Revisiting the monetary conditions index for Bangladesh

Monetary Conditions Index (MCI) is a way of measuring the changes in monetary condition that influences the economic activities. To assess the changes in monetary conditions, central banks calculate MCI that combine the effect of interest rates and exchange rates on the price level and aggregate demand. The weights of interest rate and exchange rate can be obtained employing inflation model or aggregate demand model using the econometric technique. The weights represent the relative impacts of the variables (interest rate and exchange rate) on policy goals. In theory, this calculation allows central banks to monitor the effect of short-term monetary policy by linking changes in interest rates set by central banks with changes to exchange rates influenced by the foreign exchange market. The measure is typically used to help central banks craft monetary policy.

Monetary policy affects economic activities through a series of channels, which are collectively known as the transmission mechanism. Many central banks around the globe, particularly in emerging economies, are entrusted with the responsibilities of pursuing multiple objectives of maintaining price stability, supporting inclusive, equitable, and environmentally sustainable economic growth along with the financial stability. Therefore, central banks pursue monetary policies that might have a fragile commitment to its prime objective i.e. price stability. Assigning multiple objectives to central banks induce them to deemphasize on single transmission channels of monetary policy.

In the implementation of policies, central banks try to affect the final targets of monetary policy (usually inflation and growth) with its policy instruments (such as short-term interest rate) through influencing key financial variables such as interest rates, exchange rates etc., with different lags. But the financial deregulations and innovations (both financial and technological) make it difficult for central banks to follow a single channel of monetary policy.

Thus, not only from the point of view of pursuing multiple objectives but also from the perspective of implementation of monetary policy, it is difficult for central banks to rely on a single channel of transmission. As a result, the MCI is getting higher importance in central banks' thinking. The appeal of the MCI can be seen from two perspectives:

Firstly, the MCI is based on the transmission of monetary policy that combines two main channels with two monetary transmission variables including the interest rate and exchange rate.

Secondly, the primary usefulness of such a composite index is that the signal provided by the underlying variables is clear and more employable.

Interest rate affects output through its impact on the intertemporal consumption and savings decisions of households, as well as the intertemporal investment decisions of firms. Meanwhile, the exchange rate influences output through its impact on the relative price of domestically versus foreign-produced goods. Thus, a combination of interest rates and exchange rates provides a better indicator of policy stance than either variable alone (Freedman 1995).

Bangladesh has adopted a number of measures in the last decade, including financial innovations within the banking system, financial inclusion activities and updating payment technologies that rapidly transformed the landscape of the financial sector. These financial reforms seem to have affected the behavioural pattern of the velocity and hence could cause instability in the underlying money demand relationship with important consequences for the conduct of monetary policy. Technological development led to greater integration of financial markets and facilitates the faster transaction of monetary policy impulses, thereby helping interest rates emerge as a most preferred operating instrument for Bangladesh.

On the external front, with significant trade and financial account openness in the last two decades, Bangladesh economy has become considerably more integrated with the global economy. Despite the dominance of domestic demand, the role of foreign flows in conditioning the growth process in Bangladesh has become important over time. The domestic economy now reflects global economic developments reasonably quickly. A higher degree of trade openness and integration of Bangladesh economy with the rest of the world have also added difficulties in targeting exchange rates, inducing Bangladesh Bank (BB) -- the central bank of Bangladesh -- to increasingly adopt flexible exchange rate regime. As a result, instead of putting increasing reliance on either monetary targeting or exchange rate targeting in the conduct of monetary policy, BB may rely more on an assessment of overall monetary conditions originating from changes in both domestic and external macroeconomic factors.

The most obvious benefit of the MCI is that it is straightforward and easy to understand. In general, two steps are involved to construct the MCI. In the first step, weights of interest rate and exchange rate need to be calculated using some econometric model. The model could be either output model or inflation model. This study relies on output model where the dependent variable is Quantum Index of manufacturing industries (QI) instead of GDP as QI data is available at the monthly frequency (GDP data is available on yearly basis only). The weighted average lending rate is used as a representation of interest rates. We use the nominal exchange rate (dollar per taka) as another variable in the model.

In light of the foregoing, the objectives of the study are to

• Construct MCI in the context of Bangladesh; and

• Identify the extent of interest rate and exchange rate on the MCI.

The study attempts to answers three following questions

• What are the important sources of changes in monetary conditions in Bangladesh?

• How MCI and inflation is moving over time;

• How should we use MCI in explaining the current stance of monetary policy?

Our study contributes to the existing literature on MCI in Bangladesh in several ways. Firstly, in the earlier study, Yonus (2012) estimated the weights of interest rate and exchange rate based on inflation model. However, the effect of interest rate and exchange rate are viewed as equally important influencing output in small open economies (Kannan 2006, Hyder 2006). In this paper, we exploited aggregate demand model to estimate the relative weights of interest rate and exchange rate. Our results suggest that the weight of interest rate and exchange rate is 0.65 and 0.35 respectively. And the estimated monetary conditions ratio is 1.86:1, implying that a 1.0 percentage point rise (100 basis points) in the interest rate or a 1.86 per cent increase (depreciation) in the exchange rate has about the same effects over time on aggregate demand. That implies that the interest rate channel is stronger than the exchange rate channel in influencing monetary conditions in Bangladesh.

Secondly, while calculating MCI, the common practice is to deduct the actual value of interest rate and exchange rate from that of a specified base period. In such case, the movement in MCI (up or down) needs to be compared to that base period. However, few papers also do the deviation of interest rate and exchange rate from their equilibrium levels. For instance, the Czech National Bank (CNB) in their inflation report published in the second quarter of 2015 utilised that technique. MCI that uses the deviation of interest rate and exchange rate from their equilibrium level make it possible to compare the movement of MCI of a specific time point relative to the same time point. This paper tried to estimate the equilibrium level of interest rate and exchange rate by using Hodrick-Prescott (HP) filter as did by CNB and finally obtained MCI values .

Obtained estimates of MCI using the weights of interest rate and exchange rate suggest that in the observed period monetary policy in Bangladesh was mostly expansionary, as reflected by easing monetary condition. The paper also identifies four tight and three soft periods of monetary stance during 2004 to 2020. Furthermore, our findings show that the movements between MCI and inflation are broadly opposite, suggesting that cautionary monetary policy can tame inflation.

LITERATURE REVIEW: Monetary Condition Index was developed in the early 1990 and used as an operational target by the Bank of Canada and Reserve Bank of New Zealand (Neil R. Ericcson et al., 1998). Moreover, many international institutions such as IMF, OECD, Goldman Sachs, JP Morgan, Merrill Lynch, and many others calculates MCI for different countries to track monetary policy stance.

In 1997, Dennis, R. estimated MCI for New Zealand using monthly data over the period 1986-1996. To estimate the effect of real interest rate and real exchange rate on excess demand, the study exploits output gap equations. The result indicated a ratio of interest rate and exchange rate which is approximately 2:1. The findings of this study suggested MCI give a better indication of the monetary policy stance than either variable alone (interest rate and exchange rate).

Hataiseree, R. (1998) constructed MCI for Thailand over the period of January 1990 to July 1998 based on inflation model linking to import price index, agricultural price indices and government fiscal indicator. Their result indicated the ratio of interest rates and exchange rates were 3.3:1. Their study employed autoregressive distributed lagged model as econometric technique. The resultant MCI ratio indicates that 1 percent change of interest rate in monetary stance is offset by 3.3 percent change of exchange rate.

Kesriyeli and Kocaker (1999) generated monetary condition index (MCI) for Turkey using inflation model. Their study incorporates real interest rate and real effective exchange rate while estimating weights. The study suggests that the exchange rate is more sensitive than the interest rate for the monetary transmission channel in Turkey.

Afterwards, in 2002, Abdul Qayyum estimated a monetary condition index (MCI) for Pakistan over the period 1990 to 2001. The study relied on inflation model to estimate the weights of interest rate and exchange rate. The estimated weights of interest rate and nominal exchange rate were 0.736 and 0.264 and in terms of ratio, it becomes 2.79:1. Their resultant MCI indicates that monetary condition was tight during 1997 to 1999.

In another Study, Peng and Leung (2005) calculateed a monetary conditions index (MCI) using quarterly data from 1994Q1 to 2004Q2 for assessing monetary conditions on Mainland China. They estimated two forms of MCI (narrow and board) using real interest rates, real effective exchange rates and credit supply in aggregate demand equation. The estimated MCI suggests easing monetary conditions with an appreciation of the local currency, reducing the interest rate, grew of bank credit which is accelerated to economic growth.

Tobias (2005) developed a monetary condition index for South Africa over the period of 1994Q1-2003Q4. They estimated the weights of real interest rate and real effective exchange rate by least square approach where the output gap was the dependent variable. The study shows the ratio of interest rate and exchange rate was 1.9:1 that means the real interest rate is more influential than the exchange rate on the monetary transmission process for South Africa.

Hyder and Khan (2006) constructed the monetary condition index for Pakistan and relative weights of interest rate and exchange rate have been calculated using Johansen cointegration approach. The estimated MCI found that there were eight tightening and six easing episodes of monetary conditions in Pakistan over the period of 1991 to 2006.

Khannan et al. (2006) estimated monetary condition index (MCI) for India over the period of 1996Q2 to 2007Q1. Their paper constructed broad MCI which derived from credit growth with interest rate and exchange rate channel along with traditional narrow MCI. Their analysis indicates that interest rate is more sensitive than the exchange rate to explain the monetary condition in India.

Similarly, Poon, W. C, et al. (2008) estimated a monetary condition index by examining the relationship among real interest rate, exchange rate, share price and claims on private sector credit with regards real output in Singapore. This study uses ARDL bound test approach to calculate the weight of the selected variable as estimated to MCI ratio. The result of this study indicates that monetary authorities consider MCI indication to take their monetary decision because MCI is significantly interlinked with real output in Singapore. This analysis suggests the MCI will more efficient in inflation targeting regime in Singapore.

Younus, S. (2012) derived Monetary Condition Index (MCI) for Bangladesh using weights of real lending rate and nominal exchange rate through the price equation model over the period of 2004 to 2011. The paper shows the weights of interest rate and the exchange rate was 0.83 and 0.17 respectively and the ratio of these two rates become 4.88:1. It indicates that 1 percentage change in the lending rate would have 4.88 percent offsetting effect on the exchange rate.

Horry, H., et. al. (2018) calculated the monetary condition index for Iran for the period of 1978 to 2012. They used ARDL approach to estimate the weight of MCI variable based on the demand equation. They found the exchange rate is more powerful than the interest rate to influence monetary condition in Iran.

The authors are from the Chief Economist's Unit and the Governor Secretariat of Bangladesh Bank. [email protected]