Post on 29-Dec-2015
Observations and Suggestions Observations and Suggestions for Improving Agricultural and for Improving Agricultural and Rural Statistics in Developing Rural Statistics in Developing
CountriesCountries
Isidoro P. DavidIsidoro P. David
ICAS III, Cancun, MexicoICAS III, Cancun, Mexico2-4 November 20042-4 November 2004
Observations and Suggestions Observations and Suggestions for Improving Agricultural and for Improving Agricultural and Rural Statistics in Developing Rural Statistics in Developing
CountriesCountries
Isidoro P. DavidIsidoro P. David
ICAS III, Cancun, MexicoICAS III, Cancun, Mexico2-4 November 20042-4 November 2004
ContentsContents
• IntroductionIntroduction• Some definitions: Implications on Some definitions: Implications on
Data Analysis & Availability.Data Analysis & Availability.• The Future of Agricultural CensusesThe Future of Agricultural Censuses• Outstanding Design, Measurement & Outstanding Design, Measurement &
Estimation ProblemsEstimation Problems• Improving Statistics on the Food Improving Statistics on the Food
Poor, Undernourished, & HungryPoor, Undernourished, & Hungry
On DefinitionsOn DefinitionsRural & AgriculturalRural & Agricultural• Used interchangeably?Used interchangeably?• Rural relates to condition, state or Rural relates to condition, state or
geographic area (with shifting boundaries)geographic area (with shifting boundaries)• Agricultural relates to activities, e.g. raising Agricultural relates to activities, e.g. raising
cropscrops
China’s 1996 agri census was really rural China’s 1996 agri census was really rural censuscensus
Table 1a. Population and Number of Villages in 1980 and 1990 CPH, Table 1a. Population and Number of Villages in 1980 and 1990 CPH, PhilippinesPhilippines..
19801980 19901990
Population (million)Population (million) 48.148.1 60.760.7
Of which: Urban (million)Of which: Urban (million) 18.018.0 29.429.4
Urban (%)Urban (%) 37.537.5 48.548.5
Villages (thousand)Villages (thousand) 40.240.2 41.341.3
Of which: Urban (thousand)Of which: Urban (thousand) 7.77.7 10.210.2
Urban (%)Urban (%) 19.219.2 24.824.8
Table 1b. Poverty Incidences, 1985 – 1997 Table 1b. Poverty Incidences, 1985 – 1997 PhilippinesPhilippines
1985198519881988 19911991 19941994 19971997
Poverty Incidence Poverty Incidence (%)(%)
4949 5050 4545 4141 3737
Urban (%)Urban (%) 3838 3434 3636 2828 2222
Rural (%)Rural (%) 5656 5252 5555 5353 5151Source: David and Maligalig (2001)
In Philippines, Rural – Urban In Philippines, Rural – Urban dropped as strata in the new dropped as strata in the new master sample for household master sample for household
surveys that was implemented surveys that was implemented beginning 2003.beginning 2003.
Short-term (less than one year) poverty is averaged Short-term (less than one year) poverty is averaged
out in poverty statistics presented as annual and out in poverty statistics presented as annual and
broken down into rural, urban, regions. Thus, broken down into rural, urban, regions. Thus,
dearth of statistics on transient poverty dearth of statistics on transient poverty
experienced by agricultural households in rainfed experienced by agricultural households in rainfed
and upland areas, fishermen during typhoon and upland areas, fishermen during typhoon
season, also poverty brought about by reduced season, also poverty brought about by reduced
off-farm employment in physical infrastructure off-farm employment in physical infrastructure
projects that slow down during the wet season.projects that slow down during the wet season.
Statistics on food deprivation and Statistics on food deprivation and under-nutrition.under-nutrition.
Is undernourished the same as Is undernourished the same as hungry?hungry?
(To be discussed last)(To be discussed last)
Future of Census of Future of Census of Agriculture (CA)Agriculture (CA)
Declining support for CA becauseDeclining support for CA because
• Users are not clear about the role of CA vis-à-vis surveysUsers are not clear about the role of CA vis-à-vis surveys
• CA reports are released very lateCA reports are released very late
• Large deviations between CA and sample surveys, thus Large deviations between CA and sample surveys, thus limiting the use of CA mainly to rates, proportions and limiting the use of CA mainly to rates, proportions and distributions (e.g. land use) instead of levels.distributions (e.g. land use) instead of levels.
Civil strife, ethnic/religious conflicts, terrorism prevent CA Civil strife, ethnic/religious conflicts, terrorism prevent CA in parts of a growing list of countries – Sri Lanka, Nepal, in parts of a growing list of countries – Sri Lanka, Nepal, Philippines, Indonesia, Myanmar, Solomon Islands in Philippines, Indonesia, Myanmar, Solomon Islands in Asia-Pacific. Other regions have their lists.Asia-Pacific. Other regions have their lists.
Future of CAs, cont’dFuture of CAs, cont’d
• Sampling in previous CAs are confined to small Sampling in previous CAs are confined to small farm households stratum.farm households stratum.
• We are bound to see more extensive sampling: 3-We are bound to see more extensive sampling: 3-stage in Indonesia, 2-stage in Philippines. stage in Indonesia, 2-stage in Philippines.
• Sampling frame problem is solved through multi-Sampling frame problem is solved through multi-phase sampling (David 1998), or through CPH.phase sampling (David 1998), or through CPH.
Some countries have done away with censuses Some countries have done away with censuses (India), or called a sample survey a census (India), or called a sample survey a census (Indonesia). (Indonesia).
China, Vietnam are exceptions.China, Vietnam are exceptions.
Some Design, Measurement and Some Design, Measurement and Estimation ProblemsEstimation Problems
• Need to strengthen design and analysis capability Need to strengthen design and analysis capability towards estimating distributions.towards estimating distributions.
• Estimation of distributions better served by integrated Estimation of distributions better served by integrated surveys, e.g. agricultural labor force with nationwide surveys, e.g. agricultural labor force with nationwide LFS, agricultural/rural income with HIES.LFS, agricultural/rural income with HIES.
• Integration through master sample; e.g. PhilippinesIntegration through master sample; e.g. Philippines
• Include minimum agric info in CPH to enable injecting Include minimum agric info in CPH to enable injecting at design stage of master sample.at design stage of master sample.
• Integration is more difficult with decentralized Integration is more difficult with decentralized statistical systems.statistical systems.
Why is a large subset of national Why is a large subset of national agricultural database still produced agricultural database still produced
from subjective methodsfrom subjective methods??• Measurement problems too difficult and costly to Measurement problems too difficult and costly to
solve?solve?• Agristats lower priority in agriministry or in Agristats lower priority in agriministry or in
national statistical system?national statistical system?• Donor assistance skewed towards non-agristats?Donor assistance skewed towards non-agristats?
Non- agristats already based mainly on Non- agristats already based mainly on objective methods, which will make objective methods, which will make integration more difficult. integration more difficult.
Objective methods, e.g. crop-cutting, Objective methods, e.g. crop-cutting, losing effectiveness. Experiments losing effectiveness. Experiments needed to try other alternatives.needed to try other alternatives.
Examples:Examples:• Regression with two-phase sampling.Regression with two-phase sampling.• Consumption from HIES to adjust crops and Consumption from HIES to adjust crops and
livestock output estimates.livestock output estimates.
Improving Statistics on Food Poor, Improving Statistics on Food Poor, Undernourished and HungryUndernourished and Hungry
• MDG1 – eradicate MDG1 – eradicate extreme povertyextreme poverty and and hungerhunger• WB $1 a day poverty incidence for extreme povertyWB $1 a day poverty incidence for extreme poverty
Uses national estimates based on household Uses national estimates based on household surveysurvey2100kcal/capita/day energy threshold2100kcal/capita/day energy thresholdIncludes food and non-food componentsIncludes food and non-food componentsBottom of low income countries, hence severeBottom of low income countries, hence severe
• FAO proportion of undernourished persons for hungerFAO proportion of undernourished persons for hunger 2100 threshold also 2100 threshold also Uses national food supplies and estimate of Uses national food supplies and estimate of
how how supply is distributed to populationsupply is distributed to populationIncludes food only.Includes food only.
• Both statistics indicators of the same thing? Both statistics indicators of the same thing? • Or is being extremely poor same as being Or is being extremely poor same as being
hungry?hungry?• FAO indicator (5) < WB indicator (1) FAO indicator (5) < WB indicator (1)
always?always?• Both indicators showing consistent trend?Both indicators showing consistent trend?• Can FAO methodology be aligned with other Can FAO methodology be aligned with other
indicators, e.g. household survey-based.indicators, e.g. household survey-based.
Table 2. $1 a day poverty and undernutrition estimates in eight most populous developing countries
Country$1 a Day Undernutrition Populatio
n in 20001990 1995 2000 1990 1995 2000
China 1275
Incidence (%) 33 17.4 16.6 17 12 11
Persons (Mns) 381 212 212 193 145 135
India 1017
Incidence 42.1 42.2 34.7 25 21 21
Persons 356 393 353 215 195 214
Indonesia 212
Incidence 17.4 13.9 7.2 9 6 6
Persons 32 27 15 17 11 13
Brazil 172
Incidence 14 10.5 8.2 12 10 9
Persons 21 15 14 19 17 16
Table 2. $1 a day poverty and undernutrition estimates in eight most populous developing countries (con’t)
Country$1 a Day Undernutrition Populatio
n in 20001990 1995 2000 1990 1995 2000
Pakistan 143
Incidence 47.8 33.9 13.4 26 19 19
Persons 53 42 19 29 24 27
Bangladesh 138
Incidence 35.9 28.6 36 35 38 32
Persons 39 35 49 39 48 44
Nigeria 115
Incidence 59.2 70.2* …* 13 8 8
Persons 51 70* 80* 11 8 9
Mexico 99
Incidence 15.8 8.4 9.8 5 5 5
Persons 13 8 10 4 5 5
Totals
Incidence (weighted) 34.7 27.1 23.7 19.4 15.4 14.6
Persons (Mns) 945 802 752 524 453 463
Table 2. Official Poverty Rates (%), Table 2. Official Poverty Rates (%), NCR, PhilippinesNCR, Philippines
Type / YearType / Year 19971997 20002000
Total PovertyTotal Poverty
FamiliesFamilies 4.84.8 5.75.7
PersonsPersons 6.5 6.5 7.67.6
Food PovertyFood Poverty
FamiliesFamilies 0.60.6 0.70.7
PersonsPersons 0.80.8 1.01.0
Multiple Sources of Household Multiple Sources of Household Food Consumption DataFood Consumption Data
• HIES, HFCS from NSOHIES, HFCS from NSO
Varying quality & availability of prices, Varying quality & availability of prices, quantities, and value of food items.quantities, and value of food items.
Less objective method of data capture.Less objective method of data capture.
FCS from Nutrition and Health InstitutesFCS from Nutrition and Health Institutes
Examples: Vietnam, PhilippinesExamples: Vietnam, PhilippinesMore objective method of data capture.More objective method of data capture.Use of subject matter specialists as data Use of subject matter specialists as data
collectors.collectors.
Table 3Table 3.. Energy Consumption Energy Consumption Distributions (% of Population) Using Distributions (% of Population) Using Three Different Divisors for Total Three Different Divisors for Total Consumption, NCR- Philippines, 2003Consumption, NCR- Philippines, 2003
Divisor/Cut-Off (kcal)Divisor/Cut-Off (kcal) <1500<1500 <1800<1800 <2000<2000 <2100<2100
Family Size, NFamily Size, N 48.048.0 74.074.0 83.083.0 88.088.0
Consumption Units, TCUConsumption Units, TCU 29.029.0 53.053.0 69.069.0 74.074.0
Adjusted for Scale Economies, Adjusted for Scale Economies, N*N*
7.97.9 16.016.0 22.522.5 26.326.3
E s ti mated E mpi r i c al C DF
0
0. 2
0. 4
0. 6
0. 8
1
1. 2
0 1500 1800 2000 2100 >2100
E n er gyLevel C ut - Off
per capita per consumption unit per adult equivalent
Advantages of Direct Approach Advantages of Direct Approach over Food Poverty Line Approachover Food Poverty Line Approach
• Does not require prices, income, expenditure, Does not require prices, income, expenditure, reference population – only quantities of food reference population – only quantities of food items consumed by household.items consumed by household.
• Comparable across time and spaceComparable across time and space• Can readily determine incidence for any Can readily determine incidence for any
choice of thresholdchoice of threshold• Provides sensitivity analysis to different Provides sensitivity analysis to different
choices of thresholdschoices of thresholds• Applicable to other nutrients and vitamins, Applicable to other nutrients and vitamins,
generalizes to joint nutrient adequacy generalizes to joint nutrient adequacy assessment, e.g. energy-protein.assessment, e.g. energy-protein.