Back Matter
  • 1 https://isni.org/isni/0000000404811396, International Monetary Fund
  • | 2 https://isni.org/isni/0000000404811396, International Monetary Fund
  • | 3 https://isni.org/isni/0000000404811396, International Monetary Fund

Abstract

This paper explores the role of exchange rates in emerging economies with inflation-targeting regimes, an issue that has become especially germane during the current episode of financial turmoil and volatile capital flows. Under inflation targeting, the interest rate is the main monetary policy tool for influencing activity and inflation, and there is little agreement about the appropriate role of the exchange rate.The exchange rate is a more important monetary policy tool for emerging economies that have adopted inflation targeting than it is for inflation-targeting advanced economies. Inflation-targeting emerging economies generally have less flexible exchange rate arrangements and intervene more frequently in the foreign exchange market than their advanced economy counterparts. The enhanced role of the exchange rate reflects these economies' greater vulnerability to exchange rate shocks and their less developed financial markets. However, their sharper focus on the exchange rate may cause some confusion about the commitment of their central banks to achieve the inflation target and may also complicate policy implementation. Global inflation pressures, greater exchange rate volatility, and the financial stresses from the global financial turmoil that began in mid-2007 are heightening these tensions.

Appendix I

Table A1.1.

Intervention Practices of Inflation-Targeting Countries, Late 2007

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Frequency refers to how often interventions have taken place in the past three years.

Categorization as “developed,” “emerging,” or “shallow” is based on how a market is designated by financial market participants active in this market.

In June 2007, New Zealand intervened for the first time since the dollar was floated in 1985.

Table A1.2.

Intervention Practices of Emerging Economies with Other Anchors, Late 2007

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Frequency refers to how often interventions have taken place in the past three years.

Categorization as “developed,” “emerging,” or “shallow” is based on how the market is designated by financial market participants active in this market.

Appendix II The Small Open-Economy Model

The first part of this appendix describes the structure and calibration of the Small Open-Economy Model used in the analysis of alternative monetary policy frameworks. The second part reviews existing model-based analyses of hybrid inflation-targeting rules, and the third part describes the simulation methodology.

Model Structure

The model used in this paper to analyze alternative monetary policy rules is a fairly conventional New Keynesian open-economy model. These models embody a synthesis of the modeling approach of the real business cycle literature and micro foundations for Keynesian concepts.110 Such models have essentially neoclassical long-run characteristics—notably including monetary neutrality—but have Keynesian short-term characteristics which provide scope for monetary policy to affect the real economy over the short to medium term. However, such models are mostly founded on explicit micro foundations, making the underlying assumptions of the model more transparent and making them less vulnerable to the Lucas critique than more ad hoc reduced-form specifications.

The model used in this paper is deliberately conventional in the sense of drawing on standard micro foundations to derive the main behavioral equations. An important feature of the model is that it abstracts from the determination of the steady state of the economy as well as from permanent shocks that change the steady state. Inflation targeting focuses on the dynamics of the return to the steady state following macroeconomic disturbances.

The model includes several features that attempt to capture some characteristics of financially vulnerable emerging economies. These include:

  • Credit constraints limiting the degree of intertemporal arbitrage in consumption (following Amato and Laubach, 2003; and Galí, López-Salido, and Vallés, 2007), to reflect the relatively undeveloped domestic financial systems in many emerging economies; this is a procyclical component of aggregate demand, which is insensitive to the interest rate and has the potential to increase the reaction required of the central bank, introducing more volatility to exchange rates.

  • An endogenous risk premium (following Céspedes, Chang, and Velasco, 2004), increasing in external indebtedness and the exchange rate.

  • Allowance for perverse exchange rate effects on income (following Morón and Winkelried, 2005) to reflect adverse balance-sheet effects.

  • Allowance for different timing of exchange rate pass-through to costs and prices (Monacelli, 2004).

  • Inclusion of an exported natural resource, providing scope for terms of trade shocks.

  • Allowance to explicitly include movements in the exchange rate in the central bank policy reaction function (Cavoli and Rajan, 2006; and Kirsanova, Campbell, and Wren-Lewis, 2006).

  • Allowance to reflect weak policy credibility in more backward-looking inflation expectations and price formation (Erceg, Henderson, and Levin, 2000; and Argov and others, 2007).

The log-linearized equations included in the model are as follows:111

Aggregate Spending

Aggregate spending on the domestically produced good, y^td, is composed of domestic spending, c^t, plus exports, x^td:

y^td=c¯y¯dc^t+x¯dy¯dx^td(1)

where:

c¯/y¯dandx¯/y¯d represent the respective shares of consumption and expoirts in domestic output in the steady state.

A fraction, λ of domestic spending is by optimizing (Ricardian) consumers, c^t0, and the rest is by “rule-of-thumb” (non-Ricardian) consumers, c^tr:

c^t=λc^tr+(1λ)c^t0(2)

Spending by optimizing Ricardian consumers is derived from a standard separable utility function on consumption, Ct, and labor, Nt:

U(Ct,Nt)=(CtγCt1)1σ11σNtv(3)

where:

σ is the coefficient of relative risk aversion

γ is the degree of habit formation in consumption.

This introduces an element of inertia into consumption, and is a fairly standard feature of New Keynesia models.

The first-order conditions of utility maximization provide the Euler equation that guides consumption:

where:

c^t0=(γ1+γ)c^t10+(11+γ)c^t+10(1γ1+γ)1σ[(i^t)π^t+1](4)

i^t is the current nominal interest rate

π^t+1 is the inflation rate expected in period t+1.

Rule-of-thumb or non-Ricardian consumers do not smooth consumption through borrowing and lending. The lack of consumption smoothing may reflect limited access of some households to financial markets.112 As a consequence, for these consumers, spending is based on current income:

where:

c^tr=w^tp^t+n^t(5)

ŵt is the nominal wage rate per unit of work a supplied

P^t is the price level

n^t is the number of units of work supplied.

In addition to domestic demand, there is also foreign demand for the domestically produced good, x^td. Export demand depends on foreign real income and the real exchange rate:

x^td=ρxdy^t1d+(1ρ)[τq^t+y^t*](6)

where:

y^t*is foreign real income

q^t is the real exchange rate (the real cost of foreign currency)

ρxd is the degree of persistence in domestically-produced exports

τ is the exchange rate elasticity of demand for domestically-produced exports.

Aggregate Production

Output in the economy consists of two types of goods. One is a composite good produced by monopolistically competitive firms using labor and imported goods as inputs. This good is both consumed domestically and exported. The second is a natural endowment commodity which is exported.

The composite good is produced using a CES production technology with inputs of labor and an imported input. This production function is particularly convenient because of its generality, given that it embeds a Cobb-Douglas or even a Leontief technology, depending on the size of the elasticity of input substitution chosen:

y=At[αItσs1σs+(1α)Ntσs1σs]σsσs1(7)

where:

σs is the elasticity of substitution in production

It is the imported intermediate input

Nt is the labor input

α is the share of the imported good in production—the openness of the economy

At is total factor productivity.

Production costs reflect the costs of the labor and the imported inputs, as well as labor. The real cost of imported inputs is determined by the real exchange rate, q^t, while the real wage, (w^tp^t), is determined by the equilibration of producers’ demand for labor, n^t, with the supply of labor by households. The supply of labor is derived from maximization of utility in Equation (3)113 by both types of consumers. Aggregate supply depends positively on real wage and negatively on consumption. This is a typical result obtained from the first order condition with respect to labor of separable utility functions:

n^t=1(v1){(w^tp^t)σ[(11γ)c^t(γ1γ)c^t1]}(8)

where:

v is the coefficient of disutility of labor.

With the production technology specified in Equation (7), the real marginal cost of production, m^crR, is given by:

m^crR=(1α)σs(w^tp^t)+ασsq^t[(1α)σs+ασs]α^t(9)

where:

ŵt is the nominal wage rate per unit of work supplied

p^t is the price level q^t is the real exchange rate (the real cost of foreign currency)

α^t is the (log) deviation of At from its steady state value.

Equation (9) shows that the more open the economy, the larger the impact of exchange rate movements on production costs and inflation. The elasticity of substitution in production also plays an important role: the lower the possibility of substituting domestic labor for imported inputs, the larger the impact of an exchange rate movement on costs.

Production of the second endowment type good, x^tCM, is essentially exogenous and is completely exported. The amount produced of this commodity does not react to its price, and the requirement of local inputs to its production is negligible. Its value depends on the real exchange rate and its price, p¯tCM, abroad, which is given by international markets. Consequently, the value of production is determined as:

x^tCM=q^t+p^tCM(10)

Firms set the price of output for the domestic market in one of two ways. One group of firms, accounting for a fraction, μ of sales of the domestic good, follows a simple, backward-looking approach to adjusting their prices.114 In effect, this leads to an element of indexation of prices, generating persistence in inflation. Another group of price-setters takes a forward-looking optimization approach to price setting but only adjust their prices periodically, à la Calvo. In any given period, it is assumed that only a fraction, (1-8), of the optimizing firms adjust their prices. The backward-looking component of price setting can be motivated by uncertainty regarding the central bank’s inflation objective (Erceg, Henderson, and Levin, 2000) or limited credibility of the policy framework (Argov and others, 2007). In both cases, agents will tend to place a greater weight on recent inflation outcomes in forming inflation expectations than otherwise.

Taking these considerations into account, the aggregate inflation rate in the economy will be summarized by a New Keynesian Phillips curve of the form:

π^t=(β1+βμ)π^t1+(μ1+βμ)π^t1+(φ1+βμ)m^crR(11)

where:

β is the subjective rate of time preference

μ is the proportion of price adjustment based on a simple indexation formula, φ=1θθ(1βθ), where (1-θ) is the average frequency of price adjustment by optimizing firms

m^crR is the real marginal cost of production.

This Phillips curve has three elements. The first is an expected inflation component. This reflects the assumption that firms adjust their prices periodically rather than continuously, so that when prices are adjusted, firms take into account the expected evolution of inflation. The second term is a lagged inflation component reflecting the indexation applied to a fraction, μ of prices. The third term reflects the incorporation of marginal costs into optimizing firms’ prices. Exchange rate movements feed into inflation through their impact on marginal costs. The speed of pass-through into inflation depends both on the proportion of optimizing firms and on the average frequency of price adjustments.

Exchange Rate Determination

The real exchange rate is assumed to be determined by the real uncovered interest parity condition, together with a risk premium:

q^t=q^t+1+[i^t*π^t+1*][i^tπ^t+1]+φ^t(12)

where:

q^t=s^t+p^t*p^t is the real exchange rate t is the spot price of foreign exchange and p^t* is the foreign price level)

i^t*is the foreign nominal interest rate

π^t+1* is the expected foreign inflation rate

φ^t is the risk premium.

Following Céspedes, Chang, and Velasco (2004), the risk premium, φ^t , depends on debt, the exchange rate, and GDP:115

φ^t=φ0(b^t+1*y^t)φ1(x¯dx¯d+x¯cmx¯td+(x¯cmx¯d+x¯cm1)q^t)(13)+φ2(I^t)+φ3(q^t)

where:

  • (b^t+1*y^t) is the projected external debt-to-GDP ratio.

  • The risk premium consists of four elements:

  • The first term in the equation, φ0(b^t+1*y^t), says that the risk premium is an increasing function of the ratio of external debt to GDP. This friction in the international capital markets is required to ensure stationarity of the external debt-to-GDP ratio.116

  • The second and third terms, φ1(x¯dx¯d+x¯cmx¯td+(x¯cmx¯d+x¯cm1)q^t)+φ1(I^t), relate the risk premium negatively to exports and positively to imports, so that a weakening of the current account raises the risk premium.

  • The last term, φ3(q^t), captures the adverse impact of currency depreciation on the domestic currency value of external debt—the balance sheet effect. As the debt service burden on borrowers rises, the risk premium increases. For a financially vulnerable economy, the adverse impact of depreciation through the balance sheet effect must outweigh the beneficial effects of depreciation on the current account so that depreciation has a net harmful effect on activity. This imposes restrictions on the values of the parameters in the risk premium equation.117

Monetary Policy

Monetary policy is described by the alternative reaction functions presented in the main text.

Equilibrium Identities

Total output of the economy is the sum of the domestic consumption and exports of the domestically produced good, together with the exports of the exported endowment commodity:

y^t=c¯y¯c^t+x¯dy¯x^t+x¯CMy¯x^tCM(14)

where:

c¯/y¯,x¯d/y¯,andx¯CM/y¯ are shares of consumption, exports of domestically produced goods, and exports of the endowment commodity in total production.

The balance of payments or economy-wide constraint is built adding up the consumer, government, and firm resource constraints:

c¯y¯c^t=y^tαyy¯dy¯(I^t+q^t)(15)+b¯y¯1(1+i^*)φ[πt+1*+b^t+1*(q^t+1q^t)(1+t^t*)φt]b¯*y¯b^t*

The net change in foreign debt should be equal to the current account, which is composed of the trade balance and interest payments abroad.

Model Calibration

Differences in the calibration of the financially robust advanced and the financially vulnerable emerging economies are shown in Table A2.1 and reflect the following considerations:

  • Domestic financial development. In the emerging economy, the share of “rule-of-thumb spending” based on current income is set at 30 percent, compared to 0 percent in the advanced economy, to reflect limited access of agents to borrowing opportunities and greater use of quantitative credit rationing rather than use of retail interest rates. Better access to borrowing and saving opportunities in advanced economies is also reflected in higher persistence in spending behavior, with the persistence coefficient set at 0.5 versus 0.3 in emerging economies.

  • External financial constraints. More limited capital mobility and international asset substitutability in vulnerable emerging economies is reflected in: (1) a risk premium with a substantially higher coefficient related to the level of the external debt-to-GDP ratio (0.05 compared to 0.01 for the advanced economy (based on Schmidt-Grohé and Uribe, 2003)); and (2) a higher coefficient on the current account balance (0.3 compared to 0.2 for the advanced economy).118 In addition, the balance sheet vulnerability of the emerging economy is reflected in a much higher elasticity of the risk premium with respect to exchange rate movements than in the advanced economy (0.5 compared to 0.05).

Table A2.1.

Parameter Calibration of the Advanced and Emerging Economy Models

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A crucial implication of these parameter configurations is that currency depreciation in the financially robust advanced economy will be expansionary as the stimulus to net exports will outweigh any adverse balance sheet effects. In contrast, currency depreciation has a net contractionary effect in the vulnerable emerging economy as the stimulus to net exports is more than offset by the adverse impact on balance sheets and, consequently, on consumption and investment.

  • Openness. The share of imports in production rather than GDP (following McCallum, 2006) is set at 25 percent for the advanced economy and at 30 percent for the emerging economy, consistent with international evidence.

  • Policy credibility. In the robust advanced economy, price formation is based on a purely forward-looking approach to formation inflation expectations (μ= 0). Implicitly, this assumes that agents know and believe the central bank’s policy rule. In the emerging economy, price formation is assumed to be much more backward looking (μ = 0.8), reflecting limited credibility of the central bank’s commitment to an inflation objective (following Rudebusch and Svensson, 1998; Erceg, Henderson, and Levin, 2000; and Argov and others, 2007).

Evidence on the Performance of Alternative Frameworks

This section reports the performance of alternative hybrid monetary policy rules in financially robust advanced and financially vulnerable emerging economies. It reviews existing model-based analyses of hybrid rules and then discusses the simulations and findings using the model described above.

Existing Studies of Hybrid Policy Rules

Taylor (2001) reviews the limited number of studies that had looked at the issue of whether it would be appropriate to take the exchange rate explicitly into account in monetary policy in an open economy.119 He concludes there was little evidence that including a systematic response to exchange rate movements would improve macroeconomic performance, even in an open economy. He attributes this to two principal factors: (1) even in the plain vanilla framework, monetary policy already responds to the indirect impact of exchange rate movements on output and inflation, and (2) the appropriate response to exchange rate movements should depend on the cause of the movement. He suggests that adding a mechanistic response to exchange rate movements in the policy reaction function could worsen performance, depending on the typical array of shocks affecting the economy. Both Taylor (2000) and Mishkin (2000), however, recognize that more research is needed in this area before any strong conclusions can be drawn.

More recent research has begun to examine whether differences in economic and financial structure between emerging and more advanced economies may explain the “fear of floating” evident in many emerging and developing economies and may justify including systematic dampening of exchange rate movements in the central bank policy reaction function.120 Below is a brief summary of some of the main findings for each of the hybrid inflation-targeting exchange rate frameworks.

Open-Economy Inflation Targeting

Model-based analyses generally find little benefit from including the exchange rate in the monetary policy reaction function. Indeed, several studies argue that including the exchange rate worsens macroeconomic performance. However, in some other studies, including the exchange rate in the reaction function is found to be beneficial if the economy is financially fragile or if the central bank is very uncertain of how the exchange rate is determined:

  • Céspedes, Chang, and Velasco (2004) consider the impact of exchange rate movements in economies with a high degree of dollarization and constrained access to international borrowing opportunities. In such circumstances, exchange rate movements can give rise to strong balance sheet effects opposite to the normal competitiveness effects of exchange rate movements. Which effect dominates depends on each country’s situation. However, the authors find that exchange rate flexibility outperforms a fixed exchange rate regime.

  • Morón and Winkelried (2005) compare optimal hybrid reaction functions in financially vulnerable and financially robust economies. In general, the optimized rules for a vulnerable economy place much less weight on smoothing output and more weight on dampening exchange rates than in a robust economy. The analysis does not directly compare the performance of such hybrid rules against otherwise similar rules excluding exchange rate terms. Nonetheless, the finding that some exchange rate smoothing is involved in the optimal rules appears to imply that rules excluding exchange rate smoothing perform less well in minimizing inflation or output volatility or both. It is not clear, however, why some exchange rate smoothing appears optimal for both the vulnerable and robust economies.

  • Cavoli and Rajan (2006) compare variations on plain vanilla and hybrid Taylor rules for a financially vulnerable economy (calibrated to the Thai economy). Key results of interest are that: (1) in optimally weighted, open-economy Taylor rules (including an exchange rate term), the optimal weight on the exchange rate is low; (2) open-economy Taylor rules may well lead to greater macroeconomic volatility than plain vanilla Taylor rules; and (3) the emphasis put on the level of the real exchange rate versus changes in the exchange rate has important consequences for macroeconomic outcomes. It is not clear, however, whether these results would carry over to a model with more forward-looking behavior, including more forward-looking policy formulation.

  • Batini, Levine, and Pearlman (2007), using a calibrated model of the Peruvian economy with dollarization and financial “frictions,” compare fixed and flexible exchange rate regimes. They find that a fixed exchange rate delivers much poorer performance. They conclude that, because dollarization weakens the output gap channel of transmission relative to the exchange rate channel, nothing should be done to limit the flexibility of the exchange rate in order to achieve the inflation target.

  • Ravenna and Natalucci (2008) use a model loosely calibrated to the transition economies of Eastern Europe to examine the implications of the Balassa-Samuelson effect. They find that when the economy is experiencing a prolonged period of more rapid productivity growth in the tradables than in the non-tradables sector, macroeconomic performance is much better with a flexible exchange rate than with a rule involving a high degree of exchange rate management.

  • Leitemo and Söderstöm (2005) and Wollmershäuser (2006) both consider the performance of alternative policy rules when there is uncertainty surrounding the determination of the exchange rate. Although not specifically an emerging economy issue, uncertainty about the determination of the exchange rate may be even greater in such economies than in more advanced economies. The authors of both papers find a small gain from including the exchange rate in the reaction function when there is no uncertainty about exchange rate determination. However, when uncertainties are introduced, Leitemo and Söderstöm find that a Taylor rule is slightly more robust than an open-economy rule, while Wollmershäuser finds that open-economy rules are more robust to a wider range of exchange rate uncertainties.

Table A2.2.

Reaction Function Coefficients

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Inflation Targeting with an Exchange Rate Band

It is unclear how well this type of framework compares with a more conventional inflation-targeting framework in terms of macroeconomic performance:

  • Lahiri and Végh (2001) suggest that an exchange rate band may be appropriate if nominal exchange rate movements and higher interest rates have output costs and if intervention is costly. In such circumstances, a fairly free float within an exchange rate band may be optimal, at least in response to some kinds of shocks.

  • Morón and Winkelried (2005) examine such a policy in their model of a financially vulnerable economy and find that it tends to outperform a policy involving a more linear response to exchange rate movements. The authors note, however, that the analysis fails to take into account the impact that limiting exchange rate movements will have on the behavior of economic agents. In particular, if the central bank limits the range of exchange rate movement, this could encourage agents to increase their foreign currency liabilities, accentuating the vulnerability of the economy. This would make the economy particularly vulnerable to real shocks shifting the equilibrium real exchange rate.

Exchange-Rate-Based Inflation Targeting

McCallum (2006) compares the performances of plain vanilla and exchange-rate-based approaches to inflation targeting in an economy with varying degrees of openness. The first key finding is that, as the degree of openness increases, an exchange-rate-based approach to inflation targeting does much better than the standard interest-rate-based approach in stabilizing output, with no adverse consequences for inflation variability. The second key finding is that, in the interest-rate-based approach, the variability of the interest rate is low while that of the exchange rate is high, whereas in the exchange rate-based approach, the opposite occurs. These results suggest, broadly, that in a very open economy, smoothing the exchange rate rather than interest rates may contribute to reducing output volatility.

Simulation Method

Construction of Volatility Tradeoff Frontiers

The volatility trade-off frontiers shown in the main text are constructed as follows:

  • For each of the two types of country models, 10 variants of each alternative policy reaction function were constructed, each with a slightly different weighting on the inflation and output objectives, as shown in Table A2.2. The sum of the coefficients on the two objectives was held constant, as were the coefficients on the exchange rate objective and the lagged instrument term.

  • Each country model, with each variation of the parameterization of the alternative policy rules, is then simulated in response to each of three kinds of shocks: demand, cost-push, and risk premium shocks.

  • Each simulation involves a 200-period run. In each period, the model is subjected to a shock drawn from a normal distribution.121 For each kind of shock, the 200-period simulation is replicated 50 times.122

  • These simulations provide 50 time series with 200 observations for each kind of shock, each policy rule variant, and each of the 29 endogenous variables. Of these, the variables of most interest are inflation, output, the interest rate, the exchange rate, and the current account balance. The standard deviation of the time series for each variable is then computed, between the 100th and 120th observation, and then averaged over each of the 50 replications to produce a representative standard deviation for each variable in response to each kind of shock and policy variant.123

The same kind of simulation exercises could be carried out for variations of the weight of the exchange rate objective as opposed to the output, inflation, or instrument-smoothing objective. In this analysis, however, inflation and output smoothing are considered to be the ultimate objectives of monetary policy, whereas smoothing of the policy instrument or an exchange rate objective is to be evaluated in terms of their performance in achieving the foremost policy objectives.

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