Probabilistic Approach to Assessing Macroeconomic Uncertainties

PRAMU

ESRC/ORA Project

Inflation uncertainty for Japan


Data for all graphs and tables can be downloaded here

 

1. Figure 1. Minimum distance characteristics of fitted TPN and WSN distributions to U-uncertainties

MD-Japan

WSN fits better than TPN, especially for medium and long horizons.

 

2. Figure 2. Term structure of the compound strength of forecast-induced monetary policy

Strength-Japan

The compound strength is computed as: Strength=|\alpha|\cdot D_m+|\beta|\cdot D_k, where D_a=\int_{|a|}^\infty t^2\varphi(t)dt=1-\Phi(|a|)+|a|\varphi(a). In the policy-input symmetric case, where m=-k (and this is the assumption applied for empirical estimation), the multipliers D_a can be ignored.

 

3. Table 1. Forecast uncertainty measures

h th.uncert RMSE(u) std(v) UR NUR
1 0.0294 3.45 3.08 1.61 0.71
2 0.0658 3.57 3.13 1.55 0.685
3 0.11 5.5 5.51 2.03 0.895
4 0.161 6.09 6.15 2.07 0.912
5 0.218 6.48 6.3 1.91 0.843
6 0.281 6.88 6.76 1.95 0.862
7 0.348 7.79 7.58 1.91 0.844
8 0.42 8.74 8.45 1.89 0.835
9 0.497 9.7 9.85 2.09 0.922
10 0.577 9.98 9.72 1.92 0.847
11 0.662 9.88 9.47 1.86 0.821
12 0.75 12.6 12.6 2.02 0.893
13 0.817 11.5 11.7 2.1 0.927
14 0.868 1 1 2.02 0.893
15 0.907 1 1 2.02 0.893
16 0.937 1 1 2.02 0.893
17 0.96 1 1 2.02 0.893
18 0.976 1 1 2.02 0.893
19 0.987 1 1 2.02 0.893
20 0.994 1 1 2.02 0.893
21 0.998 1 1 2.02 0.893
22 1 1 1 2.02 0.893
23 1 1 1 2.02 0.893
24 1 1 1 2.02 0.893

 

4. Figure 3. Ex-post and ex-ante inflation fan charts

japan_ea japan_ep
Ex-ante uncertainty           Ex-post uncertainty

 

Data for all graphs and tables can be downloaded here