matthias till diapom –state of play directorate statistics · slide 6 | 7 january 2019 adjust...

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DIAPOM –State of Play

UNECE TF on Disaggregation of Poverty Measurement

Matthias TillDirectorate Social Statistics

ViennaNovember 29th, 2018

www.statistik.at slide 2 | 7 January 2019

Work to be continued...

Hans Rosling 1948 ‐ 2017

Vijay Verma1946 ‐ 2018

Tony Atkinson 1944 ‐ 2017

DESIGNINGSURVEYS

FINDING INDICATORS

TELLINGPEOPLE


Mandate of the TF

Collect & analyse good practice: Assessment of survey designs, sampling

precision, intra‐household data and coverage on the sub‐national level;

Innovative strategies and survey designs to cover hard‐to‐reach populations and population living in institutions;

Methods to account better for differing consumption needs of different population sub‐groups, such as children, older people or those with a disability;

Inclusion of social transfers in kind, housing wealth and imputed rent in the measurement of poverty.


Current TF Members

7 National Statistical Agencies:Austria, Canada, Mexico, Russian Federation, SlovakRepublic, United Kingdom, United States of America8 international organisations:CIS STAT, EU‐FRA (Fundamental Rights Agency), World Bank, Eurostat, OECD, UNDP, UNICEF, UNSDplusOxford Poverty & Human Development Initiative (OPHI)Additional NSIs are welcome, esp. to support work on nonresponse and sampling precision!


Time schedule

Nov‐Dec 2017 Launching the Task Force Jan‐Feb 2018 Discussion of work plan Mar‐July 2018 Collection of good practiceso Sep‐Dec 2018 Review & analysis of collected

information, identification of gapso Jan‐June 2019 drafting recommendations & conclusionso July‐Sep 2019 Editing the reporto Oct 2019 Review of full report by the CES Bureauo Oct‐Dec 2019 Revisions to address Bureau’s commentso Jan‐Apr 2020 Electronic consultation (CES members)o June 2020 Expected endorsement by CES plenary


Adjust Table of Contents /identify (and fill) gaps?Material for chapter on nonresponse & sampling precision?

Preliminary suggestions/draft recommendations

Editing and review procedure?

Next steps, assignment of tasks

(Possibly) discuss new material:Russian FederationONSMexicoUNDP, UNICEF

TF meeting


Table of ContentsI. Introduction: measurement of poverty for policy relevant target groupsII. Standard core variables for disaggregation (5)

i. Policy relevant target groups for poverty disaggregation;ii. Defining target groups and analytic/geographic location variables;iii. Examples of applications to the poverty disaggregation (studies, press releases, infographics).III. Coverage problems in poverty measurement (10a+b)

i. Innovative survey programs to address hard-to-reach-populationsii. Adjusting survey methodology for hard-to-reach-populations and persons in institutionsiii. Specific sampling strategies to reach the poorIV. Response rates and sampling precision for target groups (10a)i. How can precision requirements and selectivity of nonresponse be assessed?ii. How can estimation enhance precision and compensate for nonresponse?V. Supplemental poverty measuresi. What is the role of differences in cost of living? (10c)

ii. What is the role of unequal sharing of resources within households? (10a)

iii. What is the role of Social Transfers in Kind (STIK)? (10d)

iv. What is the role of housing wealth and imputed rent? (10d)

VI. Recommendations on production, analysis & dissemination of disaggregated indicators (11)

VII. Topics for further work

ready for review‐volunteers?…

consolidation pending…

additional material needed

consolidation pending…

Suggestions?


Collection/ disaggregation of poverty data to be guided by:1. Participation2. Disaggregation3. Self‐identification4. Privacy5. Transparency6. Accountabilityhttps://www.ohchr.org/HRBAD

Principles for collection & dissemination


• “Nothing about us without us”• Do no harm• Retain trust in official statistic• Free, active and meaningful participation• Relates to indicators definition, data

collection, dissemination and analysis• Human rights / statistics focal points

Participation


• By grounds of discrimination prohibited by international human rights law

• Average, deprivation and inequalityperspectives (see OHCHR Human Rights Indicators guide)

• Hard-to-count populations• Multiple disparities or discrimination

Data Disaggregation


• Freedom to self-identify, in particular when touching personal identity (religious beliefs, sexual orientation, gender identity and ethnicity)

• Do no harm• Gender and cultural sensitive data collection

approaches• Subjective/objective criteria (language,

geographic location)

Self-identification


• People’s right to (statistical) information (freedom of expression, International Covenant on Civil and Political Rights, Art. 19 ; Principle 1 of Fundamental Principles for Official Statistics)

• Transparency in legal, institutional and methodological framework within which NSOs/NSS operate

• Metadata• Dissemination calendar

Transparency


• Data protection and confidentiality (ICCPR, Art. 17)

• Data collected to produce statistical information must be strictly confidential and use exclusively for statistical purposes (Principle 6 of FPOS)

• Watch data disaggregation and privacy issues

• Data protection and access to information bodies

Privacy


• Accountability in data collection• Data collection for accountability• Open data• As other state institutions, NSOs have

obligations to respect, protect and fulfil human rights as it pertains to their area of work

• Challenge incorrect use/interpretation of data• Relevance of statistics legislation and

implementation

Accountability


1. Poverty measurement should be guided by six principles of a human rights based approach to data (HRBAD): participation, self‐identification, disaggregation, privacy, transparency, accountability.

2. Disaggregation should consider economic and social policy drivers of poverty as well as grounds of discrimination prohibited by international law.

preliminary suggestions – general


4. As a minimum, comparable disaggregations should consider relevant groups as defined in this report. In practice, international standards for disaggregation should be complemented according to requirements of national poverty policies.

The list of selected variables describing target groups covered in this report is the following: Sex (target group of women); Age (target groups of children, youth and older people); Disability status (target group of persons with disabilities); Migratory status (target group of migrant population); Ethnicity (target groups defined by ethnicity or race).

preliminary suggestions– general


The list of selected variables describing socio‐economic and geographic strata is the following: Household type (characteristics of household composition); Employment status (characteristics of labour force

participation); Tenure status of the household (characteristics of arrangement

of occupancy of housing unit by a private household); Receipt of social transfers (characteristics of income

composition); Degree of urbanisation (characteristics related to urban/rural

composition).



5. Disaggregation can benefit from supplemental poverty measures which better reflect group specific requirements, implied for example by differences in cost of living across regions or by disability status, receipt of social transfers in kind or unequal sharing of resources within househeolds.



6. Following the HRBAD principle of transparency, NSIs should assess the accuracy of poverty estimates at regular intervals. Quality reports need to assess „total error“ as specified by the Atkinson Commission.

7. As a minimum, standard quality reports should be published every 5 years, addressing the extent of: a. (under‐)coverage b. sampling errors c. nonresponse rates d. departures from international measurement guidelines e. postsurvey adjustments (e.g. imputations, weighting, gross‐

net conversions…)

preliminary suggestions – „Total Errors“


8. Following the Human Rights Approach to Data, it is recommended to emphasise participation and self‐identification of groups which may be subject to discrimination.

9. It is recommended that NSIs adopt survey protocols to the specific needs of those groups, including questionnaire design and interviewer training. In particular, all survey material, letters, questionnaires etc. should be interculturally accessible, for example providing foreign language versions.

preliminary suggestions – coverage I


10. Specific groups may require adjusted sampling strategies, eventually implying target group specific data collections to be carried out at least every 5 years. The EU MIDIS Minority and Discrimination survey provides a comprehensive toolbox to accomplish improved coverage.

11. Although target group specific data collections may involve other agencies than NSIs, and have different objectives and require adjusted poverty definitions, these should still be guided as far as possible by the standards used in official statistics to measure poverty.

preliminary suggestions – coverage II


12. As a general rule, poverty measurement has to ensure equivalence of standards of living for all regions and groups within a country, notably with regard to needs of children/ persons with health impairments or disabilities.

13. Equivalence of measurement should always be assessed empirically. Sensitivity analysis may involve comparing poverty profiles of official poverty measures with supplemental poverty measures.

14. Supplemental poverty measures may be obtained by adjusting either the resource measure (income or expenditure) or the poverty threshold. Both should be consistent.(e.g. health expenditure vs. health needs).

preliminary suggestions – Cost of living


15. STIK can be particularly relevant for comparisons between different welfare systems, where STIK are more important than cash transfers in one country (or group) than another.

16. Figures on total STIK should be presented together with poverty measures wherever possible as a useful indicator in its own right.

17. Social transfers in kind (STIK) should be included in the measurement of poverty if their value can be empirically estimated on household or individual level with sufficient precision.

preliminary suggestions – STIK


18. Particularly relevant for poverty measurement are STIKs for food, shelter, clothing, and utilities. Some countries also make provisions for health care and education.

19. If poverty headcounts of relevant groups would change by 10% after STIK some consideration in the poverty measure is highly advisable. If however measurent is very poor or its effect on poverty profiles is within the margin of sampling error, STIK should not be included in poverty measures.



20. STIK can be valuated at equivalent insurance cost or actual consumption or as a mix. Its total value and estimated number of recipients need to be assessed against administrative data on the total public cost on STIK.

21. The value of STIK needs to be capped to a meaningful maximum. If STIKs are included in the ressource measure, its value should never exceed the poverty threshold.

22. If STIK are included in the ressource measure this may affect the equivalence scale.



23. If the value of STIK received is too difficult to obtain, the deduction of out‐of‐pocket expenses from the resource measure are a viable alternative. In such a situation however some poor individuals who have already curtailed certain expenditure may eventually appear as non‐poor.

24. Given the unavoidable and essentially arbitrary methodological choices regarding valuation and distribution of STIK , these need to be made fully transparent in regularly updated quality reports. In any case, users should be given the possibility to assess poverty measures with and without adjustments for STIK.



25. Comparison between countries or regions with a strong rental market and those with house owers need to take housing equity into account. Different age profiles of owners and renters may also influence socio‐economic poverty profiles.

26. Three different approaches for imputing rent are possible: assessing rental equivalence (provided that a rental market exists and selection is controlled for); user cost model (which is the hypothetical return on capital); subjective self assessment.

preliminary suggestions – imputed rent


27. As a minimum, it is recommended to collect empirical information on actual housing cost, separating between mortgage payments, rent and utility cost as these components are essential for any method.

28. The user cost model is considered the most universally applicable imputation approach. Information on the value of housing assets needs to be collected for that purpose.

29. As housing equity is the most common form or household wealth, collecting this information will also be a major step towards future poverty measurement which integrates income, consumption and wealth.



30. As an alternative to imputing rent, residual income after actual housing cost may be considered as a resource measure which reflects housing equity.

31. Given that the choice of method may depend on the available data and may contain essentially arbitrary elements, methodological choices need to be made fully transparent in regularly updated quality reports. In any case, users should be given the possibility to assess poverty measures with and without adjustments for imputed rent.



32. The question of intra ‐household distribution is usually ignored by standard poverty measures which is potentially restricting policy implications. Official poverty rates for men, women, children (or other socio ‐demographic subgroups) should therefore be accompanied with results which consider unequal sharing of resources.

33. As a minimum, NSIS should carry out sensitivity analysis for poverty profiles contrasting the conventional full pooling assumption with partial pooling and full separation of resources.

preliminary suggestions ‐ individual povertymeasures I


34. The functioning of social transfer and wage systems is best represented if the amount of personal income sources is collected for each household member. In addition, survey questions on the within‐household distribution of household income can be used to allocate personal and household income resources to individual household members.

35. Questions on material deprivation for each household member are an alternative if the income distribution within the household is unknown. This is especially recommended for countries which follow a consumption based approach.

preliminary suggestions ‐ individual povertymeasures II


36.Wherever possible, income and material living standards should be considered in combination to validate assumptions of within household income distributions.

37. Existing questions on sharing of personal income and/or personal material living standard can be adapted with relatively little additional effort from EU ‐SILC.

preliminary suggestions ‐ individual povertymeasures III


Next steps: tasks aheadassignment of chapter editors/reviewers

review chapter‐editorI. Introduction: measurement of poverty for policy relevant target groupsII. Standard core variables for disaggregationi. Policy relevant target groups for poverty disaggregation;ii. Defining target groups and analytic/geographic location variables;

iii. Examples of applications to the poverty disaggregation (studies, press releases, infographics).

III. Addressing coverage problems in poverty measurementi. Innovative survey programs to address hard-to-reach-populationsii. Adjusting survey methodology for hard-to-reach-populations and persons in institutionsiii. Specific sampling strategies to reach the poorIV. Improving response rates and sampling precision for target groupsi. How can precision requirements and selectivity of nonresponse be assessed?ii. How can estimation enhance precision and compensate for nonresponse?V. Supplemental poverty measuresi. What is the role of differences in cost of living?ii. What is the role of unequal sharing of resources within households?iii. What is the role of Social Transfers in Kind (STIK)?iv. What is the role of housing wealth and imputed rent?VI. Recommendations production, analysis & dissemination of disaggr. indicatorsVII. Topics for further work


Time schedule

o February 5th Teleconferenceconsolidated chapter 5 (SPM) ‐> reviewerdraft chapter 4 (errors)final sign‐off chapter 2 incl. recommendations (core vars)

o April 6th Teleconferenceconsolidated chapter 3 (coverage) ‐>reviewconsolidated chapter 4 (errors)sign‐off chapter 5 incl. recommendations (SPM)

o June 7th Teleconferencesign‐off chapters 3 & 4topics for future work

o July Take over by editing teamo September Sign‐off report for Bureau

matthias till diapom –state of play directorate statistics · slide 6 | 7 january 2019 adjust...

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