Measuring Consumption and Poverty in ZambiaGSS methodology conference, 27 June 2012

Presentation summary

• Why a poverty trend needed to be developed retrospectively in Zambia

• LCMS 2010 fieldwork delays lead to problems • Adjustments to 2010 data to ensure

comparability

• Political environment – Lessons?

Zambia consumption surveys 1996-2006

• Living Conditions Monitoring Surveys (LCMS) 1996, 1998, 2004, 2006

• Conducted over 2 – 4 months • Consumption data collected in a one time HH

interview

• LCMS 2002/3• Longitudinal survey• Diary method• In field for 12-15 months

Zambia consumption surveys 1996-2006

• Differences in survey design:• Questionnaires • Sample size and selection• Dates for data collection

• Differences in analysis methods• Poverty lines• Consumption aggregate

• Thus no comparable trend available

Questionnaire differences 1996-2006

• Differences in lists of food items (e.g . ‘other vegetables’, poultry)

• Significant differences in maize and maize products

• Use of different recall periods (2 weeks, 4 weeks, 1 month, 12 months)

Questionnaire differences 1996-2006

• Some surveys included quantities and values of own production, allowing prices to be generated.

• Others had seperate community price questionnaires

Differences in sample size and sample selection

• Sample selection of SEAs based on 2000 census sample frame - consistent over surveys

• Sample size varies from 6,000 to 20,000 households

• Sample of households per strata within SEAs selected by supervisors or enumerators

Zambia poverty lines 1996-2006

8

  Zambia poverty lines

food poverty line overall poverty line

1996 20,181 28,979

1998 32,861 47,187

2004 78,223 111,747

2006 65,710 93,872

Decline in the poverty line btw 2004 and 2006 shows that the methodology of updating the poverty line changed over time. (CPI Food inflation 2004-2006 = 20%)

Developing methodology to establish the poverty trend, retrospectively

• Reviewed questionnaires and available data for 1996, 1998, 2004 and 2006

• Developed a new method that could be applied to data 1996-2006

• New food basket based on consumption shares on each food item for HHs in 5th and 6th deciles (2006)

Developing methodology to establish the poverty trend, retrospectively

• Valued food basket for each year using item specific CPI indices (avoiding differences in CPI structure over time)

• Derived overall poverty line based on non food share of HHs in 5th and 6th deciles

• Developed a consistent consumption aggregate based on best practice and available data across surveys

Comparison of overall poverty lines ('000 Kwacha), 1996 - 2006

New Poverty trend – Zambia 1996-2006

Poverty headcount (% poor) Zambia, urban and rural

0

10

20

30

40

50

60

70

80

90

1996 1998 2000 2002 2004 2006

Per

cen

tag

e

Rural

Zambia

Urban

LCMS 2010

LCMS 2010

• CSO required that the LCMS 2010 serve two purposes:

1. To monitor poverty trends 2006 – 2010

2. Develop separate urban and rural poverty lines.

• Lessons learned from previous surveys - Questionnaire had more specific consumption items listed

LCMS 2010: Continuing poverty trend

•Developed a ‘Narrow’ consumption aggregate, strictly excluding all items NOT in the 2006 LCMS

•Included items likely to be under ‘other’ categories in 2006

LCMS 2010 ‘Other’ categories excluded

• Own production/’receipt from other sources’ of other vegetables, fruits and own poultry these were ‘accidentally’ crossed out in 2004 and 2006 questionnaires

• ‘Narrow’ consumption aggregate therefore excludes these items

LCMS 2010: A key difference

• Problem: LCMS field work was delayed by 2 months

• Rainy season (access)

• Lean season

• 2010 data showed a large increase in poverty when trends (2009) methodology applied

Attempts to deal with ensuring comparability in analysis

• Adjustment (i): Use Dec./Nov. 2009 prices to evaluate the food poverty line

• Argument: Fieldwork was 2 months later than the 2006 survey period, Prices in the period January to March were slightly higher than Nov-Dec .

Adjustments to deal with comparability in analysis

• Adjustment (ii): Reduce the food share of the overall poverty line

• Argument: Households have a lower non-food consumption in the period January to April (lean period) than from Nov. to Dec.

• LCMS 2002/03 show that the non-food share in the period Jan. to April is indeed lower than in the period Nov.-Dec.

• The non-food share of the total poverty line in 2010 was lowered by 3 percentage points, from 41.5% to 38.5% (was reviewed with 1.5% and 3% reductions)

• However the LCMS 2002/03 report shows lower poverty in Q1

Adjustments to deal with comparability in analysis

• Adjustment (iii) Take out the price increase for imported rice from the pricing of the poverty line

• Argument: Between 2006 and 2010 the national median price for local rice increased roughly by the factor 2.14, for imported rice by the factor 4.17.

Adjustments to deal with comparability in analysis

• Adjustment (iv): Use an extended consumption aggregate

• Consultants requested to create an ‘extended’ consumption aggregate, to include own-produced and items received of other vegetables, fruits and poultry

• Comparing item specific budget shares over time reveals that own produced ‘other vegetables’ are extremely important consumption items.

Adjustments to deal with comparability Adj. (iv) – extended cons. agg.

• Share (of total consumption) of other vegetables was 1.7% in 2006 and 2% in 2010 – under the narrow consumption aggregate (inc. only purchases)

• Share of ‘other vegetables’ in ‘extended’ consumption aggregate (2010) is 11%

• This indicates that the narrow 2010 consumption aggregate is actually more comparable to the 2006 aggregate.

Adjustment (iv): outcome

• When ‘Extended’ aggregate is used to generate poverty headcount, results ……………………

• Poorer quintiles gained against the overall trend of a decline in real consumption (own produced vegetables, fruits and poultry are of much greater relevance to poorer quintiles)

• Significant discomfort with this adjustment

Further revisions made by CSO

• Spatial price differences removed

• Remittances sent added to HH consumption aggregate

• Consumption aggregate for 2010 includes all food items (e.g. ‘other own production’)

Effects of adjustments on poverty headcount

Changes in poverty line methodology Poverty Lines Headcount Estimates

Prices usedImported Products

Food shareFood

Poverty Line (K)

Overall Poverty Line (K)

Base Consumption

Aggregate

Extended Cons. Aggregate

Base scenario poverty line

Jan-March 2010

local and imported rice

Constant (58.5%) 103,611 177,123 70.2% 67.2%

Combinations of changes

Nov-Dec 2009

local rice only Constant (58.5%) 98,505 168,394 68.4% 65.5%

Nov-Dec 2009

local rice only Ad-hoc (60% =

+1.5%) 98,505 164,175 67.6% 64.3%

Nov-Dec 2009

local rice only Ad-hoc update (61.5% = +3%) 98,505 160,171 66.7% 62.8%

Final method: All food consumed and remittances sent inc. in consumption agg. provincial price deflator removed

96,366 146,009   60.5%

Political situation

• CSO senior management change half way through survey (temporary promotion)

• GRZ preparing for election and CSO under pressure to show reduction in poverty

• Clear steer for ST that poverty must have fallen (argument anecdotal)

• President announces fall in poverty before final numbers agreed

Lesson learning

• Survey had on-going evaluation – Paper available

• Summary of lessons learned in brief paper

• Political lessons• Management lessons• Technical lessons

Thank you!