7. MAIN RESULTS AND POLICY IMPLICATIONS
7.1 Main results for the nine SSA countries
In this paragraph we examined the model for each single country; in other words we confronted the model results of SSA – 9 with results for each one of the nine countries separately, block by block. The next tables show the starting point levels – 1990 –, the data of last year – 2005 – and the average of these sixteen years. The complete database is in appendix III of chapter 6.
This approach is important for two reasons; first, because these results support the idea that future research could possibly analize single countries with this model.
Second, it has made possible to identify and measure the improvements and the main policy implications in every single For example: the results of the first block show that the improvement in of 1% point of PR and PS mean the improvement of HCPRI in 0.91 and 1.1 point respectively. This confirmed the results of classical school of human behaviours: as soon as farmers start to feel safe and secure, they also begin to invest more for the future (Skinner and Maslow).
However, PR index shows itself to be much more efficient than PS in a singular analysis; this means that rural population believe more in the future and will invest more in education when they have land rights; only Rwandan population had different trend, but we supposed that the genocides of Rwanda explain this behaviors.
156 On the other hand, when the HCPRI and PR and PS indexes of one country are very low, and PR and or PS had a fast pickup, the HCPRI reacted very well as Malawi, Rwanda and Uganda that had had HCPRI levels below of the SSA – 9 average, and finished in 2005 with numbers higher than the cluster.
Table 7.1: Relationship among PS and PR indexes and HCPRI.
Country PS > HCPRI PR > HCPRI
SSA - 9 1,1 0,91
Burundi -0,17 8,1
Ghana 0,32 1,8
Malawi -18 44
Mozambique 0,4 -0,4
Rwanda 13 -0,0008
Uganda -7 5
Tanzania -3 2,6
Zambia -0,0008 -0,6
Zimbabwe 0,98 4
Source: Calculated by author
Table 7.2: Individual levels of HCPRI, PS and PR.
HCPRI level PS level PR level
Country 1990 2005 average 1990 2005 average 1990 2005 average SSA - 9 54,3 64,9 56,6 3,56 10,44 6,58 4,05 7,40 5,44 Burundi 30,5 41,7 41,4 3,00 9,00 5,94 4,32 4,56 4,55 Ghana 58,8 63,5 60,6 3,00 12,00 7,50 8,29 10,03 8,97 Malawi 43,4 115,1 84,7 1,00 16,00 7,63 1,00 8,61 4,40 Mozambique 57,0 44,6 41,5 3,00 15,00 9,19 2,00 8,19 5,00 Rwanda 43,2 84,8 57,9 3,00 6,00 3,56 3,00 5,27 3,86 Uganda 46,7 76,3 51,0 3,00 6,00 4,69 1,83 8,62 5,17 Tanzania 50,0 40,8 43,0 4,00 9,00 6,06 4,00 8,75 5,97 Zambia 67,6 60,9 64,2 1,00 15,00 9,69 1,00 8,51 3,88 Zimbabwe 94,0 56,2 65,3 11,00 6,00 4,94 11,00 4,06 7,18
Source: Calculated by author
With respect to the second block, the SSA – 9 model, shows that the loss of soil nutrient NPKL changed, when HCPRI, AVA and DCPS increase by one point in the following order: -0,52, -2,9 and -0,68. When we look to each country, it is possible to see different trends mainly in the NPKL, HCPRI and DCPS factors.
157 First of all, as we know NPKL is the collateral effect human intervention and the local natural resources, and NPKL indicate the sustainability of agriculture in the long term.
The human intervention plays a role, but the start point of soil quality is also very important: thus country as Uganda, with a very good soil quality, has a comparative advantages.
HCPRI (human capital) is a social instrument for developing countries, because people with better education tend to produce more farm crops and manage better the NPKL using good agricultural techniques; however the model analyzed only quantitative data and not qualitative levels of education, thus it could happened that two countries with the same numbers had really different levels of human capital.
Furthermore the DCPS is essential tool; in other words it does matter if I have or not access to the credit system.
Table 7.3: Relationship among HCPRI, AVA, GDPPC and NPKL.
Country HCPRI> NPKL AVA> NPKL GDPPC>NPKL DCPS>NPKL
SSA - 9 -0,52 -2,9 0,0025 -0,68
Burundi -0,37 -1,6 -0,47 -0,12
Ghana -0,0009 1 -0,0008 1,9
Malawi 0,23 -1,5 0,35 2,7
Mozambique -0,2 1,5 -0,0008 0,58
Rwanda 2,3 -0,62 -0,0006 -6,6
Uganda 0,23 -0,55 -0,0001 -1,6
Tanzania 0,55 -0,3 0,11 0,19
Zambia -1,6 -0,3 -0,0009 0,92
Zimbabwe 0,0002 -0,15 0,0004 -0,0002
Source: Calculated by author
158 Table 7.4: Individual levels of NPKL, HCPRI and AVA.
NPKL level HCPRI level AVA level
Country 1990 2005 average 1990 2005 average 1990 2005 average SSA - 9 -82,52 -66,61 -78,90 54,3 64,9 56,6 39,5 30,5 35,0 Burundi -153,00 -83,40 -125,28 30,5 41,7 41,4 55,9 34,8 46,4 Ghana -72,75 -63,60 70,35 58,8 63,5 60,6 45,1 40,9 41,7 Malawi -118,80 -75,28 -115,08 43,4 115,1 84,7 45,0 32,6 36,9 Mozambique -28,35 -54,20 -40,15 57,0 44,6 41,5 37,1 27,0 31,5 Rwanda -134,48 -85,58 -131,13 43,2 84,8 57,9 32,5 38,4 39,4 Uganda -82,16 -84,30 -82,51 46,7 76,3 51,0 56,6 26,7 39,9 Tanzania -80,03 -65,04 -75,41 50,0 40,8 43,0 46,0 31,8 40,1 Zambia -21,60 -31,02 -18,63 67,6 60,9 64,2 20,6 23,3 21,7 Zimbabwe -51,50 -57,04 -51,53 94,0 56,2 65,3 16,5 19,2 17,3
Source: Calculated by author
Table 7.5: Individual levels of GDPPC and DCPS.
GDPPC level DCPS level
Country 1990 2005 average 1990 2005 average
SSA - 9 333,36 348,34 292,06 10,54 12,40 12,41
Burundi 199,27 107,87 137,84 8,61 22,27 17,88
Ghana 393,25 489,17 372,18 4,93 15,54 9,00
Malawi 198,99 201,80 184,04 10,95 7,91 8,26
Mozambique 181,88 315,75 208,90 17,59 11,84 13,03
Rwanda 361,43 287,05 256,75 6,92 11,21 8,67
Uganda 242,76 313,60 242,91 0,00 8,63 5,36
Tanzania 167,31 362,54 246,94 13,90 10,18 7,71
Zambia 415,71 609,69 387,33 8,88 7,72 7,02
Zimbabwe 839,66 447,56 591,65 23,04 16,28 34,76
Source: Calculated by author
The third block shows that, when NPKL and INFR increase by one point, this implies a corresponding increase by 0,02 and 0,57 point of API . On the other hand when RPDAL increase by one point, API declines by 0,04 point.
The negative balance of NPK does not mean the slump the API like a cutting axe.
NPKL is slowly weakening the foundations of current production and reducing the changes of future sustainability form an economic and social point of view.
159 INFR has strong and quick effects on API: good roads and rail lines are the main link between regions and have a significant impact to reduce the costs and improve the trade of goods. Furthermore, building infrastructure in marginal areas creates jobs and spreads welfare immediately.
On the other hand, RPDAL should be supported by INFR and influence directly the NPKL; RPDAL without adequate infrastructure the agricultural development could not happen.
Table 7.6: Relationship among NPLK, INFR, RPDAL and API
Country NPKL> API INFR> API RPDAL> API
SSA - 9 -0,0002 0,57 -0,0004
Burundi -0,41 -6,1 -0,39
Ghana -1,3 3 -0,31
Malawi -0,0004 6,4 -0,53
Mozambique -0,81 -2,6 0,0001
Rwanda 0,0005 -0,72 -7
Uganda 0,43 -0,0007 -0,0005
Tanzania 0,32 -16 -0,16
Zambia -0,27 -1,1 0,0002
Zimbabwe -3,6 -0,39 1,1
Source: Calculated by author
Table 7.7: Individual levels of API and NPKL.
API level NPKL level
Country 1990 2005 Average 1990 2005 average
SSA - 9 96,25 97,10 96,44 -82,52 -66,61 -78,90
Burundi 128,68 99,58 110,45 -153,00 -83,40 -125,28
Ghana 55,15 99,97 86,20 -72,75 -63,60 70,35
Malawi 71,13 85,57 87,19 -118,80 -75,28 -115,08
Mozambique 91,80 94,60 93,07 -28,35 -54,20 -40,15
Rwanda 95,54 100,70 95,51 -134,48 -85,58 -131,13
Uganda 112,28 99,89 106,22 -82,16 -84,30 -82,51
Tanzania 92,22 100,34 85,14 -80,03 -65,04 -75,41
Zambia 98,88 100,14 92,85 -21,60 -31,02 -18,63
Zimbabwe 120,59 93,11 111,39 -51,50 -57,04 -51,53
Source: Calculated by author
160 Table 7.8: Individual levels of INFR and RPDAL
INFR level RPDAL level
Country 1990 2005 Average 1990 2005 average
SSA - 9 19,70 23,73 20,51 376,16 408,54 391,10
Burundi 52,03 44,28 50,58 572,40 705,84 617,84
Ghana 16,39 24,56 17,82 352,57 285,99 309,65
Malawi 9,28 14,50 13,49 371,34 376,41 373,35
Mozambique 3,37 4,17 3,72 309,73 303,26 311,31
Rwanda 49,84 53,00 51,13 768,66 645,09 698,20
Uganda 8,29 29,46 11,75 315,25 465,03 393,77
Tanzania 9,46 8,99 9,50 229,37 311,24 277,18
Zambia 4,86 9,04 7,79 209,15 354,22 286,02
Zimbabwe 23,79 25,57 18,85 257,00 229,79 252,65
Source: Calculated by author
The fourth block; the rural poverty line (RPL) decrease very well when PR increase.
The correlation amounting to more than one point of PR resulted in less 3.1 points of RPL, but the other two main factors have a different relationship. When RPDAL and API increased one point, the RPL also increased 0,01 and 0,14 point respectively.
With title quantity of land farmers have more security to work and produce more, can access to credit system and improve their business or yet they can sell their lands and go to the cities. In all these cases the index of RPL will fall.
The negative effect that RPDAL has on RPL was expected; some countries of SSA – 9 have low infrastructure as we saw from the previous block. Furthermore the lack of land tenure system and the high birth rate produced the “micro-land” phenomenon or trap.
However, when the API grew by one point, RPL increased by 0.14. In others words the agricultural growth increased the rural poverty.
By a thorough analysis for each country of the sample, we saw one dichotomy of results: there are countries with low agricultural development but good performance in poverty reduction as Uganda, or countries enjoying the improvement of API but with the rural poverty growing as Malawi.
The role of domestic policies like the one about land tenure, rural credit and infrastructures followed different paths and provided different outputs.
161 Table 7.9: Relationship among API, RPDAL, PR and RPL
Country API> RPL RPDAL>RPL PR>RPL
SSA - 9 0,14 0,0001 -3,1
Burundi -0,51 -0,00005 1,7
Ghana -0,046 0,22 2.3
Malawi 0,33 0,0009 -0,89
Mozambique 0,0003 0,0008 -3,9
Rwanda -0,19 -0,0003 2,4
Uganda 0,34 -0,16 -0,31
Tanzania 0,0004 -0,0004 -0,0005
Zambia -0,0005 -0,0008 -1,3
Zimbabwe 0,0006 -0,9 -3,1
Source: Calculated by author
Table 7.10: Individual levels of RPL and API
RPL level API level
Country 1990 2005 Average 1990 2005 average
SSA - 9 53,43 53,06 57,73 96,25 97,10 96,44
Burundi 36,20 70,68 75,92 128,68 99,58 110,45
Ghana 48,00 20,87 37,09 55,15 99,97 86,20
Malawi 51,70 54,14 59,24 71,13 85,57 87,19
Mozambique 83,90 47,90 66,62 91,80 94,60 93,07
Rwanda 51,70 64,20 61,89 95,54 100,70 95,51
Uganda 65,00 34,20 48,25 112,28 99,89 106,22
Tanzania 41,35 37,74 39,40 92,22 100,34 85,14
Zambia 83,00 76,80 83,12 98,88 100,14 92,85
Zimbabwe 20,00 71,00 48,03 120,59 93,11 111,39
Source: Calculated by author
162 Table 7.11: Individual levels of RPDAL and PR
RPDAL level PR level
Country 1990 2005 average 1990 2005 average
SSA - 9 376,16 408,54 391,10 4,05 7,40 5,44
Burundi 572,40 705,84 617,84 4,32 4,56 4,55
Ghana 352,57 285,99 309,65 8,29 10,03 8,97
Malawi 371,34 376,41 373,35 1,00 8,61 4,40
Mozambique 309,73 303,26 311,31 2,00 8,19 5,00
Rwanda 768,66 645,09 698,20 3,00 5,27 3,86
Uganda 315,25 465,03 393,77 1,83 8,62 5,17
Tanzania 229,37 311,24 277,18 4,00 8,75 5,97
Zambia 209,15 354,22 286,02 1,00 8,51 3,88
Zimbabwe 257,00 229,79 252,65 11,00 4,06 7,18
Source: Calculated by author