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

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GDPMalawi Kwacha (millions)about 10% each. It is, therefore, expected that tobacco exports and GDP will be highly correlatedas shown in Figure A1.The annual time series for the regression of tobacco exports on GDP covered the period 1968-2006 and the regression results are presented in Table A1. Both variables were I(1) and,accordingly, an error correction model was estimated. ERROR is the error correction term. Thecoefficient of tobacco exports, 20.83184, was used as a weight to compute weighted individualerrors in the trend interpolation of tobacco exports, which in turn are used for adjusting the lineartrend interpolation of GDP.Figure A2 shows actual and interpolated tobacco exports, the difference of which is weightedagainst the calculated coefficient of tobacco exports (20.83184) to adjust the linear trendinterpolation of GDP. The interpolated monthly GDP series is expected to be highly correlatedwith the actual monthly tobacco exports series as shown in Figure A3.Figure A1: GDP and Tobacco Exports for Malawi (1968-2006)500,000450,000400,000350,000300,000250,000200,000150,000100,00050,000GDPTobacco Exports60,00050,00040,00030,00020,00010,000Tobacco ExportsMalawi Kwacha (millions)-1969 1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005-Source: NSO (Malawi)iii | P a g e
TABLE A1: Regression Results of GDP on Tobacco ExportsDependent Variable: GDPCoefficient Std. Error t-Statistic Prob.TOBACCO(-6) 20.83184 1.649441 12.86171 0.0000ERROR(-4) -0.820164 0.283190 2.896157 0.0077R-squared 0.674937Adjusted R-squared 0.635929S.E. of regression 14849.58Durbin-Watson stat 1.413473Figure A2: Tobacco Export (Actual) and GDP (Interpolated)8,0007,0006,0005,0004,0003,0002,0001,0000Tobacco Exports (Actual)Tobacco Exports (Interpolated)1988:1 1990:3 1992:5 1994:7 1996:9 1998:11 2001:1 2003:3 2005:5Source: NSO (Malawi)Figure A3: Tobacco Exports (Actual) and GDP Interpolated (1988:1-2005:12)80007000600050004000Tobacco Exports (Actual)GDP (Interpolated)30002000100001988:1 1990:3 1992:5 1994:7 1996:9 1998:11 2001:1 2003:3 2005:5400000350000300000250000200000150000100000500000Source: NSO (Malawi)iv | P a g e
Page 1 and 2: University of Cape TownSchool of ec
Page 3 and 4: Among the few studies undertaken on
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 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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