GEOGRAPHY INDEX
FIDCI VS HDI V
FOOD IN DEVELOPING COUNTRIES INDEX & THE HUMAN DEVELOPMENT INDEX
by elena lie
N O I T C U D O INTR According to the United Nations Development Program, development is the process of economic, social and political development leading to an improved quality of life for the inhabitants. The Food In Developing Countries Index directly relates to the first United Nations Millennium Development Goal, which is to eradicate extreme poverty and hunger as well as reduce child mortality. FIDCI is a composite index that includes three different aspects; proportion of undernourished in the population, population in multidimensional poverty and agricultural land. According to the Food and Agriculture Organization, food security exists when all people, at all times, have physical and economic access to sufficient, safe and nutritious food to meet their dietary needs and food preferences for an active and healthy life. The index is meant to merge three interconnected food-related issues of undernourishment, poverty and scarcity of land that are present in developing countries. The FIDCI will then be evaluated against the Human Development Index (HDI), which is composed of life expectancy, literacy, education and standards of living. Hypothesis I predict countries with higher HDI value to score poorer in the Food In Developing Countries Index as development and food security go hand in hand. Therefore, I predict that as the value of the HDI increases, the value of the FIDCI will decrease, creating a negative correlation between the two index.
1) The proportion of undernourished in the population (2010-2012) was extracted from the Global Hunger Index report published in 2013. The data set simply divides the number of undernourished people in the population from the total number of population. Undernourishment is defined as having insufficient food or other substances for good health and condition (Oxford English Dictionary). I chose this set of data because undernourishment is directly related to the access of food and nutrition, which is what this index is meant to measure. 2) The population in multidimensional poverty (2007-2010) from the Human Development Report 2013 divides the number of people in the population living under multidimensional poverty from the total number of population. The three dimensions taken into account in the index is health, education and living standards. Since food is one of the basic necessities and the top priority for those living under poverty, it’s an important indicator for a country’s development in terms of its food resources. 3) The % of agricultural land (2009) was taken from the Human Development Report 2013. I want to find out on how developed a country can be when a large percentage of its land is used for agricultural purposes, instead of industries, parks, residences, etc. With more agricultural land should indicate more resources being used to produce food, and should therefore be sufficient enough to support its population.
METHOD Finding the countries I used the developing countries that are represented in Li Po Chun United World College in the academic year of 2013-2014. If the data for any of the developing country represented in the college is unavailable, I simply exclude it from the index. Combining the data After attaining the value for each of the components, ranking them is the next step. In order to rank them accordingly, I decided to rank each component in the FIDCI with 1 as the most developed and 30 as the least developed. For the HDI, I have decided to rank 1 as the least developed and 30 as the most developed.
MAP OF 30 COUNTRIES REPRESENTED IN THE INDEX
D AT A Table 1 Values and ranking for three components of FIDCI 1) The proportion of undernourished in the population 2) The population in multidimensional poverty 3) The % of agricultural land 1
Rank
2
Rank
3
Rank
1
Rank
2
Rank
3
Rank
1
Argentina
4.0
7
2.9
2
51.3
11
16
Nepal
15.0
13
44.2
16
29.6
26.5
2
Armenia
3.0
6
0.3
1
61.6
7
17
Nicaragua
20.1
17
28.0
13
42.8
17
3
Bangladesh
16.8
14
57.8
22
70.3
5
18
Nigeria
8.5
9
54.1
20
81.8
2
4
Burundi
73.4
30
84.5
29
83.7
1
19
Pakistan
1.9
3
49.4
18
34.1
25
5
China
11.5
11
12.5
7
56.2
9
20
Philippines
17.0
15
13.4
8.5
40.1
20.5
6
Colombia
12.6
12
5.4
4
38.3
23
21
Rwanda
28.9
20
69.0
26
81.1
4
7
Egypt
1.6
2
6.0
5
3.7
30
22
Senegal
20.5
18
74.4
27
49.4
13
8
Ethiopia
40.2
27
87.3
30
35.0
24
23
Sierra Leone
28.8
19
77.0
28
47.4
15
9
Guatemala
30.4
21.5
25.9
12
41.0
19
24
South Africa
2.9
5
13.4
8.5
81.7
3
10
Haiti
44.5
28
56.4
21
66.8
6
25
Tanzania
38.8
25
65.6
25
40.1
20.5
11
India
17.5
16
53.7
19
60.5
8
26
Thailand
7.3
8
17.1
10
38.7
22
12
Indonesia
8.6
10
20.8
11
29.6
26.5
27
Timor Leste
38.2
26
68.1
24
25.2
29
13
Kenya
30.4
21.5
47.8
17
48.1
14
28
Turkey
0.9
1
6.6
6
50.6
12
14
Mexico
2.1
4
4.0
3
52.9
10
29
Zambia
47.4
29
64.2
23
31.5
28
15
Namibia
33.8
23.5
39.6
15
47.1
16
30
Zimbabwe
32.8
23.5
39.1
14
42.4
18
D AT A Table 2 Values and ranking of FIDCI and HDI Central & South America
Europe
Asia & the Pacific
FIDCI
Rank
HDI
Rank
d
d2
Africa
FIDCI
Rank
HDI
Rank
d
d2
55.5
21.5
0.463
9
-13
156
1
Argentina
20
5
0.811
30
25
625
16
Nepal
2
Armenia
14
1
0.729
27
26
676
17
Nicaragua
47
15
0.743
28
13
169
3
Bangladesh
41
11
0.515
12.5
2
2
18
Nigeria
31
7
0.471
10
3
9
4
Burundi
60
25
0.355
1
-24
576
19
Pakistan
46
14
0.515
12.5
-2
2
5
China
27
6
0.699
24
18
324
20
Philippines
44
13
0.654
21
8
64
6
Colombia
39
9
0.719
25
16
256
21
Rwanda
50
17
0.434
5
-12
144
7
Egypt
37
8
0.662
22
14
196
22
Senegal
58
24
0.470
6
-18
324
8
Ethiopia
81
30
0.396
3
-27
729
23
Sierra Leone
62
26
0.359
2
-24
576
9
Guatemala
52.5
18.5
0.581
17
-2
2
24
South Africa
16.5
2
0.629
19.5
18
306
10
Haiti
55
23
0.456
8
-15
225
25
Tanzania
70.5
27
0.476
11
-16
256
11
India
43
12
0.554
15
3
9
26
Thailand
40
10
0.690
23
13
169
12
Indonesia
47.5
16
0.629
19.5
4
12
27
Timor Leste
79
28
0.576
16
-12
144
13
Kenya
52.5
18.5
0.519
14
-5
20
28
Turkey
19
4
0.722
26
22
484
14
Mexico
17
3
0.775
29
26
676
29
Zambia
80
29
0.448
7
-22
484
15
Namibia
54.5
20
0.608
18
-2
4
30
Zimbabwe
55.5
21.5
0.397
4
-18
306
CORRELATION BETWEEN FIDCI AND HDI Zambia
Ethiopia
The graph illustrates a dubious negative correlation as most points are quite far from the line of best fit.
Timor Leste
Tanzania
To test the significance and strength of the correlation between the two indexes, a Spearman rank was used:
SPEARMAN RANK ÎŁd2=7927 | n=30
1Nigeria
6 x ÎŁd2 n (n2-n)
1- 6 x 7927
30(302-30)
= - 0.822 (3 sf) South Africa
Looking at diagram 1, we can see that there is a significant negative correlation between FIDCI and HDI.
Diagram 1 Range of Significant Results
-1.0
significant negative correlation
-0.7
limited negative correlation
-0.5
no significance
0
+0.5
limited +0.7 positive correlation
significant positive correlation
+ 1.0
A N A LY S I S Relationship The significant negative correlation between the Food In Developing Countries Index (FIDCI) and the Human Development Index (HDI) supports my hypothesis as shown by the Spearman rank and the graph. Food, as the basic necessity of survival, without a doubt plays an important role in development. With the majority if not all of the population with access to food, the country is capable in developing more effectively on other aspects of development, thus supporting the relationship predicted of as the FIDCI decreases, the HDI will increase. The Spearman rank indicates that there is a clear significant negative relationship between the two indexes, which successfully quantifies the correlation present between food development in a certain country and their human development.
i. The Proportion of Undernourished in the Population Undernourishment, being the first component of the index, only occurs when one fails to attain sufficient amount of nutrition from the food they are consuming, where it is most likely not getting access to food in the first place. In the case where food is not accessible, health is being compromised, and education, environment and job stability will be postponed. In this component, Turkey is ranked first, whereas Burundi is ranked last. Countries located in Africa with the exception of South Africa, Egypt and Nigeria, ranked quite poorly in undernourishment. We can also see a geographical trend in Asia, where undernourishment is also an issue faced by quite a number of the population, with the exception of Pakistan and Thailand, with 1.9% and 7.3% of the population undernourished. Central and South America’s stance is also quite similar to Asia’s, with the exception of Argentina and Mexico, with 4% and 2.1% of the population respectively. Europe on the other hand, ranked incredibly well in the undernourishment component, with Armenia and Turkey ranking 3% and 0.9% respectively. Countries that score relatively well in the undernourishment component tends to be more inclined towards commercial agriculture, where if they would export their crops as well as import food instead of subsistence agriculture, which is supporting themselves at a minimum level, which at most times can lead to undernourishent. ii. The Population in Multidimensional Poverty With small income, prioritizing spending would be crucial, and even though food is supposedly one of the top priorities, economically developing regions are hypothesized to score poorer in the FIDCI index in comparison to the HDI. In this index, the proportion of population living in multidimensional poverty is most dominant in Ethiopia with 87.3%, whereas Armenia is ranked first in this particular component. In the overall FIDCI index, Ethiopia is ranked last, whereas Armenia is ranked first. We can see a direct relationship between living under poverty and not being able to afford the food, with food security itself. We can see from this component that as more of the population live in multidimensional poverty, food security would not be as secure.
A N A LY S I S iii. Percentage of Land Used for Agriculture The percentage of land being utilized for agriculture should act as a positive thing for food accessibility in a certain area, but at most cases is supported to be quite the opposite in terms for development. Burundi, who scored poorly in the first and second component with the rankings 30 and 29 respectively, scored first in the third component with 83.7% of the land being used for agriculture. To further support the point, Egypt, who scored very well in the first two components with rankings 2 and 5 respectively, scored last in agricultural land with a mere 3.7% of the land being used for agriculture. The trend continues for most of the countries in the index, excluding South Africa, Armenia and China, where all three components are ranked at more or less the same value. The geographical location and climate in Egypt isn’t really suitable for agriculture, in contrast with Burundi’s suitable climate and geographical location for agriculture, making it easier for a large percentage of its land to be utilized for agriculture
Anomalies Even though there is a significant negative correlation in FIDCI and HDI as shown in the graph, there are data points that are too far off from the trendline, whether it being more or less than the line of best fit. The negative correlation is shown to be dubious, instead of a perfect or good correlation, as the data points don’t quite follow the trendline, and they’re quite spread out. However, there’s no significant anomaly that completely goes against the trend that the best-fit line illustrates. Below the best fit line Nigeria and South Africa are both much below the best-fit line. Nigeria is quite an interesting case, where they ranked quite high in the first and third component but quite poorly in the second component, multidimensional poverty. 40% of Nigeria’s economy is strongly linked with agriculture as they are blessed with a geographical location of diversed and fertile land suitable for vegetation. Even though a large portion is focused on food, they are struggling with keeping up with the rapid population growth, which forces them to import food and face a decline in crop exports, causing them to rank poorly in the poverty component. However, Nigeria is moving towards a growing urban population, and a lot of exports and imports of good, particularly food in this case, which can assist with food security in the country. It is clear that in this case both South Africa and Nigeria are both developing at a better rate in FIDCI compared to HDI. Above the best fit line Ethiopia, Zambia, Tanzania and Timor Leste, on the other hand, all score relatively high in the FIDCI, where they are meant to score much lower for the HDI value that they have, with the relationship shown by the best fit line. This shows that the development of food security in these four countries aren’t developing as well as the indicators in the HDI.
CO N C L U S I O N How does it relate to HDI? Food security, as previously mentioned played a huge role in development, as it is directly connected with the first UNMDP, which is to eradicate poverty and hunger. There aren’t any anomalies because of the strong correlation between the HDI and FIDCI. This is mainly because food is such an integral part of development, which makes it an important fundamental for other aspects of development. Furthermore, Criticizing my index The reliability of Food In Developing Countries Index (FIDCI) can be questioned, as a lot of the variables aren’t being kept constant. The most important variable is time, because the components involved in making the index are spread from the time range of 2007-2012, which is quite stretched out. The component regarding multidimensional poverty covers a wide range of years from 2007-2010 of attaining the statistics, making time an inconsistent variable, as aspects connected to development such as economics, politics and society change as time differs, thus directly affecting the data. The components involved in the index can also be well criticized, as they might not be quite relevant to the topic of food in developing countries. For instance, multidimensional poverty might not be directly linked to food itself, and could instead be substituted with perhaps the amount of meat consumed or amount of food waste produced. The interrelation between the three components can be strengthened and improved. The index in general, however presents a strong set of thirty data points showcasing countries from four different regions, which is a pretty decent sample size, making it a relatively reliable index.
Bibliography "Multidimensional Poverty Index." Wikipedia. Wikimedia Foundation, 12 Aug. 2013. Web. 09 Dec. 2013. <http://en.wikipedia.org/wiki/ Multidimensional_Poverty_Index>. Malik, Khalid. Human Development Report 2013. Rep. N.p.: n.p., n.d. United Nations Development Report. Web. 09 Dec. 2013 Von Grebmer, Klaus. Global Hunger Index 2013. Rep. Washington, DC: International Food Policy Research Institute, 2013. Web. Dec.-Jan. 2013. <http://www.ifpri.org/sites/default/files/publications/ghi13.pdf>. "Factors That Affect the Distribution of Agriculture." A-level Geography Agriculture Revision -. N.p., n.d. Web. 09 Dec. 2013. <http://www.scool.co.uk/a-level/geography/agriculture/revise-it/factors-that-affect-thedistribution-of-agriculture>. "Geography - Rural Poverty Portal." Rural Poverty Portal. N.p., n.d. Web. 07 Dec. 2013. <http://www.ruralpovertyportal.org/ar/country/geography/tags/ nigeria>. "Geography of Agriculture." About.com Geography. N.p., n.d. Web. 09 Dec. 2013. <http://geography.about.com/od/urbaneconomicgeography/a/ aggeography.htm>. "Food Security." Wikipedia. Wikimedia Foundation, 12 May 2013. Web. 07 Dec. 2013. <http://en.wikipedia.org/wiki/Food_security>. "Visited Countries Map." Visited Countries Map. N.p., n.d. Web. 09 Dec. 2013. <http://www.ammap.com/visited_countries/index.php>. A. Rae (2006) Using Spearman’s Rank Correlation. GeoFile.