TABLES
1.
All CPP
Parameters and Data Sources
Table 3. Arable
Land
Statistics (thousands hectares).
Country |
2002 |
2001 |
2000 |
1999 |
1998 |
1997 |
Aver |
Scale |
Weighted-2 |
|
|
2550 |
2450 |
2380 |
2300 |
2250 |
2100 |
2338 |
3 |
6 |
|
BFA |
4348 |
4198 |
4050 |
3900 |
3750 |
3600 |
3974 |
2 |
4 |
|
|
4660 |
4660 |
4634 |
4610 |
4610 |
4610 |
4630 |
2 |
4 |
5.
Reclassification of Model Output
Table 5. Reclassification
of Model Output.
Code |
Rank |
IIASA |
SWAC |
CPPM |
0 |
Very High |
1 |
200001-250000 |
200.7-213.0 |
1 |
High |
2 |
100001-200000 |
213.1-221.2 |
2 |
Good |
3 |
50001-100000 |
221.2-230.6 |
3 |
Medium |
4 |
40001-50000 |
230.6-239.8 |
4 |
Moderate |
5 |
20001-40000 |
239.8-248.0 |
5 |
Marginal |
6 |
10001-20000 |
248.0-257.5 |
6 |
Very marginal |
7 |
1-10000 |
257.5-274.7 |
6.
Summary of Model Data by Administrative Unit
Table 6. Summary
of Model Data by
Administrative Unit.
|
CPPM |
SWAC |
IIASA |
Mean |
3.226154 |
4.741538462 |
3.483077 |
Standard Error |
0.080707 |
0.09798949 |
0.086636 |
Median |
3 |
6 |
3 |
Mode |
1 |
7 |
7 |
Standard Deviation |
2.057627 |
2.498251611 |
2.208791 |
Sample Variance |
4.23383 |
6.241261112 |
4.878758 |
Kurtosis |
-1.12665 |
-1.201308437 |
-0.99117 |
Skewness |
0.116604 |
-0.589203692 |
0.436591 |
Range |
7 |
7 |
7 |
Sum |
2097 |
3082 |
2264 |
Count |
650 |
650 |
650 |
Con. Lev. (95.0%) |
0.158478 |
0.192414703 |
0.170121 |
7.
Parameter Values at the National Scale
Variables |
Country |
|
|
|
E1 |
External Cotton Price |
NA |
NA |
NA |
E2 |
Domestic demand |
15 |
15 |
15 |
E3 |
Risk of public default |
6.40 |
6.80 |
7.60 |
E4 |
Equilibrium budgets and
payments |
2.90 |
2.60 |
2.80 |
E5 |
Risk of inconvertibility
and devaluation |
5.80 |
5.70 |
5.90 |
E6 |
Banking system health |
7.40 |
7.60 |
8.40 |
E7 |
Producer price |
8 |
0 |
16 |
E8 |
Producer price trend |
8 |
0 |
16 |
E9 |
Producer price variance |
8 |
0 |
16 |
E10 |
Foreign direct investment |
4 |
8 |
6 |
P1 |
Arable land in country |
4 |
4 |
6 |
P2 |
Historic cotton area |
NA |
NA |
NA |
P3 |
Irrigated share of
cropland |
6 |
8 |
8 |
|
|
|
|
|
P4 |
Irrigation potential |
NA |
NA |
NA |
P5 |
Tractors |
2 |
2 |
4 |
P6 |
Ginnery capacity |
8 |
4 |
8 |
P7 |
Distance to ginnery |
NA |
NA |
NA |
P8 |
Road condition |
NA |
NA |
NA |
P9 |
Fertilizer use intensity |
9 |
9 |
6 |
P10 |
Landlocked |
13 |
6 |
1 |
P11 |
Energy price |
9 |
12 |
4 |
P12 |
Cattle Distribution |
NA |
NA |
NA |
P13 |
Terrestrial Ecoregions |
NA |
NA |
NA |
P14 |
Precipitation |
NA |
NA |
NA |
P15 |
Problem soils |
NA |
NA |
NA |
S1 |
Population density |
NA |
NA |
NA |
S2 |
Distance to city |
NA |
NA |
NA |
S3 |
Agricultural
researchers |
8 |
12 |
8 |
S4 |
Human Development Index |
20 |
20 |
20 |
S5 |
Rule of Law Index |
12 |
12 |
12 |
S6 |
Political Stability and
Absence of Violence Index |
20 |
20 |
10 |
S7 |
Corruption Index |
13 |
14 |
13 |
S8 |
Agricultural labor
intensity |
15 |
10 |
15 |
8.
Summary of Assets Data
Table 8. Summary
of Assets Data.
|
PHYSICAL |
ECONOMIC |
HUMAN |
MIN |
53.34465 |
45.7 |
65 |
MAX |
182.75351 |
81.69999 |
98.00083 |
MEAN |
123.15695 |
60.38413 |
76.43606 |
STD RANGE |
29.33036 See maps |
7.30344 See maps |
3.33872 See maps |
9.
Descriptive Statistics for All Models
Table 9. Descriptive
Statistics for All
Models.
|
CPPM |
SWAC |
IIASA |
Mean |
3.22 |
4.74 |
3.48 |
Standard Error |
0.08 |
0.10 |
0.09 |
Median |
3 |
6 |
3 |
Mode |
1 |
7 |
7 |
Standard Deviation |
2.06 |
2.50 |
2.21 |
Sample Variance |
4.23 |
6.24 |
4.88 |
Kurtosis |
-1.13 |
-1.20 |
-0.99 |
Skewness |
0.12 |
-0.59 |
0.44 |
Range |
7 |
7 |
7 |
10.
Kappa Indices of Agreement
Table 10. Kappa
Indices of
Agreement.
|
Overall
Kappa |
IIASA |
0.3009 |
SWAC |
0.2683 |
11.
Overall Accuracy (Agreement) of CPPM
Table 11. Overall
Accuracy (Agreement) of CPPM.
|
Cells |
Percentage |
CPPM |
650 |
100.00% |
IIASA |
106 |
16.31% |
SWAC |
41 |
6.31% |
TOTAL |
34 |
5.23% |
12.
ANOVA Test on Models
Table 12. ANOVA
Test on Models.
|
SS |
df |
MS |
F |
P-value |
F crit |
Between Groups |
854.9938 |
2 |
427.49 |
83.52 |
1.57E-35 |
3.00 |
Within Groups |
9964.648 |
1947 |
5.11795 |
|
|
|
Total |
10819.64 |
1949 |
|
|
|
|
13.
Correlation Matrix of Models
Table 12. Correlation
Matrix of Models.
|
CPPM |
SWAC |
IIASA |
CPPM |
1 |
|
|
SWAC |
-0.101615515 |
1 |
|
IIASA |
0.523453153 |
0.265872259 |
1 |
14.
Descriptive Statistics for Model Performance at National Level
Table 14. Descriptive
Statistics for Model Performance at
National Level.
|
|
|
|
|
|
|
BFA |
|
|
|
CPPM |
SWAC |
IIASA |
CPPM |
SWAC |
IIASA |
CPPM |
SWAC |
IIASA |
Mean |
4.46 |
2.74 |
4.52 |
4.27 |
3.90 |
3.78 |
1.72 |
6.06 |
2.78 |
ST Error |
0.10 |
0.15 |
0.16 |
0.19 |
0.26 |
0.25 |
0.07 |
0.08 |
0.10 |
Median |
5 |
2 |
4.5 |
5 |
3 |
3 |
2 |
7 |
3 |
Mode |
5 |
7 |
7 |
5 |
3 |
7 |
1 |
7 |
3 |
STD |
1.68 |
2.48 |
2.57 |
1.66 |
2.31 |
2.23 |
1.24 |
1.31 |
1.67 |
Variance |
2.82 |
6.17 |
6.60 |
2.75 |
5.36 |
4.96 |
1.54 |
1.72 |
2.81 |
Kurtosis |
-0.79 |
-0.72 |
-1.63 |
2.30 |
-1.46 |
-1.25 |
-0.75 |
0.63 |
0.45 |
Skewness |
-0.30 |
0.83 |
-0.26 |
-1.74 |
0.33 |
0.26 |
0.41 |
-1.38 |
0.63 |
Range |
6 |
7 |
7 |
6 |
6 |
7 |
4 |
4 |
7 |
Minimum |
1 |
0 |
0 |
0 |
1 |
0 |
0 |
3 |
0 |
Maximum |
7 |
7 |
7 |
6 |
7 |
7 |
4 |
7 |
7 |
Sum |
1212 |
744 |
1229 |
329 |
300 |
291 |
518 |
1824 |
837 |
Count |
272 |
272 |
272 |
77 |
77 |
77 |
301 |
301 |
301 |
Largest |
7 |
7 |
7 |
6 |
7 |
7 |
4 |
7 |
7 |
Smallest |
1 |
0 |
0 |
0 |
1 |
0 |
0 |
3 |
0 |
CL (95.0%) |
0.20 |
0.30 |
0.31 |
0.38 |
0.53 |
0.51 |
0.14 |
0.15 |
0.19 |
15.
ANOVA Tests for Every Country
Table
15a ANOVA
of models
in
Source of Variation |
SS |
df |
MS |
F |
P-value |
F crit |
Between Groups |
10.24242424 |
2 |
5.121212121 |
1.175052931 |
0.310666 |
3.035441 |
Within Groups |
993.6883117 |
228 |
4.358282069 |
|
|
|
Total |
1003.930736 |
230 |
|
|
|
|
Table
15b ANOVA
of Models
in
Source of Variation |
SS |
df |
MS |
F |
P-value |
F crit |
Between Groups |
557.03186 |
2 |
278.5159 |
53.57697952 |
1.39E-22 |
3.006798 |
Within Groups |
4226.3199 |
813 |
5.198425 |
|
|
|
Total |
4783.3517 |
815 |
|
|
|
|
Table
15c ANOVA
of Models
in BFA
Source of Variation |
SS |
df |
MS |
F |
P-value |
F crit |
Between Groups |
3080.361 |
2 |
1540.181 |
762.0423 |
2.3E-194 |
3.005726 |
Within Groups |
1819.01 |
900 |
2.021122 |
|
|
|
Total |
4899.371 |
902 |
|
|
|
|
16.
Correlation Matrices for Models by Country
Table 16. Correlation Matrices for
Models by
Country
|
|
|
|
|
|
|
|
BFA |
|
|
|||||||||||||||||
Correlation Matrix (R) |
|
|
Correlation Matrix (R) |
|
|
Correlation Matrix (R) |
|
||||||||||||||||||||
|
CPPM |
SWAC |
IIASA |
|
CPPM |
SWAC |
IIASA |
|
CPPM |
SWAC |
IIASA |
|
|||||||||||||||
CPPM |
1.000 |
0.625 |
0.660 |
CPPM |
1.000 |
0.055 |
0.383 |
CPPM |
1.000 |
-0.387 |
0.129 |
|
|||||||||||||||
SWAC |
0.625 |
1.000 |
0.605 |
SWAC |
0.055 |
1.000 |
0.123 |
SWAC |
-0.387 |
1.000 |
0.269 |
|
|||||||||||||||
IIASA |
0.660 |
0.605 |
1.000 |
IIASA |
0.383 |
0.123 |
1.000 |
IIASA |
0.129 |
0.269 |
1.000 |
|
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|
|
|
|
|
|
|
|
|
|
|
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t Statistic |
|
|
|
t Statistic |
|
|
|
t Statistic |
|
|
|||||||||||||||||
|
CPPM |
SWAC |
IIASA |
|
CPPM |
SWAC |
IIASA |
|
CPPM |
SWAC |
IIASA |
|
|||||||||||||||
CPPM |
- |
13.171 |
14.442 |
CPPM |
- |
0.481 |
3.592 |
CPPM |
- |
7.262 |
2.252 |
|
|||||||||||||||
SWAC |
13.171 |
- |
12.493 |
SWAC |
0.481 |
- |
1.074 |
SWAC |
7.262 |
- |
4.826 |
|
|||||||||||||||
IIASA |
14.442 |
12.493 |
- |
IIASA |
3.592 |
1.074 |
- |
IIASA |
2.252 |
4.826 |
- |
|
|||||||||||||||
|
|
|
|
|
|
|
|
|
|
|
|||||||||||||||||
Correlation Significance
(P) |
|
Correlation Significance
(P) |
|
Correlation Significance
(P) |
|||||||||||||||||||||||
|
CPPM |
SWAC |
IIASA |
|
CPPM |
SWAC |
IIASA |
|
CPPM |
SWAC |
IIASA |
|
|||||||||||||||
CPPM |
- |
0.000 |
0.000 |
CPPM |
- |
0.632 |
0.001 |
CPPM |
- |
0.000 |
0.025 |
|
|||||||||||||||
SWAC |
0.000 |
- |
0.000 |
SWAC |
0.632 |
- |
0.286 |
SWAC |
0.000 |
- |
0.000 |
|
|||||||||||||||
IIASA |
0.000 |
0.000 |
- |
IIASA |
0.001 |
0.286 |
- |
IIASA |
0.025 |
0.000 |
- |
|
|||||||||||||||