Cost effective method of collecting quarterly poverty estimates in Peru

Javier HERRERA Institut de Recherche pour le Développement (IRD-DIAL)

herrera@dial.prd.fr

More Frequent, More Timely and More Comparable Data for Better Results: The

Challenges and How Bank Teams are Responding

Washington, April 20th, 2011

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1) To compare poverty in different households and in different regions within the country

2) To compare & monitor poverty indicators over time

3) To help defining policies to reduce poverty

4) To evaluate the impact of poverty reduction policies

5) To compare poverty across countries

The reasons why poverty is measured provide guidelines for designing household surveys and defining poverty lines & welfare indicator

1) To compare poverty in different households and in different regions within the country Poverty lines should be welfare-consistent (there

would by many poverty lines, mainly due to regional price differences)

Geographic coverage should be national, not just urban (poverty incidence, gap and severity are higher in rural households)

In countries in which the decentralization has taken place, poverty needs to be monitor at a geographic disaggregated level (need for higher sample sizes)

The reasons why poverty is measured provides guidelines for designing household surveys and defining poverty lines & welfare indicator

2) To compare & monitor poverty indicators over time Repeated similar household surveys are needed Methodology for constructing welfare indicator

should be the same Welfare level represented by the poverty line

should remain constant

The reasons why poverty is measured provide guidelines for designing household surveys and defining poverty lines & welfare indicator

3) To help defining policies to reduce poverty Poverty indicators should be produce timely The survey should include socio-demographic

and economic household characteristics (knowing who are the poor allows to focus on the poor)

Panel data is highly desirable. Analyzing poverty transitions and poverty dynamics allows to identify specific factors associated to moving out of poverty and causes of poverty traps (ie. spatial poverty traps).

The reasons why poverty is measured provide guidelines for designing household surveys and defining poverty lines & welfare indicator

1) To evaluate the impact of poverty reduction policies The survey design should ensure the possibility

of comparing the “treated” group with a control group before and after the treatment (sample design and questionnaire design).

The reasons why poverty is measured provide guidelines for designing household surveys and defining poverty lines & welfare indicator

The Peruvian national Household Survey (ENAHO)Four stages:

I. 2000 Restoring credibility. Revising poverty lines methodology (poverty consistency, updating sample frame) and publishing new poverty figures within the frame of a participatory process

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The Peruvian national Household Survey (ENAHO)Four stages:

II. 2001-2002 More disagreggated (“Departamental” level) poverty estimates, improving quality control, correcting for non response bias, timely results, participatory process (“informal Poverty Committee”), improving PL methodology, bilateral spatial price deflator, informal sector, multidimensional poverty, fixed panel

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The Peruvian national Household Survey (ENAHO)

Four stages

III. 2003-2006 permanent survey (quarterly indicators are allowed, but not published-pending methodological issues)

IV. 2007-2010 rotating panel, new sample based on 2005 Census, using PDA (reducing errors and shortening the time length of data processing), formal Poverty Committee

V. 2011-… new rotating panel, improved questionnaire (taking into account social programs,

conceptual adjustments, etc.,); multilateral regional price index, new poverty line 9

Why is useful high frequency data collection? In The ENAHO, there were two purposes for

having a permanent survey: Data collection costs and efficiency: to

spread the work implied by the bigger sample size over all months instead of concentrating the field work in 3 months. This also improved quality control (real-time quality indicators) and allowed to have a reduced well-trained supervisors/surveyors team and reduced also fixed costs.

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The other purpose was to have higher frequency living conditions indicators. Inei published some of them in their (new) quarterly reports.

However, quarterly poverty rates were never published. Why? Because quarterly poverty rates showed wide

–unexpected and unexplained-fluctuations for which the INEI was unable to furnish an explanation (greater seasonal fluctuations in urban than in rural areas).

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Why is useful high frequency data collection?

Quarterly welfare indicator in the ENAHO survey

Seasonality of poverty rates is an under-researched topic. Inei was very reluctant to publish a figure that will necessarily be revised by the end of the year. They thought that this will damage their credibility.

There was some seasonality in non-response rates and that there were two kinds of adjustments of expansion (weight) factors: one with partial information and another with full (annual) information and that both figures not necessarily coincide. We need to reconcile adjustments for quarterly and annual non response rates

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The Peruvian national Household Survey (ENAHO) Transparency policy

Microdata and all technical documents are also downloadable (sampling, questionnaires, variable dictionary are readily available for download (3 different access: ANDA, “microdata”, “Poverty results”) through INEI’s web pages

http://www.inei.gob.pe/srienaho/index.htm http://webinei.inei.gob.pe/anda/ http://proyectos.inei.gob.pe/DocumentosPublicos/

Pobreza/2009/

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The Peruvian national Household Survey (ENAHO)

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2006-1er.

Quart..

2006-2do.

Quart..

2006-3er.

Quart..

2006-4to.

Quart..

2007-1er.

Quart..

2007-2do.

Quart..

2007-3er.

Quart..

2007-4to.

Quart..

2008-1er.

Quart..

2008-2do.

Quart..

2008-3er.

Quart..

2008-4to.

Quart..

2009-1er.

Quart..

2009-2do.

Quart..

30.0

32.0

34.0

36.0

38.0

40.0

42.0

44.0

46.0

48.0

50.0

Poverty rate

National quarterly poverty rates 2006-2009; point estimate and confidence intervals

Source: INEI-ENAHO 2004 1st Quart. - 2009 2nd Quart. (unpublished)

The Peruvian national Household Survey (ENAHO)

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Lima Metrop, quarterly poverty rates 2006-2009; point estimate and confidence intervals

Source: INEI-ENAHO 2004 1st Quart. - 2009 2nd Quart. (unpublished)

2006-1er.

Quart..

2006-2do.

Quart..

2006-3er.

Quart..

2006-4to.

Quart..

2007-1er.

Quart..

2007-2do.

Quart..

2007-3er.

Quart..

2007-4to.

Quart..

2008-1er.

Quart..

2008-2do.

Quart..

2008-3er.

Quart..

2008-4to.

Quart..

2009-1er.

Quart..

2009-2do.

Quart..

5.0

10.0

15.0

20.0

25.0

30.0

35.0

Poverty rate

The Peruvian national Household Survey (ENAHO)

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Rest urban quarterly poverty rates 2006-2009; point estimate and confidence intervals

Source: INEI-ENAHO 2004 1st Quart. - 2009 2nd Quart. (unpublished)

2006-1er.

Quart..

2006-2do.

Quart..

2006-3er.

Quart..

2006-4to.

Quart..

2007-1er.

Quart..

2007-2do.

Quart..

2007-3er.

Quart..

2007-4to.

Quart..

2008-1er.

Quart..

2008-2do.

Quart..

2008-3er.

Quart..

2008-4to.

Quart..

2009-1er.

Quart..

2009-2do.

Quart..

20.0

25.0

30.0

35.0

40.0

45.0

50.0

Poverty rate

The Peruvian national Household Survey (ENAHO)

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Rural quarterly poverty rates 2006-2009; point estimate and confidence intervals

Source: INEI-ENAHO 2004 1st Quart. - 2009 2nd Quart. (unpublished)

2006-1er.

Quart..

2006-2do.

Quart..

2006-3er.

Quart..

2006-4to.

Quart..

2007-1er.

Quart..

2007-2do.

Quart..

2007-3er.

Quart..

2007-4to.

Quart..

2008-1er.

Quart..

2008-2do.

Quart..

2008-3er.

Quart..

2008-4to.

Quart..

2009-1er.

Quart..

2009-2do.

Quart..

50.0

55.0

60.0

65.0

70.0

75.0

Poverty rate

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The Peruvian national Household Survey (ENAHO)

Source: INEI-ENAHO 2004 1st Quart. - 2009 2nd Quart. (unpublished)

1er. Trim.

2do. Trim.

3er. Trim.

4to. Trim.

1er. Trim.

2do. Trim.

3er. Trim.

4to. Trim.

1er. Trim.

2do. Trim.

3er. Trim.

4to. Trim.

1er. Trim.

2do. Trim.

2006 2007 2008 2009

100

150

200

250

300

350

400

450

500

550

600

Quarterly average monthly per capita expenditures (Soles constantes=2001 Lima's prices)

Lima Metropolitana

Resto urbano

Rural

Total (point estimate and confidence interval)

ENAHO Sample size

Frame Year Seleccted dwelings

Householdsvisited

Households interviewed

Non response

%

Sample reduction

due to sampling

frame issues

Expansion factor

Pop. Census 1993

1997 - IV 7200 7221 6487 7.4 3.0

Projection CPV 1993

1998 - IV 7938 8054 6952 8.7 5.5

1999 - IV 4016 4107 3517 10.2 4.7

2000 - IV 4063 4447 3721 12.0 4.9

Pop. Pre Census

1999-2000

2001 - IV 18179 18824 16515 6.7 6.0

Projection CPV 1993Projection CPV 2007

2002 - IV 19673 21120 18598 8.6 7.3

2003 20084 14892 12580 8.8 9.7

2004 21430 23900 19502 9.0 12.2

2005 21919 25643 19803 13.3 13.7

2006 21920 25807 20577 8.0 14.3

Pop. Census

2005-2007

2007 22640 26527 22204 5.2 12.1Projection CPV 1993Projection CPV 2007

2008 22640 26010 21502 6.8 11.3

2009 22640 26,598 21753 6.4 12.9

2010 22640 27,176 21496 7.2 14.9

Using the ENAHO for poverty analysis Herrera, J., F. Roubaud (2007), Urban poverty dynamics in Peru

and Madagascar, International Planning Studies, 75(1), 2007, pp.70-95.

De Vreyer, Ph., Herrera, J., S. Mesplé-Somps (2009), Consumption growth and spatial poverty traps : an analysis of the effect of social services and community infrastructures on living standards in rural Peru. In Poverty, Inequality and Policy in Latin America, Klasen S. (ed.), CESifo Series, Harvard: MIT Press, pp.129-155.

Herrera, J., (2009), Reducción de la pobreza urbana y el mercado de trabajo en el Perú: Evolución 2004-2006. In Crecimiento reciente y reducción de la pobreza en el Perú. Una oportunidad que no se puede dejar pasar. World bank, Washington DC. pp.32-61.

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Herrera, J., M. Razafindrakoto, F. Roubaud (2008), Poverty, Governance and Democratic Participation in Francophone Africa and the Andean Region, OECD Journal on Development, Special Issue: Measuring Human Rights and Democratic Governance. Experiences and Lessons from Metagora, June, p.99-121.

Herrera, J., M. Razafindrakoto, F. Roubaud (2008), The determinants of subjective poverty: A comparative analysis in Madagascar and Peru. In Poverty, Inequality and Migration Dynamics in Latin America, Stephan Klasen and Felicitas Nowak-Lehmann D., (ed.), Peter Lang Verlag, Frankfurt am Main, p.181-220.

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Using the ENAHO for poverty analysis