The appendix contains the basic parameters of the statistical distributions of commodity prices in both real and nominal terms.
When measuring the variability, or spread, of a data set, two components must be looked at: (1) how spread out are the data observations from the centre, and (2) how fat are the tails. The importance given to this depends on the selected numerical measure. The most common measures of spread are, the variance, and the standard deviation. The variance is the arithmetic average of the squared distance from the mean. Squaring the distance from the mean has the effect of giving greater weight to values that are far out from the mean. The variance can, therefore, be greatly influenced by the nature of the tail. The standard deviation is simply the square root of the variance to express the average deviations in the same units of measurement of the variables.
A complementary description of the data includes skewness and kurtosis. Skewness is a measure of symmetry. A data set, or distribution, is symmetric if it has a similar shape to the left and right of a centre point. The skewness of a normal distribution is zero. Negative values for the skewness indicate that observations are skewed leftwards, or that the left tail is heavier than the right tail. The indication here is that there were more episodes of downward spikes than upward spikes in commodity prices for periods with heavier left tails. For example, in decade 3, the distribution of real sunflower prices exhibit skewness of 0.3 down from 0.6 during decade 2. Therefore, sunflower prices showed more episodes of price declines in decade 3 than decade 2. Positive skewness, on the other hand, indicates more upward spikes (episodes of rising prices) than negative ones. For example, nominal wheat prices display a negative skewness in decade 2, and a positive one in decade 3. Hence, nominal wheat prices exhibit a higher frequency of rising prices in the decade 3. In real terms, six out of the eighteen price exhibit higher frequencies of declining prices in the decade 3 than in the decade 2. None of the series shows negative skewness in decade 1.
Kurtosis measures whether the price distribution is peaked or flat in comparison to a normal distribution^{[20]}. Data sets with low kurtosis tend to have a flat top near the mean instead of sharp peaks which characterizes higher kurtosis values. Real rice prices in the decade 3 had a flatter distribution than in decade 2 indicating that large swings in prices where common in decade 2 relative to decade 3. In both real and nominal terms, substantial kurtosis was observed for maize in the decade 3. This implies that large price movements were common for maize in decade 3 relative to the other two decades
Table App. II1: Basic Statistics, by decade
Decade 
Variable 
Mean 
Std Dev 
Coeff. Of 
Skewness 
Kurtosis 
1970/80 
banana n 
216.8 
64.9 
29.9 
0.6 
0.6 

banana r 
543.5 
89.0 
16.4 
0.5 
0.0 

cocoa n 
1777.9 
1202.5 
67.6 
0.7 
1.0 

cocoa r 
3970.1 
1765.4 
44.5 
0.9 
0.2 

coffee n 
2219.8 
1412.4 
63.6 
1.2 
0.8 

coffee r 
5159.0 
2172.5 
42.1 
1.9 
4.1 

cotton n 
1243.3 
438.2 
35.2 
0.0 
1.4 

cotton r 
3059.3 
666.7 
21.8 
1.7 
2.9 

jute n 
322.7 
57.9 
17.9 
1.0 
0.2 

jute r 
845.0 
201.4 
23.8 
0.3 
1.4 

maize n 
98.6 
26.7 
27.1 
0.4 
0.8 

maize r 
226.2 
51.8 
22.9 
0.4 
0.7 

palmoil n 
466.0 
164.8 
35.4 
0.1 
1.2 

palmoil r 
1028.6 
247.7 
24.1 
1.3 
1.8 

rapeoil n 
496.7 
170.7 
34.4 
0.0 
0.5 

rapeoil r 
1108.4 
299.0 
27.0 
1.3 
1.7 

rapeseed n 
263.6 
81.3 
30.8 
0.3 
0.6 

rapeseed r 
592.2 
148.5 
25.1 
1.2 
0.9 

rice n 
285.4 
127.2 
44.6 
0.6 
0.0 

rice r 
682.2 
254.6 
37.3 
2.0 
3.3 

rubber n 
676.0 
271.5 
40.2 
0.5 
0.5 

rubber r 
1641.9 
344.7 
21.0 
1.1 
2.1 

sisal  n 
476.6 
271.9 
57.0 
0.9 
0.0 

sisal r 
1141.2 
553.3 
48.5 
1.6 
1.5 

soybeans n 
237.9 
69.5 
29.2 
0.0 
0.1 

soybeans r 
540.2 
149.1 
27.6 
2.4 
9.0 

soymeal n 
196.3 
68.9 
35.1 
1.5 
5.4 

soymeal  r 
451.0 
181.5 
40.3 
3.4 
14.5 

sugar n 
243.4 
198.8 
81.7 
2.5 
7.4 

sugar r 
595.4 
424.3 
71.3 
2.5 
7.1 

sunflmeal n 
153.3 
44.8 
29.2 
0.8 
2.4 

sunflmeal r 
353.6 
118.6 
33.5 
2.6 
8.4 

tea n 
1532.3 
607.3 
39.6 
1.7 
3.7 

tea r 
3802.9 
892.6 
23.5 
2.4 
8.4 

wheat n 
123.5 
43.8 
35.5 
0.1 
1.0 

wheat r 
284.0 
87.5 
30.8 
1.7 
2.5 







1980/90 
banana n 
406.3 
83.4 
20.5 
1.2 
2.2 

banana r 
557.4 
104.4 
18.7 
0.7 
0.1 

cocoa n 
2060.1 
428.7 
20.8 
0.3 
0.6 

cocoa r 
2882.9 
769.7 
26.7 
0.1 
0.5 

coffee n 
2892.9 
569.4 
19.7 
0.9 
1.2 

coffee r 
4031.8 
990.4 
24.6 
0.2 
0.3 

cotton n 
1625.3 
319.7 
19.7 
0.4 
0.3 

cotton r 
2254.3 
524.6 
23.3 
0.3 
1.1 

jute n 
361.1 
138.7 
38.4 
2.5 
5.8 

jute r 
507.7 
247.0 
48.6 
2.7 
6.4 

maize n 
112.8 
22.6 
20.0 
0.3 
0.5 

maize r 
154.5 
42.2 
27.3 
0.1 
1.1 

palmoil n 
448.4 
157.0 
35.0 
0.9 
0.5 

palmoil r 
622.5 
273.7 
44.0 
0.9 
0.2 

rapeoil n 
454.1 
124.7 
27.5 
0.9 
0.6 

rapeoil r 
626.1 
232.4 
37.1 
1.0 
0.1 

rapeseed n 
267.5 
58.7 
21.9 
0.1 
0.0 

rapeseed r 
369.1 
115.3 
31.2 
0.1 
0.7 

rice n 
294.4 
92.7 
31.5 
1.0 
0.2 

rice r 
404.1 
132.7 
32.8 
1.0 
0.4 

rubber n 
997.3 
203.3 
20.4 
1.2 
0.8 

rubber r 
1379.5 
313.5 
22.7 
0.8 
0.5 
1980/90 
sisal  n 
594.5 
85.8 
14.4 
1.3 
1.1 

sisal r 
822.7 
145.6 
17.7 
0.4 
0.1 

soybeans n 
259.6 
43.1 
16.6 
0.6 
0.6 

soybeans r 
351.0 
71.6 
20.4 
0.5 
0.5 

soymeal n 
219.3 
41.8 
19.1 
0.4 
0.4 

soymeal  r 
294.4 
56.1 
19.0 
0.5 
0.3 

sugar n 
236.6 
168.3 
71.1 
1.9 
3.7 

sugar r 
320.9 
224.0 
69.8 
2.0 
3.6 

sunflmeal n 
143.2 
38.5 
26.9 
0.3 
0.5 

sunflmeal r 
193.7 
58.6 
30.3 
0.6 
0.9 

tea n 
2131.0 
564.5 
26.5 
1.8 
2.8 

tea r 
2991.0 
1035.2 
34.6 
1.6 
2.0 

wheat n 
149.2 
23.1 
15.5 
0.5 
0.7 

wheat r 
203.2 
39.8 
19.6 
0.4 
1.2 







1990/00 
banana n 
480.5 
104.3 
21.7 
0.7 
0.5 

banana r 
514.0 
115.3 
22.4 
0.7 
0.3 

cocoa n 
1340.0 
226.5 
16.9 
0.0 
0.9 

cocoa r 
1434.4266.9 
18.6 
0.5 
0.5 


coffee n 
2095.6 
805.6 
38.4 
0.9 
0.1 

coffee r 
2238.4 
860.0 
38.4 
0.9 
0.2 

cotton n 
1632.6 
307.1 
18.8 
0.3 
0.0 

cotton r 
1741.3 
306.7 
17.6 
0.1 
0.5 

jute n 
329.7 
80.7 
24.5 
0.6 
0.6 

jute r 
351.1 
80.2 
22.8 
0.5 
0.8 

maize n 
111.2 
23.9 
21.5 
2.0 
4.9 

maize r 
118.1 
24.1 
20.4 
1.6 
3.7 

palmoil n 
477.6 
125.7 
26.3 
0.3 
1.3 

palmoil r 
509.1 
139.1 
27.3 
0.4 
0.9 

rapeoil n 
507.2 
100.2 
19.8 
0.1 
1.3 

rapeoil r 
541.5 
117.1 
21.6 
0.2 
1.2 

rapeseed n 
248.9 
47.4 
19.0 
0.0 
1.5 

rapeseed r 
265.7 
55.1 
20.7 
0.0 
1.3 

rice n 
285.5 
41.6 
14.6 
0.1 
0.3 

rice r 
304.1 
44.4 
14.6 
0.2 
0.5 

rubber n 
993.4 
66.9 
6.7 
0.2 
1.0 

rubber r 
1061.2 
71.4 
6.7 
0.2 
0.5 

sisal  n 
700.4 
109.6 
15.6 
0.2 
0.6 

sisal r 
749.0 
121.5 
16.2 
0.3 
0.3 

soybeans n 
250.6 
33.7 
13.5 
0.5 
0.2 

soybeans r 
267.1 
39.4 
14.8 
0.2 
0.5 

soymeal n 
205.5 
40.0 
19.5 
0.6 
0.2 

soymeal  r 
218.8 
43.8 
20.0 
0.6 
0.2 

sugar n 
234.7 
51.3 
21.9 
0.1 
0.4 

sugar r 
251.0 
55.6 
22.2 
0.1 
0.1 

sunflmeal n 
116.8 
24.5 
21.0 
0.2 
0.7 

sunflmeal r 
124.3 
26.3 
21.2 
0.3 
0.7 

tea n 
2002.6 
334.3 
16.7 
1.1 
1.6 

tea r 
2147.0 
409.0 
19.0 
1.2 
2.1 

wheat n 
146.4 
32.2 
22.0 
1.1 
1.3 

wheat r 
155.5 
32.3 
20.8 
0.7 
0.8 
(rreal, nnominal)
^{[20]} The kurtosis for a
normal distribution is 3. 