A. Output and Real Interest Rates

Quarterly output is divided into gap and potential, $y_t={\overline{y}}_t+yga{p}_t$, where potential output ${\overline{y}}_t$ follows an autoregressive process of order one in first differences: $\mathrm{\Delta }{\overline{y}}_t={\rho }_{\overline{y}}\mathrm{\Delta }{\overline{y}}_{t-1}+(1-{\rho }_{\overline{y}})\mathrm{\Delta }\overline{y}+{\varepsilon }_t^{\overline{y}}$⁸ The output gap is given by a hybrid IS curve. It depends on real monetary conditions (rmc_t) and foreign demand $\left(yga{p}_t^{*}\right)$ as well as past and future output gaps:

Real monetary conditions are composed of the real interest rate gap (rrgap_t)—the difference between actual real interest rates $(r_t-E_t\left[{\pi }_{t+1}\right])$ and neutral real interest rates ${\overline{rr}}_t$—and the real exchange rate gap $(zga{p}_t=z_t-{\overline{z}}_t):rm{c}_t=(1-{\beta }_4)rrga{p}_t+{\beta }_{4}zga{p}_t$⁹

B. The Philips Curve

Quarterly (annualized) inflation $({\pi }_t=4(P_t-P_{t-1})$, where P_t is a headline price index is the sum of two components, a persistent component π_1t and noise ${\varepsilon }_t^{\pi noise}:{\pi }_t={\pi }_{1t}+{\varepsilon }_t^{\pi noise}$. The noise component captures sudden, temporary, changes in inflation that are unrelated to the state of the economy and the underlying inflationary pressures, and are unlikely to endure.

The dynamics of π_1t are instead given by a hybrid Phillips curve:

where $\overline{\pi }$ is the inflation target, Δs_t is the quarterly (annualized) nominal depreciation rate of the exchange rate, and $\mathrm{\Delta }{\overline{s}}_t$ is the depreciation rate consistent with both the domestic and foreign inflation targets and the equilibrium real exchange rate $\mathrm{\Delta }{\overline{z}}_t:\mathrm{\Delta }{\overline{s}}_t=\mathrm{\Delta }{\overline{z}}_t+\overline{\pi }-{\overline{\pi }}^{*}$.

The above specification merits a few comments. First, it implies the long-run Phillips curve is vertical, so that there is no long-run output/inflation tradeoff. Second, depending on parameter α₁ it allows for inflation to be considerably backward-looking, which can capture indexation practices. Third, the Phillips curve allows for an immediate impact from nominal depreciation (pass-through) above and beyond equilibrium levels $\left(\mathrm{\Delta }{\overline{s}}_t\right)$, possibly reflecting dollarization of the economy and imperfect policy credibility. Finally, inflation depends on real marginal costs that depend on the domestic output gap (ygap_t) and the real exchange rate gap (zgap_t, where under-valuation, zgap_t >0, is inflationary), and by supply shocks with more persistent effects $\left({\varepsilon }_t^{{\pi }_1}\right)$.¹⁰

C. Uncovered Interest Parity and Real Exchange Rate Dynamics

Exchange rate dynamics are driven by an uncovered interest rate parity condition:

where $\mathrm{\Delta }{s}_{t+1}^e$ is the expected rate of quarterly nominal depreciation (in annualized terms). θ_χ captures the strength of the effect of interest rates on the exchange rate, and it is allowed to deviate from 1 (to improve the model’s empirical fit). $\mathrm{\Delta }{s}_{t+1}^e$ is given by: $\mathrm{\Delta }{s}_{t+1}^e=4({\theta }_2{E}_t[st+1]+(1+{\theta }_2)(s_{t-1}+1/2\left(\mathrm{\Delta }{\overline{s}}_t\right))-s_t)\mathrm{.}\text{ If }{\theta }_2<1$ the expected nominal depreciation deviates from rational expectations. ${\varepsilon }_t^s$ captures temporary shocks to the exchange rate, while prem_t is the country risk premium: $pre{m}_t={\rho }_{prem}pre{m}_{t-1}+(1-{\rho }_{prem}){\overline{prem}}_t+{\varepsilon }_t^{prem}$. Shocks to the risk premium ${\varepsilon }_t^{prem}$ have persistent effects on the exchange rate. Finally, the equilibrium risk premium is consistent with neutral real interest rates in both countries and the equilibrium real exchange rate appreciation: ${\overline{prem}}_t={\overline{rr}}_t-{\overline{rr}}_t^{*}-E\left[\mathrm{\Delta }{\overline{z}}_{t+1}\right]$.

D. Money Demand

We use a specification that potentially allows for both short-run and long-run dynamics in the demand for real money balances m_t (m_t = M_t — P_t). Quarterly (annualized) real money demand growth is given by an error correction equation:

Equation (4) states that changes in demand for real money balances Δm_t depend on changes in output y_t, the annualized nominal interest rate i_t, velocity ν_t, and the real money gap mcorr_t. We define mcorr_t as a deviation of real money balances from its long run value: $mcor{r}_t=m_t-{\delta }_4{y}_t+{\delta }_5{i}_t+{\upsilon }_t\mathrm{.}{\upsilon }_t$ denotes (or is closely related to) trend velocity, and it follows an AR(1) in first differences with drift: $\mathrm{\Delta }{\upsilon }_t={\rho }_{\upsilon }\mathrm{\Delta }{\upsilon }_{t-1}+(1-{\rho }_{\upsilon })\mathrm{\Delta }\upsilon +{\upsilon }_t^{\pi }$.

Note that there are two types of shocks to money demand: shocks with temporary effects on the level of desired real money balances $\left({\varepsilon }_t^{\mathrm{\Delta }m}\right)$, with persistence inversely related to the coefficient on the error correction term $\left({\delta }_3\right)$, and shocks with persistent effects on the growth rate of desired real money balances $\left({\varepsilon }_t^v\right)$.

E. Monetary Policy

We adopt a general specification to characterize monetary policy in Uruguay, with several components. The first building block is an unobserved interest rate that follows a standard forward-looking Taylor rule:

where ${\overline{\iota }}_t$ is the neutral nominal interest rate $({\overline{\iota }}_t={\overline{rr}}_t+\overline{\pi })$, and π_4t+2 is the expectation for the yoy inflation rate two quarters ahead.¹¹ This level of interest rates will serve as a reference both before and during the money targeting period.

Since it is unlikely that monetary policy followed the prescription implied by such a rule in recent years, we make two additional assumptions to take the model to the data. First, throughout the entire period (both pre- and during MT) we assume that interest rates deviate from the rule by a volatile and persistent term (dev_t):

where $de{v}_t={\rho }_{dev}de{v}_{t-1}+{\varepsilon }_t^{dev}$. The above specification plays two roles. On the one hand, it helps match the data, since it does not require observed interest rates in Uruguay to follow the above rule. On the other hand, once the model is used to produce a projection for the Uruguayan economy, it provides an interest rate path consistent with the rule.¹²

For the money targeting period, we make the additional assumption that the central bank also steers interest rates to bring yoy money growth $\left(\mathrm{\Delta }{M}_{4,t}\right)$ closer to its target $\left(\mathrm{\Delta }{\overline{M}}_{4,t|t-1}\right)$:

The above specification implies that positive target deviations (when actual money growth exceeds the target) elicit an increase in interest rates, as the authorities tighten policy to steer money growth toward the target. γ₄ captures the importance of money targets in the frameworks: the higher γ₄, the more aggressive authorities are in response to money target deviations. γ₄ therefore captures the degree of money target adherence.

The above specification is perfectly consistent with a money targeting framework. An equivalent representation is the following:

According to this representation, the authorities allow for deviations in money growth from the target whenever interest rates deviate from the Taylor prescription; 1/γ₄ measures the extent to which the level of interest rates influences the central bank decision on money growth.¹³ For instance, the policymaker would bring the rate of money growth below the target, if the interest rate i_t is below $i_t^{Taylor}$. We describe the setting of money targets next.¹⁴

F. The Setting of Money Targets

We model the money targeting framework as follows. First, we assume the central bank sets a target for yoy growth, i.e., for ΔM₄. Second, we assume the money target for period t is set one quarter in advance (at time t-1). These assumptions imply that the authorities have information up to time t-1 when setting the target, including data on nominal and real money balances. Given data up until time t-1, and a forecast for quarterly inflation next quarter, the target for yoy money growth $\mathrm{\Delta }{\overline{M}}_{4,t|t-1}$ also implies a target for quarterly nominal and real money growth $\mathrm{\Delta }{\overline{M}}_{t|t-1}\text{ and }\mathrm{\Delta }{\overline{m}}_{t|t-1}$:

Finally, we assume that the target for quarterly real money growth $\left(\mathrm{\Delta }{\overline{m}}_{t|t-1}\right)$ implied by the headline money target number $\left(\mathrm{\Delta }{\overline{M}}_{4,t|t-1}\right)$ is consistent with a forecast for money demand using the money demand equation above, up to an error term ${\varepsilon }_{t-1}^{\mathrm{\Delta }\overline{m}}$:

The term ${\varepsilon }_{t-1}^{\mathrm{\Delta }\overline{m}}$ serves two purposes. First, it can be used to incorporate any additional information about the future demand for monetary aggregates that is not explicitly modeled here, e.g., changes in M1+ stemming from fiscal operations, the effects of macro-prudential tools, or other measures. Second, when filtering data through the model, it can help match the actual, observed, money targets with the ones implied by the above equation.

The above specification implies that the money target is consistent with the interest rate intended by the monetary authorities (E_t-1[i_t]). This is the way in which money targets and interest rate policy are ex-ante consistent. Ex-post however, money target misses will reflect forecast errors in money demand, stemming from both forecast errors in inflation, output, and interest rates, and unexpected and exogenous changes in demand:

This completes the presentation of the model.¹⁵

G. Consistency between the Model and the MT Framework in Uruguay

We acknowledge that the above framework may not perfectly coincide with all aspects of the framework in Uruguay. The model is consistent with the Uruguay experience in that: (i) targets are set in advance, using information up to t-1, and, as will be shown below, (ii) there are large and persistent deviations between target and actual money growth, which indicates that the degree of target adherence is part of the policy response, and that adherence is typically far from complete.

The assumption that the money target is a forecast of money demand consistent with a desired interest rate policy is harder to prove. On the one hand, the Central Bank has at times referred to the stance of policy implied by the money targets as contractionary by showing that nominal interest rates have increased, which suggests some analytical consistency between money target setting and desired interest rates. On the other hand, the path of money targets since end 2013 displays a very gradual path that is likely to be inconsistent with pure money demand forecasting.¹⁶

H. On the Role of Monetary Aggregates in the Model

As discussed earlier, monetary aggregates do not play a direct role in the transmission of monetary policy, i.e., they do not appear directly in either the IS equation or the Phillips curve. Such a role is reserved to the interest rate and the exchange rate. This approach is consistent with most macro models going back to IS-LM or Mundell-Fleming, but it does raise the question of whether it is the right modeling approach for Uruguay.

We address this question with two regressions. First, we follow Bernanke and Blinder (1993) and run a regression of quarterly GDP in levels on two lags of quarterly GDP, the price level, nominal money balances, the nominal exchange rate, and the one month interest rate on BCU securities, for the period 2004:I-2014:III. We then perform marginal significance tests (F tests) for the hypothesis that either M1+ or the interest rate can be excluded from the regression. We find that the interest rate is a much better predictor of economic activity (much lower marginal significance level) than monetary aggregates, which are found not to be statistically significant. We interpret this evidence as supportive of the idea that monetary aggregates are not informative of the stance of policy once interest rates are included in the analysis, which is consistent with our model.

Second, we regress yoy inflation on one lag of itself, lagged output gap obtained with the HP filter, lagged yoy M1+ growth, and lagged real money gap (also obtained with the HP filter), for the period 2004:I-2014:III. The last term is based on p-star models of inflation, which posit that the difference between the real money stock and the long-run equilibrium real money stock can contain information about future inflation (Gerlach and Svensson (2003)). In the case of Uruguay, we find that the estimated coefficient on the real money gap is insignificant, while the coefficient on money growth is negative and significant, implying that an increase in money growth is associated with a decrease in inflation. Overall, we believe this evidence does not support a more direct role for monetary aggregates in the model.¹⁷

A. Calibration

The ability of the model to interpret data and produce a reasonable medium-term projection crucially depends on its calibration. Our choice of parameters (presented in Table 1) is based on the following considerations.¹⁸ First, we assessed the calibration of the model by comparing the model’s impulse response functions with empirical evidence from a structural VAR estimated for Uruguay.¹⁹ We focused on two shocks: a shock to the risk premium for emerging market assets (captured by the EMBI spread), and a shock to monetary policy. Matching the model dynamics with the VAR evidence requires some work. The model has been designed in part to provide a useful policy recommendation going forward and not solely to replicate past policy responses, which may have been overly procyclical in response to capital flows, that is somewhat accommodative in episodes when capital inflows contributed to exchange rate appreciation pressures.²⁰ The EMBI shock is therefore reproduced in the model by a combination of three shocks (a shock to the risk premium ${\varepsilon }_t^{prem}$, a shock to monetary policy ${\varepsilon }_t^{Taylor}$ and a shock to foreign output).

Table 1.

Uruguay: Model Calibration

Table 1.

Uruguay: Model Calibration

Parameter	Value	Parameter	Value	Parameter	Value
Potential Output		Uncovered Interest Parity		Shocks (Standard Deviation)
$\mathrm{\Delta }\overline{y}$	3.5	θ1	0.6	${\sigma }_{\overline{y}}$	0.02
${\rho }_{\overline{y}}$	0.3	θ2	0.55	${\rho }_{\overline{rr}}$	0.0135
Equilibrium Real Interest Rate		Money Demand		${\sigma }_{\overline{z}}$	0.05
$\overline{rr}$	3	δ1	1	σygap	0.2
${\rho }_{\overline{rr}}$	0.1	δ2	1.5	σϕnoise	0.09
Equilibrium Real Exchange Rate		δ3	0.3	σπ1	0.08
${\mathrm{\Delta }}_{\overline{Z}}$	−1.5	δ4	1	σs	0.25
${\rho }_{\overline{z}}$	0.8	δ5	0.5	σprem	0.1
Output Gap		$\mathrm{\Delta }\overline{\upsilon }$	0.5	σΔm	0.01
β1	0.85	ρν	0.5	σν	5
β2	0.10	Monetary Policy		${\sigma }_{\mathrm{\Delta }\overline{m}}$	8
β3	0.04	γ1	0.7	σTaylor	0.04
β4	0.1	γ2	2.5	σdev	4
β5	0.1	γ3	0.2
Phillips Curve		γ4	0.25
α1	0.65	ρdev	0.5
α2	0.035
α3	0.11
α4	0.8

View Table

Table 1.

Uruguay: Model Calibration

Parameter	Value	Parameter	Value	Parameter	Value
Potential Output		Uncovered Interest Parity		Shocks (Standard Deviation)
$\mathrm{\Delta }\overline{y}$	3.5	θ1	0.6	${\sigma }_{\overline{y}}$	0.02
${\rho }_{\overline{y}}$	0.3	θ2	0.55	${\rho }_{\overline{rr}}$	0.0135
Equilibrium Real Interest Rate		Money Demand		${\sigma }_{\overline{z}}$	0.05
$\overline{rr}$	3	δ1	1	σygap	0.2
${\rho }_{\overline{rr}}$	0.1	δ2	1.5	σϕnoise	0.09
Equilibrium Real Exchange Rate		δ3	0.3	σπ1	0.08
${\mathrm{\Delta }}_{\overline{Z}}$	−1.5	δ4	1	σs	0.25
${\rho }_{\overline{z}}$	0.8	δ5	0.5	σprem	0.1
Output Gap		$\mathrm{\Delta }\overline{\upsilon }$	0.5	σΔm	0.01
β1	0.85	ρν	0.5	σν	5
β2	0.10	Monetary Policy		${\sigma }_{\mathrm{\Delta }\overline{m}}$	8
β3	0.04	γ1	0.7	σTaylor	0.04
β4	0.1	γ2	2.5	σdev	4
β5	0.1	γ3	0.2
Phillips Curve		γ4	0.25
α1	0.65	ρdev	0.5
α2	0.035
α3	0.11
α4	0.8

With regards to the monetary policy shock, it is well known in the VAR literature that standard identification techniques have a hard time generating an immediate appreciation in response to a policy tightening, what is sometimes referred to as the “exchange rate puzzle.”²¹ The same is true for the case of Uruguay. To ensure consistency between the model and the VAR, we identify the monetary policy shock as a combination of: (i) a positive shock to interest rates, and (ii) a nominal appreciation that is broadly consistent with the model.²² Under the above restrictions the model does a good job of replicating the VAR evidence, as shown in Figure 1.

Uruguay: Impulse Response Functions (Model and SVAR).

Citation: IMF Working Papers 2015, 170; 10.5089/9781513501703.001.A001

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Uruguay: Impulse Response Functions (Model and SVAR).

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Uruguay: Impulse Response Functions (Model and SVAR).

Citation: IMF Working Papers 2015, 170; 10.5089/9781513501703.001.A001

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A second source of calibration is the ability of the model to produce a coherent characterization of recent macro dynamics in Uruguay, e.g., produce estimates of potential output and trend real exchange rates that are consistent with the IMF’s assessments of demand pressures or exchange rate misalignment. Such considerations dictated the choice of parameters and standard deviations for the processes for potential output and the equilibrium real exchange rate. In addition, in the case of some of the standard deviations, the calibration was chosen to allow the model flexibility in matching the data and constructing estimates of unobserved variables. This was the case for the standard deviation to ${\varepsilon }_t^{dev}$, the shock to the deviation between the actual level of interest rates and the level implied by the Taylor rule. The standard deviation of this shock was set sufficiently high so that estimates of the Taylor-implied rates were not overly influenced by the observed interest rates. Finally, in the case of money demand, the calibration was chosen to replicate the joint behavior of interest rates and money growth in recent years.²³

A third source of calibration was the model’s ability to produce a reasonable forecast, in this case a forecast which inflation converges to the target over the medium term (under four years). The assumption is that a return to the target in four years would reflect the policymakers’ preferences about the relative weights to inflation and output stabilization. Producing such a forecast required monetary policy to be somewhat more aggressive (in terms of the response to inflation in the interest rate rule) than what is often assumed in these models.

With regards to money targeting parameter, the degree of MT target adherence γ₄ was set at 0.25. This calibration implies that a 4 percent deviation between realized money growth and its target results in a short-term interest rate that is 100 basis points higher/lower than the rule prescription. We believe this calibration provides a reasonable compromise between the MT framework and the guidance provided by the interest rate rule. We explore an alternative calibration below.

B. Data

The data is quarterly and covers the period 2007-14. The dataset includes GDP, a measure of core inflation, the peso/U.S. dollar exchange rate, the interest rate of one-month BCU securities, the measure of M1+ targeted by the BCU, the mid-point of the M1+ target band, U.S. inflation, and a trade-weighted measure of foreign output. The data set also includes a BCU survey-based measure of inflation expectations (for year on year inflation four quarters ahead, ${\pi }_{4,t}^{Survey}$). This variable is used as a noisy indicator of true (unobserved) model-based expectations. Specifically the model was extended to include the following relationship:

The latter variable helps provide further discipline on the model results, as it forces the model’s interpretation of the data to be broadly consistent with the inflation surveys.

C. Filtration Results

We filter the data set through the model with the help of the Kalman smoother.²⁴ On the basis of the data observed, the calibration of the model and the standard deviations of the shocks, the Kalman smoother produces estimates of: (i) the unobserved variables in the model (measures of potential output, equilibrium real interest rates and real exchange rates, the Taylor-rule-implied interest rate), and (ii) estimates of the shocks. The former are used to construct gap estimates, while the latter estimates can then be used to provide a shock-decomposition of the variables of interest. We provide a brief discussion of each of these in turn.

Figure 2 presents model-based estimates of the output gap, the real exchange rate gap and the real interest rate gap. Starting from a position of considerable slack following the global financial crisis, Uruguay began to experience an expansion in aggregate demand. The output gap became positive and reached a peak of 3 percent in 2011. The expansion in aggregate demand is associated with a large persistent negative real interest rate gap (when the real interest rate is below its equilibrium level) through the pre-MT period. It also coincides with a sustained appreciation of the peso (with the exception of the tapering episode in which the real exchange rate depreciated) and the opening of a sizeable real exchange rate gap with the real exchange rate being above its equilibrium level.

Uruguay: Model-Based Gap Estimates

Citation: IMF Working Papers 2015, 170; 10.5089/9781513501703.001.A001

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Uruguay: Model-Based Gap Estimates

Citation: IMF Working Papers 2015, 170; 10.5089/9781513501703.001.A001

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Uruguay: Model-Based Gap Estimates

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Figure 3 compares the observed short-term interest rate with the “notional” interest rate implied by the interest rate rule. Short-term rates stayed below the rule-implied rate through most of the pre-MT period, consistent with an accommodative monetary policy. Interest rates increased considerably with the adoption of money targeting, though they fell short again at the end of 2014.

Uruguay: Model Filtration Results

Citation: IMF Working Papers 2015, 170; 10.5089/9781513501703.001.A001

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Uruguay: Model Filtration Results

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Uruguay: Model Filtration Results

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Figure 3 also displays the decomposition of yoy inflation dynamics (measured as deviations from the inflation target) in terms of the structural shocks estimated with the Kalman smoother.²⁵ The red line shows the path for inflation. Starting from a two percent deviation by 2009, inflation started to drift up through 2014. The figure shows that monetary policy shocks (the green area) have provided a persistent stimulus to inflation. The worsening external conditions observed since mid 2013 (the increase in emerging market risk premia associated with the tapering episode, and which resulted in the large depreciation of the peso as well as other emerging market currencies) have also contributed.²⁶

Figure 4 provides similar shock decomposition for money target misses, i.e., the deviations between the targeted level of money growth (the center of the target range) and actual money growth. As previously discussed, money growth has fallen below the target over the last few quarters. According to the model, most of the target misses reflect money demand shocks, with monetary policy shocks playing a small role.

Uruguay: Model Filtration Results

Citation: IMF Working Papers 2015, 170; 10.5089/9781513501703.001.A001

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Uruguay: Model Filtration Results

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Uruguay: Model Filtration Results

Citation: IMF Working Papers 2015, 170; 10.5089/9781513501703.001.A001

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D. Projection

Figure 5 presents model-based macro projections for Uruguay starting in 2014:4. Given the path of the economy, the Kalman-smoother-based estimates of the structural shocks and unobserved variables, and a path for external variables, the model is simulated to create macro projections for Uruguay.²⁸ The projection is conditional on the model’s calibration, including the specification of monetary policy. It must be stressed that the projections indicate possible paths for the economy out of a continuum of possibilities. This is the case even if policy behaves according to the policy rule specified in the model, as there is considerable uncertainty regarding the macro shocks and the structure of the economy (including the behavior of money demand).

Uruguay: Baseline Projection

Citation: IMF Working Papers 2015, 170; 10.5089/9781513501703.001.A001

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Uruguay: Baseline Projection

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Uruguay: Baseline Projection

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In light of this uncertainty we present three projections. The first, baseline, projection, is one in which the forecast is purely model-based with the exception of the path of the risk premium term, prem_t, for the period 2015:1-2016:3. This variable has been tuned to capture external financial pressures, corresponding to one fourth (1/4) of the pressures experienced during and following the “taper tantrum” episode (2013:2-2014:4). This judgment is meant to capture our assessment that the external environment for emerging markets may be less favorable going forward, reflecting uncertainties related in part to the normalization of monetary policy in advanced economies. The two alternative projections capture: (i) a pessimistic scenario in which external pressures on the exchange rate are half as big as during the 2013-2014 period, and (ii) a benign scenario in which these pressures are not present at all and the economy benefits from disinflation forces stemming from lower oil prices.²⁹

Figure 5 presents the baseline projection. Starting from a level of around 9 percent in 2014:4, core inflation would decrease and reach 5 percent by end 2019. The inflation path is consistent with a considerable nominal and real appreciation in the short run, which has an immediate disinflationary impact and strengthens the peso further above the equilibrium level, and a subsequent nominal depreciation required to bring the real exchange rate back in line with its equilibrium value. The inflation path also reflects a sustained contraction in aggregate demand, which reduces inflationary pressures and brings GDP below potential.

The projection for inflation, output and the exchange rate is consistent with a large tightening of monetary policy. Short-term rates would increase to close to 15 percent by mid-2015, from an average of 12.5 in 2014:4, and would stay above 14 percent through mid 2016. Interest rates would start to decline as inflation is brought down, and would converge to their long run level of 8 percent by 2019. In addition, money growth would stay below 8 percent for some time, before increasing to closer 9 percent around 2016 as policy is loosened and growth resumes. Given the structure of the model, the deviation between money targets and actual money growth would not weigh on the stance of policy after the first quarter of 2015.

Under the benign scenario (Alt Scenario 1 in the Figure), inflation would fall much faster, reaching 7 percent, one full year before the baseline. The faster decline in inflation would allow for a smaller tightening of interest rates, which would still need to be around 14 percent through much of 2015.³⁰ Money growth would also be lower, due to lower inflation. Note that the effect on the output gap would be similar to the baseline, due to the small value of the interest elasticity in the IS curve (consistent with the level of financial dollarization).

Uruguay: Alternative Scenarios

Citation: IMF Working Papers 2015, 170; 10.5089/9781513501703.001.A001

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Uruguay: Alternative Scenarios

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Uruguay: Alternative Scenarios

Citation: IMF Working Papers 2015, 170; 10.5089/9781513501703.001.A001

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Under the pessimistic scenario (Alt Scenario 2), the disinflation is more protracted and costlier in terms of the increase in interest rates, which must stay above 15 percent until mid 2016. The policy tightening coincides with an increase in money growth relative to the baseline. Again, the path of the output gap does not differ considerably from the other scenarios.

Two conclusions can be drawn from this exercise. One, disinflation is costly when inflation is backward looking and inflation is considerably above target. Second, the path of money growth reflects development in nominal variables and is likely to be uninformative about the stance of policy. It can be higher or lower than the medium term target even though policy is appropriately tight. We explore the money targeting framework in more detail in the exercises below.

E. Money Targeting Analysis

We now present two exercises related to the money targeting framework. These exercises are meant to illustrate the role of: (i) target adherence, and (ii) the design of money targets.

The Role of Target Adherence

Target adherence (γ₄) is one of the key parameters in the framework. Figure 7 plots two interest rates: the observed short-term rate and a counterfactual rate. The latter is generated by simulating the model with the shocks estimated from the filtration exercise but with an alternative calibration in which adherence to money targets is much stronger (γ₄ = 2, instead of γ₄ = 0.25 in the baseline calibration). Under the counterfactual simulation, stronger adherence to money targets would have resulted in much lower interest rates during the last year than those observed. As a result, policy would have become more accommodative, and inflation would have been higher. This exercise highlights that excessive concern with hitting targets can derail the inflation stabilization process (when money growth targets are set too high relative to money demand to be consistent with a disinflation process).

Uruguay: Counterfactual simulation.

Citation: IMF Working Papers 2015, 170; 10.5089/9781513501703.001.A001

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Uruguay: Counterfactual simulation.

Citation: IMF Working Papers 2015, 170; 10.5089/9781513501703.001.A001

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Uruguay: Counterfactual simulation.

Citation: IMF Working Papers 2015, 170; 10.5089/9781513501703.001.A001

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The Design of Money Targets

We conclude the model-based exercise with the analysis of alternative ways of designing money targets. Our assumption in the model is that money targets correspond to a forecast of money demand consistent with the desired interest rate policy. In this case the targets reflect all information available up until time t-1.

We now explore two alternative rules. First, we assume that the policy rule is still as (7) but the setting of the year-on-year money growth target follows a different rule. It is now constant, equal to the long-run money growth:

$\mathrm{\Delta }{\overline{M}}_{4,t|t-1}=\mathrm{\Delta }\overline{M}=\mathrm{\Delta }\overline{y}+\mathrm{\Delta }\overline{\pi }-\mathrm{\Delta }\overline{\upsilon }\mathrm{.}$

The second alternative is the money growth that is targeted by the central bank is the (annualized) quarterly growth rate:

$i_t=i_t^{Taylor}+{\gamma }_4(\mathrm{\Delta }{M}_t+\mathrm{\Delta }{\overline{M}}_{t|t-1})+de{v}_t,$

with the money target set as: $\mathrm{\Delta }{\overline{M}}_{t|t-1}=\mathrm{\Delta }\overline{M}=\mathrm{\Delta }\overline{y}+\mathrm{\Delta }\overline{\pi }-\mathrm{\Delta }\overline{\upsilon }\mathrm{.}$

We simulate a positive shock to velocity growth ${\varepsilon }_t^{\upsilon }$ (a decrease in money demand) and assess the cost of targeting money under three money setting rules. To ensure that the three settings are comparable, we set γ₄ = 2 in the baseline and in the first alternative scenario, and γ₄ = 0.5 in the second alternative scenario. Simulations of the model under the three specifications are presented in Figure 8.

Uruguay: Shock to money demand under alternative money targeting rules

Citation: IMF Working Papers 2015, 170; 10.5089/9781513501703.001.A001

Source: Model-based simulation.

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Uruguay: Shock to money demand under alternative money targeting rules

Citation: IMF Working Papers 2015, 170; 10.5089/9781513501703.001.A001

Source: Model-based simulation.

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Uruguay: Shock to money demand under alternative money targeting rules

Citation: IMF Working Papers 2015, 170; 10.5089/9781513501703.001.A001

Source: Model-based simulation.

• Download Figure
• Download figure as PowerPoint slide

Following the shock, interest rates fall, since we assume that the central bank does not perfectly accommodate the change in money demand. Under the baseline specification, this is a one off as the money target—the money demand forecast for next period—is immediately revised to accommodate the higher growth rate of v. As a result, the effect on the exchange rate and on output and inflation is minimal.

Instead, under the two alternative scenarios, the policy mistake is more costly. Money targets are not revised, so persistent changes in money demand also have more persistent effects on interest rates. The exchange rate depreciates more on impact and output and inflation fluctuate more as a result. Note that the alternative scenario in which the authorities target year-on-year money growth—scenario 1—results in even larger and more persistent policy errors. This is because the same shock has more persistent effects on year on year money demand growth, due to base effects.

The above exercise illustrates that, to the extent money targets are used at all, these need to be set in a way that minimize the costs from policy errors. The best way to minimize these policy errors is to incorporate money demand forecasting in the design of targets. At the very least, money targets need to be set in a way that reduces the risk of base effects leading to and large and persistent policy slippages.