Dynamic Effects of Monetary Policy Shocks in Malawi* - African ...

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1.0. INTRODUCTIONWhile it is generally agreed that monetary policy can significantly affect both real economicactivity and prices in the short run and only prices in the long run, considerable debate remainsabout how monetary policy shocks are transmitted. Views differ in the emphasis placed onmoney, credit, interest rates, exchange rates, asset prices and the role of commercial banks andother financial institutions (Taylor, 1995). The differences are prevalent even in individualindustrialized countries where the topic has been a subject of research for many years. Indeveloping countries, the process is even more uncertain (Kamin, Turner, & Van't dack, 1998).In spite of the prominence given to monetary policy, the transmission process in a typicaldeveloping country is not well understood (Montiel, 1991). One of the typical developingcountries, Malawi, is no exception.Monetary policy plays a very important role in the management of the Malawi economy. Asoutlined in the Reserve Bank of Malawi (RBM) Act of 1989, one of the principal objectives ofthe central bank is to influence money supply, credit availability, interest rates and exchangerates in order to ultimately promote economic growth, employment and price stability (MalawiGovernment, 1989). Achieving this objective clearly requires an understanding of the processthrough which monetary policy affects economic activity. There is, however, no study that weare aware of that has quantitatively measured the transmission process of monetary policy inMalawi. This study, therefore, contributes to the literature by filling this gap. The study isolatesmonetary policy autonomous disturbances from other shocks, quantifies their dynamic behaviourand measures the consequent macroeconomic implications using a structural vectorautoregressive model (SVAR) with short run restrictions. Within the same framework, the studyalso assesses how the country‟s monetary policy transmission process was altered by RBM‟smigration from direct to indirect tools of monetary control in the late 1980s and 1990s.Since Sims‟ (1980) pioneering work, vector autoregression models (VARs) are consideredbenchmarks in econometric modelling of monetary policy transmission (Borys & Horvath,2007). While natural experiments would be ideal, the real world does not provide for this optionand SVARs are the only other place where experiments can be performed (Christiano,Eichenbaum, & Evans, 1998). SVAR experiments aimed at measuring the effect of monetarypolicy on economic activity have traditionally involved setting apart monetary policy shocks andtracking the response of macroeconomic variables to the monetary policy impulses.Most studies that have applied SVARs to study the dynamic behaviour of monetary policyshocks have used developed market economies as case studies (Karame & Olmedo, 2002;Bernanke & Mihov, 1998; Sims & Zha, 1998; Bernanke & Mihov, 1996; Piffanelli, 2001). Inrecent years, there has been growing attention on emerging market economies of Latin America,Asia and Easten Europe (Borys & Horvath, 2007; Vonnak, 2005; Disyatat & Vongsinsirikul,2003; Dabla-Norris & Floerkemeier, 2006) and on Australia (Berkelmans, 2005; Brischetto &Voss, 1999). In contrast, quasi-emerging market economies (QEMEs), particularly in subsaharanAfrica, have attracted very little attention.2 | P a g e
Among the few studies undertaken on QEMEs, Mutoti (2006) employed a cointegrated structuralVAR identified with short run and long run restrictions to model the monetary transmissionprocess of post-liberalisation Zambia. Using monthly data for the period 1992-2003, he foundout that much of the output volatility in the country is attributable to aggregate supply shocks,with IS shocks turning to be the most important demand factors for the business cycle. He alsonoted that money demand shocks modestly boost short run output. He further established that inthe short run, changes in consumer prices are accounted for by aggregate supply, money demandand exchange rate shocks whilst at longer horizons, they are mainly underlined by aggregatesupply shocks and modestly by foreign price shocks. The study concluded that a very smallproportion of output variance is due to monetary policy shocks.In a study of Kenya, Maturu (2007) used a structural VAR to argue that interest rate andexchange rate channels are unambigously important channels of monetary policy transmission inthe country besides the traditional money channel. On this basis, he pointed out that there ispotential for signalling monetary policy using the REPO interest rate. In another study of Kenya,Cheng (2006) also used a structural VAR to examine the impact of monetary policy shocks onoutput, prices and the nominal effective exchange rate for the country during the period 1977-2005. Cheng found out that an exogenous increase in the short term interest rate is followed by adecline in prices and an appreciation of the nominal exchange rate, but has insignificant impacton output. He further showed that variations in short term interest rates account for significantfluctuations in the nominal exchange rate and prices, while accounting little for outputfluctuations.In the case of Malawi, there are two theoretical studies, one by Bolnick (1991) and another byPhiri (2002), and no empirical analysis on the country‟s monetary transmission process. TheBolnick study was carried out at the time RBM was converting from direct to indirect tools ofmonetary management. The study investigated how the changing conditions would weaken oralter links in the country‟s monetary transmission process. Unfortunately, Bolnick was unable topredict the emergence of a reasonably competitive financial sector within the foreseeable futureand consequently concluded erroneously that after RBM‟s implementation of indirect monetarycontrols, the transmission of monetary policy shocks in Malawi would be stage-managed by thecentral bank through informal consultations with commercial bank managers. Phiri‟s study, onthe other hand, is not very useful as it falls short of going beyond a theoretical exposition oftextbook transmission channels of monetary policy. For instance, he presents the other assetprice effects channel operating through an efficient stock market as one of Malawi‟s monetarytransmission channels. However, with only eight listed companies at the time of the study, it iscommon knowledge that the Malawi Stock Exchange (MSE) was still is in its infancy to act as aconduit of monetary transmission. As at the end of June 2009, the MSE had 15 listed companiesand was still classified as „infant.‟The rest of the paper is organised as follows. Section 2 is an overview of monetary policy inMalawi since independence in 1964. A methodological framework characterising structuralVARs, identification of the structural shocks, data sources, variable definitions and measurement3 | P a g e
Page 1: University of Cape TownSchool of ec
Page 5 and 6: Interest Rate (Percent)In line with
Page 7 and 8: 3.2. Identification of Structural S
Page 9 and 10: The non-zero coefficients and in ma
Page 11 and 12: only the price level in the long ru
Page 13: long-run relationships in a linear
Page 16 and 17: Percent(RM-Innovations)Percent (BR-
Page 18 and 19: Figure 4.4 also shows that an expan
Page 20 and 21: Table 4.1 also reveals that the dif
Page 22 and 23: To determine the importance of the
Page 24 and 25: FIGURE 4.7: Impulse Responses for t
Page 26 and 27: Figure 4.9:Responses to Structural
Page 28 and 29: ates) is re-estimated with the samp
Page 30 and 31: TABLE 4.2: Variance Decomposition -
Page 32 and 33: authorities pursue both price stabi
Page 34 and 35: Dabla-Norris, E., & Floerkemeier, H
Page 36 and 37: APPENDIX AInterpolation of GDP usin
Page 38 and 39: GDPMalawi Kwacha (millions)about 10
Page 40 and 41: APPENDIX BB-1.0. Data PropertiesCoi
Page 42 and 43: Table B1: Stationarity ResultsVaria
Page 44 and 45: Table B3: Johansen Cointegration Te
Page 46 and 47: APPENDIX CTABLE C1: Roots of Charac
Page 48 and 49: APPENDIX CTABLE C3: Structural VAR
Page 50 and 51: APPENDIX CTABLE C5: Roots of Charac
Page 52 and 53:
APPENDIX DFIGURE D1:Impulse Respons
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