Food security vulnerability in South Africa. Case study Limpopo

Food security vulnerability in South Africa Case study Limpopo Content I. II. III. IV. V. Project introduction Methodology General results Food sec...
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Food security vulnerability in South Africa Case study Limpopo

Content I. II. III. IV. V.

Project introduction Methodology General results Food security determinants Policy priorities

Content I. II. III. IV. V.

Project introduction Methodology General results Food security determinants Policy priorities

Different actors & partners

Objectives • Identify the factors influencing food security (vulnerability) at household level and at municipality level • Compute a Food Security Index (FSI) based on four major components:

AVAILABILITY

ACCESSIBILITY

UTILISATION

STABILITY

Objectives lead to… • Development of an accessible assessment tool to measure food security vulnerability • Policy advice and new strategies related to food security

Content I. II. III. IV. V.

Project introduction Methodology General results Food security determinants Policy priorities

Methodology • Data source and collection: – Secondary data – Surveys (field data collection) • Survey on food security & determinants • Survey background information, municipality level

 Qualitative and quantitative data

Overview questionnaire 1. Survey identification 2. Household demographics 3. Food availability & consumption 4. Agricultural production 5. Household income & expenditure 6. Characteristics of household 7. Stresses, shocks & coping strategies

Limpopo N

Musina Mutale

Vhembe Thulamela

Makhado

Blouberg

N1 Greater Giyani Greater Letaba Aganang Mogalakwena

Lephalale

Molemole

Capricorn

Waterberg

Mopani Greater Tzaneen

Ba-Phalaborwa

Polokwane Maruleng

Thabazimbi

Fetakgomo Ñ

Legend Road N1 Municipality Boundaries District Boundaries

Lepelle-Nkumpi

Modimolle

Mookgopong

Bela-Bela

Makhudutamaga

Bohlabela

Tubatse Bushbuckridge

Sekhukhune

Marble Hall

Groblersdal

Communities District Rates 15% - 20% 20%

25

0

25

50

75 Kilometers

Scale 1 : 2 500 000

Data collection (28/07- 13/08) DISTRICT

MUNICIPALITY 1

MUNICIPALITY 2

Capricorn

Blouberg (60)

Molemole (60)

Total: 120 surveys Mopani Total: 120 surveys Sekhukhune Total: 120 surveys Vhembe Total: 120 surveys Waterberg Total: 120 surveys

 data collection  data entry Giyani (60)

4 enumerators + 1 student 1 student

Tubatse (60)

 data collection  data entry Mutale (60)

4 enumerators + 1 student 1 student

Maruleng (60)

 data collection  data entry Fetakgomo (60)

RESPONSIBLE?

4 enumerators + 1 student 1 student

Thulamela (60)

 data collection  data entry

4 enumerators + 1 student 1 student

Mogalakwena (60) Mookgopong (60)  data collection  data entry

4 enumerators + 1 student 1 student

post- data collection phase… • 15th of August – 25th of August: – Data analysis • Obtained results? • Interpretation of results?

– Writing of report

Content I. II. III. IV. V.

Project introduction Methodology General results Food security determinants Policy priorities

General results • • • • • • •

Food security & Poverty Human capital Food production Access to resources Household income Food consumption pattern Shocks & stresses

Food security & poverty in Limpopo • 53% severely food insecure • 32% less then 1$ per day • 60% less then 2$ per day

21%

Food secure

53% 26%

Moderately food insecure Severely food insecure

Validating Food Security Study results… • In 2002 it was suggested that 43% of SA households suffer from food poverty A state where physiological human needs are not adequately met as the available amount of money is not enough to purchase a basic nutritionally balanced diet

National Food Consumption Survey -Fortification Baseline Limpopo, 2011 (NFCS-FB), 2005 1 in 2 hh experienced hunger  53% severely food insecure 1 in 3 hh were at risk of hunger  26% moderately food insecure 1 in 5 ppl were food secure  21% food secure

National Values vs. Food Security Study South African situation: • 50% of the 10 to 11 million households in South Africa can be classified as low-income households

Prahalat & Hart, 2006 / NFCS, 2005

Household size

US$ / Per capita / per day

5

$0.59

StatsSA, 2005/2006

$0.60 (Poorest 10%) $1.32 (2nd poorest 10%)

Current study

32% < $1 60% < $2

6-7

Food security status district level waterberg district

18.8%

vhembe district

21.2%

15.4%

65.8%

33.1%

45.8%

Food secure

sekhukhune district

36.8%

34.2%

29.1%

Moderately food insecure Severely food insecure

mopani district

12.4%

capricorn district

14.4%

0%

24.0%

63.6%

24.6%

20%

61.0%

40%

60%

80%

100%

• Highest food insecurity levels in Waterberg & Mopani district • Lowest food insecurity levels in Sekhukhune district

Food security municipality level 25.4%

Mogalakwena

12.1%

Mookgopong

25.9%

10.0% 14.8%

Giyani

10.6%

0%

31.0%

moderately food insecure

25.9%

severely food insecure

65.0%

23.0%

62.3%

21.2%

59.6%

27.3%

20%

food secure

32.2%

25.0%

19.2%

Molemole

41.7% 37.3%

43.1%

Fetakgomo

50.0%

40.0%

30.5%

Tubatse

Blouberg

67.2%

18.3%

Mutale

64.4%

20.7%

24.1%

Thulamela

Maruleng

10.2%

62.1%

40%

60%

80%

100%

• Highest food insecurity levels in Mookgopong, Maruleng & Mogalakwena • Lowest food insecurity levels in Fetakgomo & Tubatse

Number of hungry months 60

50

Percentage

40

30 Percent

20

10

0 0

1

2

3

4

5

6

7

Average number of hungry months

8

9

10

11

12

Poverty per district

Districts of Limpopo province

Waterberg

Vhembe

Percent of people living on less than 2 $US per day

Sekhukhune

Percent of people living on less than 1 $US per day Mopani

Capricorn

0

10

20

30

40 Percentage

50

60

70

80

Poverty on district level waterberg district

69%

31%

vhembe district

81%

19%

sekhukhune district

79%

21%

> 1 US$ per day < 1 US$ per day

mopani district

50%

capricorn district

50%

62%

0%

20%

38%

40%

60%

80%

100%

• Highest poverty rates in Mopani District • Lowest poverty rates in Vhembe & Sekhukhune District

Poverty on municipality level 34%

66%

Mogalakwena

28%

72%

Mookgopong

25%

75%

Thulamela

13%

87%

Mutale

17%

83%

Tubatse

25%

75%

Fetakgomo 43%

Maruleng

43%

Molemole

63%

37%

Blouberg

62%

38%

0%

20%

1 US$ per day

40%

60%

• Highest poverty rates in Maruleng & Giyani

80%

100%

Human capital Human capital indicators

General

Household size

6-7 (3)

Education level (share of hhold head with no schooling)

33%

Gender (share of female headed hholds)

40%

Dependency ratio (income earners/ total hhsize)

0.85 (0.18)

Migrant workers (share of hholds with contributing migrant)

25,5%

Education level (hhold head) No schooling waterberg

33%

Junior primary vhembe

13%

sekhukhune

Senior primary Some Secondary

36%

mopani

Completed high school

42%

capricorn

Courses or certificates for formal training Diploma or degree

39%

0%

20%

40%

60%

80%

100%

• Overall education levels are lowest in Mopani and highest in Vhembe

Education level 35

30

25

Percentage

20

15

10

5

0 No schooling

Junior primary

Senior primary

Some Secondary

Completed high school

Courses or certificates

Diploma or degree

Activity rate 0.2 0.18 0.16

Ratio of income earners

0.14 0.12 0.1

Mean

0.08 0.06 0.04 0.02 0 vhembe

waterberg

capricorn district

sekhukhune

mopani district

Food production • 57% of households involved in crop production • 50% of households involved in livestock production • Most popular crops: – – – – –

Maize & Mango: 27% Pawpaw:15% Spinach: 15% Tomatoes & Oranges: 13% Banana & Guava: 10%

• Most popular animals: – Poultry: 50% – Cattle & goats: 22%

Crop production Share of total households (N=599) 80% 70% 60%

capricorn

50%

mopani

40%

sekhukhune vhembe

30%

waterberg

20%

general

10% 0% maize

mango

pawpaw

spinach

oranges

tomatoes

• Vhembe district: crop production most popular • Sekhukhune & Waterberg district: crop production less popular

Livestock production Share of total households (N=599) 70% 60% capricorn

50%

mopani

40%

sekhukhune

30%

vhembe

20%

waterberg

10%

general

0% poultry

goats

cattle

pigs

• Livestock production most popular in Vhembe district

Pork and offalalone Venison wild game Meat lamb goat and offal Red meat not part of a stew Mopani worms and insects Ham poloni cold meat tinned meat Beef and offal

Food Groups / Types

Legumes nuts & seeds Fish Roots & tubers Eggs Other fruits Vit. A fruits & vegetables Dairy products Other vegetables Poultry Other cereals Oil & butter Beverages Food products containing sugar Maize products 0

1

2

3

4

5

6

Mean frequency of consumption in the past seven days.

7

8

Venison wild game Pork and offalalone Mopani worms and insects Meat lamb goat and offal Red meat not part of a stew Ham poloni cold meat tinned meat

Food groups/types

Legumes nuts & seeds Vit. A fruits & vegetables Other fruits Roots and tubers Other vegetables Oil & butter Beverages Eggs Fish Dairy Sugar Beef and offal Poultry Other cereals Maize products 0

50

100

150

Average Monthly Expenditure in Rands

200

250

Acces to resources Land resources

• Average land size 0.95 ha (SD: 2.36)

Water sources

• Yard tap: 33% • Public tap: 20% • Borehole: 20%

Energy Financial

• 92% is connected to electricity

• Burial insurance: 57% • Savings account: 42%

Household income • Average income per capita: 605 R/month (SD: 1200 R/month) • Vhembe highest, Mopani lowest income per capita 25 21.2

20.0 20

15.5 15 11.1 10

5

0

7.6

6.7 4.5

7.6 5.7

900 800 700 600 500 400 300 200 100 0

share of households (monthly income categories)

monthly income per capita

Monthly income distribution of households per district 100% 90% 80% 70%

R7500
farming income • Sekhukhune -> formal salary

Food consumption pattern Food expenditure pattern 2% 4%3% 4% 6% 6% 15% 15%

34%

cereals bread non red meat fruits & veggies red meat eggs roots & tubers dairy legumes

100% 80% 60%

10% 7%



Cereals, bread & non red meat -> 60% of food expenditure Red meat ->6% of food expenditure

4% 6%

16%

14%

19%

13%

17%

40% 20%

19% 40%

33% 21%

0% Food secure



5% 6%



Moderately food insecure

Severely food insecure

Food insecurity • Relatively more spend on cereals • Relatively less spend on meat &dairy

Shocks, stresses and coping strategies • Increase in food price is most important stress in the area • Most important coping strategies: – Borrowing money & food from relatives (social capital) – Reducing food consumption & spending – Only 7,5% looks for more employment opportunities

Intra household food distribution vulnerability (%) 50 45 40

Vulnerability (%)

35 30 25 Intra-household food distribution 20 15 10 5 0 Children

Older children

Female adults

Age Category

Male adults

Importance of coping strategies share of households that use coping strategy 0

10

20

30

40 40.8

borrow money from relatives/friends 33.3

borrow food from relatives/friends

32

reduce food consumption

31.5

reduce spending 18.9

selling livestock 14.9

use own savings

13.7

receive grants or gifts look for additional employment take out loan from mashionisa take out loan from formal institution

7.5 6.9 5.7

50

Content I. Project introduction II. Methodology III. General results IV. Food security determinants V. Policy priorities

Food security determinants • Description of different food security categories • What is the difference between food secure and food insecure households?

• Who has highest probability of being food insecure?

• What are the determinants of food insecurity?

Determinants of food security Human capital

Farming system

Food security Household income

Access to resources

Overview determinants Human capital • Household size • Education level • Gender head • Dependency ratio • Migrant workers

Farming system • Subsistence food production • Livestock production

Access to resources • Land • Water • Schooling

Household income • Income per capita • Remittances per capita • Type of income

Identification determinants • Two different multivariate analysis – Regression analysis – Cluster analysis

• Different methods – Check for robustness of findings

Outcome regression analysis Coëfficient constant

Test value 5.42***

HUMAN CAPITAL Household size

0,202

5,21***

Age household head

-0.19

-4.37***

Education level (household head)

-0.23

-4.69***

Gender (household head)

0.08

2.06**

Dependency ratio (income earners/total hhsize)

0.004

0.092

Maizeproduction (dummy)

-0.01

-0.27

Mango production (dummy)

-0.05

-1.14

Pawpaw production (dummy)

-0.04

-1.03

Spinach production (dummy)

-0.08

-1.85*

Tomatoe production(dummy)

-0.01

-0.22

Cattle (dummy)

-0.06

-1.55

Goats (dummy)

0.04

0.91

Poultry (dummy)

0.06

1.45

FOOD PRODUCTION

Outcome regression analysis Coëfficient

Test value

Cropping land size (ha)

-0.05

-1.24

Distance to water source (m)

0.08

2.24**

Monthly income per capita (Rand/month)

-0.09

-2.14**

Formal income (dummy)

-0.12

-2.51**

Grants & gifts (dummy)

0.10

2.12**

Unskilled labour income (dummy)

0.17

4.65***

Remittances (dummy)

-0.16

-4.19***

Skilled labour or entrepreneurial activity (dummy)

0.05

1.18

Farm income(dummy)

-0.07

-1.60

ACCESS TO RESOURCES

HOUSEHOLD INCOME

*10% significance level, **5% significance level, ***1% significance level.

• • •

Independent HFIAS score (Food insecurity score) Negative coëfficients result in higher food security levels R= 0.57; R2=0.32

Cluster analysis – Creating clusters using different variables – Looking for overlap between different determinants & different indicators of food security – Different types of variables included

Human capital

Food production

Access to land

Food security indicators

Food security indicators •Food insecurity score •Importance of food in total expenditure (%) •Importance of cereals in food expenditure (%)

Different clusters Cluster 1 (N=384) 2 7.4 0.87 0.8 2.1 2.1 240 0.86 12 0.62

Education level (1-7) Total household size Dependency ratio Land size (ha) Crop index (Σ crops cultivated) Livestock index (Σ different animal types) Income per capita (Rand/month) Grants & gifts as income source (dummy) Food insecurity score (0-27) Food expenditure (share of total monthly expenditure) Expenditure on cereal (share of total monthly food 0.39 expenditure) *10% significance level, **5% significance level, ***1% significance level.

Cluster 2 (N=132) 3 5 0.81 1.3 2.4 2.8 830 0.64 6 0.54

Cluster 3 (N=25) 5 5.1 0.67 1.5 3.6 5.0 1900 0.32 4 0.37

0.24

0.17

Test 38.56*** 11.82*** 34.14*** 0.95 2.34* 25.13*** 1898*** 17.66*** 27.38*** 15.35***

Different clusters Education level (1-) Total household size Dependency ratio Land size (ha) Crop index (Σ crops cultivated) Livestock index (Σ different animal types)

Cluster 1 (N=384) 2 7.4 0.87 0.8 2.1 2.1

Cluster 2 (N=132) 3 5 0.81 1.3 2.4 2.8

Cluster 3 (N=25) 5 5.1 0.67 1.5 3.6 5.0

Income per capita (Rand/month) Grants & gifts as income source (dummy)

240 0.86

830 0.64

1900 0.32

Food insecurity score (0-27) Food expenditure (share of total expenditure)

12 0.62

6 0.54

4 0.37

Expenditure on cereal (share of total food expenditure) 0.39

0.24

0.17

Low education level, Least land and low crop & livestock indices Lowest income, most dependent on grants & gifts  High food insecurity score,  High importance of food & staple foods in expenditure

Different clusters Education level (1-) Total household size Dependency ratio Land size (ha) Crop index (Σ crops cultivated) Livestock index (Σ different animal types)

Cluster 1 (N=384) 2 7.4 0.87 0.8 2.1 2.1

Cluster 2 (N=132) 3 5 0.81 1.3 2.4 2.8

Cluster 3 (N=25) 5 5.1 0.67 1.5 3.6 5.0

Income per capita (Rand/month) Grants & gifts as income source (dummy)

240 0.86

830 0.64

1900 0.32

Food insecurity score (0-27) Food expenditure (share of total expenditure)

12 0.62

6 0.54

4 0.37

Expenditure on cereal (share of total food expenditure) 0.39

0.24

0.17

Higher education level, More land and higher crop & livestock indices Higherincome, less dependent on grants & gifts  Lowest food insecurity score,  Lower importance of food & staple foods in expenditure

Different clusters Education level (1-) Total household size Dependency ratio Land size (ha) Crop index (Σ crops cultivated) Livestock index (Σ different animal types)

Cluster 1 (N=384) 2 7.4 0.87 0.8 2.1 2.1

Cluster 2 (N=132) 3 5 0.81 1.3 2.4 2.8

Cluster 3 (N=25) 5 5.1 0.67 1.5 3.6 5.0

Income per capita (Rand/month) Grants & gifts as income source (dummy)

240 0.86

830 0.64

1900 0.32

Food insecurity score (0-27) Food expenditure (share of total expenditure)

12 0.62

6 0.54

4 0.37

Expenditure on cereal (share of total food expenditure) 0.39

0.24

0.17

Higher education level, More land and higher crop & livestock indices Medium income, still very dependent on grants & gifts  Lower food insecurity score, Still high importance of food in expenditure

Clusters vs HFIA category • Distribution of HFIA categories in different clusters 100% 90%

31%

24%

Share of households

80% 70%

54%

63%

60%

24% severely food insecure

27%

50%

moderately food insecure

40%

food secure

30%

26% 26%

20% 10%

42%

52% 20%

10%

0% cluster 1 Χ2 : 86,51***

cluster 2

cluster 3

general

Clusters vs HFIA category Food secure

Moderately food insecure

Severely food insecure

Total

Cluster 1

10

27

63

100

Cluster 2

42

27

31

100

Cluster 3

24

24

52

100

General

20

26

54

Identification determinants • From these analysis we find the most important determinants of food security in Limpopo area Household Income

Education level

Dependency on grants & gifts

Household food security status

Type of employment

Content I. II. III. IV. V.

Project introduction Methodology General results Food security determinants Policy priorities

Most important policy priorities • Based on determinants of food security certain policy priorities can be distinghuised • Not all determinants can be tackled directly through policy

Policy priorities Low education level High dependency ratio

Vulnerable female headed household Low household income High dependency on grants & gifts

Food production

• Promote education in rural areas

• Decrease by ensuring job opportunities & facilitating the labour market • Support female headed households • Special focus on girls and women in rural development policies • Promote employment • Facilitate labour market • Ensure sustainability of income • Promote employment • Manipulate incentives • Modify grant system • Promote the potential for household food production to contribute to food security

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