Back Matter

### APPENDIX I

#### Decomposition of Exchange Market Pressure

In this appendix, EMP is shown to contain three elements, namely a money demand element, a money supply element, and a residual term that includes changes in both the bilateral real exchange rate and foreign (U.S.) inflation.42 On the demand side, the growth of real base money (mt) is:

$\begin{array}{ccc}{{m}}_{{t}}={{\mu }}_{{t}}-{{\pi }}_{{t}}& \phantom{\rule{7.0em}{0ex}}& \left({A}.1\right)\end{array}$

where μ = ΔM/M is the growth of nominal (base) money and π is the inflation rate (ΔP/P, where P is the domestic price level).18 The inflation rate is linked to world inflation πt* through the rate of nominal depreciation ɛ:

$\begin{array}{ccc}{{\epsilon }}_{{t}}={{\pi }}_{{t}}-{{\pi }}_{{t}}^{*}+{{z}}_{{t}}& \phantom{\rule{7.0em}{0ex}}& \left({A}.2\right)\end{array}$

where zt is the deviation from (bilateral) purchasing power parity. On the money supply side, the two components of nominal base money are international reserves and net domestic credit. That is,

$\begin{array}{ccc}{{\mu }}_{{t}}={{r}}_{{t}}+{{\delta }}_{{t}}& \phantom{\rule{7.0em}{0ex}}& \left({A}.3\right)\end{array}$

where δt is the change in net domestic credit scaled by the monetary base (ΔNDA/MB). Combining (4), (5), and (6), and rearranging, EMP is expressed as:

$\begin{array}{ccc}{\text{EMP}}_{{t}}\equiv {{\delta }}_{{t}}-{{m}}_{{t}}+{{\lambda }}_{{t}}& \phantom{\rule{7.0em}{0ex}}& \left({A}.4\right)\end{array}$

where ${{\lambda }}_{{t}}={{\pi }}_{{t}}^{*}+{{z}}_{{t}}$ may be thought of as a residual term that includes real exchange rate changes.

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The current version of this paper, as well as previous drafts, benefited from the input of Messrs. Adolfo Barajas, Stanley Black, Joshua Greene, Shigeru Iwata, Gene Leon, and Saleh M. Nsouli. Special thanks go to Mr. Enzo Croce for detailed suggestions. Mrs. Patricia Obando expertly and patiently formatted the document. The authors are responsible for all remaining errors.

According to Kaminsky and Reinhart (1999), the number of crises rose from about 2.6 per year during 1970–79 to about 3.1 per year from 1980 to 1995.

This idea is central to the traditional monetary approach to the balance of payments (see, for example Frenkel and Johnson (1976)).

See, among others, Kaminsky, Lizondo, and Reinhart (1997), Sachs, Tornell, and Velasco (1996), Tornell (1999), and Berg and others (2000).

There is no single definition of contagion. Some link contagion to certain market fundamentals, rather than irrational herd behavior by investors. For example, Eichengreen, Rose, and Wyploz (1996) and Rose and Glick (1998) link regional contagion to international trade. Also, Sachs, Tornell, and Velasco (1996) and Tornell (1999) develop models of contagion in which investors use fundamental variables to inform their speculation.

The implications of outflow sterilization have been incorporated into (modified) first generation models (see Flood and Marion (1998) and second generation of crisis models (including inter alia Flood, Garber, and Kramer (1996)). Several authors have suggested such a policy was implemented in both Mexico (Calvo and Mendoza (1996), Flood, Garber, and Kramer (1996)) and in the Asian countries (Tanner (2001)).

For example, several authors have recently attempted to ascertain the ability of policy makers to defend exchange rates with tight monetary policy, and specifically with high interest rates. See, among others, Goldfajn and Gupta (1999), Dekle, Hsiao, and Wang (1999), Gould and Kamin (2000), Kraay (1999), and Zettlemeyer (2000). This paper helps test a related proposition. However, this paper examines EMP rather than exchange rates. Other papers that use EMP or a similar continuous index include Girton and Roper (1977), Sachs, Tornell and Velasco (1996), Tornell (1999), Bussière and Mulder (1999), Ahluwalia (2000) and Tanner (2001). By contrast, other papers, including Eichengreeen, Rose, and Wyploz (1996), Kaminsky, Reinhart, and Lizondo (1997), and Kaminsky and Reinhart (1999) use EMP to construct discrete a crisis dummy variable (0 = no crisis, 1 = crisis). Van Rijckeghem and Weder (1999) use both. A continuous EMP variable, generally contains more information than a discrete crisis dummy. A continuous variable permits a comparison of the severity of crises to be compared, both over time within a given country and across countries.

This is Girton and Roper’s (1977) definition. As mentioned in the text, while other definitions are used in the literature, the one proposed here has certain desirable properties.

Most other research use broader measures of the money supply to measure the stance of monetary policy. For example, Kaminsky and Reinhart (1999) use a measure of excess M1 balances as an indicator, but they find it to be a noisy indicator. By contrast, this paper this paper uses a narrower measure, namely the domestic credit component of the monetary base (like earlier literature on the monetary approach of the balance of payments and a recent paper by Aziz, Caramazza, and Salgado (2000)).

The model is similar one to developed by Tanner (2001).

Weights are computed with 1995 nominal U.S. dollar GDP.

Choosing windows in this way provides data series long enough to calculate variances. But, crisis windows for different countries are identical, both troughs and recoveries may potentially be placed within the same window if crises occur sequentially. For this reason, other calculations that use shorter, country-specific windows for periods of peak EMP are also presented below. Nonetheless, in most cases that EMP is higher and more variable during the selected windows. An exception is Asian countries during the 1997–8 Asian crisis, where variance of EMP rises dramatically but mean falls since crises occurred sequentially.

Other recent papers, including Levy-Yeyati and Sturnzegger (1999), Fischer (2001), Hernandez and Montiel (2001), and Poirson (2001) have also developed measures of exchange market intervention, or effective (rather than stated) exchange rate regime.

And, unless INTIND is zero, it would not be appropriate to test for the effect of monetary policy on exchange rates, as do several recent papers (see Footnote 8).

Other papers that present models of EMP include Connolly and Da Silveira (1979) for Brazil, Brissimis and Leventakis (1984), for Greece, Weymark (1995), for Canada, Wohar and Lee (1992), for Korea, and Burkett and Richards (1993), for Paraguay. Several authors, including Sachs, Tornell and Velasco (1996), Tornell (1999), Bussière and Mulder (1999), Van Rijckeghem and Weder (1999) and Ahluwalia (2000) construct a variant of EMP for several countries. More recently, several papers have used EMP indirectly to construct a discrete crisis indicator. These include Eichengreen, Rose, and Wyplosz (1996) and Kaminsky, Lizondo, and Reinhart (1998).

Note that papers mentioned previously use a somewhat different weighting scheme. For these other measures, this interpretation may not apply.

Most often, the monetary aggregate is a broad measure but could also be narrow money or even the monetary base. Some recent work for the U.S. focuses on unborrowed reserves (see Bernanke and Mihov (1998). Christiano, Evans, and Eichenbaum (1998) compare these different measures of monetary policy and their ability to explain aggregate fluctuations. Note also that in some other papers in the currency crisis literature (for example Kaminsky and Reinhart (1999)) broader measures of money and/or credit are used. However, these broader measures are to a large extent market determined. By contrast, the narrower measure used here more accurately reflects policy decisions.

Importantly, if sterilized intervention occurs, central bank domestic credit may have an endogenous component, as noted by Darby (1980) and more recently by Zettlemeyer (2000). The model presented in Part III of this paper addresses this issue.

This argument also holds if domestic and U.S. dollar assets are imperfect substitutes. In this case, domestic interest rates reflect perceived risk and expected exchange depreciation. With more risk or higher expected devaluation, the marginal depositor must be compensated by higher domestic interest rates keep her funds onshore. To maintain the ex-ante interest rate target, the central bank adjusts domestic credit according to the demands of the banking system. Faced with external pressures, the interest rate targeted by the central bank may not be sufficiently high ex-post to prevent a capital outflow and a corresponding drain on the banking system’s liquid reserves. These points are formalized in Part III.

Of course, strains on a country’s external sector might also be measured by the differential between domestic and world interest rates. In this vein, Eichengreen, Rose, and Wyplosz (1996) construct an EMP measure that includes the interest differential. In Part III, EMP and interest differential are modeled jointly.

The precise months plotted may vary between countries, since related crises may occur in succession, as happened in Asia.

This appears to be true for example, during the TS period. At this time, WH countries with negative EMP (reserve inflows and/or exchange rate appreciation) like Colombia and Chile had tighter monetary policy, while monetary policy was looser in countries with higher EMP like Venezuela, and Bolivia. Note also that Argentina, while subject to a currency board, has a margin of discretion in monetary policy so long as the monetary base is fully backed by international reserves (that is, net domestic credit of the central bank is not positive).

Malaysia placed limits on credits from the domestic banking system in mid-1997. However, external capital controls were imposed in September 1998 after most of the foreign capital had left. For details, see Boorman et. al. (2000).

For industrialized countries, other studies that use a VAR methodology to examine monetary policy include Christiano and Eichenbaum (1992), Friedman and Kuttner (1992), Kashyap, Stien, and Wilcox (1993), and Bernanke and Mihov (1998).

Ceterus paribus, the interest differential determines whether the marginal dollar is invested inside or outside the country. For those cases where ϕ is nonstationary in levels but stationary in first differences, it is entered instead as Δϕ.

That is, the ordering of variables in a VAR is justified by certain assumptions. Also, the system will be just identified, thus permitting a simple Choleski decomposition to be used. Otherwise, a maximum-likelihood technique like that proposed by Bernanke (1986) would be required. And, alternative orderings, discussed below, yielded similar quantitative results.

A simple accounting example helps illustrate these points. Assume a fixed exchange rate and a legal minimum reserve requirement of 10 percent. Suppose further that deposits (and their cash counterpart) in the banking system drop by 100 units. Without any other change on the balance sheet, banks require a loan totaling 90 to maintain sufficient reserves. On the central banks balance sheet, the monetary base drops by 10 units. As a counterpart to the loan to banks, NDC increases by 90 units while NIR falls by 100 units.

That is, as the interest rate rises, banks demand less funding from the central bank and the private sector is willing to hold more government paper. Note that domestic assets are assumed to be imperfect substitutes for U.S. dollar assets. Hence an increase in ϕ causes the marginal investor to keep her funds onshore.

However, if a current expansion of credit signals a threat to the exchange rate regime and this information is not captured entirely in vE, we would expect the opposite sign: βϕδ > 0. Such an ambiguity about the sign of this coefficient reflects whether “liquidity effects” dominate “Fisher effects.”

As an empirical matter, fiscal policy is explicitly introduced later in the paper. Note also that these models incorporate an interest rate “Laffer Curve:” after some point, higher interest rates are counterproductive for defending the exchange rate, since the fiscal effect of higher interest rates (one that discourages foreign investors) dominates the supportive effects of increased holdings of international reserves by the central bank.

Malta and Romania were omitted since they lacked interest rate data.

The estimations were performed in the Regression Analysis of Time Series (RATS) package. For impulse response functions, standard errors and T-Statistics were computed using the method due to Kloek and Van Djik (1978).

To conserve space, only those cases whose IRF with T-statistics that equal or exceed |2.0| are presented graphically.

This result for Indonesia is reversed if a somewhat different definition for domestic credit δ (gross rather than net credit) is used; see Tanner (2001).

Specifically, they show that prior to an exchange rate crisis, but not after, the forward premium (FP) is a linear function of domestic credit: ∂FP/∂δ(D) > 0 for 0< D<D*, where D* is the level of domestic credit that precipitates an exchange rate crisis. Note that in this context, the implied forward premium is E{[(1+i)/(1+ius) - 1], where I and is are domestic and U.S. interest rates.Thus, for all D, ∂ϕ/∂δ = ∂FP/∂δ * (1+ius)/E.

And, some tests available from the authors reveal that, for some countries, parameter estimates do differ significantly differ between crisis and noncrisis periods.

There are other potential ways to pool the data. For example, individual crises periods for all countries, in some cases reaching back to the 1970s, was also tried. Qualitatively, results (available from the author) were similar to those reported here.

A similar result occurred in Tanner (2001), when data from six countries were pooled.

To maintain cross-country comparability, these estimates include only those countries for which monthly estimates of the general government surplus SUR are available from the IFS database.

Of course, system (4) may reveal other feedback relationships between fiscal policy, monetary policy, and interest rates. Such an analysis, however, is left for future research.

For simplicity, the model is expressed in continuous time. A discrete time formulation is somewhat more complicated. Also, the model may be easily expressed in terms of a trade-weighted or effective exchange rate.

Exchange Market Pressure, Currency Crises, and Monetary Policy: Additional Evidence From Emerging Markets
Author: Mr. Evan C Tanner