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Bernard J. Laurens is Deputy Chief and Alexandre Chailloux economist in the Monetary and Capital Markets Department (MCM) of the IMF. Alain Durré is senior economist at the European Central Bank. This paper is based on informations gathered during a technical mission held in Tunisia in February 2007 for the Monetary and Capital Market Department of the IMF. The authors thank Peter Stella and Simon Gray for useful comments. All errors remain theirs.
Tunisia has been issuing debt on international capital markets since 1994, starting with issues on the Japanese market for maturities between 5 and 30 years. As of 1997, Tunisia began issuing debt on the European and American markets. On April 17, 2003, Moody’s raised Tunisia’s foreign currency bond rating to Baa2. Standard & Poor’s and the IBCA have agreed on a BBB rating since 2000.
At the time of acceptance of Article VIII obligations, lending rates had been almost fully liberalized, the prudential framework for the banking sector had been significantly strengthened, and progress had been made in liberalizing trade. However, capital controls were pervasive; banks were still required to lend to priority sectors and their ability to undertake foreign currency denominated transactions was limited.
The intervention policy is guided by the behavior of the real effective exchange rate (TCER). Since 2001, the BCT has been targeting a depreciation of the TCER in order to support export competitiveness and growth.
The former Article 33 stated that: “The ultimate objective of monetary policy is to safeguard the value of the currency by keeping inflation down to a rate close to the rate observed in partner and competitor countries.”
Taux Moyen du Marché Monétaire.
Government securities (Treasury bonds at 2, 5, and 10 years account for 2/3 of negotiable domestic debt instruments) are auctioned to primary dealers, and the bid cover ratio has been in the 300 percent region.
“Window Guidance” operations allow the central bank to steer interest rates using small operations through which key market participants are advised of the central bank’s intention, and adjust subsequently their quotations. Such operations correspond to a soft form of moral suasion.
Similar, for instance, to the London LIBOR or the EURIBOR.
In France, the development of money market mutual funds (SICAVs) has helped strengthen the redistributive role of the money market, and the diversification of interbank instruments, while diminishing the importance of captive sources of funding for banks. The transparency and competitive practices obligations (ban on having business dealings channeled predominantly through the bank promoting SICAVs), and the use of repos had stimulated the market’s development by the end-1980s.
Swaps of variable rate against EONIA are the main interest rate risk management instruments in the euro area.
This explains why, generally speaking, the VARs estimated for this purpose are unconstrained, particularly for economies in transition (see e.g., Favero (2001)).
Each estimated VAR model contains a constant and a deterministic trend.
Given the constraints set forth above setting the starting date at 2001, it is preferable to work with a monthly frequency. All data are available at this frequency, except for GDP, only available at annual and quarterly intervals. Given the high degree of correlation (nearly 60 percent) between the annual GDP growth rate and the growth rate in industrial output, this latter variable is used to establish a monthly frequency for quarterly GDP in accordance with the method proposed in Chow and Lin (1971).
Imposing long-term restrictions (cointegration) may undoubtedly improve the quality of the VAR estimation, but it may also introduce inconsistencies in the estimate when the number of observations is limited.
The standard tests for specifications for data and estimate quality have also been carried out. In particular, the LM and White tests suggest that, in all cases, the residuals of the VAR models are not correlated and are homoskedastic.
In order to limit rigidities in estimating seasonal coefficients, the X11 method was used to convert gross series into seasonally adjusted series. We cannot rule out the possibility that seasonal factors inherent in the Tunisian economy (Islamic holidays) have not been totally corrected for by the standard seasonal adjustment methods. See for example the discussion in Mongardini and Saadi-Sedik (2003).
In the literature, the exchange rate variable is generally the real effective exchange rate taking into account the presence of the price index. However, in using the nominal (not real) effective exchange rate, we are better able to isolate the exchange rate channel.
The industrial production index is used for the real activity of the euro area in order to reduce the number of lags of the exogenous variable. This can also be explained by the nature of the commercial transactions between Tunisia and the European Union.
Preliminary tests were conducted with some US economy macro variables. As the significance of these variables seemed weaker in the regressions than with the EU variables, the later were adopted. Furthermore, this is consistent in light of the alignment of the Tunisian economy with the European Union economy. Given the limited number of observations, the introduction of both set of exogenous variables would have excessively reduced the degrees of freedom.
The main argument as to why cross-correlations between shocks are large in macroeconomic models is that the data is typically monthly/quarterly and thus lagged response to a single shock within the month are aggregated and consequently treated as a contemporaneous impact when dealing with monthly data.
Although the order we have chosen is in line with the literature and seems suitable for an economy in transition like Tunisia, other sequences of variables have been tested. Although the results show a degree of sensitivity to the sequence chosen (in line with previous remarks), the overall picture of the transmission channels remains unchanged. For additional details regarding the impact of the sequence of variables on estimation results in VAR models, see Enders (1995).
From Figures 2 to 4, the variable LY denotes the logarithm of the Tunisian real GDP in level (yTUNt), LIPCSA is the logarithm of the Tunisian consumer price index in level (pTUNt) and LNEER is the logarithm of the Tunisian nominal effective exchange rate (xTUNt). Concerning the policy instrument, LHSA is the logarithm of the level of the Tunisian money base or high-power money (hTUNt) while LM3 is the logarithm of the level of the Tunisian monetary aggregate M3 (m3TUNt), whereas TMM is the Tunisian overnight interest rate (TMMTUNt). As mentioned earlier, with the exception of the overnight interest rate, (TMMTUNt), all these variables are seasonally adjusted.
It should be noted that if we replace the monetary aggregate M3 by the money base in the estimation for model 2, the lagged variables for the latter appear to be insignificant in most of the equations of the system.
The effect of the balance sheet channel as manifested through the volume (and not the value) of collateral may tend to endogeneize money supply through a more pronounced bank credit impact than generally observed. Given the constraints through collateral required by banks, the logical conclusion is that this channel, if it exists at all, functions poorly. This assumption cannot be ruled out in light of the discussions in Fatma (2001).
At the end of the year 2000, the 12-month rolling correlation between the annual inflation rate and the annual growth of the money base was 0.45 against 0.35 with the monetary aggregate M3. At the end of 2006, this correlation with the money base was only 0.29 against 0.52 with M3. Several additional factors also argue in favor of M3 as a leading indicator of inflation. The correlation between the money base (year on year) and M3 moved from 58 percent over the period 1996–2001 to 51 percent over the period 2001–06. The correlation between the year on year figures for total credit and for credit to the private sector and annual money growth is stronger with M3 (of the order of 34 percent and 33 percent respectively as against 24 percent and 18 percent for the money base). Finally, the correlation between the annual growth in credit and inflation is of the order of 18 percent and 7 percent respectively for total credit to the economy and credit to the private sector.
The estimation focuses on a classic long-term demand for money establishing a relationship between money in real terms (mt-pt), real GDP (yt), and annual inflation (πt), each expressed in natural logarithms in terms of levels and seasonally adjusted, with a monthly frequency over the period 2001:01-2006:12. With the standard error in parentheses, the results for when mt-pt=monetary base are: yt=0.22 (0.02) and πt=-0.20 (0.20). Conversely, when mt-pt=M3, the results are: yt=0.10 (0.005) and πt=-0.15 (0.06).
Both results may reflect the omission of important variables in the regression which could explain part of the determination of the TMM.
This section in based on A. Carare, M. Stone, A. Schaechter and M. Zelmer, IMF Working Paper WP/02/102 “Establishing Initial Conditions in Support of Inflation Targeting.”
Indexation may however deter dynamic use of the interest rate and, hence, affect the feasibility of IT.
As recalled by Woodford (2001), the importance of a responsible fiscal stance for price stability outcomes stem from the fact that monetary policy has significant effects on the level of the state’s outstanding debt in real terms. In his fiscal theory of price level, Woodford demonstrates that fiscal policy design matters for monetary policy (even in the absence of explicit dependence upon fiscal variables) in rational expectations equilibria associated with “non-Ricardian” policy regimes. In presence of rational expectations and frictionless financial market, this could happen when the state does not adjust its budget to neutralize, in present value, the effects of fiscal disturbances upon private sector budget constraints and hence aggregate demand. As a result, even in case of strong commitment of monetary policy to deliver price stability, Woodford (2001) shows that: “On the one hand, (non-Ricardian) fiscal expectations inconsistent with a stable price level may frustrate this outcome, even when monetary policy is itself consistent with price stability. Indeed, the combination of a Taylor rule with certain kinds of fiscal policy may result in an inflationary or deflationary spiral. And on the other hand, even when fiscal policy is consistent with stable prices, the policy regime (including the commitment to a Taylor rule) may not preclude other equally possible rational expectations equilibria, such as equilibria involving self-fulfilling deflationary spirals.” See Woodford, M. (2001), “Fiscal Requirements for Price Stability,” Journal of Money, Credit and Banking, Vol. 33, pp. 669–728.
The adoption of an IT framework does not prevent utilization of exchange market interventions as a way to ease volatility to the extent that such volatility might jeopardize price stability.
The agencies include the Institut d’Économie Quantitative (IEQ), the Observatoire de Conjoncture Économique (OCE), and the Conseil National de la Statistique (CNS).
The annual target for the monetary aggregate M3 consists in a target to be achieved at year-end, i.e., a year-on-year figure for the month of December for each year.
Apart from the target increase in M3 and the macroeconomic projections (for GDP and its internal components), these indicators also contain likely outturn figures for the current year and the anticipated annual growth in other monetary aggregates (except for monetary base), credit, national saving, foreign debt, and government finance.
In the month of December in year t, the monthly target for the monetary base for year t+1 is determined on the basis of the monthly increase computed for M3 to which the monthly money multiplier observed between the two money aggregates during year t is applied. As the exercise is conducted at end-December of year t, it is thus talking about the money multipliers observed during the eleven months of year t and one provisional multiplier for the month of December. Accordingly, a re-estimation of the monthly profile of the target for the monetary base for year t+1 is carried out at the end of the month of January in year t+1 once the money multiplier for the month of December in year t is available.
See IMF, Public Information Notice (PIN) No. 06/40, April 18, 2006.