A. The Transmission of Shocks

Recall that this paper seeks to investigate the role of monetary policy in softening the impact of the global financial crisis on the Malaysian economy. To help foster model intuition, it would be useful to focus on three shocks associated with the crisis and explore how they were transmitted to Malaysia. These shocks are: a collapse in foreign demand, distress across international capital markets, and heightened uncertainty. An overview of how these shocks are propagated within our model is discussed below in turn.

B. What Role for Monetary Policy?

In our model, the central bank alters interest rates in an attempt to achieve certain policy objectives. Before proceeding to the details, note that the policy rule to be described below implies that the monetary authority sets the nominal interest rate, taking into consideration the inflation rate deviation from the time-varying inflation objective, the output gap, the rate of exchange rate depreciation, and the previous period’s interest rate (policy smoothing).

A simplified version of the empirical interest rate rule takes the following (log-linear) form (for further details, see Alp and Elekdag, 2011):

where in this flexible specification, ${\hat{i}}_t,{\hat{\mathit{\Pi }}}_{t+1},{\hat{y}}_t,{\hat{s}}_t$ denote the (short-term policy) interest rate, the (core CPI) inflation rate, the output gap, and the nominal exchange rate, respectively. Note that ${\mathit{\in }}_{\mathit{t}}^{\mathit{i}}$ denotes the monetary policy shock—interest rate changes that deviate from the (empirical) interest rate rule would be captured by this disturbances and could be considered discretionary monetary policy. The time-varying inflation objective, ${\hat{\mathit{\Pi }}}_t^T$, is assumed to evolve according to the following stochastic process:

The time-varying inflation objective has also been used in the literature to capture structural changes in the conduct of monetary policy that are not captured otherwise (see Adolfson and others, 2007, for further details).

Anticipating the results to follow, notice that when the output gap is negative—that is, output is below potential—strict adherence to the rule above would imply that the interest rate decreases by an amount dictated by the coefficient, τ_y. However, the monetary authority (BNM) might decrease interest rates by more than what the systematic component of the rule would imply. Recall that this deviation from the rule is capture by the error term, ${\in }_t^i$, which is the monetary policy shock—thereby capturing discretionary monetary loosening. As will be discussed in further detail below, during the most intense episode of the global financial crisis, interest rates decreased by more than the amount the empirical counterpart of the rule would have implied, helping soften the impact of the global financial crisis.

C. The Monetary Transmission Mechanism

Before continuing, it might be useful to provide an overview of how monetary policy is transmitted throughout the economy. Reviewing the monetary transmission mechanism would also provide further insight regarding the dynamics of the model. Countercyclical monetary policy is propagated via three main channels in the model; for illustrative purposes, consider an interest rate increase:

• The first channel operates as interest rates affect domestic demand, which is primarily comprises consumption and investment. Working through the Euler equation, higher real interest rates foster an increase in saving as consumption is postponed to later periods. At the same time, higher real interest rates increase the opportunity cost of investment, decreasing the rate of capital accumulation. As a result, domestic demand decreases, putting downward pressure on inflation.

• The second channel brings out the open economy features of the model as it works via the exchange rate. Because of the nominal rigidities, the increase in the nominal interest rate translates into higher real interest rates and is associated with an increase in the real exchange rate. In turn, this appreciation of the real exchange rate suppresses net exports (the expenditure switching effect), further decreasing aggregate demand.

• The third channel is characterized by the financial accelerator mechanism. Higher interest rates depress asset prices (the real price of capital) bringing about a deterioration in net worth. Weaker balance sheet fundamentals cause an increase in the external finance premium thereby raising the opportunity cost of investment above and beyond the initial effect generated by the monetary tightening. This brings about an even sharper contraction in investment, which is the primary determinant of the deeper contraction. As discussed in further depth in other papers, the financial accelerator mechanism can amplify the effects of certain shocks (Bernanke, Gertler, and Gilchrist, 1999).

A. Data

The log-linearized model is estimated using Bayesian methods popularized by Smets and Wouters (2003, 2007). The model is estimated using quarterly data covering the years 2000–2010 using 12 standard time series, a few of which are shown in Figure 1. Specifically, in line with many other studies, we have chosen to match the following set of variables: the levels of the domestic policy and foreign interest rates, the inflation rates of domestic GDP deflator and core consumer price and foreign consumer price indices, as well as the growth rates of GDP, consumption, investment, exports, imports, foreign GDP, and the real exchange rate.

B. Model Parameters

We followed the literature and calibrate certain parameters (see, for example, Christiano and others, 2010), which could be thought of as infinitely strict priors. Many of the parameters are chosen to pin down key steady state ratios characterizing the Malaysian economy (including trade openness, as measured by, for example, the exports-to-GDP ratio), while the remaining parameters are taken from the literature as summarized in Table 1.

Table 1.

Calibrated Parameters

Source: Authors’ calculations.

Table 1.

Calibrated Parameters

Parameter	Symbol	Value
Discount factor	β	0.9988
Consumption intra-temporal elasticity of substitution	ρ	1.00
Share of domestic goods in consumption	γ	0.05
Investment intra-temporal elasticity of substitution	ρi	0.25
Share of domestic goods in investment	γi	0.05
Inverse of the elasticity of work effort with respect to the real wage	σι	1.00
Share of capital in production function	α	0.80
Elasticity of marginal depreciation with respect to utilization rate	ε	1.00
Steady state markup rate for domestically produced goods	μH	1.15
Steady state markup rate for imported goods	μF	1.15
Steady state markup rate for wages	μw	1.15
Share of entrepreneurial labor	1–Ω	0.01
Steady state external finance premium	χ	1.03
Number of entrepreneurs who survive each period (at steady state)	ϱ	0.9728
Variance of idiosyncratic shock to entrepreneur production	σω	0.40
Fraction of monitoring cost	μω	0.15
Depreciation rate (at steady state)	δ	0.0225
Elasticity of country risk premium with respect to net foreign debt	Φ	0.001

Source: Authors’ calculations.

View Table

Table 1.

Calibrated Parameters

Parameter	Symbol	Value
Discount factor	β	0.9988
Consumption intra-temporal elasticity of substitution	ρ	1.00
Share of domestic goods in consumption	γ	0.05
Investment intra-temporal elasticity of substitution	ρi	0.25
Share of domestic goods in investment	γi	0.05
Inverse of the elasticity of work effort with respect to the real wage	σι	1.00
Share of capital in production function	α	0.80
Elasticity of marginal depreciation with respect to utilization rate	ε	1.00
Steady state markup rate for domestically produced goods	μH	1.15
Steady state markup rate for imported goods	μF	1.15
Steady state markup rate for wages	μw	1.15
Share of entrepreneurial labor	1–Ω	0.01
Steady state external finance premium	χ	1.03
Number of entrepreneurs who survive each period (at steady state)	ϱ	0.9728
Variance of idiosyncratic shock to entrepreneur production	σω	0.40
Fraction of monitoring cost	μω	0.15
Depreciation rate (at steady state)	δ	0.0225
Elasticity of country risk premium with respect to net foreign debt	Φ	0.001

Source: Authors’ calculations.

The remaining 43 parameters, shown in Table 2, are estimated. These parameters determine the degree of the real and nominal rigidities, the monetary policy stance, as well as the persistence and volatility of the exogenous shocks. The table shows the assumptions pertaining to the choice of distribution, the means, standard deviations, or degrees of freedom. The choice of priors is in line with other studies (see Alp and Elekdag, 2011, for a selected review of the literature). The posterior estimates of the variables are shown in the same table, which reports the means along with the 5^th and 95^th percentiles of the posterior distribution of the estimated parameters obtained through the Metropolis-Hastings sampling algorithm. In general, the parameter estimates are in line with those found in other studies. We also considered a few robustness exercises, which, for example, consider different monetary policy regimes (for example, a fixed exchange rate regime)—overall results are decisively in favor of the baseline.

Table 2.

Prior and Posterior Distributions

Source: Authors’ calculations. Note: Log data density is 1,265. For inverse gamma distributions, mean and degrees of freedom are reported.

Table 2.

Prior and Posterior Distributions

Parameter			Prior distribution			Posterior distribution
Description		Symbol	Type	Mean	Standard deviation	Mean	Confidence 5%	interval 95%
Calvo parameter
	Domestic prices	θH	Beta	0.50	0.10	0.859	0.824	0.891
	Import prices	θF	Beta	0.50	0.10	0.498	0.411	0.574
	Wages	θw	Beta	0.50	0.10	0.456	0.307	0.624
Indexation
	Domestic prices	γH	Beta	0.50	0.10	0.377	0.261	0.504
	Import prices	γF	Beta	0.50	0.10	0.502	0.365	0.641
	Wages	γw	Beta	0.50	0.10	0.521	0.346	0.676
Monetary policy
	Interest rate smoothing	ρι	Beta	0.70	0.20	0.862	0.825	0.904
	Inflation reponse	τπ	Normal	1.50	0.20	1.921	1.665	2.123
	Output gap response	τy	Beta	0.20	0.10	0.011	0.005	0.018
	Nominal exchange rate depreciation response	τs	Normal	0.10	0.05	0.202	0.152	0.272
Others
	Export demand elasticity	χ	Normal	1.00	0.20	0.460	0.227	0.752
	Export demand interia	ϖ	Beta	0.50	0.20	0.712	0.532	0.917
	Habit formation	b	Beta	0.70	0.20	0.890	0.862	0.928
	Invesment adjustment cost	ψ	Normal	4.00	0.50	3.833	3.225	4.352
Shock persistence
	Stationary technology	ρα	Beta	0.80	0.10	0.881	0.841	0.915
	Unit root technology	ρζ	Beta	0.80	0.10	0.371	0.295	0.493
	Investment specific technology	ρinv	Beta	0.80	0.10	0.432	0.307	0.579
	Domestic markup	ρμh	Beta	0.80	0.10	0.609	0.456	0.715
	Import markup	ρμf	Beta	0.80	0.10	0.928	0.898	0.954
	Foreign inflation	ρπ*	Beta	0.80	0.10	0.573	0.463	0.703
	Foreign interest rate	ρi*	Beta	0.80	0.10	0.868	0.785	0.939
	Foreign demand	ρy*	Beta	0.80	0.10	0.984	0.974	0.994
	Country risk premium	ρΦ	Beta	0.80	0.10	0.604	0.429	0.808
	Preference	ρc	Beta	0.80	0.10	0.755	0.638	0.880
	Labor supply	ρl	Beta	0.80	0.10	0.791	0.639	0.948
	Exogenous spending	ρg	Beta	0.80	0.10	0.894	0.829	0.972
	Net worth	ρN	Beta	0.80	0.10	0.945	0.884	0.995
	Inflation target	ρ$\overline{\pi }$	Beta	0.80	0.10	0.706	0.571	0.835
Shock volatility
	Stationary technology	σα	Inverse gamma	0.01	2.00	0.118	0.086	0.157
	Unit root technology	σζ	Inverse gamma	0.01	2.00	0.057	0.044	0.069
	Investment specific technology	σinv	Inverse gamma	0.01	2.00	0.671	0.496	0.811
	Domestic markup	σθH	Inverse gamma	0.01	2.00	0.010	0.009	0.011
	Import markup	σθF	Inverse gamma	0.01	2.00	0.020	0.015	0.027
	Foreign inflation	σπ*	Inverse gamma	0.01	2.00	0.004	0.003	0.005
	Foreign interest rate	σi*	Inverse gamma	0.01	2.00	0.001	0.001	0.002
	Foreign demand	σy*	Inverse gamma	0.01	2.00	0.076	0.061	0.093
	Country risk premium	σΦ	Inverse gamma	0.01	2.00	0.003	0.002	0.004
	Preference	σc	Inverse gamma	0.01	2.00	0.151	0.107	0.203
	Labor supply	σl	Inverse gamma	0.01	2.00	0.007	0.003	0.010
	Exogenous spending	σg	Inverse gamma	0.01	2.00	0.025	0.022	0.029
	Net worth	σN	Inverse gamma	0.01	2.00	0.006	0.003	0.008
	Inflation objective	σ$\overline{\pi }$	Inverse gamma	0.01	2.00	0.005	0.002	0.007
	Monetary policy		Inverse gamma	0.01	2.00	0.002	0.001	0.002

Source: Authors’ calculations. Note: Log data density is 1,265. For inverse gamma distributions, mean and degrees of freedom are reported.

View Table

Table 2.

Prior and Posterior Distributions

Parameter			Prior distribution			Posterior distribution
Description		Symbol	Type	Mean	Standard deviation	Mean	Confidence 5%	interval 95%
Calvo parameter
	Domestic prices	θH	Beta	0.50	0.10	0.859	0.824	0.891
	Import prices	θF	Beta	0.50	0.10	0.498	0.411	0.574
	Wages	θw	Beta	0.50	0.10	0.456	0.307	0.624
Indexation
	Domestic prices	γH	Beta	0.50	0.10	0.377	0.261	0.504
	Import prices	γF	Beta	0.50	0.10	0.502	0.365	0.641
	Wages	γw	Beta	0.50	0.10	0.521	0.346	0.676
Monetary policy
	Interest rate smoothing	ρι	Beta	0.70	0.20	0.862	0.825	0.904
	Inflation reponse	τπ	Normal	1.50	0.20	1.921	1.665	2.123
	Output gap response	τy	Beta	0.20	0.10	0.011	0.005	0.018
	Nominal exchange rate depreciation response	τs	Normal	0.10	0.05	0.202	0.152	0.272
Others
	Export demand elasticity	χ	Normal	1.00	0.20	0.460	0.227	0.752
	Export demand interia	ϖ	Beta	0.50	0.20	0.712	0.532	0.917
	Habit formation	b	Beta	0.70	0.20	0.890	0.862	0.928
	Invesment adjustment cost	ψ	Normal	4.00	0.50	3.833	3.225	4.352
Shock persistence
	Stationary technology	ρα	Beta	0.80	0.10	0.881	0.841	0.915
	Unit root technology	ρζ	Beta	0.80	0.10	0.371	0.295	0.493
	Investment specific technology	ρinv	Beta	0.80	0.10	0.432	0.307	0.579
	Domestic markup	ρμh	Beta	0.80	0.10	0.609	0.456	0.715
	Import markup	ρμf	Beta	0.80	0.10	0.928	0.898	0.954
	Foreign inflation	ρπ*	Beta	0.80	0.10	0.573	0.463	0.703
	Foreign interest rate	ρi*	Beta	0.80	0.10	0.868	0.785	0.939
	Foreign demand	ρy*	Beta	0.80	0.10	0.984	0.974	0.994
	Country risk premium	ρΦ	Beta	0.80	0.10	0.604	0.429	0.808
	Preference	ρc	Beta	0.80	0.10	0.755	0.638	0.880
	Labor supply	ρl	Beta	0.80	0.10	0.791	0.639	0.948
	Exogenous spending	ρg	Beta	0.80	0.10	0.894	0.829	0.972
	Net worth	ρN	Beta	0.80	0.10	0.945	0.884	0.995
	Inflation target	ρ$\overline{\pi }$	Beta	0.80	0.10	0.706	0.571	0.835
Shock volatility
	Stationary technology	σα	Inverse gamma	0.01	2.00	0.118	0.086	0.157
	Unit root technology	σζ	Inverse gamma	0.01	2.00	0.057	0.044	0.069
	Investment specific technology	σinv	Inverse gamma	0.01	2.00	0.671	0.496	0.811
	Domestic markup	σθH	Inverse gamma	0.01	2.00	0.010	0.009	0.011
	Import markup	σθF	Inverse gamma	0.01	2.00	0.020	0.015	0.027
	Foreign inflation	σπ*	Inverse gamma	0.01	2.00	0.004	0.003	0.005
	Foreign interest rate	σi*	Inverse gamma	0.01	2.00	0.001	0.001	0.002
	Foreign demand	σy*	Inverse gamma	0.01	2.00	0.076	0.061	0.093
	Country risk premium	σΦ	Inverse gamma	0.01	2.00	0.003	0.002	0.004
	Preference	σc	Inverse gamma	0.01	2.00	0.151	0.107	0.203
	Labor supply	σl	Inverse gamma	0.01	2.00	0.007	0.003	0.010
	Exogenous spending	σg	Inverse gamma	0.01	2.00	0.025	0.022	0.029
	Net worth	σN	Inverse gamma	0.01	2.00	0.006	0.003	0.008
	Inflation objective	σ$\overline{\pi }$	Inverse gamma	0.01	2.00	0.005	0.002	0.007
	Monetary policy		Inverse gamma	0.01	2.00	0.002	0.001	0.002

Source: Authors’ calculations. Note: Log data density is 1,265. For inverse gamma distributions, mean and degrees of freedom are reported.

A. Setting Up the Counterfactual Simulations

Recall that this paper is trying to assess the role of the BNM’s monetary policy framework in terms of mitigating the impact of the global financial crisis on the Malaysian economy.

Though intimately related, the model allows us to separately investigate the contributions of countercyclical interest rate policy and exchange rate flexibility in terms softening the impact of the crisis. Therefore, in what follows, we consider three counterfactual simulations and compare them with the actual realization which is our baseline. Under the baseline, the monetary policy framework (which is underpinned by a flexible exchange rate) operates in accordance with estimated baseline interest rate rule discussed above. In this context, the three counterfactual experiments are as follows:

• No monetary policy shocks: this counterfactual posits strict adherence to the baseline empirical interest rate rule. It is a simulation which excludes the monetary policy shocks—that is, the monetary policy shocks, ${\mathit{\in }}_{\mathit{t}}^{\mathit{i}}$, are all set to zero in this simulation. It serves to address the following question: What would the dynamics of output have been if the BNM did not implement any discretionary loosening (deviations from the interest rate rule) during the crisis?

• Peg: in this counterfactual, the BNM is assumed to implement a strict fixed exchange rate regime. Intuitively, there are no discretionary deviations from the rule (which solely focuses on stabilizing the nominal exchange rate). Here we seek to address the following question: What would the dynamic of output growth have been if the BNM was implementing a fixed exchange rate regime?

• Peg with heightened financial vulnerability: under the last counterfactual, the BNM is presumed to operate under a fixed exchange rate regime as above, but with heightened financial vulnerabilities (achieved by calibrating the leverage ratio to three, rather than two under the baseline, see Alp and Elekdag, 2011, for further details). While not the main focus of the paper, our modeling framework allows us to construct such an illustrative counterfactual serving to address the following question: What would the dynamic of output growth have been if the BNM was implementing a fixed exchange rate regime and the economy was financially more vulnerable?

B. Results Based on the Counterfactual Simulations

Figure 2 depicts the level of real GDP with the first quarter of 2008 (the pre-crisis peak) normalized to 100 to allow the reader to better distinguish the (cumulative) effects of each counterfactual. To further highlight the main results, the figure starts in 2006, and only shows the counterfactuals over the 2008:Q1–2009:Q3 period (full set of results available from authors upon request). The figure depicts (1) the actual realization of real GDP (the baseline scenario), (2) the counterfactual scenario without the monetary policy shocks, (3) the counterfactual scenario with the fixed exchange rate regime (peg), and (4) an illustrative counterfactual scenario with the peg under heightened financial vulnerabilities.

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Counterfactual Scenarios: The Role of Monetary Policy and Real GDP

Citation: IMF Working Papers 2012, 035; 10.5089/9781463933203.001.A001

Source: Authors’ calculations.Note: Figure denotes the level of real GDP as an index with 2008Q1=100.Baseline denotes the actual evoluation of Malaysian real GDP.

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As clearly seen from Figure 2, the BNM’s current monetary policy framework underpinned by a flexible exchange rate regime clearly softened the impact of the global financial crisis of 2008-09. More specifically, it is useful to discuss two main results:

• First, as expected, output growth declines the most under the fixed exchange rate regime. The lack of the exchange rate to serve as a shock absorber decreases the resiliency of the economy to the shocks that ensued during the global crisis. Intuitively, the illustrative counterfactual experiment with heightened financial vulnerabilities, and thereby a more pronounced balance sheets channel, leads to an even sharper decline in output. These counterfactual experiments highlight the role of the exchange rate flexibility as well as financial reforms that promote the soundness of the financial system. However, it should be noted that—consistent with BNM guiding principles—the simulations assume orderly exchange rate adjustments. Also, given the experience during the height of the global financial crisis, a significantly weak exchange rate may not necessarily lift export performance given exceptionally weak external demand.

• Second, as discussed in the previous section, there is an important role for the discretionary departure from the interest rate rule, which helped soften the impact of the crisis. At first glance, while they may seem small, as we discuss in further detail in the next subsection, the role of these discretionary departures from the interest rate rule (the monetary policy shocks) are very much in line with the literature.

C. How Do Our Results Compare with Those in the Literature?

We now focus on the growth implications associated with the counterfactuals discussed above. This section tabulates the precise contributions to growth under the various counterfactuals discussed above, which are shown in Table 3. As before, the intention is to focus on the most intense period of the global financial crisis, which for Malaysia covered the four quarters spanning the 2008:Q4–2009:Q3 period.

Table 3.

The Role of Monetary Policy during the Global Financial Crisis of 2008–09

Source: Authors’ calculations. Note: Growth contributions in percent.

Table 3.

The Role of Monetary Policy during the Global Financial Crisis of 2008–09

			Growth contributions of monetary policy owing to:
			[ 1 ]	[ 2 ]	[ 3 ]	[ 4 ]
		Quarters	Monetary policy shocks	Flexible exchange rate regime	Reduced financial vulnerability	All factors ([ 1 ]—[ 3 ])
Average
	2008Q4—2009Q3	4	0.51	1.96	0.63	3.23
Christiano and others (2008)
	United States (2001Q2-2002Q2)	4	0.75
	Euro area (2001q4-2004q4)	13	1.27
Cumulative
	2008Q4—2009Q3	4	2.05	7.82	2.53	12.93
Christiano and others (2008)
	United States (2001Q2-2002Q2)	4	3.00
	Euro area (2001q4-2004q4)	13	17.00

Source: Authors’ calculations. Note: Growth contributions in percent.

View Table

Table 3.

The Role of Monetary Policy during the Global Financial Crisis of 2008–09

			Growth contributions of monetary policy owing to:
			[ 1 ]	[ 2 ]	[ 3 ]	[ 4 ]
		Quarters	Monetary policy shocks	Flexible exchange rate regime	Reduced financial vulnerability	All factors ([ 1 ]—[ 3 ])
Average
	2008Q4—2009Q3	4	0.51	1.96	0.63	3.23
Christiano and others (2008)
	United States (2001Q2-2002Q2)	4	0.75
	Euro area (2001q4-2004q4)	13	1.27
Cumulative
	2008Q4—2009Q3	4	2.05	7.82	2.53	12.93
Christiano and others (2008)
	United States (2001Q2-2002Q2)	4	3.00
	Euro area (2001q4-2004q4)	13	17.00

Source: Authors’ calculations. Note: Growth contributions in percent.

Before investigating the details, it would be useful to clarify the information contained in Table 3. The values under columns show either the average or cumulative contributions to growth during the 2008:Q4–2009:Q3 period. It presents our results, as well as the results of Christiano and others (2008)—the most closely related study to ours in terms of conducting counterfactual experiments. After tabulating the number of quarters, columns [1] through [4] indicate the incremental contribution to growth owing to the consecutive implementation of each policy. For example, Column [3] indicates that reducing financial vulnerabilities added, on average, 63 basis points to growth. In addition to this effect, the incremental growth contribution of adopting a flexible exchange rate regime, denoted under column [2], is 1.96 percentage points.

It would be useful to compare the results in Table 3 with the literature. Turning our attention to column [1], we see that the average contribution of the monetary shocks (discretionary deviations from the empirical interest rate rule) to output growth is about 77 basis points, which lies in between the values found by Chrisitiano and others (2007) for the U.S. (0.75 percent) and the euro area (1.27 percent). The cumulative growth contributions also seem reasonable, and give some further context on the role of monetary policy in terms of softening the impact of the crisis.

Table 4 summarizes our main findings. During the year covering 2008:Q4–2009:Q3, the actual growth rate was–2.9 percent. Our model-based simulations suggest that if the BNM had not departed from the empirical interest rate rule, growth would have instead been–3.4 percent. Furthermore, if instead of the current monetary policy regime, an exchange rate peg was in place, the results imply a growth rate of–5.5 percent. In sum, without the adoption of the flexible exchange rate regime, and active countercyclical monetary policy, the impact of the recent global financial crisis would have been substantially more severe.

Table 4.

Summary of the Role of Monetary Policy

Source: Authors’ calculations Note: Table presents real GDP growth rates (year-over-year, in percent).

Table 4.

Summary of the Role of Monetary Policy

	2008Q3—2009Q3	Difference	Cumulative Difference
Baseline (actual)	–2.9
No monetary policy shocks	–3.4	–0.5	–0.5
Fixed exchange rate regime (peg)	–5.5	–2.1	–2.6
Peg with heightened financial vulnerability	–6.1	–0.6	–3.2

Source: Authors’ calculations Note: Table presents real GDP growth rates (year-over-year, in percent).

View Table

Table 4.

Summary of the Role of Monetary Policy

	2008Q3—2009Q3	Difference	Cumulative Difference
Baseline (actual)	–2.9
No monetary policy shocks	–3.4	–0.5	–0.5
Fixed exchange rate regime (peg)	–5.5	–2.1	–2.6
Peg with heightened financial vulnerability	–6.1	–0.6	–3.2

Source: Authors’ calculations Note: Table presents real GDP growth rates (year-over-year, in percent).

While our results suggest that the current monetary policy framework underpinned by a flexible exchange rate supported growth during the global financial crisis, clearly other policies also played a role. It should be noted that we do not capture the direct effects of other measures implemented in response to the crisis including the provision of liquidity in the financial system, the backing of wholesale lending, and the reduction in reserve requirements.³ During a severe economic crisis like the one seen during the 2008-09 global financial crisis, interest rate cuts by themselves may not be enough. Rather, complementary measures need to be introduced to reach specific sectors of the economy. Hence, in addition to easing interest rates and the measures noted above, the authorities’ introduced a number of targeted measures to ensure continued access to financing, temporary extension of safety net, safeguarding the value of wealth and real income of deposits and cushioning highly vulnerable borrowers from the full impact of the crisis. Therefore, the results from the counterfactual scenarios on the extent to which BNM policies help soften the crisis could be viewed as conservative estimates.