Transcript Revisiting Gender Differences in Agricultural Productivity

Measuring Food Security:
Old Challenges and “New” Thinking
Gero Carletto
Development Research Group
The World Bank
ICABR, Ravello, June 2013
Outline
• Describe debate and issues
• Need for benchmarking/validation
• Methodological research
– Improving the measurement of food
consumption
• A simple example
• Final thoughts
THE GOOD: What most agree on …
• Multi-dimensional concept
• Need suite of indicators
– Availability, Access, Utilization and Stability
• Proliferation of indicators
– White noise
– Need validation/benchmarking
• Too few indicators at right periodicity and for
enough countries
… THE BAD: What most disagree on …
• Which indicators?
– Calorie intake: yes, but too difficult?
– Dietary diversity: yes, but comparable?
– FAO undernourishment: yes, but for what?
• Benchmarking
– Food consumption?
• Aggregation into composite index
– The FI “dashboard”
– What can we learn from the poverty debate?
… and THE UGLY … i.e. reality!
“No single indicator can properly capture FNS”
“No single survey can collect all needed indicators at right
periodicity”
“No single institution has mandate/capacity/willingness to
collect all needed indicators of FNS …”
“Most countries do not have capacity/resources to collect
all needed indicators …”
 we need multiple (just a few!) indicators from multiple
surveys carried out by multiple institutions
– But, how to choose?
– How do we benchmark/validate?
The Indicators
•
•
•
•
•
•
•
Caloric intake/Food quantities
Food expenditures
Dietary Diversity/Food Consumption Score
HFIAS/Hunger Scale
Coping Strategy Index
Qualitative, e.g. food adequacy
Anthropometrics
The Instruments
•
•
•
•
•
•
•
•
Household Budget Surveys (HBS)
Income and Expenditure Surveys (IES)
Living Standards Measurement Study (LSMS)
Integrated Household Surveys (IHS)
Surveys on Income and Living Conditions (SILC)
Demographic and Health Surveys (DHS)
Multiple Indicator Cluster Surveys (MICS)
Comprehensive Food Security Vulnerability
Assessment (CFSVA)
• Welfare Monitoring Survey (WMS)
• Nutrition Surveys (24-hour)
Lack of standards result in poor
comparability!
• Take Food Consumption …
– Diary vs. recall
– Household vs. individual
– Reference period
– Nomenclature (COICOP)
– Bulk purchases
– Non-standard units of measure
– Food consumed away from home (FAFH)
– Valuation of consumed own-production
Two dimensions of poor comparability
in food consumption data
P
e
r
c
e
n
t
100
90
80
70
60
50
40
30
20
10
0
70.0
41.0
24.0
Less than one week
100
P
e
r
c
e
n
t
100.0
23.0
One week
5.0
7.0
Two weeks
One month
96.0
Greater than one
month
Less than or equal to
two weeks
86.0
85.0
In-kind receipts of food
All three sources
80
60
40
20
0
Food purchases
Home-produced food consumed
Instrument design & implications
for consumption/poverty
Mean
consumption
per cap (Tsh)
520,850
Poverty
headcoun
($1.25/day
54.9
HH diary infrequent
425,298
55.6
Personal diary
510,616
47.5
Type of consumption
module in questionnaire
Long 7 day recall
Note: Test compared 8 different instruments, varying recall period and method
Beegle, Kathleen, Joachim De Weerdt, Jed Friedman, and John Gibson. 2012. “Methods of Household Consumption
Measurement through Surveys: Experimental Results from Tanzania.” J of Development Economics 98: 3-18
Take diary vs. recall …
• Diary often considered ….
– Unfeasible (low literacy rate)
– Too onerous for respondents
– Too costly
– Often, diary converts into short (2-3 day) recall
… but no metadata!
• Recall considered imprecise (telescoping,
recall bias)
• 7-day recall most frequent. Most feasible?
Can we improve on 7-day recall?
• WB-FAO joint research program
– Phase I: review
– Phase II: methodological research
•
•
•
•
•
•
•
Bounding reference period, plus 24-hour recall
Assisting households to recall
Non-Standard unit of measurement
Food item list/disaggregation
Food Consumed Away from Home
Partakers
Annualization
– Bulk purchases
– Prices/Unit values
Annualization of consumption
• Purchases+own-produced+gifts/in-kind pay in
last 7 days
• Valuation of non-purchased items at median
unit values
• (Quantity*price)*52
• But prices do change (quantities too!!)
• Apply monthly median unit values computed
from survey (or price/market survey)
• What are the implication in terms of total
consumption and poverty?
Median price/kg- maize flour
60
50
Median price/kg
40
30
20
10
0
Month
Normal Maize Flour- Median consumption
3500
3000
Kwacha
2500
2000
1500
1000
500
0
Mar-10
April
May
June
July
August September October NovemberDecember January February
Month
Method and timing of interview make a difference
Interviewed in MARCH
consumed 13.72 kg in last 7 days
At monthly
prices
Interviewed in DECEMBER
consumed 13.72 kg in last 7 days
At monthly
prices
At constant
price
At constant
price
December
2,360
2,167
3,033
January
2,259
2,167
3,101
3,033
February
2,140
2,167
June
2,295
3,033
March
3,323
2,167
July
2,401
3,033
April
3,003
2,167
August
2,215
3,033
May
3,101
2,167
September
2,310
3,033
June
2,295
2,167
October
2,360
3,033
July
2,401
2,167
November
2,286
3,033
August
2,215
2,167
December
2,360
3,033
September
2,310
2,167
January
2,259
3,033
October
2,360
2,167
February
2,140
3,033
November
2,286
2,167
30,052
36,400
30,052
26,000
March
3,323
3,033
April
3,003
May
Annual
Annual
Impact on poverty estimates
Poor (%)
Ultra-poor (%)
At constant prices
51
24
At monthly prices
45
19
Some final thoughts …
• Irrespective of indicator, need benchmarking
• Need for improved benchmark (food
consumption)
• Need harmonization
– Methods
– Efforts
• Focus on changes with highest value added
• Other issues …
– PHL
– Net Buyer-net sellers
• Technology can help