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25
Jan
2014

Empirical Performance of Monetary Aggregates in BEAC and BCEAO: Unit Root Results

In BEAC, the following variables have no unit root in level: M1D, M2D, CPI, TDBEAC; the same result is achieved by M1, M2, M1D, M2D, CPI and TDBCEAO in the BCEAO. As concern the other variables, test statistics shows that the hypothesis of a unit root cannot be rejected at the one or five percent level after one differencing. According to ADF results, we specify a VAR model in level; in the VAR specification, the differentiated form is taken for the variables which are not stationary in level.
The evaluation is made by the variance decomposition analysis drawing from VAR models. In our specification, we considered Sims’s classic 4-variables VAR, consisting in the interest rate, the logged money supply, the logged price level, and logged real GDP in that order. Table 2 and table 3 report the result of variance decomposition analysis respectively in BEAC and BCEAO. The results in table 2 show that the contribution of monetary aggregate to price level variation is less than 15%. At all horizons, inflation rate is better explained by Divisia M2. However, variance decompositions show that innovations in money explain small percentages of the variance of real GDP; but traditional M2 perform better. Table 3 point out that the contribution of money to inflation and GDP variability is worst in the BCEAO. One exception is the percentage of simple sum monetary aggregate which explain price level variability. In fact, M2 explains 15.65%, 19.40%, 22.18% and 24.55% respectively at 4, 6, 8 and 10 quarters. Figures 13 to 20 present the actual and the forecasted values of price level and real GDP from the alternatives aggregates in each Central Bank. For example, figure 13 compares the forecast of price level from the M1 VAR while figure 14 compares the forecast of real GDP from the M1 VAR in BEAC. Financial services markets

Considering figure 14 specifically, it appears that the two M1 aggregates are similar in their ability to predict real GDP. Also, there is no difference between traditional M1 and Divisia M1 in their capacity to forecast price in BEAC (figure 13).

Table 2: Variance decomposition results, BEAC

Horizon Price Level Real GDP
M1 M1D M2 M2D M1 M1D M2 M2D
4 10.3017 12.6373 8.3768 13.5339 14.9778 11.7257 16.7692 11.8419
6 13.6883 14.1389 13.8017 14.5561 12.3833 11.5384 13.6203 11.4513
8 14.3484 14.2021 14.4780 14.6007 11.4779 11.9837 12.8557 10.5718
10 14.3629 14.3724 14.6090 14.7612 10.3424 12.9290 11.6844 11.5715

Table 3: Variance decomposition results, BCEAO

Horizon Price Level Real GDP
M1 M1D M2 M2D M1 M1D M2 M2D
4 8.2436 0.4422 15.6546 3.3649 2.0627 1.6602 2.1967 1.5199
6 7.2827 0.4190 19.4067 3.5028 2.0833 1.7086 2.1937 1.5174
8 6.2503 0.7283 22.1840 3.4111 2.1032 1.7649 2.1945 1.5242
10 5.3790 1.2286 24.5590 3.2751 2.1136 1.8021 2.1955 1.5276

Figure-13

Figure 13: Price Level Forecasts, M1 BEAC

Figure-14

Figure 14: Real GDP Forecasts, M1 BEAC

Figure-15

Figure 15: Price Level Forecasts, M1, BCEAO

Figure-16

Figure 16: Real GDP Forecasts, M1 BCEAO

Figure-17

Figure 17: Price Level Forecasts, M2 BEAC

Figure-18

Figure 18: Real GDP Forecasts, M2 BEAC

Figure-19

Figure 19: Price Level Forecasts, M2, BCEAO

Figure-20

Figure 20: Real GDP Forecasts, M2 BCEAO

In BEAC, the following variables have no unit root in level: M1D, M2D, CPI, TDBEAC; the same result is achieved by M1, M2, M1D, M2D, CPI and TDBCEAO in the BCEAO. As concern the other variables, test statistics shows that the hypothesis of a unit root cannot be rejected at the one or five percent level after one differencing. According to ADF results, we specify a VAR model in level; in the VAR specification, the differentiated form is taken for the variables which are not stationary in level. The evaluation is made by the variance decomposition analysis drawing from VAR models. In our specification, we considered Sims’s classic 4-variables VAR, consisting in the interest rate, the logged money supply, the

About The Author

Kevin J. Brandon

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