to 17 percent in October 1992, and remaining above 10 percent until March 1993. During the four-day period of 500 percent interest rates, however, banks were protected by loans on more favorable terms.
In Mexico, following the sharp devaluation of the peso in December 1994, there were sharp increases in nominal interest rates, with the average cost of funds for banks rising from 17 percent a year to almost 60 percent a year in the first quarter of 1995. Set against inflation of over 70 percent (at annual rates), however, real interest rates were not especially high. Nominal interest rates then dipped to 35 percent in the third quarter, before ending the year at about 47 percent. Thereafter, interest rates fell steadily, to 40 percent by the end of the first quarter of 1996, and 20 percent by the first quarter of 1997. Other interest rates in the economy followed a similar pattern, with the nominal interest rate on commercial paper peaking at 112 percent a year (in the first quarter of 1995), dipping to 47 percent a year in the third quarter of 1995, and ending the year at 70 percent. By the first quarter of 1997, the nominal rate on commercial paper had fallen to 30 percent a year.
Deflated by the consumer price index, the real rate on commercial paper actually fell in the first quarter of 1995 (from 11 percent a year to 6.5 percent a year) before increasing to 15 percent a year at end-1995, and 22 percent a year in the first quarter of 1996. Since then, real interest rates have fallen steadily.
In Argentina, the aftermath of the Mexican crisis triggered a capital outflow in early 1995, with deposits in the Argentine banking system declining by some $8 billion, and interbank and deposit rates rising to about 20–30 percent a year in March 1995 (against an annual inflation rate of below 2 percent). A series of measures, including a substantial fiscal adjustment package, helped restore confidence, and by July 1995, lending rates had fallen to 15 percent a year, and by April 1996, they were 10 percent a year.
In the Czech Republic interest rates were raised briefly—with overnight interbank rates reaching 60 percent in nominal terms (against an annual inflation rate of 10 percent)—during the exchange rate crisis in May 1997. The authorities decided to abandon the exchange rate band and adopted a managed float instead. Following the crisis, interbank interest rates fell quickly, and within three months were at 141/2percent (about 2 percentage points above the precrisis level).
In the Slovak Republic, one-month interbank interest rates rose to 25—26 percent (against an annual inflation rate of 6 percent) in May 1997, following a speculative attack on the koruna.
There was also little evidence of tightening real credit during the second half of 1997. The measured stock of credit grew in real terms at annualized rates ranging from 13 percent in Korea, to 15 percent in Thailand, to almost 40 percent in Indonesia.25
Credit growth decelerated in all three countries in the first half of 1998: in Indonesia, there was only a slight deceleration of a rapid growth rate (to an annualized 32 percent), while in Korea real credit declined by an annualized 3 percent and in Thailand by 11 percent.
The slowing of growth rates of money and credit, although not inconsequential, appears to be far from draconian. Despite dire warnings that tightening monetary policies in the midst of a banking crisis would lead to a financial implosion, nothing like that has occurred.26 It is useful to compare them with the degree of tightening found in the experience of other countries facing exchange rate crises. Table 6.1 reports the money and credit developments surrounding three such episodes—the Czech Republic in May 1997, Mexico in December 1994, and Sweden in November 1992. In the year of an episode of substantial depreciation, not only did real money and credit growth tend to slow compared with the previous year, there were generally real contractions of money and credit. In the Asian countries, in contrast—though there have been lower rates of growth of real money and credit—only in Thailand have actual (real) contractions occurred. With regard to the deceleration of real money growth, Mexico stands out: although money growth accelerated in nominal terms, it was greatly outpaced by a surge in inflation that lowered the growth of real money by almost 26 percentage points between 1994 and 1995—while the growth rate of real GDP declined by almost 10 percentage points. The slowdown in real money and credit in the Asian programs pales in comparison.
Czech Republic, Mexico, and Sweden: Money and Credit Developments Surrounding Episodes of Devaluation or Depreciation
GDP figures are Year-on-Year.
“Year t” refers to 1997 for th e Czech Republic, 1995 for Mexico, and 1993 for Sweden. Abrupt depreciations took place in 1997 in the Czech Republic, in late 1994 in Mexico, and in late 1992 in Sweden.
Measured as the change in the number of domestic currency units per U.S. dollar.
Czech Republic, Mexico, and Sweden: Money and Credit Developments Surrounding Episodes of Devaluation or Depreciation
| Czech Republic | Mexico | Sweden | ||
|---|---|---|---|---|
| (Twelve-monthrates of change, in percent)1 | ||||
| Broad money | ||||
| Year t2 | 7.9 | 33.3 | 4.4 | |
| Yeart-1 | 9.2 | 21.7 | 3.0 | |
| Year t-2 | 19.8 | 14.5 | 4.5 | |
| Domestic credit | ||||
| Year t2 | 10.1 | 22.8 | 2.9 | |
| Year t-1 | 10.8 | 31.5 | -12.8 | |
| Year t-2 | 13.7 | 12.7 | -0.1 | |
| Real money | ||||
| Year t2 | -1.9 | -12.3 | 0.4 | |
| Year t–1 | 0.6 | 13.6 | 1.2 | |
| Year t–2 | 11.0 | 6.0 | -3.2 | |
| Real domestic credit | ||||
| Year t2 | 0.1 | -19.2 | -1.1 | |
| Year t–1 | 2.0 | 22.8 | -14.3 | |
| Year t-2 | 5.4 | 4.4 | -7.4 | |
| Memorandum items: | ||||
| CPI inflation (end of period) | ||||
| Year t2 | 10.0 | 52.0 | 4.0 | |
| Year t-1 | 8.6 | 7.1 | 1.8 | |
| Year t-2 | 7.9 | 8.0 | 7.9 | |
| Currency depreciation3 | ||||
| Year t2 | 27.0 | 95.0 | 21.6 | |
| Year t-1 | 2.6 | 26.54 | 19.3 | |
| Year t-2 | -5.5 | -0.3 | 2.8 | |
| Real GDP growth | ||||
| Year t2 | 1.5 | -6.1 | -2.2 | |
| Year t-1 | 4.1 | 4.4 | -1.4 | |
| Year t-2 | 5.9 | 2.0 | -1.7 | |
GDP figures are Year-on-Year.
“Year t” refers to 1997 for th e Czech Republic, 1995 for Mexico, and 1993 for Sweden. Abrupt depreciations took place in 1997 in the Czech Republic, in late 1994 in Mexico, and in late 1992 in Sweden.
Measured as the change in the number of domestic currency units per U.S. dollar.
Czech Republic, Mexico, and Sweden: Money and Credit Developments Surrounding Episodes of Devaluation or Depreciation
| Czech Republic | Mexico | Sweden | ||
|---|---|---|---|---|
| (Twelve-monthrates of change, in percent)1 | ||||
| Broad money | ||||
| Year t2 | 7.9 | 33.3 | 4.4 | |
| Yeart-1 | 9.2 | 21.7 | 3.0 | |
| Year t-2 | 19.8 | 14.5 | 4.5 | |
| Domestic credit | ||||
| Year t2 | 10.1 | 22.8 | 2.9 | |
| Year t-1 | 10.8 | 31.5 | -12.8 | |
| Year t-2 | 13.7 | 12.7 | -0.1 | |
| Real money | ||||
| Year t2 | -1.9 | -12.3 | 0.4 | |
| Year t–1 | 0.6 | 13.6 | 1.2 | |
| Year t–2 | 11.0 | 6.0 | -3.2 | |
| Real domestic credit | ||||
| Year t2 | 0.1 | -19.2 | -1.1 | |
| Year t–1 | 2.0 | 22.8 | -14.3 | |
| Year t-2 | 5.4 | 4.4 | -7.4 | |
| Memorandum items: | ||||
| CPI inflation (end of period) | ||||
| Year t2 | 10.0 | 52.0 | 4.0 | |
| Year t-1 | 8.6 | 7.1 | 1.8 | |
| Year t-2 | 7.9 | 8.0 | 7.9 | |
| Currency depreciation3 | ||||
| Year t2 | 27.0 | 95.0 | 21.6 | |
| Year t-1 | 2.6 | 26.54 | 19.3 | |
| Year t-2 | -5.5 | -0.3 | 2.8 | |
| Real GDP growth | ||||
| Year t2 | 1.5 | -6.1 | -2.2 | |
| Year t-1 | 4.1 | 4.4 | -1.4 | |
| Year t-2 | 5.9 | 2.0 | -1.7 | |
GDP figures are Year-on-Year.
“Year t” refers to 1997 for th e Czech Republic, 1995 for Mexico, and 1993 for Sweden. Abrupt depreciations took place in 1997 in the Czech Republic, in late 1994 in Mexico, and in late 1992 in Sweden.
Measured as the change in the number of domestic currency units per U.S. dollar.
What impact did this monetary tightening have on the economies of the Asian crisis countries? Some illustrative calculations are presented in Appendix 6.1, based on estimated impulse response functions of real GDP growth to a given deceleration of the growth of real money. These calculations suggest that for Korea and Thailand, the estimated effects of monetary tightening could account for less than one-fourth of the expected negative swing in GDP growth rates from 1997 to 1998, and a very small part of the deceleration expected for Indonesia. However, the actual effects could be even smaller, since the technique used attributes all money-growth correlation to money's influence on growth. (On the other hand, the historical relationships examined are unlikely to capture the banking-related sensitivity of output.)
Thus, available monetary indicators tend to contradict the view that monetary policy was tightened drastically in these countries and that this tightening was a major reason for the economic slowdown in the Asian crisis countries. Indeed, events in Indonesia display a breakdown of monetary control rather than severe tightening. How can this evidence be reconciled with widespread perceptions of a continuing “credit crunch” in these countries? Clearly, what the aggregate data cannot capture is a shift in credit allocation among different borrowers, in the face of widespread bankruptcies and an increased preoccupation of financial institutions with credit risk (associated in part with the tightening of prudential regulations). It would not be surprising if, in this environment, many borrowers that previously had access to credit (especially small and medium-sized enterprises) found themselves unable to obtain financing. The counterpart of this cutoff of access to credit could be an increased share of credit going to capitalize interest on loans to companies perceived as more creditworthy (especially to larger companies, as is reported to be the case in Korea). The possibility of a credit crunch in these countries is still being studied, and some preliminary evidence is discussed in Box 6.5. Disruptions in credit markets are clearly of concern although not uncommon in such circumstances.27 To the extent that they reflect structural problems in credit allocation, the main solution is to move ahead with the needed restructuring of financial systems and workout of corporate debt (as discussed in Section VIII below).
Conclusion
Monetary policy, albeit only after some period, achieved its basic objective of avoiding a depreciation/inflation spiral in both Korea and Thailand—without necessitating persistently and egregiously high real interest rates, and without causing a collapse of nominal, or even real, money or credit volumes. This is not to deny, of course, that monetary tightening had a cost for the real economy, but the alternative would have been more costly.
The currency crisis might have been less severe had stabilization been pursued earlier, more aggressively, and more consistently. In the early part of 1998, in contrast, there was some tightening of monetary conditions in Korea and Thailand—accompanied by greater signs of exchange rate stability (and even nominal appreciation). Going much further in the direction of tightening at this late stage, however, might have proved counterproductive, given the effects of much higher interest rates on balance sheets of banks and corporations already reeling from the effects of the currency depreciations.
The pattern of real interest rates in Korea and Thailand is not untypical of stabilization episodes: initially low or negative real rates as inflation surges, followed by a period of high real interest rates as nominal rates lag declining inflation. The authorities' reaction to this second phase is critical: either the impact of high interest rates on the real economy leads them to abandon the stabilization effort—confirming the doubts that were reflected in market pressures on interest rates—or they persevere and are able gradually to lower nominal and real interest rates as reforms succeed and gain credibility. It is precisely the first possibility that undermines confidence and makes the deft handling of interest rate policy crucial. During this process, some period of high real interest rates is probably unavoidable. The challenge is to ease rates down without jeopardizing stabilization. Ultimately, the decline in nominal and real interest rates needs to come more from smaller risk premiums and greater confidence, rather than from expanding money and credit.
Monetary policy in Indonesia, until the stabilization of recent months, is quite a different story: a virtually complete loss of monetary control in the face of the banking collapse and political turmoil, resulting in high nominal interest rates that reflected risk premiums while real interest rates remained negative. The resulting, highly expansionary, monetary policy was reflected in a lurch into high inflation, capital outflows, and a collapse of the currency. This experience illustrates the danger that even in a previously stable economy, a vicious circle of inflation and depreciation can emerge.
Appendix 6.1. Monetary and Exchange Rate Policies
Earlier in this section, reference was made to various results. This appendix provides details of the calculations on the following:
the monetary contraction required to offset a given increase in the risk premium;
the expected real interest rate; and
the impact of a given monetary contraction on real GDP growth.
Monetary Contraction Required to Offset a Given Increase in the Risk Premium
This section raised the question what magnitude of monetary contraction would have stabilized the exchange rate, given an exogenous increase in the risk premium demanded by investors. This requires an explicit model of the exchange rate. The simplest such framework is the monetary model of exchange rate determination. In such a model, real demand for broad money depends positively on the level of activity and negatively on the interest rate. Domestic and foreign interest rates are linked by a parity condition (including a risk premium).28 The exchange rate is then given by:
Was There a Credit Crunch?
In recent months, there has been much discussion about a “credit crunch” in the East Asian economies—most notably in Indonesia, Korea, and Thailand. While there was clearly a sharp fall in external finance available, the debate has centered on whether domestic credit conditions tightened significantly, and perhaps excessively.
The term credit crunch is perhaps best understood as a situation in which, at prevailing interest rates, there is an unsatisfied excess demand for credit. In the present context, however, the term has been used much more loosely to describe a situation of tight credit conditions in general. Of course, prevailing credit conditions are likely to have changed during the course of the crisis, with different situations calling for very different policy responses. Research on this topic is still at an early stage, and both the results and their interpretation very much mixed. This box briefly reviews some recent work on this issue.
A survey of some 1,200 manufacturing firms in Thailand was undertaken in the last quarter of 1997 and first quarter of 1998, by Dollar and Hallward-Driemeier (1998). Asked to rank the causes of the current output decline (out of four possibilities), the most important factor cited by both exporters and nonexporters was the effect of the exchange rate depreciation on input costs, followed by lack of domestic (or foreign) demand. The high cost of capital was ranked third, and lack of access to credit ranked last
Domaç and Ferri (1998) examine the relationship between increases in the spread between bank lending rates and treasury bond rates, and industrial production in Korea. (They also decompose this spread into various interest rates to examine different channels of effects.) In general, they find Granger causality from increases in the spread to subsequent declines in industrial production, and find that a 1 percentage point increase in the overall bank lending spread is associated with a 1.4 percent decline in industrial production (or 1.7 percent in the case of small- and medium-scale enterprises). As such, the paper concludes that wider spreads and higher interest rates could account for a fall in industrial production of as much as 5–10 percent.
While their evidence is suggestive, there are issues in the interpretation of their results. Most important, the estimation period covers the early 1990s through February 1998. Since the variables examined fluctuated relatively little in the sample period until the crisis period—when there was a sharp fall in production and a rise in interest rates—and since no allowance is made for other factors influencing production (such as falling domestic and foreign demand or the effects of exchange rate depreciation—as the Dollar and Hallward-Driemeier evidence suggests), the effect attributed to larger spreads and higher interest rates is necessarily substantial. Moreover, Granger causality says little about economic causality—especially in this context. If output is expected to fall (for whatever reason), the perceived riskiness of lending to the corporate sector would increase, and—assuming even minimal rationality on the part of capital markets—this should be reflected in an immediate increase in spreads and interest rates: Granger causality here could reflect nothing more than financial variables moving more quickly than the real economy.
In the debate on whether priority should have been given to stabilizing the exchange rate or lowering interest rates, Claessens, Djankov, and Ferri (1998) assess the impact of the currency and interest rate shocks (between early 1997 and September 1998) on the liquidity of a sample of firms in Indonesia, Korea. Malaysia, the Philippines, and Thailand and on their solvency. They define a firm to be illiquid when earnings (before income tax but after depreciation) fall short of debt service; and insolvent when total liabilities at the new exchange and interest rates exceed end-1996 equity. Given the magnitude of the exchange rate movements, they find that the exchange rate shock alone was sufficient to drive almost two-thirds of Indonesian firms, 20 percent of Korean firms, and 10 percent of Thai firms (in their sample) into insolvency (and 72 percent, 38 percent, and 55 percent, respectively, into illiquidity). The effect of interest rates is rather smaller, with the interest rate shock driving about 2–5 percent of firms in each of the countries into insolvency, and 15 to 25 percent into illiquidity. (The paper also notes, however, that about 35 percent of firms in these countries are solvent but illiquid—suggesting the importance of restoring credit flows rapidly.) The results are analytically interesting, but since the authors do not estimate an explicit trade-off between higher interest rates and a smaller depreciation, the direct operational implications of their findings are, perhaps, somewhat limited.
Finally, Ghosh and Ghosh (1999) examine whether there was a credit crunch—whereby the (often low or negative) real interest rates may not have cleared the credit market and there was quantity rationing. They apply an explicit disequilibrium framework, and estimate credit supply and credit demand functions. In Indonesia, they find some evidence of a credit crunch in late 1997 as the banking crisis deepened. Thereafter, credit demand also fell sharply so supply was no longer the binding constraint. In Korea and Thailand, they find that, although real credit supply did decrease in late 1997 and early 1998, the fall in real credit demand was sharper, so credit supply was not the constraining factor. (These results are thus very much consistent with the findings of Dollar and Hallward-Driemeier (1998) who found, in Thailand, that lack of access to credit was ranked last among factors accounting for the depressed activity.)
There are two important caveats to their results, how-ever. First, rising real interest rates themselves may have contributed to corporate sector distress, quite aside from any credit crunch. Second, the results pertain to the aggregate economy—at a microeconomic level, there may have been (otherwise creditworthy) firms, especially small- and medium-scale enterprises, that were denied credit in an environment of informational asymmetries, and as banks strove to improve loan portfolios and meet capital adequacy standards.
According to equation (1), the exchange rate depreciates with an increase in the money supply, a slowdown in activity, an increase in the risk premium, or a decrease in the rate of real appreciation.
The initial crisis is perhaps best modeled as an increase in the risk premium, π.29 There is, of course, no reason to suppose that the increase in risk premiums was equal across countries. The increase in the risk premium for any individual country reflects investors' perceptions about the design and implementation of the reform programs, the likelihood that other investors will remain in the market, and the prospects of continued servicing of external obligations. Nonetheless, a useful exercise is to consider the required monetary contraction to stabilize the exchange rate for a given shock to the risk premium.
Table 6.2 reports the result of such a simulation. For a given shock to the risk premium (10 percentage points), the table reports the contraction in broad money/GDP required to offset the shock. For instance, given trend increases, the ratio of broad money/GDP would have risen from 0.52 in 1996 to 0.56 in 1997. With a 10 percentage point shock to the risk premium, and given the estimated interest elasticity of money demand of -1.69 (t-stat. 2.65**), the ratio of broad money/GDP would need to decline to 0.48 (that is, a 7.6 percent decline relative to 1996), if the exchange rate is to be constant. Similar calculations can be done for each of the countries, under an assumed risk premium shock. The required contractions depend primarily on the estimated interest elasticity of money demand, which is negative and statistically significant (at least) at the 10 percent level in each of the countries except Korea.
Required Monetary Contraction to Offset Given Risk Premium Shocks
Required Monetary Contraction to Offset Given Risk Premium Shocks
| Indonesia | Korea | Malaysia | Philippines | Thailand | ||
|---|---|---|---|---|---|---|
| Parameter estimates | ||||||
| Interest elasticity | -1.69 | -0.40 | -2.90 | -0.91 | -1.91 | |
| t-statistic | (-2.65) | (-0.66) | (-2.04) | (-1.78) | (-3.74) | |
| Constant | -2.19 | -1.39 | -0.97 | -1.83 | -1.18 | |
| t-statistic | (27.90) | (9.86) | (16.29) | (25.48) | (24.69) | |
| Time trend | 0.06 | 0.01 | 0.04 | 0.04 | 0.05 | |
| t-statistic | (19.28) | (3.57) | (25.33) | (13.68) | (30.62) | |
| R2 | 0.95 | 0.74 | 0.96 | 0.88 | 0.97 | |
| Baseline | ||||||
| Broad money/GDP, 1996 (in percent) | 52.1 | 45.7 | 99.4 | 53.8 | 81.0 | |
| Interest rate, 1996 (in percent a year) | 14.0 | 7.5 | 7.3 | 9.7 | 10.5 | |
| Broad money/GDP in 1997 (in percent) | 55.6 | 46.2 | 103.4 | 56.3 | 84.8 | |
| Percentage growth, 1997 over 1996 | 6.5 | 1.1 | 4.0 | 4.5 | 4.7 | |
| Shocks | ||||||
| Risk premium shock | 5.0 | 5.0 | 5.0 | 5.0 | 5.0 | |
| Broad money/GDP in 1997 (in percent) | 51.7 | 45.4 | 90.6 | 54.0 | 78.0 | |
| Broad money/GDP 1997/1996 (growth in percent) | -0.9 | -0.7 | -8.9 | 0.3 | -3.8 | |
| Risk premium shock | 10.0 | 10.0 | 10.0 | 10.0 | 10.0 | |
| Broad money/GDP in 1997 (in percent) | 48.2 | 44.6 | 79.8 | 52.0 | 71.9 | |
| Broad money/GDP 1997/1996 (growth in percent) | -7.6 | -2.4 | -19.7 | -3.5 | -11.2 | |
Required Monetary Contraction to Offset Given Risk Premium Shocks
| Indonesia | Korea | Malaysia | Philippines | Thailand | ||
|---|---|---|---|---|---|---|
| Parameter estimates | ||||||
| Interest elasticity | -1.69 | -0.40 | -2.90 | -0.91 | -1.91 | |
| t-statistic | (-2.65) | (-0.66) | (-2.04) | (-1.78) | (-3.74) | |
| Constant | -2.19 | -1.39 | -0.97 | -1.83 | -1.18 | |
| t-statistic | (27.90) | (9.86) | (16.29) | (25.48) | (24.69) | |
| Time trend | 0.06 | 0.01 | 0.04 | 0.04 | 0.05 | |
| t-statistic | (19.28) | (3.57) | (25.33) | (13.68) | (30.62) | |
| R2 | 0.95 | 0.74 | 0.96 | 0.88 | 0.97 | |
| Baseline | ||||||
| Broad money/GDP, 1996 (in percent) | 52.1 | 45.7 | 99.4 | 53.8 | 81.0 | |
| Interest rate, 1996 (in percent a year) | 14.0 | 7.5 | 7.3 | 9.7 | 10.5 | |
| Broad money/GDP in 1997 (in percent) | 55.6 | 46.2 | 103.4 | 56.3 | 84.8 | |
| Percentage growth, 1997 over 1996 | 6.5 | 1.1 | 4.0 | 4.5 | 4.7 | |
| Shocks | ||||||
| Risk premium shock | 5.0 | 5.0 | 5.0 | 5.0 | 5.0 | |
| Broad money/GDP in 1997 (in percent) | 51.7 | 45.4 | 90.6 | 54.0 | 78.0 | |
| Broad money/GDP 1997/1996 (growth in percent) | -0.9 | -0.7 | -8.9 | 0.3 | -3.8 | |
| Risk premium shock | 10.0 | 10.0 | 10.0 | 10.0 | 10.0 | |
| Broad money/GDP in 1997 (in percent) | 48.2 | 44.6 | 79.8 | 52.0 | 71.9 | |
| Broad money/GDP 1997/1996 (growth in percent) | -7.6 | -2.4 | -19.7 | -3.5 | -11.2 | |
The required contraction in the money/GDP ratio need not, of course, come through a contraction in the nominal money supply. To the extent that there is inflation, part of the contraction will take place through an adjustment of prices.30 Inasmuch as output is contracting, however, the real monetary contraction would need to be correspondingly greater.
Finally, it is worth noting that equation (1) also provides a convenient framework for analyzing the plausibility of a monetary contraction leading to a depreciation of the exchange rate. Quite simply, the direct effects of the monetary contraction would need to be outweighed by the indirect effect on money demand through the activity term. Since the income elasticity is typically in the range of 0.5–1.0, this means that a 1 percent monetary contraction would need to contract output by more than 1 percent, or there would need to be an adverse effect on the risk premium (controlling for any effects on output). Since output elasticities with respect to money are typically well below unity, a monetary contraction would have a perverse effect on the exchange rate only if it resulted in a significant widening of the risk premium.
Expected Real Interest Rates
Real interest rates were measured using an estimate of the contemporaneous rate of inflation. Also of interest is a more forward-looking approach. To estimate expected real interest rates, some means of forecasting price dynamics must be developed; the approach adopted here is perhaps the simplest. For each country, a distributed lag model relating current inflation to lagged inflation, lagged exchange rate changes, and lagged broad money growth is estimated:
Parameter estimates, using monthly data for the period 1990–97, are reported in the top panel of Table 6.3 (with heteroscedastic-consistent t-statistics reported in parentheses). The autoregressive parameter is generally significant, and exchange rate depreciations feed into higher inflation with a one-to-two month lag. The estimated equations are then used to generate inflation forecasts—and corresponding expected real interest rates, which are reported in the bottom panel of Table 6.3.
Pass-Through Coefficients and Implied Expected Real Overnight Rates
Pass-Through Coefficients and Implied Expected Real Overnight Rates
| Indonesia | Korea | Thailand | ||
|---|---|---|---|---|
| Constant | 0.00 | 0.00 | 0.00 | |
| (2.15) | (2.51) | (3.50) | ||
| Δlog(p(-1)) | 0.24 | 0.36 | 0.07 | |
| (1.80) | (3.25) | (0.71) | ||
| Δlog(m(-1)) | 0.05 | 0.05 | -0.04 | |
| (1.19) | (1.69) | (-0.82) | ||
| Δlog(m(-2)) | 0.01 | -0.01 | -0.02 | |
| (0.36) | (-0.34) | (-0.32) | ||
| Δlog(m(-3)) | 0.00 | 0.00 | -0.01 | |
| (-0.17) | (-0.04) | (-0.11) | ||
| Sum of money coefficients | 0.05 | 0.04 | -0.06 | |
| Δlog(e(-1)) | 0.00 | 0.03 | 0.04 | |
| (-0.21) | (1.72) | (0.89) | ||
| Δlog(e(-2)) | 0.09 | 0.04 | -0.01 | |
| (2.53) | (4.92) | (0.49) | ||
| Δlog(e(-3)) | 0.01 | -0.03 | 0.03 | |
| (0.19) | (3.85) | (1.46) | ||
| Sum of exchange rate coefficients | 0.09 | 0.04 | 0.05 | |
| R2 | 0.20 | 0.42 | 0.10 | |
| (In percent a year) | ||||
| Expected real overnight rates | ||||
| 1997:Q4 | -2.5 | 6.7 | 4.2 | |
| 1998:Q1 | 5.5 | 1.1 | 5.9 | |
Pass-Through Coefficients and Implied Expected Real Overnight Rates
| Indonesia | Korea | Thailand | ||
|---|---|---|---|---|
| Constant | 0.00 | 0.00 | 0.00 | |
| (2.15) | (2.51) | (3.50) | ||
| Δlog(p(-1)) | 0.24 | 0.36 | 0.07 | |
| (1.80) | (3.25) | (0.71) | ||
| Δlog(m(-1)) | 0.05 | 0.05 | -0.04 | |
| (1.19) | (1.69) | (-0.82) | ||
| Δlog(m(-2)) | 0.01 | -0.01 | -0.02 | |
| (0.36) | (-0.34) | (-0.32) | ||
| Δlog(m(-3)) | 0.00 | 0.00 | -0.01 | |
| (-0.17) | (-0.04) | (-0.11) | ||
| Sum of money coefficients | 0.05 | 0.04 | -0.06 | |
| Δlog(e(-1)) | 0.00 | 0.03 | 0.04 | |
| (-0.21) | (1.72) | (0.89) | ||
| Δlog(e(-2)) | 0.09 | 0.04 | -0.01 | |
| (2.53) | (4.92) | (0.49) | ||
| Δlog(e(-3)) | 0.01 | -0.03 | 0.03 | |
| (0.19) | (3.85) | (1.46) | ||
| Sum of exchange rate coefficients | 0.09 | 0.04 | 0.05 | |
| R2 | 0.20 | 0.42 | 0.10 | |
| (In percent a year) | ||||
| Expected real overnight rates | ||||
| 1997:Q4 | -2.5 | 6.7 | 4.2 | |
| 1998:Q1 | 5.5 | 1.1 | 5.9 | |
Impact of a Monetary Contraction on Real GDP Growth
As discussed earlier, unrestricted vector autoregressions of real GDP growth and real money growth may provide basic insight into the possible effects of monetary tightening. For each of five Asian economies, Table 6.4 reports estimated impulse response functions of real GDP growth to a hypothetical decrease of 10 percentage points in the growth rate of real money (estimated over the period 1972–96). Such a decrease in real money growth is estimated to lower the current rate of GDP growth by about 1 percentage point in Thailand and the Philippines, by11/2percentage points in Malaysia, and by 3 percentage points in Korea. In Indonesia, the main effect occurs with a one-year lag: growth in the current year falls by only 0.3 percentage point, but in the following year it falls by 1 percentage point. If such estimates are interpreted as causal elasticities, they can be applied to the observed decelerations of real money balances to yield the estimated growth effects discussed earlier.
Effect on GDP Growth of a Decrease in Money Growth
(In percent a year, at annualized rates)
Effect on GDP Growth of a Decrease in Money Growth
(In percent a year, at annualized rates)
| Indonesia | Korea | Malaysia | Philippines | Thailand | ||
|---|---|---|---|---|---|---|
| Effects of a 10 percentage point decrease in real money growth in year 0 only | ||||||
| Effect on: | ||||||
| GDP growth in year 0 | -0.3 | -2.9 | -1.6 | -1.0 | -0.9 | |
| GDP growth in year 1 | -1.0 | -0.9 | -1.7 | -0.3 | -0.8 | |
| GDP growth in year 2 | -0.5 | 0.0 | -0.7 | -0.1 | -0.5 | |
| GDP growth in year 3 | -0.2 | 0.0 | -0.2 | 0.0 | -0.3 | |
| GDP growth in year 4 | -0.1 | 0.0 | -0.1 | 0.0 | -0.1 | |
| GDP growth in year 5 | 0.0 | 0.0 | 0.0 | 0.0 | -0.1 | |
| Effects of a 10 percentage point decrease in real money growth in quarter 0 only | ||||||
| Effect on: | ||||||
| GDP growt h in quarter 0 | … | -2.6 | … | -2.3 | … | |
| GDP growth in quarter 1 | … | -2.5 | … | -0.8 | … | |
| GDP growth in quarter 2 | … | 0.4 | … | -0.5 | … | |
| GDP growth in quarter 3 | … | -2.5 | … | -0.1 | … | |
| GDP growth in quarter 4 | … | -0.2 | … | 0.0 | … | |
| GDP growth in quarter 5 | … | 0.0 | … | 0.0 | … | |
Effect on GDP Growth of a Decrease in Money Growth
(In percent a year, at annualized rates)
| Indonesia | Korea | Malaysia | Philippines | Thailand | ||
|---|---|---|---|---|---|---|
| Effects of a 10 percentage point decrease in real money growth in year 0 only | ||||||
| Effect on: | ||||||
| GDP growth in year 0 | -0.3 | -2.9 | -1.6 | -1.0 | -0.9 | |
| GDP growth in year 1 | -1.0 | -0.9 | -1.7 | -0.3 | -0.8 | |
| GDP growth in year 2 | -0.5 | 0.0 | -0.7 | -0.1 | -0.5 | |
| GDP growth in year 3 | -0.2 | 0.0 | -0.2 | 0.0 | -0.3 | |
| GDP growth in year 4 | -0.1 | 0.0 | -0.1 | 0.0 | -0.1 | |
| GDP growth in year 5 | 0.0 | 0.0 | 0.0 | 0.0 | -0.1 | |
| Effects of a 10 percentage point decrease in real money growth in quarter 0 only | ||||||
| Effect on: | ||||||
| GDP growt h in quarter 0 | … | -2.6 | … | -2.3 | … | |
| GDP growth in quarter 1 | … | -2.5 | … | -0.8 | … | |
| GDP growth in quarter 2 | … | 0.4 | … | -0.5 | … | |
| GDP growth in quarter 3 | … | -2.5 | … | -0.1 | … | |
| GDP growth in quarter 4 | … | -0.2 | … | 0.0 | … | |
| GDP growth in quarter 5 | … | 0.0 | … | 0.0 | … | |
Impulse response functions based on quarterly data for Korea and the Philippines give broadly similar results. It is estimated that a 10 percentage point reduction in the growth rate of real money for a single quarter would lower GDP growth in Korea by about 2.5 percentage points (at annualized rates) in the current quarter and the first quarter following the monetary tightening; the estimated effects are somewhat smaller in the Philippines, but cumulatively over the year are of roughly the same magnitude. (Quarterly GDP data are not available for the other countries.)
The sharp exchange rate movements make it relatively straight-forward to pin down the beginning of the crisis in each country, at least to within a one-month period. For instance, using the definition of a 10 percent depreciation (relative to end-1996) as the beginning of the crisis period gives a starting date of July 1997 for Thailand, August 1997 for Indonesia, and November 1997 for Korea.
Over time, as the likelihood of further overwhelming exchange rate pressures seemed to fade, there was a subtle firming of understandings to defend the exchange rate within some band, at least in Thailand.
The Korean program is a case in point. As widely reported in the press, there was an understanding in early 1998 that the authorities would not reduce interest rates until the exchange rate had substantially appreciated back to W 1,400 per U.S. dollar. But there was no explicit commitment to raise interest rates further if necessary to achieve such appreciation.
This argument, made explicitly in the original Thai program, was based on the assumption of a low probability of a surge in capital inflows. This assumption proved correct, but by 1998 soaring current account surpluses instead created the opportunity for unprogrammed purchases of foreign exchange.
The difference between the floor on NIR and the program's central scenario was not trivial; for the program's first quarterly test date, it was the equivalent of 20 percent of the beginning-of-period base money stock (at program exchange rates).
The program precluded a complete offset; there was a partial adjustor to the base money ceiling to limit such sterilization to four-fifths of any NIR shortfall (while the extent of such intervention would be limited by the NIR floor).
For instance, understandings might call for nominal rates to be maintained within a certain range for some time, or for cuts in nominal rates to be contingent upon a specified exchange rate outcome. As regards the response to adverse exchange rate shocks, however, program documents tended to state that the authorities understood the need to stand ready to raise interest rates, but were otherwise unspecific.
Figures are for cumulative percent growth, relative to March 1997. The “program expectations” are based on the first program document to specify a projection for that date (usually the initial program document). While there were program revisions, these do not alter the basic story—as discussed below.
Implicit in Figure 6.2, and discussed further below, is the fact that both the Thai and especially the Korean programs underestimated the money multiplier.
See also Section VIII below.
During the period between late-1997 and early 1998, for instance, interbank lending may have fallen by as much as two-thirds.
In contrast, in Thailand liquidity support was provided without expanding base money, by recycling reserves from strong to weak banks.
Broadmoney also grew by an annualized 87 percent during the same period (79 percent excluding foreign currency deposits).
The increasing share of foreign currency deposits, which grew to over 30 percent by mid-1998, mainly on account of valuation effects, also seriously complicated control of broad money. Since this share is similar to estimates of the share of imports in the consumer price index (CPI), currency depreciation now automatically generates its own validating increase in liquidity in roughly the same proportion as its direct effect on the price level. Another source of instability is that any withdrawals from foreign currency deposits spilled directly into the foreign exchange market.
It should be noted that not only in Indonesia, but also in Korea and Thailand, banking sector troubles complicated the conduct of monetary policy. For example, in mid-December 1997, still early in Korea's program, the Bank of Korea injected liquidity of about W 8 trillion, or more than one-third of reserve money at end-November 1997. In contrast to the Indonesian case, the authorities quickly sterilized this large injection.
The interpretation of such margins requires some caution, however. For example, rather than tighter-than-programmed central bank credit, the large NDA margins in Korea in fact reflect NIR developments. In general, accumulation of NIR through means other than exchange market intervention (for example, sovereign bond issues, or the repayment of foreign loans extended by the central bank, in excess of program assumptions) leaves reserve money unchanged, so that measured NDA contracts even with unchanged credit policy. If NDA ceilings are not adjusted downward for such contingencies, large margins can result.
Of course, these margins are also consistent with the interpretation that the de facto interest rate targets were set too high to be consistent with the reserve and broad money growth targets. Hence, it is essential also to examine the behavior of nominal and real interest rates, as is done later in the section.
See also Goldfajn and Baig (1998).
An analysis of ex post dollar rates of return indicates that realized returns were consistently negative from July 1997 in Thailand and September 1997 in Korea, but turned sharply positive in February 1998.
Another benchmark for policies is the contraction in real money needed to stabilize exchange rates in the face of an increase in risk premiums demanded by investors. IMF staff simulations suggest that, to have stabilized exchange rates in the face of an assumed 10 percentage point shock to the risk premium would have required contractions in the broad money/GDP ratio of 3 percent to 10 percent in 1997 relative to 1996. In contrast, as discussed below, real money balances continued to grow in the second half of 1997 in both Indonesia and Korea, although in Thailand they did decline in 1997 (by about 5 percent). A tightening of monetary conditions (as measured by real money balances) in Korea and Thailand starting in January 1998 was associated with greater nominal exchange rate stability. Real money also declined in Indonesia in the first quarter of 1998, but this was more a reflection of mounting inflation than of policy tightening.
Notably, in Indonesia the Balanced Budget Law prohibits domestic financing of a government deficit, which has contributed to stifling the development of a domestic government bond market. See, for example, Molho (1994).
Figure 6.5 shows the evolution of two real interest rate measures—the overnight and average lending rate, deflated by an estimate of contemporaneous CPI inflation. Whereas the CPI represents the real interest rate relevant to household, the wholesale price index (WPI) may be a better indicator of the real interest burden on manufacturers; the WPI increased more rapidly than the CPI in these countries, so the CPI-deflated interest rate if anything overstates the real interest burden. The lending rate shown is taken from the International Financial Statistics, and is not fully comparable across countries. (See Figure 6.5 for details.)
Appendix 6.1 reports ex ante real interest rates, based on a simple inflation forecasting model that relates CPI inflation to its own lag, and lagged changes in broad money and the exchange rate. The implied ex ante real interest rates are somewhat lower for Korea and Thailand, because actual inflation has been “unexpectedly” low (even in relation to the historically low exchange rate pass-through coefficients).
ForKorea, where inflation has been minimal and household saving has been increasing, the growth of real balances may reflect an increase in money demand. In Indonesia, however, it is more likely related to lags in the money-inflation relationship.
One caveat regarding the interpretation of these measured changes is that some of the increased credit reflected valuation changes affecting foreign-currency-denominated credit—a factor that was particularly important in Indonesia. The measure presented includes these valuation changes (consistent with the treatment of the effects of inflation) as they nonetheless affect the amount of real financing or real liquidity being provided to the economy. An alternative approach, based on credit flows, gives a different month-to-month pattern but does not greatly alter the overall picture.
In the classic example of the United States during the Great Depression, the nominal money stock fell by one-third (Lebergott, 1984).
Moreover, credit crunches have sometimes occurred in the absence of either a currency crisis or severe monetary policy tightening, for example, in the United States in 1990–91.
For simplicity, it is assumed that the shock to the risk premium occurs only in the first year. To the extent that the risk premium increase extends over several years, the current (or expected future) monetary contraction must be greater.
In terms of equation (1), this would be captured by an increase in the real exchange rate, ν, which would reflect higher inflation for a given nominal exchange rate.
References
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Domac, Ilker, and Giovanni Ferri, 1998, “The Real Impact of Financial Shocks: Evidence from Korea (unpublished; Washington: World Bank)
Enoch, Charles, and Anne-Marie Guide, 1997, “Making a Currency Board Operational,” IMF Paper on Policy Analysis and Assessment No. 97/10 (Washington: International Monetary Fund).
Furman, Jason, and Joseph Stiglitz, 1998, “Economic Crises: Evidence and Insights from East Asia,” paper prepared for the Brookings Panel on Economic Activity (Washington, November).
Ghosh, Atish R., Anne-Marie Guide, and Holger C. Wolf, 1998, “Currency Boards: The Ultimate Fix?” IMF Working Paper No. 98/8 (Washington: International Monetary Fund).
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Goldfajn, Ilan, and Taimur Baig, 1998, “Monetary Policy in the Aftermath of Currency Crises: The Case of Asia,” IMF Working Paper No. 98/170 (Washington: International Monetary Fund).
Goldfajn, Ilan, and Poonam Gupta, 1998, “Does Tight Monetary Policy Stabilize the Exchange Rate?” (unpublished; Washington: International Monetary Fund).
Kraay, Aardt, 1998, “Do High Interest Rates Defend Currencies During Speculative Attacks?” (unpublished; Washington: World Bank).
Lebergott, Stanley, 1984, The Americans: An Economic Record (New York: W.W. Norton).
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