Mauritius: Selected Issues and Statistical Appendix

International Monetary Fund

doi:10.5089/9781451827804.002.A004

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Mauritius: Selected Issues and Statistical Appendix

Author: International Monetary Fund

Publication Date:: 09 Aug 2005

eISBN:: 9781451827804

Language:: English

Keywords:: ISCR; CR; worker; Mauritius; bond market; inflation targeting regime; inflation expectation; inflation targeting framework; BOM bill; objectives of the BOM; Inflation; Real exchange rates; Foreign exchange intervention; Short term interest rates

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This Selected Issues paper and Statistical Appendix provide background information and analytical support for key policy issues discussed in the 2004 Article IV Consultation discussions with Mauritius. The impact of the erosion of trade preferences on exports, growth, and employment is assessed under two scenarios—a moderate and an extreme scenario. To quantify the adverse impact of trade liberalization, the paper estimates various elasticities of GDP growth to exports, and unemployment to growth. The paper also analyzes the labor market institutions and low-skilled employment in Mauritius.

Abstract

IV. Inflation Targeting in Small Open Economies: The Mauritius²¹

A. Introduction

79. Along with remarkable economic growth and diversification, Mauritius has also achieved low and stable inflation. Inflation (year-on-year) fell from around 8 percent in mid-1996, when Mauritius introduced its current informal inflation targeting regime, to around 4 percent in the year to March 2004 (Figure IV.1).²² Over the same period, output growth was high—averaging more than 5 percent per year—at rates comparable with those of the former Asian tigers. Therefore, Mauritius’s informal inflation targeting regime has, so far, been associated with a decline in inflation. Nonetheless, as this success has been won during a period of relatively subdued inflation worldwide, a true test of its inflation targeting regime will come if global inflation picks up in the future.

80. Mauritius’s institutional environment suggests that inflation targeting could be successful there. Mauritius has a long tradition of strong independent public institutions, and although it has relatively high government debt (estimated at almost 60 per cent of GDP in 2003/04), it has moderate (and declining) external debt.²³ The government has no history of extensively borrowing from the central bank, and is actively reducing its budget deficit.⁴ In addition, Mauritius has both a highly developed (on-shore and off-share) banking sector, as well as a primary dealer’s network to facilitate the trade in treasury bills. Although the central bank is not technically independent, the government has maintained “arms-length” transactions with the bank. Moreover, its central statistical office produces good and timely macroeconomic data. These factors are important prerequisites for the central bank to establish the credibility required for inflation targeting.²⁵

81. This paper investigates Mauritius’s experience with inflation targeting and finds that inflation targeting has been associated with a fall in inflation, principally through the anchoring of expectations. A series of financial sector deregulation measures in the 1980s and 1990s set the stage for the Bank of Mauritius (BOM) to pursue informal inflation targeting, through a de facto public commitment to low (CPI) inflation in the mid-1990s. Interestingly, this informal inflation targeting occurred against the backdrop of a managed (although relatively flexible) exchange rate. While the BOM’s informal inflation targeting seems to have been generally successful, it took the BOM some time to earn the credibility required to anchor lower inflationary expectations.

82. Mauritius’s favorable experience jointly managing an informal inflation target and a managed exchange rate could provide a useful policy example for other small open island economies. In attempts to provide credible nominal anchors, many small island economies have chosen hard pegs (through dollarization, monetary union, currency boards, and fixed pegs without bands). However, hard pegs can easily reduce an economy’s flexibility in the face of real and external shocks, running the risk of overvaluation, and possibly resulting in balance of payments difficulties. For example, the countries of the Eastern Caribbean Currency Union (ECCU) are facing balance of payments adjustment challenges in the context of trade liberalization and the loss of trade preferences.²⁶ Mauritius’s experience provides a “practical” example of a small island economy—with strong institutions and a lack of fiscal dominance—that has controlled inflation by using inflation targeting as a nominal anchor.

83. Mauritius’s experience may also provide an interesting case to compare with the recommendations of the theoretical literature on inflation targeting. Some studies have suggested that including the prices of tradables in an inflation target may lead to policy responses that generate large output volatility (Ball, 1999; Svensson, 2000; Dennis, 2001).²⁷ Mauritius’s successful targeting of aggregate CPI inflation suggests that these concerns may be overstated. Not only is aggregate CPI inflation a more transparent target than “domestic” inflation, Mauritius’s experience suggests that by focusing expectations, successful inflation targeting may be able to influence the pace and extent of pass-through, thereby limiting the damage to the nontradables sector.²⁸ Moreover, by conducting monetary policy (indirectly) through the interest rate, at the same time as managing the exchange rate, the BOM has effectively followed Ball’s (1999) recommendation that small open economies should conduct policy through some form of Monetary Condition Index (MCI) (based on both the interest rate and the real exchange rate).

84. The methodology used to investigate the informal inflation targeting framework is based on a new open economy macrofinance model that combines a no-arbitrage finance specification of the term structure, with a standard open economy empirical macroeconomic model. This allows the explicit modeling of the yield curve in a way that permits interactions between the macro economy and bond yields. While this paper’s framework is similar to that of Hördahl, Tristani, and Vestin (2003) and Rudebusch and Wu (2003), it is the first to extend the framework to a small open economy.

85. This approach has several strengths: (i) it exploits information on the maturity structure of interest rates, leading to a direct link between policy interest rates and the longer-term interest rates that influence real activity and inflation; (ii) it separates the effects of the level and slope of the yield curve on activity and inflation; and (iii) it provides a direct link between inflationary expectations and the target inflation rate. This last aspect is especially useful, since it allows an investigation of the degree to which inflationary expectations have been anchored over the inflation targeting period.

86. This paper is organized as follows: Section B describes the development of inflation targeting in Mauritius, including the main components of its inflation targeting framework. Section C introduces the macrofinance open economy model; Section D discusses the estimation of this model; while Section E describes the implicit behavior of inflationary expectations. Section F concludes.

B. Development of Inflation Targeting

A brief history of monetary policy

87. This section briefly describes the history of monetary policy implementation in Mauritius. The BOM was established as the central bank with the passage of the Bank of Mauritius Act in 1967. This enabled the BOM to act as the lender of last resort, as well as be the banker of the government. The powers of the BOM were further enhanced in 197l, when it was granted wide supervisory powers over banks, and given the authority to issue bank prudential regulations.

88. Prior to the 1990s, the BOM conducted monetary policy mainly through direct instruments, such as ceilings on commercial bank credit and administered interest rates. However, the financial reforms in the late 1980s brought some liberalization of exchange controls on both current and capital transactions.²⁹ The liberalization of capital controls, and the establishment of an interbank foreign exchange market were completed in 1994. The basket-peg regime was replaced with a more flexible exchange regime, although limited intervention continued. Reflecting the emphasis of monetary policy on exchange rates during this period, annual inflation averaged close to 9 percent over the years between 1989 and 1993, and was also considerably volatile. Credit ceilings were also abolished in July 1993.

89. In line with the liberalization of the financial sector and exchange rate, the BOM reconsidered its monetary operations and objectives in the 1990s. The BOM began conducting monetary policy through open market operations—in weekly treasury bill auctions—from 1991. The gradual floating of the exchange rate that commenced in 1994, required the BOM to choose a new nominal anchor. As a result, in 1996 the BOM introduced informal inflation targeting, while maintaining its intervention in the foreign exchange market.

90. This liberalization has allowed Mauritius to develop a relatively large and comprehensive domestic financial system and a growing offshore sector. The domestic banking system is sound and profitable. The basic financial sector infrastructure, such as payment, securities trading and settlement systems, is modern and efficient. There is also a primary dealers network to facilitate the trade in government securities. However, the development of the corporate capital market has lagged behind that of the banking sector.

Inflation targeting framework

91. Mauritius’s informal inflation targeting regime encompasses five main elements: (1) the public announcement of an annual target for aggregate inflation (CPI inflation) instead of nontradable inflation; (2) an express commitment to price stability as the primary goal of monetary policy; (3) an integrated operational strategy in which many variables, including foreign exchange intervention, are used to set the monetary policy instruments, while maintaining the managed float of the exchange rate regime; (4) a flexible monetary policy rule in which interest rate smoothing, inflation expectation, real exchange rate and output gap are included; and (5) transparent monetary policy operations. Therefore, although its inflation targeting regime is “informal,” its regime encompasses the main elements required for formal inflation targeting (Mishkin, 2004).

Public announcement of aggregate inflation targets

92. The BOM began announcing an aggregate inflation target in its 1996/97 (June-July) annual report. The BOM pursued a very gradual approach to lowering its inflation objectives. It began with targets of over 8 percent for 1996/97, and gradually lowered them to 4 percent—see Table IV.1. This gradualist strategy allowed the BOM to establish solid credibility in managing inflation by allowing the public to observe the achievement of a sequence of realistic targets. However, the BOM mainly gets its annual inflation target based on the available inflation expectation information. For example, the BOM increased its target from 6 percent in 1997/98 to 8 percent in 1998/99, so that it can accommodate the strong inflation expectation at that time and therefore preserve the credibility of inflation targeting.

Table IV.1.

CPI Inflation Targets and Outcomes

De facto commitment to price stability

93. The original Bank of Mauritius Act established the BOM to “safeguard the internal and external value of the currency of Mauritius and its internal convertibility,” and to “direct its policy toward achieving monetary conditions conducive to strengthening the economic activity and prosperity of Mauritius.” The 1988 amendment of this Act granted the BOM the responsibility for the formulation and execution of monetary policy consistent with price stability. Even though price stability was not established as the BOM’s overriding objective, the BOM has increasingly focused on this objective, and has declared its commitment to achieving this goal since 1996. In a number of speeches, the governor of the BOM has made it clear that price stability is the primary goal of the BOM. Nonetheless, the BOM also remains concerned about economic growth and competitiveness of the economy.

An integrated operational strategy

94. As in many emerging market countries, Mauritius’s secondary government bond market is relatively illiquid and underdeveloped. Therefore, the BOM cannot easily target short-term interest rates directly through open market operations in this market. As an alternative, the BOM has used a mix of integrated policy instruments to target short-term interest rates indirectly, including through the primary government bond market. Underlying its choice of settings for these instruments is the BOM’s detailed and information-inclusive reserve money program. The BOM publicly announced the existence of its reserve money program for liquidity management and forecasting purposes in 1996. The main objective of this is to maintain the monetary base on a path consistent with the BOM’s inflation target, and the Central Statistical Office’s economic growth forecast. However, as the BOM has found it difficult to achieve its reserve money target, it has never announced its reserve money and associated M2 targets.

Open market operations

95. The BOM has increasingly relied on short-term interest rates as its operational target, despite maintaining the reserve money target as a complementary operational target. In the primary government bond market, treasury (or, more recently, the BOM) bills of 3-, 6-, 12- and 24-month maturities are sold at weekly auctions.³⁰ This has tended to produce fairly stable yield curves, with the resulting price discovery likely to be relatively efficient. These auctions have been used to implement the reserve money program.³¹

The BOM varies its sales of treasury and BOM bills in the primary market auction in order to influence the level of liquid reserves held by commercial banks. While the amount of treasury bills sold at the weekly auction is guided by the reserve money program, the interest rates resulting from these auctions have been used as an indicator of the stance of monetary policy.
Repurchase transactions (repo) and reverse repo operations have also been used periodically since 1999 for fine tuning, complementing the primary auction of treasury bills.
The BOM’s secondary market cell (a portfolio of treasury bills) is occasionally employed in secondary market trading, allowing market participants to adjust their liquidity between the weekly primary auctions.

The signaling role of interest rates

96. As the lender of last resort, the BOM provides a Lombard facility where banks can borrow overnight to meet reserve requirements. The BOM mainly uses the Lombard rate to signal the stance of monetary policy, since the market generally seems to have adjusted its rates in line with movements in the Lombard rate in the past. However, with the money market rate currently much lower than the Lombard rate, this facility has not been used extensively in recent times.

Foreign exchange intervention

97. The BOM has gradually reduced its foreign exchange intervention, and has always denied any predetermined target path for the real exchange rate. For example, the BOM’s 2002 Annual Report only specifies that it aims at “reflecting the macroeconomic fundamentals of the country” (statement of the Governor, page 7), although the level of the real exchange rate has remained roughly unchanged throughout the inflation targeting period—see Figure IV.2. To keep its foreign exchange market interventions consistent with its inflation target, the BOM integrates its foreign exchange market interventions into its open market operations through its reserve money program. However, as its inflation targeting regime has increasingly gained credibility, the BOM has tended to reduce its intervention in the foreign exchange market—see Table IV.2. This reduction should further strengthen the BOM’s credibility in anchoring aggregate inflation expectation. However, given Mauritius’s very thin foreign exchange market, some intervention may remain necessary to smooth volatility.

Table IV.2.

Bank of Mauritius Foreign Exchange Market Intervention, 1996/97-2003/04

(In millions of U.S. dollars)

Source: Bank of Mauritius Annual Reports.

Table IV.2.

Bank of Mauritius Foreign Exchange Market Intervention, 1996/97-2003/04

(In millions of U.S. dollars)

	1996/97	1997/98	1998/99	1999/00	2000/01	2001/02	2002/03	2003/04
Sale	392.1	252.4	126.6	94.0	118.3	19.0	0	0
Purchase	38.9	37.0	11.0	15.7	0	21.1	189.0	68.0

Source: Bank of Mauritius Annual Reports.

Table IV.2.

Bank of Mauritius Foreign Exchange Market Intervention, 1996/97-2003/04

(In millions of U.S. dollars)

	1996/97	1997/98	1998/99	1999/00	2000/01	2001/02	2002/03	2003/04
Sale	392.1	252.4	126.6	94.0	118.3	19.0	0	0
Purchase	38.9	37.0	11.0	15.7	0	21.1	189.0	68.0

Source: Bank of Mauritius Annual Reports.

A flexible monetary policy rule

98. The main focus of the BOM’s implicit monetary policy rule is targeting inflationary expectations. However, the BOM clearly places some weight on the exchange rate. The 2001 BOM Annual Report stated that “the basic thrust of monetary policy continued to be directed toward the achievement of low inflation and a stable exchange rate” (statement from the Governor, page 6). This makes its rule similar to Ball’s (1999) MCI—based on both the interest rate and the exchange rate. In addition, current inflation and output (gap) also influence policy (and the setting of the MCI) through the reserve money program.

Transparent monetary policy operations

99. The transparent operation of monetary policy has benefited from frequent consultations between the BOM and commercial banks, as well as public statements by its Governor. Commercial banks seem generally satisfied with their frequent dialogue with the BOM. The BOM also maintains an informative website, publishes a comprehensive annual report and a comprehensive monthly statistical monetary bulletin, and has a relatively open policy towards, the media. The introduction of the Lombard facility, and the framework for repurchase and reverse repurchase transactions, were designed to increase transparency further.

C. An Open Economy Macrofinance Model

100. This section formally investigates the informal inflation targeting framework described above. To do this, a macrofinance model (similar to that of Hördahl, Tristani, and Vestin (2003), and Rudebusch and Wu (2003)), is combined with an empirical open economy model (similar to that of Svensson, 2000). This model integrates open economy macroeconomic and financial models, combining an affine model of the term structure (which imposes no-arbitrage constraints), with an open economy, new Keynesian model, where monetary policy is represented by a simple interest rate rule. By using the yield curve to extract inflation expectations, new information can be brought to bear on the performance of inflation targeting.

101. A relatively standard new-Keynesian representation of aggregate demand in an open economy is of the form:³²

\begin{matrix} y_{t} = μ_{y} E_{t} y_{t + 1} + (1 - μ_{y}) ⌊ β_{y 1} y_{t - 1} + β_{y 2} y_{t - 2} ⌋ + β_{q y} q_{t - 1} - β_{r} (i_{t - 1} - L_{t - 1}) + ɛ_{y t} & (1) \end{matrix}

where y_t is output gap, E_ty_t+1 is the expected output gap at time t, q_t is real exchange rate, i_t is the short-term interest rate, and ε_yt ͠ N(0, σ_y) represents real demand shocks. The latent factor, L_t, represents the level of yield curves and is typically interpreted as the underlying rate of inflation (see Rudebusch and W_u, 2003). Consistent with this interpretation, L_t may be viewed as the inflation rate targeted by the central bank, and, ultimately, as the inflation rate expected by private agents. These expectations play a very important role in the context of Mauritius’s annual centralized wage determination system, since they provide a focal point for the behavior of wage- and price-setters.³³ A depreciation of the real exchange rate also leads to an expansion in output with a lag, through its effects on net exports. The parameter μ_y measures the relative importance of the expected future output gap.

102. Agents are assumed to gradually modify their views about inflationary expectations, as represented by L_t, with actual inflation according to

\begin{matrix} L_{t} = ρ_{L} L_{t - 1} + (1 - ρ_{L}) π_{t} + ɛ_{L t}, & (2) \end{matrix}

where p_L is the relative weight between the past inflation expectation to the actual inflation, and ε_Lt ͠ N(0,σ_L) represents other nonsystematic influences on expectations formation.

103. The open economy supply equation (Phillip’s curve) is given by

In this specification, current inflation, π_t, reflects a weighted average of the public’s forward looking expectation of the inflation rate, which we identify as L_t, with backward looking expectations represented by two lags of inflation. A key parameter in (3) is μ_π, which measures the relative importance of forward- versus backward-looking pricing behavior. The output gap, as well as changes in competitiveness, are also assumed to influence inflation. The innovation, ε_πt ͠ N(0,σ_π), represents stochastic cost-push factors.

104. Provided that the real interest parity condition holds, real effective exchange rate dynamics may be written as³⁵

\begin{matrix} q_{t} = E_{t} q_{t + 1} - (i_{t} - E_{t} π_{t + 1}) + ɛ_{q t} . & (4) \end{matrix}

The current real exchange rate is determined by the expected future real exchange rate, E_tq_t+1, and the ex ante real interest rate (i_t - E_tπ_t+1). Assuming some inertia in the formation of real exchange rate expectations, we assume that the real exchange rate is given by

\begin{matrix} q_{t} = E_{t} q_{t + 1} + β_{q 1} q_{t - 1} + β_{q 2} q_{t - 2} - β_{q s} (i_{t} - L_{t}) + ɛ_{q t}, & (5) \end{matrix}

where β_qS reflects transitional dynamics.

105. Due to the underdeveloped secondary government bond market, the BOM is not able to conduct high frequency open market operations to directly control the short-term interest rate. However, this rate is determined by both the monetary policy of the BOM (which influences the slope of the yield curve), and the inflationary expectations of participants in the primary bond market. As discussed above, while the BOM uses several instruments, its operational target is the short-term interest rate. Therefore, we take the short term interest rate as the policy variable, and following Rudebusch and Wu (2003), we assume that behavior of this rate may be captured by two latent term structure factors, L_t and S_t, in

\begin{matrix} i_{t} = δ_{0} + L_{t} + S_{t} . & (6) \end{matrix}

One of these factors, S_t, represents the slope of the yield curve (i.e., the spread between the long-run interest rate and the short-run interest rate), while the other, L_t, represents the level of the yield curve. If, as we do, one interprets L_t as representing inflationary expectations, then S_t can also be interpreted as the real interest rate. Finally, the specification of longer-term yields is determined assuming that they satisfy an affine no-arbitrage formulation.³⁶

106. The BOM’s monetary policy rule is assumed to be similar to that recommended by Ball (1999) for small open economies. It includes the output gap y_t, inflation expectation (as captured by L_t), the deviation between actual inflation and inflation expectation (π_t - L_t), the real exchange rate q_t, as well as a desire to smooth the real interest rate:

\begin{matrix} i_{t} = L_{t} + ρ_{s} (i_{t - 1} - L_{t - 1}) + (1 - ρ_{s}) ⌊ γ_{q} q_{t} + γ_{π} (π_{t} - L_{t}) + γ_{y} y_{t} ⌋ + u_{S t} & (7) \end{matrix}

\begin{matrix} u_{S t} = ρ_{u} u_{S, t - 1} + ɛ_{S, t} . & (8) \end{matrix}

Equation (7) has the nominal policy interest rate centered about inflationary expectations, and captures the various possible monetary policy objectives of the BOM: to stabilize the real economy; to maintain an appropriate real exchange rate; and to close the gap between actual inflation and its inflation target. It also allows for some persistence in the setting of this rate. Using (6), equation (7) may be easily expressed in terms of the slope factor S_t as

\begin{matrix} S_{t} = ρ_{s} S_{t - 1} + (1 - ρ_{s}) ⌊ γ_{q} q_{t} + γ_{π} (π_{t} - L_{t}) + γ_{y} y_{t} ⌋ + u_{S t} . & (9) \end{matrix}

The parameter estimates of equation (9) should reveal the relative importance of each of these objectives to the BOM. In addition, the dynamics of S_t allow for both partial adjustment, and (through (8)) serially correlated unanticipated monetary policy shocks. If p_S = 0, the dynamics of S_t arise from monetary policy partial adjustment. Conversely, if p_S ≠ 0, the BOM’s monetary policy choice exhibits persistence, and occurs in gradual adjustments. Using (1) and (6) we can obtain (1^′)

\begin{matrix} y_{t} = μ_{y} E_{t} y_{t + 1} + (1 - μ_{y}) ⌊ β_{y 1} y_{t - 1} + β_{y 2} y_{t - 2} ⌋ - β_{r} S_{t - 1} + ɛ_{y t}, & (1') \end{matrix}

and using (5) and (6) we can obtain (5^′)

\begin{matrix} q_{t} = E_{t} q_{t + 1} + β_{q 1} q_{t - 1} + β_{q 2} q_{t - 2} - β_{q S} S_{t} + ɛ_{q t} . & (5') \end{matrix}

The dynamic structure of the transition for the state of the economy is determined by equations (1’), (2), (3), (5’), (8) and (9). The state space of the combined rational expectations open economy macrofinance model is outlined in Appendix I.

D. Model Estimation

107. The above macrofinance model is estimated by maximum likelihood for the informal inflation targeting period—July 1996 to March 2004. Monthly data on government bond yields (for 3-, 6-, and 12-month maturities) provided by the BOM, annualized CPI inflation from the IMF’s International Financial Statistics, and the real exchange rate from the IMF’s Information Notice System are used to estimate the model. Due to the unavailability of less than annual GDP (or even unemployment) data, we use detrended, seasonally adjusted, monthly credit to the private sector as a proxy for the output gap.³⁷

108. Appendix II presents the parameter estimates of the open economy macrofinance model. First, consider the dynamics of the latent factors. The factor representing inflationary expectations, L_t, is extremely persistent with ρ_L estimated at 0.9921. This means that inflation expectations are very persistent, potentially difficult to change, with actual inflation carrying a very small weight in inflation expectation formation. In short, once a good reputation is established, it should last a long time.

109. The estimated BOM’s monetary policy rule is

\begin{matrix} S_{t} = 0.9958 S_{t - 1} + 0.0042 [0.8172 q_{1} + 0.362 1 (π_{t} - L_{t}) + 0.0084 y_{t}] + u_{S t} \\ u_{S t} = 1 \exp (- 5) u_{S, t - 1} + ɛ_{S, t .} \end{matrix}

Since the estimated ρ_S = 0.9958, S_t is also highly persistent. This seems reasonable in terms of the considerable inertia seen in the BOM’s monetary policy setting, represented by its gradual reduction in targeted inflation. However, this also implies that the BOM has relatively weak control over the short-term interest rate ((1 - ρ_S) = 0.0042.), although this could be an artifact of the indirect nature of the BOM’s interest rate targeting, and the relatively crude proxy for the output gap. The relative importance of the inflationary deviations, the output gap, and the real exchange rate are revealed by the estimates of γ_π, γ_q and γ_y—0.3621, 0.8172 and 0.0084, respectively. These estimates suggest that multiple monetary policy objectives influence policy, implying a flexible rather than strict inflation targeting in Mauritius. Unfortunately, though, all of these parameters are very imprecisely estimated (possibly because ρ_S is so large), with none actually being significant. There is also no autocorrelation in unanticipated monetary shocks, u_st (as ρ_u = 1exp(-5)).

110. The estimated parameters of the aggregate supply (Phillips curve) equation suggest that current inflation depends primarily (and weakly significantly) on inflationary expectations ( μ_π = 0.9110). This indicates the importance of framing expectations throughout the setting of monetary policy, and suggests that central bank credibility is crucial. Surprisingly, all other explanatory variables, including real exchange rate and output gap, are much less important than expectations, and are insignificant. However, the weak impact of the real exchange rate may reflect the past reliance on (inflexible) administered prices for several imported goods, as well as the crude proxy of the monthly output gap. The preeminent role of inflationary expectations in Mauritius is relatively unsurprising, though, given the important role these expectations play in the centralized wage-setting process.

111. The estimated parameters describing the aggregate demand equation suggest that, at a monthly frequency, there is a negligible weight on forward-looking output expectations (μ_y = 0.0223 ). The estimated value of β_qy = 0.0004 implies a very weak impact of real exchange rate changes on output. This could partially be explained by the relatively flat nature of the real exchange rate over the inflation targeting period.

E. Dynamics of Inflation Expectation

112. Figure IV.3 presents the latent factor that represents the level of the yield curve, L_t , as well as the slope, S_t . Two observations are immediate: (i) inflationary expectations in Mauritius are time-varying; and (ii) both the average level and volatility of expected inflation have declined significantly, especially since late-2000. This suggests that the BOM has earned credibility for its inflation targeting performance.

113. However, as measured by expectations, the implementation of inflation targeting has not been even. Inflationary expectations increased rapidly in mid-1998 (following a couple of years of relatively large foreign exchange interventions), before subsequent falling in 2000. The rapid decline could, in part, reflect the gradual reduction in foreign exchange interventions, but also follows a significant move by the BOM against inflationary pressures.³⁸ It also coincides with the introduction of the Lombard facility, which the BOM introduced to improve transparency and its ability to signal the stance of monetary policy. The behavior of the slope suggests that aside from one (or, possibly, two) episodes, the spread between short- and long-term securities has remained relatively flat. Its sudden decline during 2000 may reflect lower (real) returns available in more advanced economies, and, possibly, a revision of growth prospects, given uncertainty about the future of trade preferences.

F. Conclusion

114. Mauritius’s informal inflation targeting regime has been associated with a fall in inflation, and—as seen in Figure IV.3—an impressive fall in inflationary expectations. That is, inflation targeting appears to have been able to provide a strong nominal anchor that has moderated inflationary expectations, and resulted in a steady reduction in actual inflation. These expectations are particularly important in the case of Mauritius, since they can provide a focal point during the centralized wage bargain process, thereby affecting inflation far into the future.

115. Although Mauritius does not yet have a fully fledged inflation targeting regime, its experience to date suggests the potential value of informal inflation targeting. Moreover, Mauritius has been able to anchor these expectations even while maintaining a managed exchange rate. By focusing on the aggregate CPI inflation expectation, the BOM has also anchored actual inflation, without generating excessive output volatility. Mauritius’s experience suggests that, if carefully applied, inflation targeting jointly with a managed exchange rate can be a feasible policy alternative to a hard peg for small island economies.³⁹

116. However, Mauritius’s experience can be taken only so far. First, its experience comes against that backdrop of relatively subdued inflation worldwide. It remains to be seen how Mauritius’s inflation targeting regime will fair if global inflation rises significantly. Second, it shows that even in a country with solid institutions, a lack of fiscal dominance, and low external debt, it can take a long time before the central bank has earned sufficient credibility to anchor expectations for low inflation.

Appendix I State space representation

The dynamic system, (1’), (2), (3), (5’), (7), (8) and (9), can then be given the following state space representation Γ₀Y_t = Γ₁Y_t-1 + Ψµ_t + Πη_t, where the x^th of η_t is η_xt =x_t - E_t-1x_t, or the expectational forecasting error, and where

Y_t = [π_t π_t-1 q_t q_t-1 y_t y_t-1 L_t S_t u_st E_ty_y+1 E_tq_y+1]^′, ε_t = [ε_πt ε_qt ε_yt ε_Lt ε_St]^′ and

Γ_{0} = [\begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} 1 \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ ρ_{L} - 1 \end{matrix} \\ (ρ_{s} - 1) γ_{π} \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} 0 \\ 1 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} 0 \\ 0 \end{matrix} \\ 1 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ (ρ_{s} - 1) γ_{q} \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 1 \end{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} 0 \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 1 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} 0 \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 1 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ (ρ_{s} - 1) γ_{π} \end{matrix} \\ 0 \end{matrix} \\ 1 \end{matrix} \\ 0 \end{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} 0 \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 1 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} {\begin{matrix} - μ \end{matrix}}_{π} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 1 \end{matrix} \\ (1 - ρ_{s}) γ_{π} \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} 0 \\ 0 \end{matrix} \\ β_{q S} \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 1 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} 0 \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ - 1 \end{matrix} \\ 1 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} 0 \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ - μ_{y} \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} 0 \\ 0 \end{matrix} \\ - 1 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix}]

Γ_{1} = [\begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} (1 - μ_{π}) α_{π 1} \\ 1 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} (1 - μ_{π}) α_{π 2} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} α_{q} \\ 0 \end{matrix} \\ β_{q 1} \end{matrix} \\ 1 \end{matrix} \\ β_{q y} \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} 0 \\ 0 \end{matrix} \\ β_{q 2} \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} α_{y} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ (1 - μ_{y}) β_{y 1} \end{matrix} \\ 1 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} 0 \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ (1 - μ_{y}) β_{y 2} \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} 0 \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ ρ_{L} \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} 0 \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ - β_{r} \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ ρ_{S} \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} 0 \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ ρ_{u} \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} 0 \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 1 \end{matrix} \\ 0 \end{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} 0 \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 1 \end{matrix}]

\begin{matrix} Ψ = [\begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} 1 \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} 0 \\ 0 \end{matrix} \\ 1 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} 0 \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 1 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} 0 \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 1 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} 0 \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 1 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix}], a n d & Π = \end{matrix} [\begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} 0 \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 0 \end{matrix} \\ 1 \end{matrix} \\ 1 \end{matrix}] .

Using the Sims (2001) algorithm for linear rational expectations models, the system can be transformed into the form Y_t = ΓY_t-1 + Ωε_t, with the state vector of the system following the law of motion F_t = ρF_t-1 + Σε_t, where the state is F_t = [π_t π_t-1 q_t q_t-1 y_t y_t-1 L_t S_tu_St]^′.

No arbitrage conditions

For an economy where the state evolves according to F_t = ρF_t-1 + Σε_t, and the price of the risk associated with the factors underlying the term structure is represented by $\hat{Λ} = {\hat{λ}}_{0} + {\hat{λ}}_{1} F_{t}$ , Rudebusch and Wu (2003) derive a recursive structure for an affine noarbitrage bond-pricing model. With the very short-term interest rate, i_t, expressed as a linear function of the state of the economy, $i_{t}^{1} = - {\bar{A}}_{1} - {\bar{B}}_{1}^{'} F_{t}$ , they show that the yield on other maturities $(i_{t}^{j} = - {\bar{A}}_{j} - {\bar{B}}_{j}^{'} F_{t})$ must satisfy following recursive patterns for j>1:

{\bar{A}}_{j} = {\bar{A}}_{j - 1} - {\bar{B}}_{j - 1}^{'} Σ {\hat{λ}}_{0} + \frac{1}{2} {\bar{B}}_{j - 1}^{'} Σ Σ^{'} {\bar{B}}_{j - 1} + {\bar{A}}_{1}, a n d

{\bar{B}}_{j} = {\bar{B}}_{j - 1}^{'} (ρ - Σ {\hat{λ}}_{1}) + {\bar{B}}_{1}^{'} .

Likelihood function of the macro finance model

As described in the paper, the authors use data on inflation, private sector credit, and the real exchange rate, as well as the yields on 3-, 6-, and 12- month treasury securities. We stack the observed values in a vector $z_{t} = {[\begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} π_{t} & q_{t} \end{matrix} & y_{t} \end{matrix} & i_{t}^{3} \end{matrix} & i_{t}^{6} \end{matrix} & i_{t}^{12} \end{matrix}]}^{'}$ . Since we are estimating two latent factors from three yields, we must assume that one yield is measured with error. Following common practice, we assume the yield associated with the middle maturity—6 months—is measured with error (and distributed N(0,σ₆)). Assuming that conditional on the first t-1 observations, the tth observation is Gaussian, then $z_{t} = Γ^{z} F_{t - 1} + Ω^{z} ξ_{t}$ , where

$\begin{matrix} Γ^{z} = [\begin{matrix} \begin{matrix} \begin{matrix} ρ_{1, .} \\ ρ_{3, .} \end{matrix} \\ ρ_{5, .} \end{matrix} \\ B_{ρ} \end{matrix}], Ω^{z} = [\begin{matrix} \begin{matrix} \begin{matrix} Σ_{1, .} \\ Σ_{3, .} \end{matrix} \\ Σ_{5, .} \end{matrix} & \begin{matrix} \begin{matrix} 0 \\ 0 \end{matrix} \\ 0 \end{matrix} \\ B Σ & B^{m} \end{matrix}], B^{m} = [\begin{matrix} \begin{matrix} 0 \\ σ_{6} \end{matrix} \\ 0 \end{matrix}], a n d & ξ_{t} = [\begin{matrix} ɛ_{t} \\ ɛ_{t}^{m} \end{matrix}], w h e r e ɛ_{t}^{m} \end{matrix}$ is the measurement error and where B = [B₃ B₆ B₁₂]^′, $A_{j} = - {\bar{A}}_{j} / j,$ and $B_{j} = - {\bar{B}}_{j} / j$ . The log of the conditional density of the tth observation is

l l h_{t} = - \frac{1}{2} [\ln (2 π) + \ln (\det (Ω^{z} {Ω^{z}}^{'})) + {(z_{t} - Γ^{z} F_{t - 1})}^{'} {(Ω^{z} {Ω^{z}}^{'})}^{- 1} (z_{t} - Γ^{z} F_{t - 1})],

with the conditional log likelihood being $L_{z_{T}, ..., z_{2} | z_{1}} (z_{T}, ..., z_{2} | z_{1}; θ) = Σ_{2}^{T} l l h_{t}$ . Standard errors are computed using the outer product of gradients estimator.

Appendix II Mauritius: Parameter Estimates of the Macrofinance Open Economy Model⁴⁰

References

Ball, Laurence, 1998, “Policy Rules for Open Economies,” Research Discussion Paper 9806 (Sydney: Reserve Bank of Australia).
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Mishkin, Frederic S., 2004, “Can Inflation Targeting Work in Emerging Market Countries?,” paper presented at an IMF conference in honor of Guillermo A. Calvo, Washington, D.C., April.
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Prepared by Nathan Porter and James Yao.

An inflation rate of 3 to 5 percent sustained over time is generally accepted in Mauritius as low inflation.

According to the 2003 reports of the World Economic Forum and Transparency International, Mauritius is among the top five African countries for quality of public institutions and perceptions of corruption.

In fact, since 2002 the Bank of Mauritius (BOM) has been a net debtor of the government—that is, the government has maintained substantial (net) deposits with the BOM.

As such, Mauritius’s institutional setting contains many of the institutional factors Mishkin (2004) regards as essential to the success of inflation targeting.

ECCU countries consist of Antigua and Barbuda, Dominica, Grenada, St. Kitts and Nevis, St. Lucia, St. Vincent and the Grenadines.

Subsequent, more micro-founded analysis, suggests similar considerations (Galí and Monacelli, 2003 and Parrado, 2004).

Miskin (2004) also argues that successful inflation targeting can, through expectations formation, lessen the affect of exchange rate fluctuations on the economy.

Mauritius accepted the obligations of Article VIII of the Articles of Agreement of the International Monetary Fund in 1993.

The Development Loan Stock with maturities up to 15 years are issued annually, while five-year bonds are issued quarterly.

From July 2003, the BOM began to issue its own central bank bills.

Micro-founded small open economy models produce a similar expression for the output gap (Galí and Monacelli, 2003; Parrado, 2004).

Under Mauritius’s centralized tripartite wage setting mechanism, there is automatic across-the-board wage indexation for any inflation above 5 percent in a year.

Again, micro-founded small open economy models produce a simlar Phillips’ curve, although for domestic inflation (Galí and Monacelli, 2003; Parrado, 2004).

This is similar to equation 2.11 in Svensson (2000).

The affine no-arbitrage term structure model is presented in Appendix I. We also assume that the price of the risk associated with the factors underlying the term structure may be represented as $Λ_{t} = λ_{0} + λ_{1} [\begin{matrix} L_{t} \\ S_{t} \end{matrix}] .$ Since we use demeaned data in the following empirical exercise, we can, without loss of generality, normalize δ₀ and λ₀ to zero.

Since the constant term in latent factor models cannot typically be identified, we work with de-meaned data. Also, as we are estimating two latent factors from three bond maturities, we assume that six-month bond yields are measured with error.

In 1999, the BOM deliberately introduced a tight monetary policy to head off inflationary pressures during the recovery in 1998/99. Despite slow growth in 1999/00, the Lombard rate was raised to 12.0 percent, and to 12.5 percent in late-September and November 2000, respectively. The tighter stance was kept in place until May 2001, when the BOM began a series of easings, lowering the Lombard rate from 12.5 percent to 9.5 percent as of January 2004.

Indeed, Mishkin (2004, p. 25) concludes that in the context of inflation targeting “... there is a rational for central banks in emerging market countries to smooth exchange rates,” provided they do not go too far.

P-values are in square brackets.

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Mauritius: Selected Issues and Statistical Appendix

Author: International Monetary Fund

Volume/Issue:: Volume 2005: Issue 280

Publisher:: International Monetary Fund

ISBN:: 9781451827804

ISSN:: 1934-7685

Pages:: 149

DOI:: https://doi.org/10.5089/9781451827804.002

View raw image

Annual CPI Inflation

(In Percent)

View raw image

Nominal and Real Effective Exchange Rates

View raw image

The Level and Slope of the Yield Curve

Aggregate demand curve
μ_y = 0.0223 [0.4999]	β_y1 = 0.0171 [0.4996]	β_y2 = 0.1443 [0.4971]
β_qy = 0.0004 [0.4997]	β_r = 0.0064 [0.4971]
Aggregate supply curve
μ_π = 0.9110 [0.1712]	α_π1 = 0.0216 [0.4958]	α_π2 = 0.3810 [0.4722]
α_q = –0.1914 [0.4987]	α_y = –0.0135 [0.49982]
Inflation dynamics
ρ_L = 0.9921 [1.4exp(-64)]
Real exchange rate dynamics
β_q1 = 0.996 [0.3860]	β_q2 = 0.999 [0.0017]
β_qS = –0.0175 [0.3229]
Monetary policy reaction function
ρ_S = 0.9958 [2.7exp(-13)]	γ_q = 0.8172 [0.4998]	γ_π = 0.3621 [0.4857]
γ_y = 0.0084 [0.4999]	ρ_u = 1exp(- 5) [0.4999]
Risk pricing matrix
$λ_{1}^{L L}$ = –0.1169 [0.3809]	$λ_{1}^{L S}$ = 0.9903 [0.2398]
$λ_{1}^{S L}$ =-0.0151 [0.4674]	$λ_{1}^{S S}$ = –0.0259 [0.4870]
Standard deviations
σ_L = 0.2802 [0.0050]	σ_S = 0.1545 [0.2195]
σ_π = 4.9877 [9exp(-22)]	σ_q = 0.0563 [0.2163]	σ_y = .0400 [0.1200]
Standard deviation of measurement error for the 6-month bond yield
σ₆ = 0.1690 [5.7exp(-27)]

Aggregate demand curve
μ_y = 0.0223 [0.4999]	β_y1 = 0.0171 [0.4996]	β_y2 = 0.1443 [0.4971]
β_qy = 0.0004 [0.4997]	β_r = 0.0064 [0.4971]
Aggregate supply curve
μ_π = 0.9110 [0.1712]	α_π1 = 0.0216 [0.4958]	α_π2 = 0.3810 [0.4722]
α_q = –0.1914 [0.4987]	α_y = –0.0135 [0.49982]
Inflation dynamics
ρ_L = 0.9921 [1.4exp(-64)]
Real exchange rate dynamics
β_q1 = 0.996 [0.3860]	β_q2 = 0.999 [0.0017]
β_qS = –0.0175 [0.3229]
Monetary policy reaction function
ρ_S = 0.9958 [2.7exp(-13)]	γ_q = 0.8172 [0.4998]	γ_π = 0.3621 [0.4857]
γ_y = 0.0084 [0.4999]	ρ_u = 1exp(- 5) [0.4999]
Risk pricing matrix
$λ_{1}^{L L}$ = –0.1169 [0.3809]	$λ_{1}^{L S}$ = 0.9903 [0.2398]
$λ_{1}^{S L}$ =-0.0151 [0.4674]	$λ_{1}^{S S}$ = –0.0259 [0.4870]
Standard deviations
σ_L = 0.2802 [0.0050]	σ_S = 0.1545 [0.2195]
σ_π = 4.9877 [9exp(-22)]	σ_q = 0.0563 [0.2163]	σ_y = .0400 [0.1200]
Standard deviation of measurement error for the 6-month bond yield
σ₆ = 0.1690 [5.7exp(-27)]

Aggregate demand curve
μ_y = 0.0223 [0.4999]	β_y1 = 0.0171 [0.4996]	β_y2 = 0.1443 [0.4971]
β_qy = 0.0004 [0.4997]	β_r = 0.0064 [0.4971]
Aggregate supply curve
μ_π = 0.9110 [0.1712]	α_π1 = 0.0216 [0.4958]	α_π2 = 0.3810 [0.4722]
α_q = –0.1914 [0.4987]	α_y = –0.0135 [0.49982]
Inflation dynamics
ρ_L = 0.9921 [1.4exp(-64)]
Real exchange rate dynamics
β_q1 = 0.996 [0.3860]	β_q2 = 0.999 [0.0017]
β_qS = –0.0175 [0.3229]
Monetary policy reaction function
ρ_S = 0.9958 [2.7exp(-13)]	γ_q = 0.8172 [0.4998]	γ_π = 0.3621 [0.4857]
γ_y = 0.0084 [0.4999]	ρ_u = 1exp(- 5) [0.4999]
Risk pricing matrix
$λ_{1}^{L L}$ = –0.1169 [0.3809]	$λ_{1}^{L S}$ = 0.9903 [0.2398]
$λ_{1}^{S L}$ =-0.0151 [0.4674]	$λ_{1}^{S S}$ = –0.0259 [0.4870]
Standard deviations
σ_L = 0.2802 [0.0050]	σ_S = 0.1545 [0.2195]
σ_π = 4.9877 [9exp(-22)]	σ_q = 0.0563 [0.2163]	σ_y = .0400 [0.1200]
Standard deviation of measurement error for the 6-month bond yield
σ₆ = 0.1690 [5.7exp(-27)]

	1996/97	1997/98	1998/99	1999/00	2000/01	2001/02	2002/03	2003/04
Target	8.0	6.0	8.0	6.0	5.0-5.5	6.0	6.0	4.0
inflation
Actual	7.9	5.4	7.9	5.3	4.4	6.3	5.1	4.0
inflation

	1996/97	1997/98	1998/99	1999/00	2000/01	2001/02	2002/03	2003/04
Target	8.0	6.0	8.0	6.0	5.0-5.5	6.0	6.0	4.0
inflation
Actual	7.9	5.4	7.9	5.3	4.4	6.3	5.1	4.0
inflation

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Abstract

IV. Inflation Targeting in Small Open Economies: The Mauritius21

A. Introduction

B. Development of Inflation Targeting

A brief history of monetary policy

Inflation targeting framework

Public announcement of aggregate inflation targets

De facto commitment to price stability

An integrated operational strategy

Open market operations

The signaling role of interest rates

Foreign exchange intervention

A flexible monetary policy rule

Transparent monetary policy operations

C. An Open Economy Macrofinance Model

D. Model Estimation

E. Dynamics of Inflation Expectation

F. Conclusion

Appendix I State space representation

No arbitrage conditions

Likelihood function of the macro finance model

Appendix II Mauritius: Parameter Estimates of the Macrofinance Open Economy Model40

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IV. Inflation Targeting in Small Open Economies: The Mauritius²¹

Appendix II Mauritius: Parameter Estimates of the Macrofinance Open Economy Model⁴⁰